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Google Marketing Platform launches first monthly Drop

Google Marketing Platform launches the first monthly Drop series, rounding up the latest product updates. The Display & Video 360 Marketplace is curated by Gemini models, offering personalized media packages that can be activated with one click, and now includes programmatic inventory from LinkedIn CTV Ads; the new Search Ads 360 homepage likewise uses Gemini to consolidate insights, generate recommendations, and simplify execution. Gartner has named Google a Leader in the Magic Quadrant for Ad Platforms, ranking first across all three use cases: full-funnel, awareness, and performance.

Google and Voltus Advance a 1 GW Virtual Power Plant in the PJM Grid

Google and Voltus are raising their virtual power plant target for the PJM grid tenfold, from 100 MW set in June to 1 GW, with data center developers paying users to reduce electricity use or provide battery capacity during peak demand. Voltus has already secured customer commitments to supply power through 2040, far longer than PJM capacity auctions typically require three years in advance. PJM serves about 67 million people, and its cost of meeting peak demand has risen more than eightfold in recent years; large loads such as data centers are expected to add 30 to 34 GW of demand by the early 2030s.

Google DeepMind and Cambridge paper: AI agent autonomously discovers exact rules for 11 unsolved Turing machines

A new paper from Google DeepMind and Cambridge shows that a Gemini-based agent can autonomously discover new mathematics, finding and providing exact rules for 11 Busy Beaver Turing machines that previously had no analysis on record. The agent tests edge cases in a simulator, drafts informal proofs, and then completes the proofs in the Lean proof checker; all the relevant rules passed Lean verification. The paper states that this reflects AI moving from answering mathematical questions posed by humans toward open-ended discovery.

Google Open-Sources AQuA Quality Agent: What Should Test Teams Hand Over to It

On October 8, the Google Developers Blog published a reference implementation of AQuA (Ambient Quality Agent), which runs a quality agent alongside production agents, responsible for clustering failed conversations, reviewing issues, and anchoring diagnoses to deployed source code snapshots. The article argues that it will not make testing disappear, but rather hands over to test teams the tasks of defining anomalies, calibrating evidence, and bearing release responsibility, and presents three validation methods: injecting known faults, blind review controls, and root-cause replay.

Google Open-Sources AQuA Quality Agent: What Should Test Teams Hand Over to It?

On October 8, the Google Developers Blog published the AQuA (Ambient Quality Agent) reference implementation, which places a quality agent alongside production agents, responsible for clustering failed conversations, reviewing issues, and anchoring diagnoses to deployed source code snapshots. The article argues that this type of outer-loop quality inspection may still share blind spots with production agents in models, logs, and business definitions, and that test teams need to shift toward designing observability surfaces, calibrating anomaly labels, maintaining evidence chains, and defining escalation rules. The article also presents three validation methods—injecting known faults, blind-review controls, and root-cause replay—as well as a phased adoption path for small teams.

Google paper proposes OO-Harness: evolving specialized agent harnesses by task type

A new Google paper proposes OO-Harness, which evolves agent harnesses by code class: each specialized harness inherits from a parent class and changes only the parts that its task cluster needs adjusted, after which a router selects a specialized harness or keeps the base result based on the base run's outcome. On AutomationBench business workflows, this method scores 77.41%, versus 61.62% for the base harness and 63.92% for the global method Meta-Harness; on unfamiliar applications it retains the base harness and maintains a 59.18% pass rate, while Meta-Harness's global harness drops to 44.90%. The authors recommend using the base harness as a fallback for mixed workloads and routing to a specialized harness only when a run exposes a known problem.

OpenAI Models Launch on Google Cloud: GPT-6 Astra and Two Others Now Available

Google Cloud announced that it is bringing OpenAI models into its model garden, with GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna now available on Google Cloud. Google Cloud says it is the only hyperscale cloud provider offering leading closed-source large models from all three of OpenAI, Anthropic, and Google, with more than 200 other models also on the platform.

OpenAI models and Codex agent workflows to launch on Google Cloud Model Garden

OpenAI announced that it is bringing its frontier models and Codex agent workflows to Google Cloud's Model Garden, enabling enterprises to use these technologies within their existing build environments. The original article did not disclose a specific launch date, the list of available models, or pricing information.

Sundar Pichai responds to Google's free cash flow turning negative for the first time while still ramping up AI capital expenditure

Alex Heath asked Google CEO Sundar Pichai why the company recently let free cash flow turn negative for the first time in order to increase AI capital expenditure, and Pichai responded that it is not based on hope alone. He said making this decision requires confidence on multiple levels: Google sees early signals of diverse opportunities and strong demand from consumers to enterprises; at the same time, the company itself, as an AI user, also has demand signals and can independently assess progress at the capability frontier, and research breakthroughs led him to judge that Gemini 5.0 will be significantly stronger than Argon. He also mentioned that Google is signing long-term contracts with committed revenue, so it is planning its business portfolio and investing in a responsible and disciplined manner.

Pichai discusses Google's space data center project Suncatcher

Google CEO Pichai said that the company's space data center project Project Suncatcher is about to reach its "hello world" moment with TPUs, and the team will achieve important milestones within 10 to 20 years. He said that sun-synchronous orbit can provide 24/7 energy, which is the first-principles basis for the project, while Earth's physical space is limited and difficult to support the exponential growth of computing demand over the next 20 years.

