Att yahoo mail

Yahoo! Customer Care

2019.09.14 16:43 Yahoo-CustomerCare Yahoo! Customer Care

You’ve reached Yahoo Customer Care’s official SubReddit. Thanks for taking the time to visit! While this Reddit isn’t actively monitored at this time, we wanted to be sure you had the best source for legitimate options on how to reach us.
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2020.03.11 05:07 DenverMobile Yahoo_Mobile

New subreddit for Yahoo Mobile. This new wireless service appears to be $39.99 for unlimited everything on Verizon Wireless' network, and includes Yahoo Account Pro and Mail Pro services.
[link]


2017.07.14 02:11 Airmailapp Airmail is a mail client for iOS and Mac

Airmail is a mail client with fast performance and intuitive interaction. It offers support for iCloud™, MS Exchange, Gmail™, Gsuite™, IMAP, POP3, Yahoo!™, AOL™, Outlook.com™, and Live.com™.
[link]


2023.06.01 23:11 unwantedhated What do I do if I keep getting emails,calls,and empty packages?

It all started with calls,I haven’t dealt with scams until I bought followers by giving my account info for Instagram in 2019 but more recent is Facebook where fake people messaged me but not as bad.Facebook keeps telling me to provide my identity so one of my accounts is compromised.
Someone tried to use my account to create a Facebook account on an email that I rarely use that is newer than the one I actually use.I created an account under my newer email they tried to use so they wouldn’t plus didn’t confirm the link when tried to finish creating their own Facebook with that email(which happened this year).
Now I’ve been getting emails that someone signed up an account at Kay Jewelers with my email I normally use and created the name according with chase but the routings were different and checked my bank.They seem legit too because got 5 in a row and the email isn’t random like most fake scam emails of winning someone.
I know in the past I would get a iPhone alert that I won something or that a virus has been detected and needed to download a certain security app.I have Yahoo mail rn but these seemed like a pop up.
I’m worried because today I got a empty package from Repolls Survey and there was nothing in there.I know yesterday I got a call that I owed $5,000 from Amazon but an automated message.
submitted by unwantedhated to Scams [link] [comments]


2023.06.01 22:04 Alene_Arre The Definitive, Redditor-Friendly Guide Towards Creating and Publishing Your Personal Wikipedia Page

