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Bill Lambert is Not Real – Claims of Google Filters Likely False

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bill lambert is not real claims of google filters likely false via martinibuster

There’s been discussion about a Google insider who claims Google filters traffic from publishers. Is Google filtering website traffic? As fringe as that idea sounds, there actually is a Google patent on filtering web results.

Bill Lambert is Not Real

This article was published several hours before Mueller tweeted the following denial. Added as an update.

As I suspected and this article concluded, John Mueller confirmed that the persona known as Bill Lambert is not a Google contractor with access to inside information.

Consider anything sourced from that persona to be misinformation. 

Bill Lambert Google

Claim that Google Filters Traffic

A WebmasterWorld discussion about Google’s broad core algorithm update quoted someone who claims inside knowledge about filters designed to take away publisher traffic.

In the quote they said:

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“Bill Lambert: “As I explained, prior to an update you will see traffic & metrics like you are used to. This is because while the core algo is updated the various “filters” designed to take your traffic away are not live. While the update rolls you will see flux.

Post update you will see traffic levels around where they were prior to the update BUT these will slowly drop away. We are still in filter drop mode. Geo targeting will be out for the next few days too (as it was last week with the test).”

If you listen to Googlers and read patents and research papers, you will not find evidence of a Google filters that takes “your traffic away.”

But there is a patent about filtering the search results.

Google Filter Algorithm Patent

The Google patent is called, Filtering in Search Engines

The research focused on satisfying user intent and information needs by filtering the search results.

This is how the paper describes the problem:

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“…given the same query by two different users, a given set of search results can be relevant to one user and irrelevant to another, entirely because of the different intent and information needs.”

The research paper then states that a problem with identifying user intent is that user intent varies by user.

“Most attempts at solving the problem of inferring a user’s intent typically depend on relatively weak indicators, such as static user preferences, or predefined methods of query reformulation that may be educated guesses about what the user is interested in based on the query terms.

Approaches such as these cannot fully capture user intent because such intent is itself highly variable and dependent on numerous situational facts that cannot be extrapolated from typical query terms.”

The proposed solution is to filter the results “based on content sought by a user.

Then it describes a method of filtering results based on content in the URL, like the word “reviews” which signals that the page may satisfy the user intent.

The paper proposes creating a database that has a label that represents the search query and URLs containing words that match that search query.

“Annotation database… may contain a large collection of annotations. Generally, an annotation includes a pattern for a uniform resource locator (URL) for the URLs of documents, and a label to be applied to a document whose URL matches the URL pattern. Schematically, an annotation may take the form:

<label, URL pattern>

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where label is a term or phrase, and URL pattern is a specification of a pattern for a URL.

For example, the annotation

<“professional review”, www.digitalcameraworld.com/review/>

would be used to apply the label “professional review” to any document whose URL includes a prefix matching the network location “www.digitalcameraworld.com/review/”. All documents in this particular host’s directory are considered by the provider of the annotation to be “professional review(s)” of digital cameras.”

I recall seeing something like this with two word search queries shortly after the Caffeine update. It looked like Google was excluding commercial sites for a specific SERP that used to feature commercial sites. After Caffeine it was preferring government and educational research related pages.

Except for one commercial site. One commercial site was still ranking.

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That site had the word “/research” in the URL. Strange, right?

Google Filter Algorithm is Not About Taking Away Traffic

That patent is about satisfying user intent. It’s not about taking traffic away from publishers.

The idea of a Google algorithm that deprives users of traffic is part of an old myth. This myth holds that Google is purposely making it’s search results poor in order to increase ad clicks.

That myth is typically spread by SEOs whose sites have suffered in the search results and haven’t recovered. In my opinion it’s easier to blame Google of bad intents than it is to admit that maybe the SEO strategy is lacking. After all, commercial sites still rank for commercial queries.

The idea that Google filters traffic to help ad clicks is a myth. All information retrieval research and patents I have read focus on satisfying users. Google can’t win by being a poor search engine.

Only SEOs Talk About Google Filters

Filtering is an SEO viewpoint. Filtering is how an SEO sees things from their point of view.

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Remember the theory of the Sandbox? SEOs believed that the algorithm was filtering websites that were new or that Google was filtering sites that had affiliate ads.

At the time, the SEO strategy was to create a website and link it up with directory links, reciprocal links and/or link bait viral links.

