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Google BERT Update – What it Means

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Google announced what they called the most important update in five years. The BERT update impacts 10% of search queries. What is BERT and how will it impact SEO?

BERT is a Major Google Update

According to Google this update will affect complicated search queries that depend on context.

This is what Google said:

“These improvements are oriented around improving language understanding, particularly for more natural language/conversational queries, as BERT is able to help Search better understand the nuance and context of words in Searches and better match those queries with helpful results.

Particularly for longer, more conversational queries, or searches where prepositions like “for” and “to” matter a lot to the meaning, Search will be able to understand the context of the words in your query. You can search in a way that feels natural for you.”

What is the BERT Algorithm?

Search algorithm patent expert Bill Slawski (@bill_slawski of @GoFishDigital) described BERT like this:

“Bert is a natural language processing pre-training approach that can be used on a large body of text. It handles tasks such as entity recognition, part of speech tagging, and question-answering among other natural language processes. Bert helps Google understand natural language text from the Web.

Google has open sourced this technology, and others have created variations of BERT.”

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The BERT algorithm (Bidirectional Encoder Representations from Transformers) is a deep learning algorithm related to natural language processing. It helps a machine to understand what words in a sentence mean, but with all the nuances of context.

BERT And On Page SEO

I asked search algorithm expert Dawn Anderson (@dawnieando on Twitter) what that meant for SEOs and she responded that it won’t help websites that are poorly written.

According to Dawn:

“BERT and family improve the state of the art on 11 natural language processing tasks. Even beating human understanding since linguists will argue for hours over the part of speech a single word is.

But what if the focus of a page is very weak? Even humans sometimes will be like “what’s your point?” when we hear something.

And pronouns have been very problematic historically but BERT helps with this quite a bit. Context is improved because of the bi-directional nature of BERT.

There will still be lots of work for us to do since we need to emphasise importance, utilise clear structures, help to turn unstructured data into semi structured data, utilise cues on content light pages (e.g. image heavy but not text heavy eCommerce pages) using such things as internal linking.”

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BERT Improves Search Query Understanding

Google’s BERT Update improves how Google understands search queries. BERT analyzes search queries, not web pages. However, as Dawn said, on page SEO becomes more important in terms of using words in precise ways. Sloppy content may not be helped by the Google BERT update.

Dawn Anderson observed:

“It’s knocking human understanding out of the water in loads of natural language understanding tasks. BERT is like a WordPress plugin which is a starting point and then they customise it and improve it.

The word “rose” means several things but it’s exactly the same word. The context must accompany the word otherwise the word means nothing.”

Dawn is correct. During the course of researching a presentation I was to give at PubCon Vegas 2019, I did a search for a tricky phrase that relied on context to get it right.

An Example of Context and BERT

The phrase was “how to catch a cow fishing?

In New England, the word “cowin the context of fishing means a large striped bass.

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A striped bass is a popular saltwater game fish that millions of anglers fish for on the Atlantic coast.

So I typed the phrase, “how to catch a cow fishing” and Google provided results related to livestock, to cows.

Even though I had purposely used the word “fishing” to provide context, Google ignored that context and provided results related to cows. That was on October 1, 2019.

Today, October 25, 2019 the same query results in search results that are full of striped bass and fishing related results.

The BERT algorithm appeared to have understood the context of the word “fishing” as important and changed the search results to focus on fishing related web pages.

Dawn Anderson explained that new search result like this:

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“Bass means different things. There are different meanings for the single words. The context around the word provides more meaning.”

She’s right. That’s exactly what Google did in the search query, “how to catch a cow fishing.” BERT appears to have used the word “fishing” to add context to that search query.

BERT May Be Just the Beginning

Dawn Anderson said:

“A researcher I know used BERT in his work with assistants, e.g. similar to Google Assistant, to test the use of clarifying questions. So it has many uses. It’s just a starting point.”

I asked:

“So you see this as one step in a longer journey?”

And Dawn replied:

“Yes, but it’s a big step. Huge… It’s like a quantum leap huge.”

I agree. I wouldn’t go out and create thousands of longtail phrases to try to capitalize on Google’s ability to understand context better.

However, like Dawn, I see this as an opportunity to bring more traffic with content that is more focused and well organized.

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Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

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A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

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The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator

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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

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Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

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Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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GOOGLE

Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

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Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

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While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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