Introduction
Hey and welcome to the WikipediaPageCreation subreddit! This is a subreddit dedicated to discovering and exploring various methods and strategies of securing Wikipedia pages for a brand or person. My name is Nikolas Lemmel and I’m the team-lead at a boutique digital agency by the name of Maximatic Media. As we’ve spent the last couple of years dissecting the art of Wikipedia page creation, I’ve decided to open this sub in hopes of sparking a discussion on various impactful and non-impactful factors affecting the creation of stickied Wikipedia pages. I’m hoping to start the birth of this sub off strong so I’m gonna try to provide an in-depth overview of what we’ve learned about creating and stabilizing Wikipedia pages thus far as a company in this post. If you have any experience with either of the components I’ll be mentioning or would like to share one that we’ve yet to cover, please feel free to comment down below.
Page Stickiness
Let’s start this journey by first recognizing the weird word I’ve used like 3-4x in the introduction: “stickied”. This is a word you’ll see appear often the deeper dive into the Wikipedia publishing world.
The concept of "stickiness" in the context of Wikipedia publishing has to do with the longevity and resilience of a newly published Wikipedia page. Wikipedia is an open-source platform that relies on volunteer editors to maintain the quality of content on the site. These editors follow a set of guidelines to decide what content is notable and reliable enough to appear on Wikipedia.
When a new page is created, it undergoes scrutiny from higher-tier editors and admins, who assess whether the page meets Wikipedia's stringent notability and reliability criteria. If they decide that it doesn't, the page can be deleted or heavily revised, oftentimes within a matter of days from its publishing date. This constant monitoring and removal process is part of Wikipedia's commitment to maintaining a high-quality, reliable source of information and minimizing the extent to which Wikipedia is used in an advertorial fashion.
Stickiness, therefore, refers to the ability of a new page to withstand this scrutiny and remain live on the site. A stickied page is one that has been well-constructed, sufficiently sourced with credible references, and clearly meets the notability requirements. The page not only gets published but also stays published, or "sticks.”
Now, this may already be common knowledge to the bulk of you that are actively researching Wikipedia page creation for your brand. However, since we’ve launched our service, we’ve dealt with a lot of clientele who have attempted to create a Wikipedia page for themselves in the past and were hit with this harsh reality check. An alarming percentage of those cases fell prey to freelancers or companies specializing in Wikipedia publishing that charged them anywhere between $600 - $2000 to draft and publish a Wikipedia page, knowing full well that there was absolutely zero chance that the page would actually remain on Wikipedia. Not an outright scam, mind you, but very much bordering on one in my point of view.
The truth of the matter is that 95% of entities seeking a Wikipedia page do not truly warrant one and this statement is corroborated by Wikipedia’s own statistic, stating that a mind-boggling 98% of newly published pages get nominated for deletion. So how do we combat these ridiculously low odds? Well, let’s delve into what’s arguably the biggest factor of all when it comes to page stickiness:
Notability
So diving right into the nitty-gritty of Wikipedia Publishing, we must first cover the concept of notability - the most important aspect out of all of the points I’ll be covering in this guide. Notability in the context of Wikipedia simply means how often reputable, secondary sources are referencing you in their media output. Said references come in many forms, whether it be a full feature article, a short bio in a listicle or just a basic citation. However, not all references are made equal. Some references carry significantly more weight than others, either due to its “comprehensiveness” (i.e. a full feature article with the sole focus being on you) or the “reputability” of the source doing the referencing (i.e. mentioned in Forbes vs mentioned in “Biznes-News-Blog”).
Comprehensiveness
Let’s first delve into the topic of comprehensiveness. The comprehensiveness of your reference can be calculated by just a couple factors: the word count of the article, the keyword density of your entity’s name within said article and whether the entity is being referenced in the title/headline of the article. These three components determine the significance laid upon the entity by the reporting outlet. The more extensive the coverage, the higher the significance in the eyes of Wikipedia (i.e. a full-feature, 750-word article on Forbes vs a 150 word entry in “Top 30 E-Commerce Businesses of 2023” listicle on Forbes).
Reputability
Now that we’ve covered what I mean by “comprehensiveness”, let’s talk about the other component influencing the power of your media coverage: reputability. The concept of reputability is basically as straightforward as it gets. Just about any semi-famous news or media outlet that you can think of is viewed as a “reputable” source by Wikipedia. The likes of Forbes, Mashable, USA Today, etc are all stellar examples of significant coverage that corroborates you or your brand as a notable entity in the eyes of Wikipedia. However, a full feature article on each of those aforementioned sites costs $15,000, $2,400 and $6,500 respectively. If you as an entity see no utility in being featured on these media outlets beyond simply meeting the eligibility criteria for a Wikipedia page, it makes little sense to purchase those placements.
The Role of Domain Authority
This is where a more esoteric metric comes into play: Domain Authority. A DA score is effectively a ranking assigned to a domain which we can use to assess any given site’s authority in comparison to the rest of the web. It is calculated using the domain’s age, the amount of other sites referring to it and the reputability of said referrals. Basically the same criteria influencing the site’s probability of getting their own stickied Wiki page but quantified by a score from 1 to 100. Now let’s return back to three examples of reputable media outlets I’ve given above: Forbes, Mashable and USA Today. Forbes has a DA score of 95, Mashable has a DA score of 92 and USA Today has a DA score of 94. So all in all, all three publications are highly renowned, outpacing the vast majority of other sites on the web with scores of 90 and above. However, if referring back to the pricing of each placement, we see a pretty drastic incongruence with the value derived from each media outlet in the context of GKP creation. Forbes, despite being one measly basis point off of USA Today’s DA score, carries more than a 200% higher price tag. Now sure, Forbes has a significantly higher readership and holds far more clout than USA Today but if focusing solely on its impact in the context of a Wikipedia reference, it really doesn’t warrant the price you pay for it when compared to other viable alternatives.
And these are just the three sites we’ve mentioned so far. Take a look at the following spreadsheet containing 400+ available media placements and keep an eye on the DA column:
https://docs.google.com/spreadsheets/d/1SX7bI0YSZeJCWwxaMEZ1LG-QtoiLFnDVJZjW1n-ZvQ0/edit?usp=sharing
As you scroll through, you’ll find that there are a plethora of Google-News-Approved sites that have a relatively high DA despite costing a fraction of what the internationally distinguished media outlets cost. Sites like Village Voice, HackerNoon, Times of Malta, Chiang Rai Times, etc. Now granted, they don’t exactly pack the same sort of punch that Forbes does but in the context of a Wikipedia page, you are considerably better off securing five B-tier placements in comparison to a singular A tier placement. So long as you are not cheaping out by opting for “Biznes-News-Blog” as your referring source and stick to Google-News-Approved publications, a varied list of reputable placements within your references section will take you much further than just one extremely reputable citation.
Reliability
Now that we’ve extensively covered the topic of notability, let’s talk about a factor of media assessment that is unique to Wikipedia: Reliability. Reliability is Wikipedia’s way of determining how trustworthy the source of incoming information is. It’s one of the only ORM services that views this factor as being separate from notability, which makes the process of selecting publications a bit more complex.
As a PR agency, we deal with a lot of ORM requests ranging from Google Knowledge Panels to Wikipedia Publishing to Social Media Verifications on platforms like Instagram, Facebook, TikTok and Youtube. Theoretically, say that we receive a client seeking to get verified on all social platforms, get a GKP and get a Wikipedia page published about them. All in all, the works. Let’s say that they also came to us with a decent bit of pre-existing media coverage and have full feature articles about them published on the Daily Mail, Newsweek, RT News, OK Magazine and E! News.
Now, in the context of GKP Creation and Social Media Verification, we would notify this imaginary client that we are prepared to move forward with their case and are relatively optimistic about their probability of success. Given that their PR stems from highly recognizable publications with DAs in the high 80s/90s, there is little reason to suspect that they’d get rejected on the basis of notability. However, when it comes to Wikipedia, we unfortunately would have to reject this case and I’ll explain why. Despite the fact that each of those publications is considered notable by Wikipedia’s standards (which more or less follow the same criteria as Google and Meta mind you), not a single one of those listed outlets is viewed as a trustworthy source by Wikipedia. Newsweek is viewed as a biased news reporter, RT News is viewed as propagandized and state-run media, and Daily Mail, OK Mag and E! News are all considered low-quality, tabloid-like sources of information. Creating a Wikipedia page with only these articles as citations is basically a guaranteed nomination for deletion waiting to happen.
This is largely why, when purchasing press for Wikipedia, you want to stick to media outlets that are independent, journalistic sources with a good reputation behind them. So going back to the spreadsheet of PR placements, sites like Times of Malta and Chiang Rai Times are good examples of reputable, independent news sites that meet the notability criteria whilst remaining relatively affordable. The cream of the crop, however, would be publications like Wisconsin State Journal, Arizona Daily Star, Sacramento Bee, Miami Herald, etc. Localized, independent news sources that have a significant amount of authority within their local domains while having an international readership similar to that of the NYT and Chicago Tribune.
Lastly, let’s talk about press releases from reputable sites like Yahoo, Bloomberg, Business Insider, etc. Wikipedia views press releases, especially those bought from press release aggregators, with a measure of suspicion, considering them as 'purchased' content. Purchasing these is really like blowing money down the drain since these can only be used as secondary sources. Stay away from these and stick only to editorial articles — those written by the staff of the publication and not distributed through the plethora of press release services out there.
The Question of Quantity
A pretty common question we get asked in our Wikipedia publishing consultations with clients is what amount of references guarantees a stickied page. What is the absolute minimum that I can get away with? And truth be told, we honestly have a hard time answering this question as we don’t truly know. Without foreseeing the future and knowing which admin gets assigned to review the page and what their opinion is on each referring publication, it is impossible to predict the actual amount. In our experience of creating Wikipedia pages over the last couple of years, we’ve found no shortage of BS reasons given for rejecting a specific source. The way Wikipedia is organized, it really just comes down to luck. We’ve witnessed a client get a stickied page with just five references and we’ve also witnessed a client get their page deleted with upwards of 15 strong references.
Having said that though, if taking into account the median number of references across all of our successful cases, a good benchmark to aim for would be roughly 6 semi-strong, corroborating references with a DA of 75 and above. Again, this number is not set-in-stone and may vary contingent on the entity (living persons oftentimes given more leniency than corporate brands) but six is basically the optimal zone. In the event an admin decides to reject one of the citations, the page still has five other references to fall back on, making it difficult to argue a lack of notability within a nomination vote. But if you really wanna take your chances, three strong references is the absolute minimum. Just be aware that you are fully at the mercy of the admin in this scenario.
“Veteran” Editor Accounts
Now that we have finally finished covering the most important factor impacting your Wiki page’s stickiness, let’s move onto what is likely the 2nd most important factor: the Wiki account doing the publishing. Let’s imagine for a second that we have a ready-to-go Wikipedia article that is well-constructed, worded in an objective, non-advertorial manner and contains plenty of citations from reputable sources verifying each and every piece of factual information within the article. Now, let’s imagine that we take this exact same article, word-for-word and publish it from two separate editor accounts. One of those accounts has been around for 7+ years and has made 3,000+ edits across various existing pages alongside the 300+ pages they’ve created and published themselves. The other account was registered three days ago, has zero experience editing other people’s entries, and their very first edit is about to be a brand new page that very few people ever heard of, despite how well-cited it may be.
Assuming they both publish the exact same content, word-for-word with the same references section, who do you think will receive more scrutiny over the brand new page from admins? The guy who’s been around for close to a decade and has a historical track record of quality contributions? Or the guy who literally just made an account on Wikipedia and decided that publishing a page about a little-known entity is a good first step in his life-long Wikipedia journey?
I think that’s really all that can be said about this topic as it's quite straightforward. Aged accounts with a history of edits simply tend to be more trusted when it comes to new page creation than accounts that are brand new. If you have a semi-strong page with somewhat questionable references, the reputation and history of the editor doing the publishing can be the thing that nudges it over the edge of acceptance.
That’s partially why we charge $1,500 for our Wikipedia publishing service. No one should pay fifteen hundred bucks to write a 400 word entry about their brand, that’s obscene. You pay for the privilege of being published by a somewhat renown Wikipedia editor, minimizing the degree to which your entry elicits suspicion and thus, maximizing your chances of success.
Drafting the Page
Now that we’ve covered the two most important aspects influencing your page’s stickiness probability, let’s move onto the last and arguably, least important factor out of them all: the actual writing. Now don’t get me wrong, a poorly written page is still very much a massive red flag when entering the sandbox stage. However, the knowledge required to write an objective, Wikipedia-compliant page is far more prevalent and less clandestine than the knowledge required to make the entity eligible for one.
Just read about a dozen or so pages on living persons and emulate the language and writing style used by the editors to the best degree you can. Assuming that you are a native speaker and don’t have any glaring grammatical errors within your writing, nine times out of ten, the page ends up being eligible for publishing. We’ve had plenty of clients write their own pages that required little to no editing on our side prior to being published.
There’s not much I can add to this that hasn’t already been covered by Wikipedia themselves (which you can read on this link here:). https://en.wikipedia.org/wiki/Wikipedia:Biographies_of_living_persons
Aside from the common tidbits of knowledge such as not using promotional language or writing in an informal tone, my one piece of unorthodox advice is to not go overboard with the length of the article. The shorter your page is, the lower the attack surface. The best pages are those that have just a couple of paragraphs in them, ranging between 200 and 350 words. The longer your page is, the higher the chances that you may get flagged for some factoid that didn’t get referenced enough within the sources you’ve cited to be considered “factually verifiable”.
Keep it to a minimum and only write about things that are easily fact-checked and warrant being on Wikipedia. Beyond that, just refer to Wikipedia’s own guidelines for written content and read a couple of pages for a quick inspo-sesh.
Conclusion
Given that we’ve covered each aspect of Wikipedia creation worth mentioning, let’s do a brief overview given that this post ended up being far longer than I had initially anticipated. We've dug deep into the nitty-gritty world of Wikipedia publishing, dissected the perplexing idea of "stickiness", navigated through the labyrinth of notability, comprehensiveness, reputability, and reliability, and peered into the halls of "Veteran" editor accounts.
So, let’s summarize what we’ve learned. Wikipedia's demanding notability and reliability criteria mean you can't simply grab any media coverage and hope it sticks. Quality over quantity, friends. Be discerning in your source selection, aim for varied, reputable sources, and steer clear of low-quality, biased outlets. You need to be strategic and smart about it. A Wikipedia page isn’t a walk in the park, it's a marathon, demanding preparation, skill, and persistence.
Never forget the importance of the account that does the publishing. An aged, trusted account can make the difference between sailing through or sinking like a stone. And remember, Wikipedia is not a billboard. It’s not about shouting your brand or achievements from the rooftops, it’s about providing an unbiased, informative, well-referenced and worthwhile contribution to the collective human knowledge.
We've shared the tricks of the trade, the ins, the outs, and the in-betweens of securing your Wikipedia page and have hopefully proven ourselves to be an above-average service provider of Wikipedia Publishing Services in the process.
Hopefully, y’all found this sub’s first post to be useful and a good introduction into the world of Wikipedia publishing. Myself and my team member, Marcus will be sticking around for an AMA on this post in case people have questions regarding any of the factors we’ve covered in this guide. Don’t forget guys, we started this subreddit out of the desire to make the process of securing a Wikipedia page less daunting and more of a community endeavor. It's a place where we can share our triumphs and challenges, learn from each other, and navigate the Wikipedia landscape together. So whether you’re a newbie trying to secure your own page or a PMarketing professional with years of experience in the field, please do not hesitate to share your journeys along with any factors you’ve found to have an impact that we failed to cover in the guide.
Let’s make WikipediaPageCreation the focal point of every Wikipedian’s self-publishing endeavor!
submitted by Alene_Arre to WikipediaPageCreation [link] [comments]