Google Cloud launches OpenAI models, offering them on the same platform as Gemini and Claude

Google Cloud has begun offering Gemini, Claude, and OpenAI models on the same platform, becoming the only major cloud provider to list all three. The OpenAI models launched this time include GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna, initially available as a private preview to select enterprise customers, and they will appear in Gemini for Business and Google Antigravity, with fees billed uniformly through Google Cloud. Google says customer data will not be used for training, and the article also mentions the resource conflict between providing compute for cloud customers and its own Gemini team.

Google Research uses AI to assist blind-sweep ultrasound assessment of gestational age, with error comparable to experts

Google Research published a study in JAMA Network Open; its AI gestational age assessment model based on blind-sweep ultrasound achieved a mean absolute error of 4.18 days in prospective testing in Chicago (n=192) and Nairobi (n=193), reaching non-inferiority compared with expert sonographers' 4.48 days. The model was fine-tuned only on data from 120 participants in Chicago and did not use Nairobi data; the errors in the two locations were 4.10 days and 4.27 days, respectively. The study used a Clarius C3 handheld probe, with standardized blind sweeps performed by operators without professional ultrasound training.

Google Agents CLI Launches Extension System: From ADK to LangChain, All Can Plug In

Starting with version 1.5.0, Google Cloud's Agents CLI introduces an Extension System that allows developers to override or add commands without forking the tool; version 1.8.0 debuts the first LangChain extension, replacing ADK-bound commands with equivalent LangChain implementations. Extensions are declared via agents-cli-extension.yaml in a Git repository and can override built-in commands such as playground, deploy, and eval generate, or add new commands; enterprise platform teams can use this to enforce policies such as SBOM scanning in deployment pipelines.

Google Cloud Brings GPT-Astra and GPT-6 Series to Model Garden

On October 21, 2026, Google Cloud announced the launch of OpenAI's GPT-Astra, GPT-6.1 Sol, and GPT-6 Luna on Model Garden, with all three models opening private preview to select enterprise customers the same day. GPT-Astra targets coding, computer operation, professional tasks, and scientific research; GPT-6.1 Sol focuses on lower-cost agentic coding and professional work; GPT-6 Luna is positioned for fast, low-cost large-scale everyday tasks. OpenAI models are billed through Google Cloud Marketplace, with usage consolidated into a single bill and applied toward existing cloud commitments, allowing customers to dynamically switch models based on performance, latency, and cost.

Google AI and Prune Nourry Recreate Lost Workshops of Women Sculptors

Artist Prune Nourry, in collaboration with Google Arts & Culture, used Google generative AI and image editing models to reconstruct the lost workshops of 19th-century Parisian women sculptors such as Nancy Elizabeth Prophet, Jane Poupelet, and Camille Claudel, and built a custom tool based on Gemini to generate walkable 3D models from archival photographs. The project is accompanied by a 10-minute documentary honoring 18 women sculptors overlooked by art history. The "Visionaries" exhibition will be on view at the Petit Palais in Paris from October 20, 2026, to January 30, 2027.

Google Cloud to open Vera Rubin-based A5X instances to all customers next month

Google Cloud will open Vera Rubin-based A5X instances to all customers next month. Early tests by London advertising group WPP show that AI agent workloads that previously required multiple server clusters can run on a single A5X instance. Externally, racks are interconnected via ConnectX-9 network cards and Google's Virgo network, scaling across multiple sites to 960K Rubin GPUs; the design targets reinforcement learning, where faster CPU-to-GPU and GPU-to-GPU links can shorten each training round.

OpenAI and Google Reach AI Distribution Agreement; GPT-6 Astra and Codex to Launch on Google…

OpenAI and Google have reached an AI distribution agreement. Within weeks, OpenAI will list GPT-6 Astra and Codex on Google Cloud's Model Garden, extending its model coverage to all three major U.S. clouds. Customers can purchase these models through Google Cloud Marketplace and count the spending toward their committed cloud consumption quotas, eliminating a separate procurement process; regulated customers can also run agent workflows built with OpenAI models within Google Cloud's access control and data governance tools. The agreement only became possible after April 27, 2026, when Microsoft's license to OpenAI technology became non-exclusive and Microsoft stopped paying OpenAI a revenue share on Azure resales; AWS had previously been first to launch Codex on Bedrock.

Pichai: Google Cloud Sacrifices Short-Term Revenue for Frontier AI

Sundar Pichai said that the Google Cloud business "is giving up short-term revenue at any given moment" because the company is making compute trade-offs to support the development of frontier AI. The quote comes from a video on Alex Kantrowitz's YouTube channel.

English translation is being prepared.

Sundar Pichai: Google Argon Reaches 25 Trillion Tokens in Usage Within 72 Hours of Launch

Sundar Pichai said that within 72 hours of Google's Argon going live, usage approached 25 trillion tokens, roughly 3 times the usage of Gemini 3.0 over the same period. He also mentioned that the model is currently being served, but compute capacity is constrained. These remarks come from a video on Alex Kantrowitz's YouTube channel.