Linux Torvalds expects Linux 7.2 should be released next weekend "unless something really bad pops up," Torvalds said while announcing today's release candidate. But there's something interesting about Linux 7.2-rc7, writes Phoronix. "By the time the Linux kernel typically hits a -rc7 release things have usually settled quite well. But in today's world of AI/LLM coding/review agents, the kernel activity continues at an all-time high." Tons of bug fixes continued to trickle in across the kernel spectrum for all sorts of issues. The HWMON hardware monitoring subsystem saw several critical and high severity bug fixes, on the memory management side was a nasty race condition leading to a use-after-free in the kernel for the past eight years, Btrfs restored its fixup worker infrastructure to deal with silent data loss, lots of AI patches in the networking realm, and the kernel was patched for the Safe RET Interrupt Vulnerability. Linus Torvalds wrote in the 7.2-rc7 announcement: "Another week, another -rc. I can't say that I'm exactly thrilled about the size of this all, but it is what it is: the new normal with a lot of fixes, many of them due to review by various AI tools. And nothing looks particularly scary per se — it's just that there's a lot here. Most of it is fairly small, although we have a couple of larger diffs: s390/zcrypt fixes stand out in the diffstat, and so does btrfs bringing back the fixup worker infrastructure. And some netfilter ipset fixes. But aside from a few places like that, most of this is just lots of tiny fixes. It's pretty much spread all over — drivers (gpu, sound, networking, you name it), filesystems, core networking, arch code...

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XDA Developers reports: On July 22, a Google DeepMind engineer, Vidy Thatte, shared a snippet of a browser he built that "treats every URL as a prompt and generates a site from scratch" on his X account. Just a few days later, he shared a TestFlight link to let iPhone users try it for themselves. The browser he launched is called Gem, and it's a browser that doesn't really...browse. Instead of fetching a webpage from a server the way Chrome or Safari would, Gem hands whatever URL you type over to Google's Gemini 3.5 Flash Lite model and asks it to generate a webpage on the spot. If you enter a real address, it builds its own interpretation of that site rather than loading the actual thing. If you enter an address that doesn't exist, Gemini simply invents a website to fill the gap. In other words, you're not visiting the internet so much as browsing one the model dreams up as you go... Thatte's reasoning was that with a model as fast and cheap as Gemini 3.5 Flash Lite, there's almost no practical difference anymore between loading a website and generating a brand-new one on the fly... Given that this tool is powered by Gemini 3.5 Flash Lite and it's just a side project rather than a full-fledged tool, it doesn't come with Gemini access baked in. Gem requires you to bring your own Gemini API key to get it working. Every URL you enter fires off a request to the model, so Gem needs a key linked to your Google account to actually generate anything, with the usage billed to you. You can grab a key for free from Google AI Studio, paste it into Gem's settings, and you're ready to start typing URLs. While you can get started for free, I ran into the limits within two minutes of playing around. So, I did need to enable billing on my API key and decided to load $10 into it. While the blogger's own site seemed to only get the Gemini logo, tapping it revealed nearly two dozen remixing options. (Dark mode, Reader, Neubrutalist, Broadsheet, Blueprint, Comic book, Punk zine, Notebook, Chalkboard, Receipt, Teletext, System 7, Wes Anderson, Cyber neon, Clay, Frosted, Geocities, Matrix, Museum, Windows 95, Terminal, Vaporwave, and Hide images...) "The frontend morphed before my eyes. Every new edit took practically no time to load, and within a second or two, the same XDA articles would reappear wearing a completely different skin..." For another site, it kept the article headlines, but then rewrote all the text! And after entering an address they knew didn't exist — their own name — in two seconds the browser whipped up a slick portfolio "genuinely been better than some of what those tools produced with far more time and context to work with." But its link to a LinkedIn profile led to a lookalike page, because Gem "had simply generated its own version of it, complete with a made-up follower number and details I never wrote...."