2023.06.01 21:17 Temporary_Noise_4014 Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report

Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report
Predictmedix – a great way to surf the Artificial Intelligence wave.

https://preview.redd.it/p6vawwx2ig3b1.png?width=741&format=png&auto=webp&s=16344b32088e8959d3e838a528a893994685ec85
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:
  1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
  2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
  3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
  4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.
I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.
submitted by Temporary_Noise_4014 to PennyCatalysts [link] [comments]


2023.06.01 21:16 Temporary_Noise_4014 Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report

Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report
Predictmedix – a great way to surf the Artificial Intelligence wave.

https://preview.redd.it/gj9fc2nzhg3b1.png?width=741&format=png&auto=webp&s=f87c4488fd2fac4388b4b65e352e8b286af88c9c
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:
  1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
  2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
  3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
  4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.
I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.
submitted by Temporary_Noise_4014 to Canadapennystocks [link] [comments]


2023.06.01 21:16 Temporary_Noise_4014 Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report

Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report
Predictmedix – a great way to surf the Artificial Intelligence wave.

https://preview.redd.it/madn1nknhg3b1.png?width=741&format=png&auto=webp&s=afdc89b341aef03eb0099910359090687d69568d
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:
  1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
  2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
  3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
  4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.
I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.
submitted by Temporary_Noise_4014 to CanadianStockExchange [link] [comments]


2023.06.01 21:14 Temporary_Noise_4014 Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report

Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) Special Report
Predictmedix – a great way to surf the Artificial Intelligence wave.

https://preview.redd.it/1euasjh6hg3b1.png?width=741&format=png&auto=webp&s=bca3509be737c63b59eab69398f5a735d746c185
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:
  1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
  2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
  3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
  4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.
I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.
submitted by Temporary_Noise_4014 to 10xPennyStocks [link] [comments]


2023.06.01 20:42 thedrolick The Definitive, Redditor-Friendly Guide to Creating Your Google Knowledge Panel

