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PageSpeed Insights Now Shows More Field Data

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PageSpeed Insights Now Shows More Field Data

PageSpeed Insights and the API have been updated to now show more field data than before. The updated PageSpeed Insights scoring is live and should reflect the new way of handling field data.

PageSpeed Insights previously only displayed the field data if all of the field data was collected.

This was problematic because 30% of web pages don’t record one of the metrics, First Input Delay (FID).

Field Data in PageSpeed Insights

Field data is the page speed metrics of real users that Google collects through Chrome mobile browsers that have opted-in to sending anonymized performance information from site visitor’s actual experience on a web page, which is then used for calculating the page speed metrics.

Lab data is what is used in Google Lighthouse, a tool that is used to estimate what a PageSpeed score may be.

Lighthouse ships in the Chrome browser and powers the dev tools.

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Right clicking any where on a web page opens up Chrome Dev Tools and from there Lighthouse can be used to simulate what the PageSpeed metrics are.

But these are only simulations, estimates, of what the values may be.

The actual data that Google may use for ranking purposes is called Field Data and that’s the data that is collected from real users downloading actual pages on mobile devices under real circumstances.

Available Field Data is Now Shown

The change Google made in the PageSpeed Insights API and the tool is that Google will show the field metrics that have been collected, even if other field data has not been collected.

Previously Google would only report if all the data that has been collected met a specific threshold of data.

According to Google’s Rick Viscomi on Twitter, he calls this a big deal because the missing data happens to 30% of origins in the Chrome User Experience Report where the First Input Delay data is missing, while the other data was there.

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“Previously you’d see “no data” if you were just missing FID data. Now you’ll see whatever is available.

This is a big deal because ~30% of origins in CrUX were missing FID data!”

Why Does First Input Delay (FID) Go Missing?

First Input Delay is a metric that measures the responsiveness of a website by measuring the delay in processing an event like clicking a button, tapping on a menu or entering data with a keyboard press and the time it takes for the web page to respond.

Scrolling and zooming in on text or images do not count as an interaction with the web page.

According to Google’s Web.dev page on FID, many users do not interact with a web page and for that reason the Chrome User Experience Report (CrUX) will not have this metric recorded.

“Not all users will interact with your site every time they visit. And not all interactions are relevant to FID…

…FID is a metric that can only be measured in the field, as it requires a real user to interact with your page.”

Rick Viscomi explained in a follow up tweet why First Input Delay (FID) tends to go missing: 

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“FID is especially prone to be absent because, unlike other Web Vitals, it relies on a user interaction to be measured. Nearly all page views incur an LCP or CLS, but not all of them have user interactions!”

This is a positive step from Google because the additional information will allow more publishers to make better decisions on what needs to be fixed in relation to PageSpeed metrics.

This is how Google’s official announcement explained it:

“PageSpeed Insights field data is now provided for pages and origins that might have insufficient data for a metric, but sufficient data for other metrics.

Previously, field data was only surfaced if all metrics for a page or origin met a threshold of data.

Now, any metric that meets the data threshold will be provided.

This is reflected in the loadingExperience and originLoadingExperience objects in the API, and also in the frontend.”

Good News for Web Publishers, Developers and SEOs

This is great news for publishing community because field data reflects the actual site visitor user experience on a web page.

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The more field data information publishers have the more accurate and complete action can be taken to fix real world problems.

Video Illustrating How First Input Delay is Measured

Citations

Release Notes for PageSpeed Insights API and PageSpeed Insights UI

Differences Between Field Data in PSI and CrUX

Google Web.dev Page on First Input Delay (FID)
What If a User Never Interacts With Your Site?

PageSpeed Insights API Documentation

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PageSpeed Insights Tool

How to Open Chrome Dev Tools

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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’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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