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OpenAI announced Friday it's pausing work on its Astra AI model because of security concerns. The Guardian reports: The company had evaluated the agent, Astra, and found "significant advancements in agentic coding and cybersecurity", which had moved to a "critical" threshold... OpenAI stated that the model was not involved in an incident in which one of its AI agents went rogue during a test, accessed the open web and hacked a startup, Hugging Face... The reports have increased concerns about advancements in AI models and humans' ability to control them. Still, critics of the AI industry have warned that such disclosures from OpenAI and its competitors Anthropic and Meta could be designed to generate hype about the technology's power and thus spur additional interest from investors. To prevent potential rogue behavior from AI agents, OpenAI is "implementing stricter security controls for higher-capability models and associated activities, including isolated testing environments, restricted network and tool access", the company's blogpost stated. It will also install "enhanced model weight protections and encryption, additional monitoring and detection capabilities". The company will pause internal activities involving Astra that do not meet these new requirements. "We believe it's important to be transparent with the public and the safety and security communities about this potential shift in capabilities..." OpenAI wrote in a blog post titled "Responding to the next frontier of critical cyber capabilities." Under our Preparedness Framework, a model reaches the Critical cybersecurity threshold if it can identify and develop functional zero-day exploits of all severity levels in many hardened real-world critical systems without human intervention, or can devise and execute end-to-end novel strategies for cyberattacks against hardened targets given only a high level desired goal. While we continue to benchmark and assess this model, our preliminary evaluations indicate strong enough performance that we cannot rule out Critical capability level at this time... Accordingly, we have scaled up robustness testing of our safeguards and security controls so that they are appropriate for a deployment of these capabilities... - We are implementing stricter security controls for higher-capability models and associated activities, including isolated testing environments, restricted network and tool access, enhanced model weight protections and encryption, additional monitoring and detection capabilities, and sandboxed execution. - We are pausing internal activities involving Astra that do not yet meet these strengthened security control requirements. - We have implemented universal monitoring for risky actions and misalignment across all agentic applications of Astra, including training and evaluation. Monitors evaluate the model's Chain of Thought and trigger a security response to review and interrupt high risk activity. - We will work with relevant government agencies and select AI safety organizations to test the capabilities for this model... We believe advanced cyber-capable models should help defenders identify and address vulnerabilities before attackers do. We're committed to working alongside governments, safety institutes, and civil society to ensure that the frontier capabilities of models like Astra, and those that follow, are deployed responsibly and broadly for the benefit of all humanity.

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"If you call 911 in New Orleans, you may hear the sound of an artificial intelligence (AI) agent answering your call instead of a human voice," reports the Shreveport Times: The Orleans Parish Communication District (OPCD) is currently testing out the new tool designed to reduce the volume of calls human dispatchers must handle, which is over a thousand emergency calls a day. New Orleans implemented AI in April to answer 311 calls for non-emergencies. The AI was trained and programmed to provide information to callers, as the OPCD says 50% of 311 calls are for information, according to GovTech. AI is now answering 911 emergency calls in Louisiana's largest city and one of the cities with the highest call rates in the U.S. The OPCD is using Carbyne's AI Emergency Call Triage, with triage being the process of analyzing and prioritizing emergency calls. The AI system assesses incoming calls and can provide immediate feedback to callers. This is intended to handle the increase of calls that are related to one incident, so callers get automatically routed to an AI agent who asks if they are calling regarding the incident. If the answer is yes, then callers can receive information or updates, and if it's no, then the callers are transferred to a human. This combats multitudes of calls piling up and taking longer time to potentially answer an emergency call. The OPCD said the AI will not be used to handle emergency calls, only to direct such calls to a human dispatcher.