Introduction
Hey and welcome to the GoogleKnowledgePanels subreddit! This is a subreddit dedicated to discovering and exploring various methods and strategies of securing a Google Knowledge Panel for a brand or person. My name is Nikolas Lemmel and I’m the team-lead at a boutique digital agency by the name of Maximatic Media. As we’ve recently begun offering Google Knowledge Panel creation services, I’ve decided to open this sub in hopes of sparking a discussion on various working and non-working knowledge graph generation methods for Google. I’m hoping to start the birth of this sub off strong so I’m gonna try to provide an in-depth overview of what we’ve learned about creating and stabilizing Google knowledge panels thus far as a company. If you have any experience with either of these components or would like to share one that we’ve yet to cover, please feel free to comment down below.
The Notability Factor
So diving right into the nitty-gritty of GKP creation, we must first cover the concept of notability; arguably, the most important aspect out of all of the points I’ll be covering in this guide. Notability in the context of GKPs simply means how often reputable, secondary sources are referencing you in their media output. Said references come in many forms, whether it be a full feature article, a short bio in a listicle or just a basic citation. However, not all references are made equal. Some references carry significantly more weight than others, either due to its “comprehensiveness” (i.e. a full feature article with the sole focus being on you) or the “reputability” of the source doing the referencing (i.e. mentioned in Forbes vs mentioned in “Biznes-News-Blog”).
Comprehensiveness
Let’s first delve into the topic of comprehensiveness. The comprehensiveness of your reference can be calculated by just a couple factors: the word count of the article, the keyword density of your entity’s name within said article and whether the entity is being referenced in the title/headline of the article. These three components determine the significance laid upon the entity by the reporting outlet. The more extensive the coverage, the higher the significance in the eyes of Google (i.e. a full-feature, 750-word article on Forbes vs a 150 word entry in “Top 30 E-Commerce Businesses of 2023” listicle on Forbes).
The Influence of Topical Relevance
Topical relevance also plays a role in the equation as the contents of the reference should be somewhat aligned with what other sources are discussing when mentioning your entity’s name. If every article that your entity appears in has a completely different context or is overly-generalized, it decreases Google’s certitude of what it truly knows about said entity. That’s largely why it’s not recommended to always opt for brand mentions or stuff keywords into random guest posts as it can drastically impact what Google thinks it knows about you.
Reputability
Now that we’ve covered what I mean by “comprehensiveness”, let’s talk about the other component influencing the power of your media coverage: reputability. The concept of reputability is basically as straightforward as it gets. Just about any semi-famous news or media outlet that you can think of is viewed as a “reputable” source by Google. The likes of Forbes, Mashable, USA Today, etc are all stellar examples of significant coverage that corroborates you or your brand as a notable entity in the eyes of Google. However, a full feature article on each of those aforementioned sites costs $15,000, $2,400 and $6,500 respectively. If you as an entity see no utility in being featured on these media outlets beyond simply meeting the eligibility criteria for a Google Knowledge Panel, it makes little sense to purchase those placements.
The Role of Domain Authority
This is where a more esoteric metric comes into play: Domain Authority. A DA score is effectively a ranking assigned to a domain which we can use to assess any given site’s authority in comparison to the rest of the web. It is calculated using the domain’s age, the amount of other sites referring to it and the reputability of said referrals. Basically the same criteria influencing your probability of getting a GKP but quantified by a score from 1 to 100. Now let’s return back to three examples of reputable media outlets I’ve given above: Forbes, Mashable and USA Today. Forbes has a DA score of 95, Mashable has a DA score of 92 and USA Today has a DA score of 94. So all in all, all three publications are highly renowned, outpacing the vast majority of other sites on the web with scores of 90 and above. However, if referring back to the pricing of each placement, we see a pretty drastic incongruence with the value derived from each media outlet in the context of GKP creation. Forbes, despite being one measly basis point off of USA Today’s DA score, carries more than a 200% higher price tag. Now sure, Forbes has a significantly higher readership and holds far more clout than USA Today but if focusing solely on its impact in the SEO space, it really doesn’t warrant the price you pay for it when compared to other viable alternatives.
And these are just the three sites we’ve mentioned so far. Take a look at the following spreadsheet containing 400+ available media placements and keep an eye on the DA column:
https://docs.google.com/spreadsheets/d/1SX7bI0YSZeJCWwxaMEZ1LG-QtoiLFnDVJZjW1n-ZvQ0/edit?usp=sharing
As you scroll through, you’ll find that there are a plethora of Google-News-Approved sites that have a relatively high DA despite costing a fraction of what the internationally distinguished media outlets cost. Sites like Village Voice, HackerNoon, Times of Malta, Chiang Rai Times, etc. Now granted, they don’t exactly pack the same sort of punch that Forbes does but in the context of a Google Knowledge Panel, you are considerably better off securing five B-tier placements in comparison to a singular A tier placement. So long as you are not cheaping out by opting for “Biznes-News-Blog” as your referring source and stick to Google-News-Approved publications, a varied list of reputable placements within your Schema.org set-up (which we’ll be covering later in the guide) will take you much further than just one extremely reputable reference.
The Question of Quantity
A pretty common question we get asked in our GKP consultations with clients is what amount of references guarantees a panel. What is the absolute minimum that I can get away with? And truth be told, we honestly have a hard time answering this question as we don’t truly know. Without an inside look at the inner-workings of Google’s GKP algorithm, it’s impossible to say what the actual amount is. The variables it utilizes are dynamic and there isn’t a constant sum that can be calculated across all cases. We’ve witnessed a client get a GKP with just three mid-tier references in their Schema and we’ve also witnessed a client fail to get a GKP with upwards of 20 strong references.
Having said that though, if taking into account the median number of references across all of our successful cases, a good benchmark to aim for would be roughly 8 semi-strong, corroborating references with a DA of 70 and above. Again, this number is not set-in-stone and may vary contingent on the amount of “keyword-pollution” (i.e. other entities vying for the same moniker) occurring for your entity’s name along with other factors only Google is cognizant of.
Debunking the Myth: The Wikipedia-GKP Connection
Now, let's clear up a common misconception that I've seen floating around: having a Wikipedia page is not a prerequisite for getting a Knowledge Panel. Our anecdotal experience proves no solid line connecting the two. There is absolutely no need to worry about going through the hoops and hurdles of Wikipedia to earn your spot in the Knowledge Graph.
A Wikipedia page is only useful in the context of adding a short bio within your Knowledge Panel which can only be derived from a Wikipedia entry. Beyond that, nothing else about the panel changes. You can still have your website, your logo/image, your social media links and everything else that makes a panel a useful tool within one’s online reputation management’s arsenal.
Believe it or not, securing a stickied Wikipedia page is far, far more difficult than obtaining a GKP. A source like Daily Mail, a highly reputable reference in the eyes of Google, is seen as an “untrustworthy”, “tabloid-like” source of information in the eyes of Wikipedia. As I’ve explained above regarding the Forbes placement, unless you have a separate need for a Wikipedia page beyond its utility in the GKP context, it makes little sense to go through the effort of establishing it. However, if you’re dead-set on getting a Wikipedia page for your personal or corporate brand, you can check out our separate guide about successfully acquiring a Wikipedia page on WikipediaPublishing.
Schema.org Set-Up
Now that we’ve extensively covered the topic of notability, this brings us to the following component which is the nice and robo-friendly organization of your notability indicators. This is where your Schema comes in. Schema.org is a collaborative initiative started by major search engines, including Google, Yahoo, Bing, and Yandex, to create a shared vocabulary that webmasters can use to structure metadata on their websites. It's basically a form of microdata, a type of HTML specification used to nest metadata within existing content on web pages. When implemented correctly, a Schema markup can significantly improve your presence in the SERPs by helping search engines understand your content more efficiently as soon as it surfaces on the web.
In the context of a Google Knowledge Panel, using a Schema markup eliminates the degree of guess-work involved on Google’s end to determine which piece of content belongs to your entity and which doesn’t. This is what enables Google's algorithm to use this structured data to generate rich, informative search results – the kind that Knowledge Panels are known for. This part is especially crucial to those of you who are competing for the same name in the SERPs.
Here's how you'd go about setting up a Schema.org markup:
Step 1: Identify Your Schema Type
Choose the right type of Schema.org markup that suits your content. There are hundreds of Schema types available, from creative works (like books, movies, and music) to organizations, persons, places, and more.
Step 2: Generate Your Markup
Once you've identified your Schema type, use a tool like Google's Structured Data Markup Helper or JSON-LD Schema Generator to create your markup. These tools are user-friendly and guide you through the process step-by-step.
Step 3: Implement Your Markup
Once generated, this markup needs to be added to the HTML of your website. The placement of the markup will depend on the type of Schema you're using and the CMS of your site.
Step 4: Test Your Markup
After implementation, use Google's Rich Results Test to verify if your markup is correctly implemented and can be read by Google.
Remember, adding Schema.org markup to your site does not guarantee a Knowledge Panel, but it does indeed increase your chances by helping Google better understand and represent your content. It's just one piece of the puzzle in creating an informative, robust online presence that can contribute to your GKP creation.
Conclusion
In bringing this all together, let me say this: carving out your space on the web with a Google Knowledge Panel is a fine-tuned mixture of art, science, and a bit of ol’ fashioned luck. We've talked at length about the importance of building notability, making sure we're being talked about in all the right places and in the right way. We've also stressed the need to take stock of the value each media placement brings to the table, balancing their domain authority and cost to get the most bang for our buck (refer back to the spreadsheet).
We've also established that there's no magic number of references that'll open the GKP gates for us. Like a lot of things in life, it’s not just about quantity but quality and relevance that counts. And although having a Wikipedia page may seem like the golden ticket, it's not the be-all and end-all; you can absolutely secure a GKP without one.
As for structuring our online presence for Google’s scrapers, using a Schema.org markup is a crucial piece of the puzzle. It’s like leaving breadcrumbs for Google's algorithm, making sure it can effortlessly find and understand our content. The detailed steps we've covered should help guide you through this process, but remember, it’s not a guarantee for a panel - just a tool in your arsenal.
At the end of the day, there isn't a foolproof recipe for securing a GKP. The path to success can vary wildly, each one unique and filled with its own set of disadvantages. But with some patience, a touch of strategy, and a deep understanding of how Google's algorithm works, we can certainly increase our odds.
Hopefully, y’all found this sub’s first post to be useful and a good introduction into the world of GKP creation. Myself and my team member, Marcus will be sticking around for an AMA on this post in case people have questions regarding any of the factors we’ve covered in this guide. Don’t forget guys, we started this subreddit out of the desire to make the process of securing a GKP less daunting and more of a community endeavor. It's a place where we can share our triumphs and challenges, learn from each other, and navigate the GKP landscape together. So whether you’re a newbie trying to secure your own panel or an SEO professional with years of experience in the field, please do not hesitate to share your journeys along with any factors you’ve found to have an impact that we failed to cover in the guide.
Thanks for reading!
submitted by thedrolick to GoogleKnowledgePanels [link] [comments]


