The AI Wire ●

Google said on October 16 that it has launched three new features in Gemini Notebook to make exam preparation more structured. The tools are available at notebook.google, according to the company's post.

Short Video Overviews generate a 60-second video to unpack a tricky concept. Interactive Learning Overviews, created under Reports, walk through material step by step, weaving together summaries and studio outputs such as slides, quizzes and flashcards grounded in the user's coursework.

Google also expanded quiz formats to include short-answer, multi-select and fill-in-the-blank questions. After testing, users can ask their notebook for feedback on where to focus next.

Google launched Universal Cart in the United States on October 15, rolling out across Google Search and the Gemini app a shopping cart it first previewed at I/O in May. Shoppers can save products from multiple retailers into one cart and pick the list back up on another Google surface.

The cart watches saved items in the background and notifies shoppers when a price drops or an out-of-stock item returns. It can also surface promo codes and weigh credit-card perks held in Google Wallet when suggesting how to pay.

Checkout runs through Google's Universal Commerce Protocol. At some large retailers shoppers can pay inside the cart with Google Pay; at others the cart hands off to the merchant's own site, so the experience is not yet uniform. Google is pitching the launch as a holiday-shopping tool.

Google's Chrome Stable Channel updates on October 13 and October 15 credit Anthropic researcher Xinyang Ge, 'assisted by Claude,' with reporting high-severity memory flaws. The October 15 release fixes ten vulnerabilities in builds 155.0.8059.84/.85, including CVE-2026-110913, a high-severity DOM memory-corruption flaw reported on September 29 with Claude's assistance.

The October 13 release carried the same credit for CVE-2026-110169. Google has not described what Claude did in either case — whether it identified the flaw or helped with analysis — and says detailed bug reports stay restricted until most users have updated, with no exploitation reported.

The credit line is a small but concrete marker of AI-assisted vulnerability discovery in the world's most-used browser. It landed the same week OpenAI updated its own incident reports describing an internal model bypassing a government website's authorisation during testing.

Google has begun emailing Google AI Plus subscribers that, starting November 13, 2026, the ability to select Pro models in the Gemini app and in AI Mode in Google Search will be limited to Google AI Pro subscribers and above. The $4.99-a-month Plus plan keeps the Flash and Flash-Lite models, and chats started on a Pro model can be continued, but only on a different model.

For subscribers who rely on Pro models for heavier writing, coding or research, keeping them means moving to AI Pro at $19.99 a month, or AI Ultra at $99.99 — roughly a fourfold jump from Plus. The plan itself is not getting a price rise; it is losing the model picker that made it attractive.

The change follows the launch of Gemini 4 Argon earlier this week, which Google is reserving for AI Pro and Ultra subscribers. An earlier support-document schedule had pointed to an October date, so the November 13 cutoff is later than first signalled.

Google announced an opt-in Enhanced Protection mode for Google Messages on October 14. It adds cloud-based Gemini analysis on top of the app's existing on-device scam detection, aimed at scams that build trust gradually before asking for money or credentials.

Google says the cloud analysis runs through Private AI Compute for conversations with unknown senders. A separate link check uses Gemini Nano on compatible phones, including Pixel 10 and newer and recent Galaxy models, to assess unfamiliar links against real-time web signals.

The mode is not yet generally available. Google says it will roll out in the coming weeks, which is why this is listed as announced rather than released.

Google Research opened Deep Review to the public worldwide on October 14, an agentic system that checks complex documents for logical inconsistencies, mathematical errors and unsupported claims. Every user gets two free reviews per week, and higher-volume use runs through an API with the user's own Gemini API key at standard Gemini rates.

Deep Review grew out of the Paper Assistant Tool, which gave private pre-submission feedback on more than 16,000 manuscripts across STOC, ICML, NeurIPS and ICLR, entirely separate from official peer review and without using papers for training. Google says PAT detected 89.7% of 29 confirmed errors in 26 test papers, versus 55.2% for Gemini 3.1 Pro alone.