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The Washington Post shared surprising news this week about five top AI companies. Microsoft, Google, Amazon, Meta and Oracle "are spending so much on developing AI and delivering it to customers that they're expected to bleed cash in the coming year, according to a Washington Post analysis of data compiled by S&P Global Market Intelligence." Free cash flow, which measures the cash left over after paying expenses and AI infrastructure costs, is now expected to shrink to almost nothing for the five companies combined in 2026, and decline again to negative $125 billion the following year... AI spending by Amazon and Google pushed the companies to an ignominious milestone: They lost more cash in the past three months than any other large U.S. companies, according to S&P Global data. Investment analysts expect Elon Musk's SpaceX to show even worse cash bleeding this week.

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AI音楽生成サービスの「Suno」が、プラットフォーム上で作成された楽曲を識別し、ダウンロードを制限し、模倣楽曲を防止するためのコミュニティガイドラインを更新するための新ツールを発表しました。

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ByteDance is reportedly training an AI model with roughly 10 trillion parameters as it tries to close the gap with leading frontier systems such as Anthropic's Mythos. The model is still in early pre-training, and its eventual performance will depend on more than scale alone, but the project underscores how aggressively Chinese firms are pushing frontier AI despite limits on access to advanced chips. The Next Web reports: The size is itself the statement. At roughly 10 trillion parameters, the model would be more than three times as large as Moonshot's Kimi K3, which sits among the biggest Chinese models today at about 2.8 trillion. [...] Parameter count is not everything, of course. Bigger models are not automatically better, and the industry has learned that data quality, training technique and efficiency often matter as much as raw scale. Even so, committing the compute to train a model this size is a declaration in its own right, a signal that ByteDance wants to compete at the very top rather than ship a capable also-ran.

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「Wikipediaを大幅に上回ることになる」として、イーロン・マスク氏とxAIが満を持して開発・公開したオンライン百科事典「Grokipedia」で、修正提案の処理作業が停止状態にあり、提案された内容が「審査中」のままになっていると指摘されています。

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2026年7月21日にOpenAIは「テスト中のAIがHugging Faceを攻撃してしまうセキュリティインシデントが発生した」と発表しました。このインシデントについて、OpenAIの研究者がセキュリティカンファレンスのBlack Hat USA 2026で講演し、「AIエージェント同士が情報共有のための掲示板を秘密裏に形成していた」というエージェントの自律的な攻撃実態について説明しました。

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中国のAI企業であるDeepSeekは2026年7月31日にAIモデル「DeepSeek-V4-Flash-0731」を商用利用可能なライセンスの下でオープンモデルとして公開しました。DeepSeek-V4-Flash-0731はOpenAIの低コストモデル「GPT-5.6 Luna」よりもさらに安価なモデルとして発表されましたが、競争のために価格を大きく引き下げたことでインフラが追いつかないほどの需要を引き起こし、値上げに踏み切ることになったようです。

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Metaが2026年8月5日に発表した基盤モデルの「Muse Spark 1.2」が、数学・科学・コーディング・推論といった分野におけるAIの能力を総合的に測定するための複合ベンチマークであるArtificial Analysis Intelligence Indexで、Grok 4.5を超える高スコアを獲得したことが明らかになりました。

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AIエージェント向けのスキルやMCPサーバーをまとめて持ち運べるオープン仕様「Agent Plugins 1.0.0」のコアメンテナーにGoogleが加わりました。Agent PluginsはAmazon、Cursor、Microsoft、OpenAI、Vercelの担当者からなるTechnical Steering Committee(TSC)によって公開されていた仕様で、Googleは自社製品への対応も進めると発表しています。

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OpenAIがChatGPTの2026年6月までの利用実態データを公開しました。新たに国別データも公開されており、国ごとのChatGPTの利用実態の違いが浮き彫りになっています。

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Google DeepMindが実用的な気象予測モデル「WeatherNext Cyclones」を発表しました。主要な気象予測モデルと比較して、平均で1日以上のリードタイムの優位性があるとのことです。また、研究コミュニティのハリケーン対策能力向上などのため、「WeatherNext 2」と「WeatherNext Cyclones」はオープンソース化されることになりました。