2023.06.01 18:56 kyotoko77 I can't log into my yahoo mail account because its asking me to provide recovery information to protect my account.

I forgot my password so I used my phone number to get into my account, yahoo won't let me through because it wants me to provide ANOTHER recovery phone number and email, please help me because this is driving me insane.
submitted by kyotoko77 to yahoo [link] [comments]


2023.06.01 16:52 DoctorVanNostrande Swan killers leave. People who aren't swan killers stay, have a little lunch, enjoy themselves, socialize, get to know the members, there is nothing wrong.

Swan killers leave. People who aren't swan killers stay, have a little lunch, enjoy themselves, socialize, get to know the members, there is nothing wrong. submitted by DoctorVanNostrande to curb [link] [comments]


2023.06.01 16:46 Onemoniter Allow your kids to use WhatsApp freely by WhatsApp Spy Online

Allow your kids to use WhatsApp freely by WhatsApp Spy Online
https://preview.redd.it/3uuzitcq5f3b1.png?width=1020&format=png&auto=webp&s=a0499e5debff9f741ec312f9661a675f43ab0612
Today’s kids are considered to be more clever and smart as compared to the kids 10 years ago. Because of technology they always play smart when it comes to hiding something or keeping the conversation done with their friends a secret. As a parent, we are always concerned about the changes that can be seen in the kids. The WhatsApp spy Online app will give you the track of all the data which is stored on your kid’s phone. WhatsApp Spy Online will send you the data of all the chats and images which has been clicked and sent by your kids through WhatsApp or any other application.
The most discussed topic in today’s scenario among parents are the messages which are shared through the social media platforms or the kinds of people to whom your kids chat on daily basis. Spy Whatsapp feature of Whatsapp Spy online will be recording all the messages and calls which are made from the target phone. Whatsapp Tracker gives you parental control to trace each and every detail of your child’s life even then when you are not present with them. With the help of Whatsapp Spy Software, you will be able to locate your child anytime from anywhere.
What Kids Usually Do?
When it comes to hiding things or keeping secrets from parents kids usually play smart. They may delete the messages or keep it in their Archive folder. They may use other platforms which are not known by you. SMS messages were trackable by then as it was included in the phone bills but now Instant messaging apps are proved to be as a lifeguard for the children. They just need to connect with the internet and can send unlimited messages from these platforms. Parents are always disturbed and stressed when they see fingers running on the keyboard for a whole day. To the only solution to this problem is track WhatsApp chat from your kid’s phone. But that is also a cumbersome task. As all the Android phones are always updating their security options with fingerprint locks or patterns or even face locks. So the question which arises is how to Spy WhatsApp installed on your kid’s smartphones. The answer to this question is :
ONESPY App, A WhatsApp Spy online is a solution to this problem
ONESPY app is a leading monitoring app that proved to be helpful for the parents who want to have a strict parental control over their kid's phone. ONESPY app is possibly the right option to choose when it comes to Whatsapp Spy online software. When talking about this ONESPY app, it comes with WhatsApp spy software, and not only WhatsApp it comes with spying many other applications installed on the phone. The main features of this WhatsApp Spy Online online are listed below:
  1. Hidden Call Recorder: In the past days we used to make phone calls from normal calling applications installed on our phone which are easily trackable from the phone bills. But as WhatsApp comes with the call feature Whatsapp Tracker comes with a hidden call recording feature which will record the incoming and outgoing calls and surround sound recordings too. ONESPY app will record the calls and will send you the audio file to your control panel which is accessible for next 30 days.
  2. Track WhatsApp Chats: Whatsapp Spy Online will track WhatsApp chat which is stored anywhere on the phone. Children think that possibly their chats can’t be seen when they delete the chats from the application, but their chats are saved on the database which is retrieved by the Whatsapp Spy Software and is sent to your control panel.
  3. Location Tracker: Smartphones nowadays come with noise cancellation option which mutes the background sound when we are on call. This has made easy for the kids saying lie to their parents when they are asked about their location. Whatsapp Spy Online will be continuously notify about the changes in Location made by your kid. ONESPY will catch the location from the GPS locator installed on every phone.
  4. Image Tracker: ONESPY app will send you all the images as and when it is clicked from your kid's phone. WhatsApp Spy online will send you the record of the clicked pictures which are sent or received by your kid. Spy Whatsapp software will record every single word or images which are stored on your child’s phone.
  5. Email Tracker: If your kid starts feeling fishy about the phone applications been traced by you they may switch to Emails for the conversations to be done smoothly. ONESPY WhatsApp Spy Online app will trace all the emails from various platforms such as Google messenger, Yahoo messenger or Outlook messenger that will be a bonus feature of WhatsApp Spy Software.
How to get the Whatsapp Spy Online installed?
ONESPY software is easily available on the website onespy.in.You can visit the website and purchase the app. They will ask you to choose the subscription which is available on their website. You can do the formalities and make the payment by choosing one from various payment modes available. After making a payment you will get a link sent to your Email. That link will direct you to the page from which you can download the .apk file. Keep the target phone handy with you, so you can install the Whatsapp Spy online easily it will take not more than 5 minutes to complete the installation process just follow the installation guide which is sent by the Whatsapp spy software with the mail. The WhatsApp tracker is easy to operate and at the same time, it is undetectable. It can’t be removed or uninstalled even if the phone goes through factory reset option or an OS upgrade.
For any further assistance which you will need in near future, you can connect to ONESPY technical support directly. Not only this but also ONESPY provides you the online chat support which will help you in real time problems.
submitted by Onemoniter to u/Onemoniter [link] [comments]


2023.06.01 14:05 escitalopramsucks One more month, one more donation

submitted by escitalopramsucks to PSSD [link] [comments]


2023.06.01 06:14 valy225 Jagex Launcher dont work but Steam seems to work!!

