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Google Is Creating A New Core Web Vitals Metric

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In a recent HTTPArchive Almanac article about CMS use worldwide, the author mentioned that all platforms score great on the First Input Delay (FID), a Core Web Vitals metric and that Google is working on a new metric, which one might presume may replace First Input Delay (FID).

Every year the HTTPArchive publishes multiple articles about the state of the web. Chapter 16 is about content management systems (CMS). The article was written by a Backend Group Manager and Head of Web Performance Wix engineer and reviewed and analyzed by various Googlers and others.

The article raised an interesting point about how the First Input Delay metric has lost meaning and mentioned how Google was developing a new metric.

First Input Delay

Core Web Vitals are a group of user experience metrics designed to provide a snapshot of how well web pages perform for users and First Input Delay (FID) is one of those metrics.

FID measures how fast a browser can respond to user interaction with a website, like how long it takes for a response to happen when a user clicks a button on a website.

The thing about FID is that all major content management systems, like WordPress, Wix, Drupal and others all have lightning fast FID scores.

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Everyone Wins An FID Trophy

The article first mentions that most CMS’s score exceptionally well for FID. And the platforms that score less well still have relatively high scores that lag behind by only 5 percentage points.

The author wrote:

“FID is very good for most CMSs on desktop, with all platforms scoring a perfect 100%. Most CMSs also deliver a good mobile FID of over 90%, except Bitrix and Joomla with only 83% and 85% of origins having a good FID.”

What’s happened to FID is that it’s basically a metric where everyone gets a trophy. If almost all sites score exceptionally well, if everyone gets a trophy, then that means there really isn’t much of a reason for the metric to exist because the goal of getting this part of the user experience fixed has been reached.

The article then mentions how Google (the Chrome team) is currently creating a new metric for measuring responsiveness and response latency.

The article continued:

“The fact that almost all platforms manage to deliver a good FID, has recently raised questions about the strictness of this metric.

The Chrome team recently published an article, which detailed the thoughts towards having a better responsiveness metric in the future.”

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Input Response Delay Versus Full Event Duration

The article linked to a recent Google article published on Web.dev titled, Feedback wanted: An experimental responsiveness metric.

What’s important about this article is that it reveals that Google is working on a new input delay metric. Knowing about this metric can give a head start to preparing for what is coming in the future.

The main point to understand about this new metric is that it isn’t measuring just single interactions. It is measuring groups of individual interactions that are part of a user action.

While the article cited in HTTPArchive cited a November 2021 article that asks for publisher feedback, this new metric has been under development for awhile now.

A June 2021 Web.dev article outlined these goals for the new measurement:

“Consider the responsiveness of all user inputs (not just the first one)

Capture each event’s full duration (not just the delay).

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Group events together that occur as part of the same logical user interaction and define that interaction’s latency as the max duration of all its events.

Create an aggregate score for all interactions that occur on a page, throughout its full lifecycle.”

The Web.dev article states that the goal is to design a better metric that encompasses a more meaningful measurement of the user experience.

“We want to design a metric that better captures the end-to-end latency of individual events and offers a more holistic picture of the overall responsiveness of a page throughout its lifetime.

…With this new metric we plan to expand that to capture the full event duration, from initial user input until the next frame is painted after all the event handlers have run.

We also plan to measure interactions rather than individual events. Interactions are groups of events that are dispatched as part of the same, logical user gesture (for example: pointerdown, click, pointerup).”

It’s also explained like this:

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“The event duration is meant to be the time from the event hardware timestamp to the time when the next paint is performed after the event is handled.

But if the event doesn’t cause any update, the duration will be the time from event hardware timestamp to the time when we are sure it will not cause any update.”

Two Approaches To Interaction Latency Metric

Web.dev explains that the Chrome engineers are exploring two approaches for measuring the interaction latency:

  1. Maximum Event Duration
  2. Total Event Duration

Maximum Event Duration

An interaction consists of multiple events of varying durations. This measurement bases itself on the largest duration out of a group.

Total Event Duration

This is a sum of all the event durations.

FID Is Likely Going Away?

It’s possible that FID could remain as part of Core Web Vitals but what’s the point if ever site scores 100% on it?

For that reason, it’s not unreasonable to assume that FID is going away sometime in the relatively near future.

The Chrome team is soliciting feedback on different approaches to measuring interaction latency. Now is the time to speak up.

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Citations

HTTPArchive Web Almanac: CMS

Feedback wanted: An experimental responsiveness metric

Towards a better responsiveness metric

Searchenginejournal.com

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AI

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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