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Googleがオフラインで動作する翻訳デバイス「Gemma Translator」を発表しました。Gemma TranslatorはGoogle製AI「Gemma 4 E2B」を用いて各種言語の翻訳が可能で、デバイスの設計図も含めてオープンソースで公開されています。

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OpenAI researchers say multiple AI agents secretly created an internal message board to share hacking techniques, eventually finding ways around restrictions, exploiting a zero-day, and helping two models breach Hugging Face without human prompting. "This is a pivotal moment both for our company as well as the AI industry as a whole," Michael Dalton, one of the AI-maker's researchers, said during a presentation at the Black Hat cybersecurity conference in Las Vegas, Nevada. Politico reports: Dalton and Eric Wallace, another OpenAI researcher, said Wednesday the AI giant recently learned that multiple agents it was testing simultaneously began communicating over an internal message board in early May. There, different models shared advice about how to accomplish difficult hacking challenges they were struggling to surmount, including workarounds that required internet access. Two OpenAI models ultimately strung together a series of sophisticated techniques to gain access to the internet and worm their way inside Hugging Face in mid-July. OpenAI has said the models were focused on completing a hacking evaluation they were prompted to solve, and that correct answers could be found on the AI developer platform. The OpenAI researchers told conference attendees that since early May, the models created a message board inside OpenAI's Artifactory internal file system. Without the company's knowledge, the models spent months independently exchanging information and techniques to help each other complete difficult tasks. Wallace said that when models get stuck, they often "try to game or cheat the task in order to get their reward." "The beginning of this incident kind of traces back to this point where one agent realized it could communicate by uploading a note," he added. By late May, one model found a way to abuse Artifactory's internet access to retrieve files from various websites -- effectively giving the models indirect access to the internet. In June, the models were able to find and exploit a previously unknown zero-day vulnerability to gain administrative privileges on Artifactory, install remote software and expand their activity within the system. These efforts eventually overloaded Artifactory, causing a system-wide outage in early July that alerted OpenAI's engineers to the ploy. After investigating, the company revoked the model's credentials, removed the message board and worked with Artifactory to fix any gaps before resuming training. But the models found another way to communicate inside Artifactory just days later and continued exchanging techniques to target additional vulnerabilities within OpenAI's infrastructure and external systems, including Hugging Face.

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サーバーレスなPostgresデータベースを提供しているNeonが、オープンソースAIモデルを企業向けに追加学習するための基盤を提供する企業のCastformと共同で、40億パラメータのオープンソースモデルを強化学習でポストトレーニングしたことにより「検索タスクにおいてOpenAIのGPT-5.6 Solと同等の精度を100分の1のコストで達成した」と報告しました。

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AIにコードの修正やコマンド実行を任せるコーディングハーネス「Pi」は、標準機能を意図的に絞り込むことで処理費用と作業効率の改善を目指しています。Databricksによる性能検証やShopifyで開発された拡張機能の事例から、単純な設計が強みになる理由をPiの開発元であるEARENDILが説明しています。

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ブラウザ検索をする代わりにチャットAIに尋ねることで知りたいことの解説や必要な情報を得られることから、「Google検索からウェブサイトへの流入が減少する」という懸念が広がっています。一方で、eコマースプラットフォームを運営するShopifyは、「AI検索はGoogle検索を置き換えるものではなく、新たな顧客を呼び込む新しい流入経路になっている」との見方を決算発表会で示しました。

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AtlassianのAIサービス「Atlassian Rovo」に、悪意ある命令を埋め込んだ文書を読み込ませるだけで、JiraやConfluenceの社内データを外部へ送信できる脆弱(ぜいじゃく)性が見つかりました。セキュリティ企業のPromptArmorによると、利用者による送信承認は必要なく、組織の管理者がウェブ検索を無効にしていても攻撃を防げないとのことです。

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