After two days of giving up on all hopes i tried logging in using steam and after i got sent to link my runescape account with steam i ended up with over 10 verification codes one after another on my yahoo mail every time i opened runescape with steam and at the same time i opened the jagex launcher and managed to get in.
Not sure for how long i will be logged in on the launcher or if it will work when i get back but this is best we can do for now. Anyway rs is loading really slow for me on steam and dont want to try playing using steam even on low but this is better than nothing
I suggest anyone that dont want to get stuck outside of the game to only link one account for the golden cape only on the jagex launcher and nothing more and only link them all when Beta is over since this might not be the last time we will experience this sort of problem.
submitted by valy225 to runescape [link] [comments]


2023.06.01 04:15 RedsModerator The Reds defeated the Red Sox by a score of 5-4 - Wed, May 31 @ 07:10 PM EDT

Reds @ Red Sox - Wed, May 31

Game Status: Final - Score: 5-4 Reds

Links & Info

Reds Batters AB R H RBI BB K LOB AVG OBP SLG
1 Newman - 3B 4 1 2 0 0 0 0 .276 .343 .366
2 McLain - SS 5 0 2 0 0 1 3 .361 .426 .541
3 India - 2B 4 1 0 0 1 2 4 .282 .369 .426
4 Steer - 1B 3 1 1 2 1 1 1 .289 .356 .498
5 Stephenson, T - DH 4 0 0 0 0 2 2 .246 .336 .340
6 Fairchild - RF 2 0 0 0 0 2 0 .246 .343 .386
a-Fraley - LF 2 0 0 0 0 1 2 .248 .337 .399
7 Senzel - CF 4 0 2 1 0 1 0 .270 .341 .405
8 Barrero - CF 2 1 0 0 1 1 3 .231 .314 .347
Casali - C 1 0 0 0 0 1 0 .154 .254 .154
9 Maile - C 3 0 1 1 0 1 0 .259 .310 .481
1-Benson - RF 1 1 0 0 0 0 0 .152 .176 .212
Totals 35 5 8 4 3 13 15
Reds
a-Flied out for Fairchild in the 6th. 1-Ran for Maile in the 7th.
BATTING: 2B: Senzel (8, Paxton); Maile (3, Paxton). HR: Steer (8, 7th inning off Winckowski, 1 on, 2 out). TB: Maile 2; McLain 2; Newman 2; Senzel 3; Steer 4. RBI: Maile (6); Senzel (26); Steer 2 (28). 2-out RBI: Maile; Steer 2; Senzel. Runners left in scoring position, 2 out: McLain; Barrero 2. GIDP: India. Team RISP: 4-for-10. Team LOB: 7.
FIELDING: E: Casali (1, catcher interference). DP: (McLain-Steer).
Red Sox Batters AB R H RBI BB K LOB AVG OBP SLG
1 Verdugo - RF 5 0 2 0 0 0 1 .294 .368 .456
2 Devers - 3B 4 0 1 1 1 1 1 .246 .288 .498
3 Turner, J - 1B 4 0 1 0 0 1 4 .263 .351 .404
4 Yoshida - DH 4 2 2 1 0 0 1 .317 .391 .508
5 Refsnyder - LF 4 0 1 0 0 1 1 .284 .408 .383
6 Duran, Ja - CF 4 0 1 1 0 1 1 .292 .340 .467
7 Hernández, K - SS 3 0 0 0 0 1 0 .233 .308 .352
a-Tapia, R - PH 1 0 0 0 0 0 1 .274 .337 .381
Reyes, P - SS 0 0 0 0 0 0 0 .273 .314 .364
8 Valdez, E - 2B 3 1 1 1 0 1 1 .250 .302 .450
9 Wong - C 4 1 1 0 0 1 1 .243 .293 .470
Totals 36 4 10 4 1 7 12
Red Sox
a-Lined out for Hernández, K in the 8th.
BATTING: 2B: Devers (13, Weaver); Refsnyder (5, Weaver); Yoshida (12, Sims); Duran, Ja (15, Sims). HR: Yoshida (7, 2nd inning off Weaver, 0 on, 0 out); Valdez, E (4, 5th inning off Weaver, 0 on, 1 out). TB: Devers 2; Duran, Ja 2; Refsnyder 2; Turner, J; Valdez, E 4; Verdugo 2; Wong; Yoshida 6. RBI: Devers (47); Duran, Ja (21); Valdez, E (11); Yoshida (31). 2-out RBI: Devers. Runners left in scoring position, 2 out: Duran, Ja; Valdez, E; Turner, J 3. GIDP: Yoshida. Team RISP: 2-for-8. Team LOB: 7.
FIELDING: E: Devers (5, throw). DP: (Hernández, K-Valdez, E-Turner, J).
Reds Pitchers IP H R ER BB K HR P-S ERA
Weaver 5.2 7 3 3 0 5 2 97-65 5.36
Gibaut (W, 5-1) 1.0 0 0 0 0 0 0 10-8 3.55
Young, Al (H, 8) 0.1 1 0 0 1 0 0 18-11 2.86
Sims (H, 5) 1.0 2 1 1 0 1 0 28-22 4.15
Farmer, B (S, 1) 1.0 0 0 0 0 1 0 16-8 2.60
Totals 9.0 10 4 4 1 7 2
Red Sox Pitchers IP H R ER BB K HR P-S ERA
Paxton 5.0 4 1 1 1 8 0 100-68 4.26
Crawford, K (H, 2) 0.2 1 1 1 2 0 0 24-12 3.52
Winckowski (L, 2-1)(BS, 3) 1.1 3 3 0 0 2 1 24-17 2.14
Martin 1.0 0 0 0 0 2 0 14-10 1.23
Pivetta 1.0 0 0 0 0 1 0 13-8 5.66
Totals 9.0 8 5 2 3 13 1
Game Info
HBP: Newman (by Pivetta).
Pitch timer violations: Weaver (pitcher).
Pitches-strikes: Weaver 97-65; Gibaut 10-8; Young, Al 18-11; Sims 28-22; Farmer, B 16-8; Paxton 100-68; Crawford, K 24-12; Winckowski 24-17; Martin 14-10; Pivetta 13-8.
Groundouts-flyouts: Weaver 6-3; Gibaut 2-1; Young, Al 1-0; Sims 0-1; Farmer, B 1-1; Paxton 2-3; Crawford, K 0-2; Winckowski 2-0; Martin 1-0; Pivetta 1-1.
Batters faced: Weaver 23; Gibaut 4; Young, Al 3; Sims 5; Farmer, B 3; Paxton 20; Crawford, K 5; Winckowski 7; Martin 3; Pivetta 4.
Inherited runners-scored: Gibaut 1-0; Young, Al 1-0; Winckowski 2-0.
Umpires: HP: Alan Porter. 1B: Jim Wolf. 2B: Mike Muchlinski. 3B: Sean Barber.
Weather: 79 degrees, Clear.
Wind: 2 mph, In From CF.
First pitch: 7:12 PM.
T: 3:02.
Att: 32,593.
Venue: Fenway Park.
May 31, 2023
Inning Scoring Play Score
Bottom 2 Umpire reviewed (home run), call on the field was upheld: Masataka Yoshida homers (7) on a fly ball to right field. 1-0 BOS
Bottom 3 Rafael Devers doubles (13) on a fly ball to left fielder Nick Senzel. Connor Wong scores. 2-0 BOS
Top 5 Luke Maile doubles (3) on a sharp fly ball to center fielder Jarren Duran. Jose Barrero scores. 2-1 BOS
Bottom 5 Enmanuel Valdez homers (4) on a fly ball to left center field. 3-1 BOS
Top 6 Nick Senzel singles on a line drive to center fielder Jarren Duran. Jonathan India scores. Spencer Steer to 2nd. 3-2 BOS
Top 7 Jonathan India grounds into a double play, shortstop Enrique Hernandez to second baseman Enmanuel Valdez to first baseman Justin Turner. Will Benson scores. Kevin Newman to 3rd. Matt McLain out at 2nd. Jonathan India out at 1st. 3-3
Top 7 Spencer Steer homers (8) on a fly ball to left center field. Kevin Newman scores. 5-3 CIN
Bottom 8 Jarren Duran doubles (15) on a ground ball to left fielder Jake Fraley. Masataka Yoshida scores. 5-4 CIN
Team Highlight
BOS Bullpen availability for Boston, May 31 vs Reds (00:00:07)
CIN Bullpen availability for Cincinnati, May 31 vs Red Sox (00:00:07)
BOS Fielding alignment for Boston, May 31 vs Reds (00:00:11)
BOS Starting lineups for Reds at Red Sox - May 31, 2023 (00:00:09)
CIN An animated look at Spencer Steer's home run (00:00:09)
BOS Masataka Yoshida's solo home run (7) (00:00:28)
BOS Rafael Devers' RBI double (00:00:20)
CIN Luke Maile's RBI double (00:00:27)
BOS Valdez's solo home run (4) (00:00:29)
CIN Nick Senzel's RBI single (00:00:17)
CIN Jonathan India's RBI groundout (00:00:26)
CIN Steer's go-ahead homer (8) (00:00:28)
BOS James Paxton K's eight (00:00:58)
BOS Jarren Duran's RBI double (00:00:32)
CIN Luke Weaver K's five (00:00:35)
CIN Nick Senzel records final out (00:00:13)
1 2 3 4 5 6 7 8 9 R H E LOB
Reds 0 0 0 0 1 1 3 0 0 5 8 1 7
Red Sox 0 1 1 0 1 0 0 1 0 4 10 1 7

