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How 500 Error Codes Can Impact Google Indexing

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How 500 Error Codes Can Impact Google Indexing

Google’s John Mueller answered a question about at what point will 500 error response codes cause Googlebot to crawl content less often. Mueller explained scenarios where 500 response codes won’t affect crawling and when they may cause pages to drop from Google’s index.

Accidentally Blocked Googlebot and Caused 500 Errors

The person asking the question explained that their content delivery system was set up to block bad bots while allowing actual human users and legit bots to browse the site.

Everything was working fine until they updated their “server monitoring suite” and apparently the previous bot blocking filters and settings weren’t carried over to the new system.

Afterward they noticed that Google Search Console began listing 500 error response codes in response to Googlebot crawling.

The person finished explaining what happened then asked the question:

“The question came up from our technology team whether this represented real user impact and why we would look specifically at Googlebot and not real user metrics to prove that there’s an issue here.

So, given that context, I have a few questions.

The first is just to get the technology concern out …of the way.

From your perspective, how does Googlebot view 500 series errors and could you give any clarity on established …thresholds at which point Googlebot will …crawl source content …less, based on those errors?”

What is a 500 Error Code?

Servers communicate a variety of status response codes to browsers and bots. These response codes communicate, for example, whether the request for a page was successful, redirected to another page, blocked or unsuccessful.

  • The 200 response code communicates that the request for a web page was successful.
  • The 500 response code means that the request for a web page was unsuccessful.

The formal name of the 500 response code is:

"500 Internal Server Error"

There are other versions of the 500 response code that communicate a specific reason why the request for a web page was unsuccessful.

The 500 response code is somewhat generic in that it simply means that the page request was unsuccessful. But it often means that the server was down but not always.

Google Search Console and 500 Error Responses

It’s a good idea to monitor the Search Console for 500 Error Responses because they are a strong indicator that something is wrong.

Sometimes it could mean that the server is under heavy load, for example from too many bots and because of that it is unable to serve web pages.

In this case it appears that the problem was due to a misconfiguration in the Content Delivery Network (CDN) that inadvertently blocked Google from accessing web pages.

How Googlebot Indexing is Affected by 500 Errors

Mueller provided a helpful explanation of the steps Google takes in response to 500 error codes and how eventually continued errors could lead to those web pages being dropped from Google’s search index.

Google’s John Mueller responded:

“We don’t have any strong thresholds on that.

But essentially what happens with 500 errors is we’ll try to retry them.

And if we continue to see …the 500 errors then we will …slow down crawling.

And if we continue to see that there are 500 errors then we will drop those URLs from the index.

So that’s something if every now and then individual pages have a 500 error, it’s like no big deal.

We will retry them, they’ll remain indexed and the next time we retry them that’s fine.”

Next, Mueller explains that the reason Googlebot slows down the crawling is in case Googlebot itself is causing the server to overload.

“But if a large part of a site consistently has 500 errors and we might assume that maybe we’re causing the problem and we’ll slow down crawling of the whole site and at some point we’ll say well, it looks like these pages are really gone, we’re going to drop them.

So that’s essentially the effects that you would see there and if you’re talking about a large site and wondering like what percentage of 500 errors is okay… I don’t know.

My feeling is if you’re seeing something more than one percent then that sounds like something is kind of broken and probably would be something where we would start to slow down.

But I don’t think we have any hard thresholds where we’d say, this many requests and this many errors means this much slowing down.”

Monitor Search Console for 500 Errors

It’s up to every publisher to decide what their daily routine is. For some people checking the search console once a week is enough. Some may find it reassuring to check Search Console once a day in order to respond to unforeseen circumstances.

In any case, 500 error codes is something to monitor Search Console for. As John Mueller mentioned, large-scale 500 errors could be a flag that something is wrong and in need of immediate attention.

Citations

World Wide Web Consortium (W3C) List of Server Response Codes

How Does Google Respond to 500 Response Codes?
Watch the discussion at the 13:48 minute mark

Searchenginejournal.com

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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.

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.

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.

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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