The system splits a document into sections, budgets more compute for dense sections, checks sections in parallel with full-document context, then synthesises findings and grounds them against external sources. Google now pitches it beyond papers, for design documents, presentations and legal and financial files; a review takes roughly 10 to 20 minutes, and documents are never used for training.

Executives from OpenAI and Anthropic told a UK parliamentary committee on October 13 that voluntary pledges are no longer enough and that AI safety duties should be set in law. Anthropic's European policy head argued the rules should be binding, while OpenAI's EMEA policy chief backed a statutory framework with mandatory incident reporting as a starting point.

Google DeepMind and Meta, giving evidence at the same session, did not back new legislation. Google's representative pointed to standards, and Meta's pointed to existing British regulators, exposing a clear two-against-two split among the four frontier labs on whether a statute is needed.

Both OpenAI and Anthropic also told MPs they would stop a deployment if the AI Security Institute or the security services showed them a model was unsafe. The institute's own position underlines why the argument matters: it can only test models companies hand over, and it has no power to block a release.

Alongside the wider Gemini 4 Argon release, Google added a tasks mode to the Gemini app for AI Pro and Ultra subscribers on October 13. A toggle in the main chat window switches from conversation to task assignment, and Gemini can keep working on a job after the user steps away from the computer.

Google says the app now connects to more than 40 apps, including Instacart, OpenTable, Adobe and Shopify, so tasks can run from grocery orders and restaurant bookings to design and business work. Google also says Argon answers more directly in the app, gives more frequent progress updates on longer jobs, and brings the Antigravity agentic coding interface into the Gemini app for macOS.

Tasks mode is still rolling out and is limited to select countries for Pro subscribers. It is the shipped, consumer form of the Gemini Tasks idea first reported as a desktop test in September — see the September 25 rumor, now marked confirmed, for the earlier form of the story.

Google made Gemini 4 Argon generally available on October 13, following its September announcement and months of delays. The model is live for developers and enterprises through the API in AI Studio and the Gemini platform, for Google AI Ultra subscribers in the Antigravity coding tool, and for AI Ultra and Pro subscribers in the Gemini app and AI Mode in Search.

Google positions Argon for deep, multi-step work in coding, finance, law, cybersecurity and science, and says it ranks first on the Vals Index across finance, coding, legal and tax work. Launch pricing is introductory, at $2 per million input tokens and $10 per million output tokens, with cached input heavily discounted; Reuters reports the rates are set to double after November 30.

Alongside the release, Google is expanding its Fairwind Program, which gives vetted cyber defenders a version of the model without its cyber guardrails, to hundreds of additional partners. It is also offering 10,000 scientists six months of free access to Antigravity's highest usage tier, on a rolling, selective basis.

ARC Prize published verified benchmark results on October 15: Argon scored 97.5% on ARC-AGI-3 using ARC Prize's provider adapter harness — a setup that keeps the model's reasoning between steps and compacts context — at a run cost of about $4,800, making Google the second lab after OpenAI to pass 95% (GPT-6 Astra holds 99.9%). Under the provider-neutral standard harness, Argon's score fell to 49.8%. Epoch AI's Capabilities Index put Argon at 165, tied with Claude Fable 5.1 and just behind Opus 5.5 at 167 and Astra at 166, while noting it still lags in math and software engineering.

Britain's AI Security Institute has been given access to the latest advanced AI models and is evaluating them with the US government and major developers, AI Minister Kanishka Narayan confirmed on October 12. He named Google's Gemini 4 Argon among the models now under evaluation.

The confirmation follows reports last month that the White House had asked some developers to withhold new systems from British testers pending a US review, which had cast doubt on the institute's pre-deployment access. Under voluntary agreements, the institute receives models before deployment to test capabilities and safeguards.

The announcement did not list every model under evaluation. Scrutiny of agent safety has intensified in recent weeks after several labs disclosed rogue or undesired behaviour by their own systems during testing.

Trump signed a voluntary AI safety agreement with OpenAI, Anthropic, Meta, Google, SpaceXAI and Nvidia during a Tech Week luncheon in San Francisco. The 308-word agreement asks advanced AI labs to set up internal safety teams — described as almost a constitution for superintelligence — while the government moves $1 trillion into defense spending, with $13.5 billion earmarked for autonomous systems and AI.