Decisions

Division Scoreboard

TB 4 @ CHC 3 - Final
PIT 9 @ SF 4 - Final
MIL 4 @ TOR 2 - Final
Next Reds Game: Thu, Jun 01, 07:10 PM EDT @ Red Sox
Last Updated: 05/31/2023 10:25:34 PM EDT
submitted by RedsModerator to Reds [link] [comments]


2023.06.01 01:06 DoubleTriple14 luigi_irl

submitted by DoubleTriple14 to luigi_irl [link] [comments]


2023.05.31 23:10 RedsModerator Game Thread: Reds @ Red Sox - Wed, May 31 @ 07:10 PM EDT

Reds @ Red Sox - Wed, May 31

Game Status: Final - Score: 5-4 Reds

Links & Info

Reds Batters AB R H RBI BB K LOB AVG OBP SLG
1 Newman - 3B 4 1 2 0 0 0 0 .276 .343 .366
2 McLain - SS 5 0 2 0 0 1 3 .361 .426 .541
3 India - 2B 4 1 0 0 1 2 4 .282 .369 .426
4 Steer - 1B 3 1 1 2 1 1 1 .289 .356 .498
5 Stephenson, T - DH 4 0 0 0 0 2 2 .246 .336 .340
6 Fairchild - RF 2 0 0 0 0 2 0 .246 .343 .386
a-Fraley - LF 2 0 0 0 0 1 2 .248 .337 .399
7 Senzel - CF 4 0 2 1 0 1 0 .270 .341 .405
8 Barrero - CF 2 1 0 0 1 1 3 .231 .314 .347
Casali - C 1 0 0 0 0 1 0 .154 .254 .154
9 Maile - C 3 0 1 1 0 1 0 .259 .310 .481
1-Benson - RF 1 1 0 0 0 0 0 .152 .176 .212
Totals 35 5 8 4 3 13 15
Reds
a-Flied out for Fairchild in the 6th. 1-Ran for Maile in the 7th.
BATTING: 2B: Senzel (8, Paxton); Maile (3, Paxton). HR: Steer (8, 7th inning off Winckowski, 1 on, 2 out). TB: Maile 2; McLain 2; Newman 2; Senzel 3; Steer 4. RBI: Maile (6); Senzel (26); Steer 2 (28). 2-out RBI: Maile; Steer 2; Senzel. Runners left in scoring position, 2 out: McLain; Barrero 2. GIDP: India. Team RISP: 4-for-10. Team LOB: 7.
FIELDING: E: Casali (1, catcher interference). DP: (McLain-Steer).
Red Sox Batters AB R H RBI BB K LOB AVG OBP SLG
1 Verdugo - RF 5 0 2 0 0 0 1 .294 .368 .456
2 Devers - 3B 4 0 1 1 1 1 1 .246 .288 .498
3 Turner, J - 1B 4 0 1 0 0 1 4 .263 .351 .404
4 Yoshida - DH 4 2 2 1 0 0 1 .317 .391 .508
5 Refsnyder - LF 4 0 1 0 0 1 1 .284 .408 .383
6 Duran, Ja - CF 4 0 1 1 0 1 1 .292 .340 .467
7 Hernández, K - SS 3 0 0 0 0 1 0 .233 .308 .352
a-Tapia, R - PH 1 0 0 0 0 0 1 .274 .337 .381
Reyes, P - SS 0 0 0 0 0 0 0 .273 .314 .364
8 Valdez, E - 2B 3 1 1 1 0 1 1 .250 .302 .450
9 Wong - C 4 1 1 0 0 1 1 .243 .293 .470
Totals 36 4 10 4 1 7 12
Red Sox
a-Lined out for Hernández, K in the 8th.
BATTING: 2B: Devers (13, Weaver); Refsnyder (5, Weaver); Yoshida (12, Sims); Duran, Ja (15, Sims). HR: Yoshida (7, 2nd inning off Weaver, 0 on, 0 out); Valdez, E (4, 5th inning off Weaver, 0 on, 1 out). TB: Devers 2; Duran, Ja 2; Refsnyder 2; Turner, J; Valdez, E 4; Verdugo 2; Wong; Yoshida 6. RBI: Devers (47); Duran, Ja (21); Valdez, E (11); Yoshida (31). 2-out RBI: Devers. Runners left in scoring position, 2 out: Duran, Ja; Valdez, E; Turner, J 3. GIDP: Yoshida. Team RISP: 2-for-8. Team LOB: 7.
FIELDING: E: Devers (5, throw). DP: (Hernández, K-Valdez, E-Turner, J).
Reds Pitchers IP H R ER BB K HR P-S ERA
Weaver 5.2 7 3 3 0 5 2 97-65 5.36
Gibaut (W, 5-1) 1.0 0 0 0 0 0 0 10-8 3.55
Young, Al (H, 8) 0.1 1 0 0 1 0 0 18-11 2.86
Sims (H, 5) 1.0 2 1 1 0 1 0 28-22 4.15
Farmer, B (S, 1) 1.0 0 0 0 0 1 0 16-8 2.60
Totals 9.0 10 4 4 1 7 2
Red Sox Pitchers IP H R ER BB K HR P-S ERA
Paxton 5.0 4 1 1 1 8 0 100-68 4.26
Crawford, K (H, 2) 0.2 1 1 1 2 0 0 24-12 3.52
Winckowski (L, 2-1)(BS, 3) 1.1 3 3 0 0 2 1 24-17 2.14
Martin 1.0 0 0 0 0 2 0 14-10 1.23
Pivetta 1.0 0 0 0 0 1 0 13-8 5.66
Totals 9.0 8 5 2 3 13 1
Game Info
HBP: Newman (by Pivetta).
Pitch timer violations: Weaver (pitcher).
Pitches-strikes: Weaver 97-65; Gibaut 10-8; Young, Al 18-11; Sims 28-22; Farmer, B 16-8; Paxton 100-68; Crawford, K 24-12; Winckowski 24-17; Martin 14-10; Pivetta 13-8.
Groundouts-flyouts: Weaver 6-3; Gibaut 2-1; Young, Al 1-0; Sims 0-1; Farmer, B 1-1; Paxton 2-3; Crawford, K 0-2; Winckowski 2-0; Martin 1-0; Pivetta 1-1.
Batters faced: Weaver 23; Gibaut 4; Young, Al 3; Sims 5; Farmer, B 3; Paxton 20; Crawford, K 5; Winckowski 7; Martin 3; Pivetta 4.
Inherited runners-scored: Gibaut 1-0; Young, Al 1-0; Winckowski 2-0.
Umpires: HP: Alan Porter. 1B: Jim Wolf. 2B: Mike Muchlinski. 3B: Sean Barber.
Weather: 79 degrees, Clear.
Wind: 2 mph, In From CF.
First pitch: 7:12 PM.
T: 3:02.
Att: 32,593.
Venue: Fenway Park.
May 31, 2023
Inning Scoring Play Score
Bottom 2 Umpire reviewed (home run), call on the field was upheld: Masataka Yoshida homers (7) on a fly ball to right field. 1-0 BOS
Bottom 3 Rafael Devers doubles (13) on a fly ball to left fielder Nick Senzel. Connor Wong scores. 2-0 BOS
Top 5 Luke Maile doubles (3) on a sharp fly ball to center fielder Jarren Duran. Jose Barrero scores. 2-1 BOS
Bottom 5 Enmanuel Valdez homers (4) on a fly ball to left center field. 3-1 BOS
Top 6 Nick Senzel singles on a line drive to center fielder Jarren Duran. Jonathan India scores. Spencer Steer to 2nd. 3-2 BOS
Top 7 Jonathan India grounds into a double play, shortstop Enrique Hernandez to second baseman Enmanuel Valdez to first baseman Justin Turner. Will Benson scores. Kevin Newman to 3rd. Matt McLain out at 2nd. Jonathan India out at 1st. 3-3
Top 7 Spencer Steer homers (8) on a fly ball to left center field. Kevin Newman scores. 5-3 CIN
Bottom 8 Jarren Duran doubles (15) on a ground ball to left fielder Jake Fraley. Masataka Yoshida scores. 5-4 CIN
Team Highlight
BOS Bullpen availability for Boston, May 31 vs Reds (00:00:07)
CIN Bullpen availability for Cincinnati, May 31 vs Red Sox (00:00:07)
BOS Fielding alignment for Boston, May 31 vs Reds (00:00:11)
BOS Starting lineups for Reds at Red Sox - May 31, 2023 (00:00:09)
CIN An animated look at Spencer Steer's home run (00:00:09)
BOS Masataka Yoshida's solo home run (7) (00:00:28)
BOS Rafael Devers' RBI double (00:00:20)
CIN Luke Maile's RBI double (00:00:27)
BOS Valdez's solo home run (4) (00:00:29)
CIN Nick Senzel's RBI single (00:00:17)
CIN Benson scores on double play (00:00:26)
CIN Steer's go-ahead homer (8) (00:00:28)
BOS James Paxton K's eight (00:00:58)
BOS Jarren Duran's RBI double (00:00:32)
CIN Luke Weaver K's five (00:00:35)
CIN Nick Senzel catches final out (00:00:13)
CIN Reds vs. Red Sox Highlights (00:03:08)
1 2 3 4 5 6 7 8 9 R H E LOB
Reds 0 0 0 0 1 1 3 0 0 5 8 1 7
Red Sox 0 1 1 0 1 0 0 1 0 4 10 1 7

