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Sunday

  1. Story1 reports · 0 facts

    Google releases Gemini 3.5 Flash

    On May 19, 2026, Google DeepMind released the Gemini 3.5 series, debuting the Gemini 3.5 Flash model first. According to its introduction, the model scored 76.2% on Terminal-Bench 2.1, outputs at 4 times the speed of other frontier models, has been fully opened up, and has become the default model for the Gemini app and AI Mode in global Search; Gemini 3.5 Pro is planned for launch next month. On May 20, Google's Noam Shazeer said that Gemini 3.5's combination of performance and speed makes it suitable for long-horizon and agentic tasks. On the same day, separate reports said that Gemini Spark, a 24/7 personal AI agent powered by Gemini 3.5, can work across apps such as Docs, Calendar, and Slides, and keeps running after the computer is turned off, with rollout starting next week.

    On May 19, 2026, Google DeepMind released the Gemini 3.5 series, debuting the Gemini 3.5 Flash model first. According to its introduction, the model scored 76.2% on Terminal-Bench 2.1, outputs at 4 times the speed of other frontier models, has been fully opened up, and has become the default model for the Gemini app and AI Mode in global Search; Gemini 3.5 Pro is planned for launch next month. On May 20, Google's Noam Shazeer said that Gemini 3.5's combination of performance and speed makes it s

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Saturday

  1. Cailianshe

    AI-driven cyberattacks erupt intensively; industry insiders call October a "Black October" for cybersecurity

    Cailianshe reported that in recent weeks hackers have massively deployed AI agents and automated tools to launch attacks, and industry insiders describe this month as Black October in the cybersecurity world. A major vulnerability was exposed in PHP, and as many as 70% of websites worldwide may face the risk of being hacked. The U.S. National Security Agency and the FBI warned enterprises to shut down their websites if they cannot patch immediately, and some government websites in Canada, Belgium, France and the Netherlands have proactively gone offline. Shane Fry, chief technology officer of security firm RunSafe Security, said AI can weaponize a vulnerability into attack code within hours, whereas in the past this took weeks or even months.

    Cailianshe reported that in recent weeks hackers have massively deployed AI agents and automated tools to launch attacks, and industry insiders describe this month as Black October in the cybersecurity world. A major vulnerability was exposed in PHP, and as many as 70% of websites worldwide may face the risk of being hacked. The U.S. National Security Agency and the FBI warned enterprises to shut down their websites if they cannot patch immediately, and some government websites in Canada, Belgiu

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    #chinese#English text is being prepared.#Safety / alignment#Agents

Friday

  1. TMTPost · AGI

    Pichai Reviews Gemini 4 Argon: Why 3.5 Pro Was Cut

    Google CEO Pichai revealed in the "Sources" interview that Gemini 4 Argon processed about 25 trillion tokens in 72 hours of launch, 3 times that of Gemini 3.0 in the same period, and is still rate-limited due to compute constraints. He explained for the first time the reason for cutting Gemini 3.5 Pro: the team found a gap in the model on Agentic Coding, first used the Flash version to complete intensive iterations from 3.5 to 3.8 in about 3 months, while Argon pretraining had already been completed at that time, so they injected the accumulated gains into Argon post-training. He also mentioned that Google internally has entered the RSI stage of researchers and models collaborating, and said the next-generation Gemini 5.0 will be much stronger than Argon.

    Google CEO Pichai revealed in the "Sources" interview that Gemini 4 Argon processed about 25 trillion tokens in 72 hours of launch, 3 times that of Gemini 3.0 in the same period, and is still rate-limited due to compute constraints. He explained for the first time the reason for cutting Gemini 3.5 Pro: the team found a gap in the model on Agentic Coding, first used the Flash version to complete intensive iterations from 3.5 to 3.8 in about 3 months, while Argon pretraining had already been compl

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    #hot-signal#Industry news#Google#DeepMind

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