As we know now, Google was neutralizing the influence of those kinds of links. So it’s likely, in my opinion, that the filtering that SEOs thought they were looking at was really the effect of their outdated link building strategies.

The point is that “filtering” is culturally an SEO way of seeing things. It’s related to the word “targeting” in that SEOs tend to believe that Google “targets” certain kinds of sites in order to “filter” them out of the SERPs.

That is not not how Google describes their algorithms.

How Google Works

Google’s research and patents tend to focus on relevance.

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  1. Understanding search queries
  2. Matching web pages to search queries

To drastically simplify how Google works, there are four basic parts to a search engine:

Google’s search engine has at least these four parts:

  1. Crawl Engine
    Crawl engine is what crawls your site.
  2. Indexing Engine
    Indexing engine represents the document set
  3. Ranking Engine
    Ranking engine is where the ranking factors live
  4. Modification engine
    The modification engine is where other factors related to personalization, geographic/time related factors, user intent and possibly fact checking.

All of those engines do many things but filtering traffic to web publishers is not one of them.

Google Filters are an SEO Idea

From the outside, to an SEO, it might look like Google is filtering. But when you read the research papers and patents, it’s really about satisfying user intent, about relevance.

Maybe the link algorithm contains processes that identify suspicious link patterns. But that’s not the “filter” being talked about.

It’s a misnomer to call them filters. Research papers and patents, especially the most recent ones, do not refer to filters or filtering.

Filters are exclusively an SEO idea. It’s how some in the SEO community perceive what Google is doing.

That is one reason among many why it seems likely to me that the so-called insider is not really an insider.

Relevance is a Google Focus

Research and patents focus on relevance. The idea that Google filters search results to keep “traffic away” is outside of accepted knowledge about Google.

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The claim can be accurately described as surreal.

It’s safe to say that Google ranks websites from the point of view of relevance, not filtering.

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We asked ChatGPT what will be Google (GOOG) stock price for 2030

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We asked ChatGPT what will be Google (GOOG) stock price for 2030

Investors who have invested in Alphabet Inc. (NASDAQ: GOOG) stock have reaped significant benefits from the company’s robust financial performance over the last five years. Google’s dominance in the online advertising market has been a key driver of the company’s consistent revenue growth and impressive profit margins.

In addition, Google has expanded its operations into related fields such as cloud computing and artificial intelligence. These areas show great promise as future growth drivers, making them increasingly attractive to investors. Notably, Alphabet’s stock price has been rising due to investor interest in the company’s recent initiatives in the fast-developing field of artificial intelligence (AI), adding generative AI features to Gmail and Google Docs.

However, when it comes to predicting the future pricing of a corporation like Google, there are many factors to consider. With this in mind, Finbold turned to the artificial intelligence tool ChatGPT to suggest a likely pricing range for GOOG stock by 2030. Although the tool was unable to give a definitive price range, it did note the following:

“Over the long term, Google has a track record of strong financial performance and has shown an ability to adapt to changing market conditions. As such, it’s reasonable to expect that Google’s stock price may continue to appreciate over time.”

GOOG stock price prediction

While attempting to estimate the price range of future transactions, it is essential to consider a variety of measures in addition to the AI chat tool, which includes deep learning algorithms and stock market experts.

Finbold collected forecasts provided by CoinPriceForecast, a finance prediction tool that utilizes machine self-learning technology, to anticipate Google stock price by the end of 2030 to compare with ChatGPT’s projection.

According to the most recent long-term estimate, which Finbold obtained on March 20, the price of Google will rise beyond $200 in 2030 and touch $247 by the end of the year, which would indicate a 141% gain from today to the end of the year.

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2030 GOOG price prediction: Source: CoinPriceForecast

Google has been assigned a recommendation of ‘strong buy’ by the majority of analysts working on Wall Street for a more near-term time frame. Significantly, 36 analysts of the 48 have recommended a “strong buy,” while seven people have advocated a “buy.” The remaining five analysts had given a ‘hold’ rating.

1679313229 737 We asked ChatGPT what will be Google GOOG stock price
Wall Street GOOG 12-month price prediction: Source: TradingView

The average price projection for Alphabet stock over the last three months has been $125.32; this objective represents a 22.31% upside from its current price. It’s interesting to note that the maximum price forecast for the next year is $160, representing a gain of 56.16% from the stock’s current price of $102.46.