Decisions

Division Scoreboard

TB 4 @ CHC 3 - Final
PIT 9 @ SF 4 - Final
MIL 4 @ TOR 2 - Final
Last Updated: 06/01/2023 12:03:53 AM EDT
submitted by RedsModerator to Reds [link] [comments]


2023.05.31 20:30 FireballPlayer0 I’ll play Mario Kart with people if I get banned for 30 days (it won’t happen)

I’ll play Mario Kart with people if I get banned for 30 days (it won’t happen) submitted by FireballPlayer0 to 691 [link] [comments]


2023.05.31 18:05 LGBTQIA_Over50 Samsung Galaxy S9 with 5G (ATT prepay) isn't charging, does that mean I need a new phone?

I bought a new charger chord, and I am trying to charge my phone using the plug in the wall socket. It isn't the wall socket. I moved it to another socket where my computer charged up just fine. This phone was mailed to me by ATT when they converted over to the 5G.
I'm on an affordable phone program due to my poverty status and being out of work. Does this mean i need a new phone if it's not charging? I did buy a new charging cord. It was working fine up until yesterday. The phone charged inside my car yesterday.
ATT store employees don't like to offer help unless I'm buying a brand new phone. Since the phone was sent to me for FREE from ATT over a year ago, where do I take my phone to get help? And if in fact I do need to upgrade to a new phone,
Q: What model is comparable? Approximately how much is it out of pocket?
Q: Can ATT employees take my text & photos from this phone that won't charge and transfer it over to a new phone?
submitted by LGBTQIA_Over50 to samsunggalaxy [link] [comments]


2023.05.31 17:00 eeyorewinners Wildlife calendar

Wildlife calendar
The picture was in the newsletter.
Thought someone .ight appreciate having it for help.planning.
Nicre in one spot.
The present will be the o e if achieve the goal.
Thank you.
submitted by eeyorewinners to JunesJourney [link] [comments]


2023.05.31 16:38 MightyMCP Yahoo Mail Problem

I accidentally sent a bunch of my regular e-mails to spam. I immediately went into the Spam folder to reverse what I did. Since then, I am not receiving most of my usual e-mails at all. They are not in spam. They are not in trash. When I go to the Subscriptions tab, I still see them as active. So, I am pretty confident I did not hit Unsubscribe. And when I check my Blocked Senders list, they are not there. They are just not coming through at all. Any suggestions on what to do would be appreciated. Thanks!
submitted by MightyMCP to yahoo [link] [comments]


2023.05.31 12:58 NeverMindUsAll New feature added to The Groot search engine... 🔎 😎 😍 Get a nice and clean interface without the information bars... Click on the Groot icon to select your choice of interface!

New feature added to The Groot search engine... 🔎 😎 😍 Get a nice and clean interface without the information bars... Click on the Groot icon to select your choice of interface!
New feature added to The Groot search engine... 🔎 😎 😍
Get a nice and clean interface without the information bars...
Click on the Groot icon to select your choice of interface!
🌐 https://groot.ssuiteoffice.com/
SSuite Office Software
The Groot Search - New Feature

The Interface Selection Options

The Information Bars is full view...
https://www.ssuiteoffice.com
#searchon #searchengine #windows #android #iphone #ipad #technews #technologynews #weather #weatherforecast #weatherupdate #bitcoin #cryptos #streaming #entertainmentnews #worldnews #wednesday #wednesdayvibe #wendesdaymorning #studentlife #lifestyle #life #businesstips #businessnews
submitted by NeverMindUsAll to News_From_The_Edge [link] [comments]


2023.05.31 11:16 ExpressShow1175 Welp..

Welp..
Goes on to say they obviously will not be open to filming with the bozos...but...not up to them who returns...
submitted by ExpressShow1175 to Vanderpumpaholics [link] [comments]


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submitted by Special-Ad-6501 to u/Special-Ad-6501 [link] [comments]