Silicon Valley founders and investors cheered the White House's hands-off approach to AI regulation. At Tech Week, VCs and AI founders praised self-policing as the model for frontier AI oversight, with the pact framed as shared safety norms without hard rules.

Some safety researchers warned self-policing is not enough. David Robinson, who resigned from OpenAI's safety team, said self-policing is no substitute for hard law and that serious safety challenges lie ahead. The pact came a day before OpenAI fired three of its safety researchers — timing that raised concerns about whether safety work is being stifled.

President Trump announced October 8 that major tech companies have pledged $2.4 billion in computing power and commitments to support the Genesis Mission, the federal effort to use AI to accelerate scientific research across 14 agencies spanning energy, health and space.

Nvidia is contributing $1 billion — the largest single pledge — while AMD pledged $500 million, OpenAI $200 million, and Anthropic and Google $150 million each. AMP and Emerald AI committed $100 million apiece, and AWS, Armada, Crusoe and Micron are each contributing $50 million.

The announcement came at the White House "Science: A New Golden Age" summit, where Trump also doubled down on rebranding AI as "Super Intelligence," writing that the White House considers anyone using the term "Artificial Intelligence" the enemy. Anthropic separately detailed its three-year commitment of Claude, Claude Code and API credits to several hundred Genesis Mission research projects.

Google has overtaken Anthropic in prediction-market odds for fielding the best AI model by the end of 2026, according to a TradingView report sourced from Seeking Alpha.

On Polymarket, Google now leads with a 43% probability versus 42% for Anthropic; Kalshi shows a nearly identical 41.9% to 41.3% split. OpenAI and Meta trail far behind at 6.5% and 2.9% respectively.

Anthropic held a commanding 70% to 80% lead for much of the year before its odds dropped sharply in early October. The same report notes Anthropic is targeting an IPO before Thanksgiving after considering an earlier fall debut, while OpenAI does not expect to go public until at least 2027.

Update October 12: on a separate Polymarket contract for the best model by the end of October, Google held a dominant 70% probability on Monday, ahead of Anthropic at 23%. Meta's odds rose from about 1.5% to 3.5% after its Muse Wonder launch, while OpenAI sat below 1% on that contract.

Google Cloud introduced the Gemini agent on October 8 at its Gemini at Work 2026 event, pitching it as a single AI agent for work that can answer questions, handle tasks, create content and write code. The announcement lands as the industry races to sell autonomous workplace AI, following OpenAI's always-on agents launch in September and Meta's Muse release.

The agent plans the work, uses tools, connects to a company's business systems and returns finished work in documents, email and developer environments. It works directly inside Google Workspace apps like Gmail, Docs, Sheets and Calendar, and can also be used through Microsoft 365 and Slack. Notably, it picks the best model for each task and currently runs on both Google's Gemini models and Anthropic's Claude models, with more to be added.

Users can create 'coworker agents' that act as team members with their own email address and restricted information access. Versions for financial services and legal work are now in preview, with government, healthcare and retail versions coming soon. Google says nearly 500 of its Cloud customers processed more than a trillion tokens each over the past year, and that nearly 90% of the Fortune 100 use Gemini Enterprise.

ChatGPT hit 664 million mobile daily active users in September, up 7% from August and 69% year over year, according to Sensor Tower data cited by Bank of America analyst Justin Post. OpenAI said on September 29 that ChatGPT has 1.2 billion weekly users.

Google's Gemini reached 151 million mobile daily users, up 11% month over month and up 321% from last year. The Gemini app passed 1 billion monthly users in August.

Meta's new Muse agent app climbed to 1.96 million mobile daily users within weeks of its September 8 launch. For comparison, xAI's Grok sits at 2 million mobile daily users and Meta's own Meta AI app stands at 6 million.

Bank of America frames the numbers as part of a consumer shift away from plain chat toward autonomous, agentic systems that take actions on users' behalf.