While the outlook for Google stock may be positive, it’s important to keep in mind that some potential challenges and risks could impact its performance, including competition from ChatGPT itself, which could affect Google’s price.


Disclaimer: The content on this site should not be considered investment advice. Investing is speculative. When investing, your capital is at risk.

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This Apple Watch app brings ChatGPT to your wrist — here’s why you want it

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Apple Watch Series 8

ChatGPT feels like it is everywhere at the moment; the AI-powered tool is rapidly starting to feel like internet connected home devices where you are left wondering if your flower pot really needed Bluetooth. However, after hearing about a new Apple Watch app that brings ChatGPT to your favorite wrist computer, I’m actually convinced this one is worth checking out.

The new app is called watchGPT and as I tipped off already, it gives you access to ChatGPT from your Apple Watch. Now the $10,000 question (or more accurately the $3.99 question, as that is the one-time cost of the app) is why having ChatGPT on your wrist is remotely necessary, so let’s dive into what exactly the app can do.

What can watchGPT do?

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Discord goes all in with AI: chatbots, automods, whiteboards and more

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Discord goes all in with AI: chatbots, automods, whiteboards and more

AI is the future, at least over on Discord.

The messaging application originally made for gamers has become Gen Z’s favorite online hangout destination of choice, and now it’s rolling out a number of features powered by artificial intelligence.

In an announcement(Opens in a new tab) on Thursday, Discord shared what’s coming to the platform soon: an AI chatbot, an automated AI moderator, a conversation summarizer, an avatar remixer, and a whiteboard. Some of these features begin rolling out today, March 9. Others will launch in the coming weeks and months.

While AI has jumped into the mainstream thanks to the popularity of OpenAI’s ChatGPT chatbot, Discord has had an active AI community for quite a while now. According to the company, third-party AI apps already on the platform already have more than 30 million monthly users. Nearly 3 million servers on Discord have some AI element integrated into the community.

In fact, the biggest community on Discord is Midjourney, a text-to-image AI project which allows users to generate art from right within the server. Discord says Midjourney’s server has more than 13 million members.

So, with AI being such an integral part of Discord already, it seemed like only a matter of time before Discord itself started bringing AI directly into the platform.

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images

AutoMod AI
Credit: Discord

The first feature coming to some Discord servers as soon as today is AutoMod AI. Discord already has an AutoMod feature, which basically automatically moderates rooms for admins based on the rules of the server. Discord has now integrated OpenAI-powered AI into AutoMod, allowing it to search the server and contact moderators when it thinks rules are possibly being broken. According to Discord, AutoMod AI can also consider the context of a conversation so, for example, users don’t get penalized for posts that are misconstrued.

Clyde is a bot that Discord users may already be familiar with, and starting next week, Clyde is getting an AI upgrade. Currently, the Clyde bot provides information, such as server error messages, and also responds to timeout or ban requests from users and mods. However, that’s pretty much all Clyde was able to do. Until now.

Clyde chatbot

Clyde
Credit: Discord

Clyde will now be able to answer all sorts of questions from users, much like OpenAI’s ChatGPT chatbot. Users simply have to type “@Clyde” followed by their prompt. Clyde will be able to pull up information and also help find specific emojis or GIFs based on a user’s description.

Another AI feature coming to Discord next week is Conversation Summaries. Again, the name is fairly descriptive of what it does. With users all over the world, many Discord channels are always moving regardless of time of day. Conversation Summaries will allow users to catch up on what they missed on a Discover Server. The AI-powered feature will “bundle” chats into topics so users can easily read up on what they find most interesting.

Conversation Summaries

Conversation Summaries
Credit: Discord

Starting today, developers can start playing with Avatar Remix, an open-source Discord app that integrates AI art into the messaging app. Avatar Remix allows users to take a fellow user’s avatar and change it up “using the power of generative image models.” What does that mean? In the demo that Discord showed Mashable, a user was able to add a party hat or a mustache to a friend’s avatar by simply mentioning their username and describing what changes they’d like to make.

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Avatar Remix

Avatar Remix
Credit: Discord

The company is also launching an “AI incubator,” offering support for developers creating AI-powered apps on Discord.

Finally, Discord revealed a feature that’s coming soon that has long been requested by the Discord community: a whiteboard. But, of course, this won’t be just any collaborative whiteboard feature. It’s going to be AI-powered, allowing users to collaborate in generating AI art and more.

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