#Google

AIJeff Dean congratulated Periodic Labs on results from its materials-science AI work. The post itself provides no specific figures, so the announcement is limited to the congratulations.

AIGoogle AI Studio released Gemini 3.8 Live, a native speech-to-speech model with an Extended Thinking variant, and made it available through the Live API. Gemini 3.5 Transcribe, released last month, supports 85+ languages with a reported 4.0% streaming and 2.6% non-streaming Word Error Rate, and accepts a custom vocabulary of up to 1,000 terms. Live API audio pricing is listed at $0.005/min for input and $0.018/min for output.

Why it matters: The post lists concrete Live API capabilities, per-minute audio pricing, and transcription accuracy figures, helping developers weigh voice agent options against their own cascaded pipelines.

AIGoogle's Gemini Notebook now offers live spoken Q&A over class materials in about 100 languages, and lets students record lectures on the go with audio notes saved automatically to a chosen notebook. University students in 140+ countries can also still get a free Google AI Plan for higher limits and access to more Google products.

AIGoogle is hosting a first-of-its-kind Gemini Audio experience in San Francisco next week, with Logan Kilpatrick attending. The post also points to new Live audio models for building real-time voice applications.

AIGoogle is rolling out Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking across several channels. Consumers get them in Search Live and Gemini Live, developers get public preview access through the Gemini API, and enterprises get private preview through Gemini Enterprise, with Customer Experience support coming soon.

Why it matters: The post lays out where each Gemini 3.8 Live variant reaches consumers, developers, and enterprises, which clarifies access paths for a voice model release.

AIGoogle DeepMind introduced Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two live dialogue models for voice agents. Extended Thinking scores 82.6 on Artificial Analysis' Speech to Speech Quality Index, 68.6% on τ-Voice, and 97.7% on Big Bench Audio. Gemini 3.8 Live is rolling out now in the Gemini API, Google AI Studio, and Search Live, with enterprise access in private preview.

Why it matters: The release covers a voice model's benchmark results and availability across developer, enterprise, and consumer products, useful for judging voice agent options.

AIGoogle introduces Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two live dialogue models for voice agents that reason and speak simultaneously. The Extended Thinking version scores 82.6 on Artificial Analysis' Speech to Speech Quality Index and 97.7% on Big Bench Audio, while 3.8 Live targets scale and cost efficiency. Developers can access both through the Gemini API in Google AI Studio, and enterprise and consumer rollouts vary by product.

Why it matters: The source names the two models, their access paths, and specific benchmark results, showing how the voice agent capabilities differ between the two tiers.

AIGoogle reports that its technologies and products now power everyday interactions in more than 300 languages used by over 7 billion people, about 86% of the global population. The post describes new speech models, including Gemini 3.5 Live Translate and Gemini 3.5 Transcribe, plus the TranslateGemma open translation models trained across 55 languages.

AIGoogle says its technologies now support more than 300 languages spoken by 7 billion people, representing 86% of the global population. The company also released its AI & Economy ATLAS, which it describes as a look at how people are using AI globally. The post highlights recent AI science work, including AlphaGenome Atlas, WeatherNext 3, and a Planetary Prediction Engine.

AIGoogle has made two audio-to-audio models, Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, generally available through the Live API. Gemini 3.8 Live, model ID gemini-3.8-live, is the default for low-latency voice agents, with interleaved reasoning and asynchronous function calling. Gemini 3.8 Live Extended Thinking, model ID gemini-3.8-live-extended-thinking, supports background reasoning during live audio and is recommended when more reasoning is needed.

Why it matters: The changelog names two model IDs and their intended use, showing how Live API developers can choose between low-latency voice and higher background reasoning.

AIPart 2 of the zero-trust agents series moves security checks from agent code to the Gemini Enterprise Agent Platform runtime. Model Armor screens prompts and responses, Semantic Governance Policies judge proposed tool calls against intent and business rules, and Agent Anomaly Detection flags multi-turn drainage that single-turn checks miss. The same Customer Support and Returns Agent from Part 1 is used, with the companion demo open-sourced on GitHub.

Why it matters: The post walks through a concrete refund agent under four attacks, showing how screening, intent judgment, and anomaly detection each catch what the others miss.

AIGoogle DeepMind released EmbeddingGemma 2, an open model under Apache 2.0 that maps text, images, video, and audio into one shared 768-dimensional vector space. The model has 740M total parameters and supports 8,192-token context, with Matryoshka truncation to 128d, 256d, and 512d. The source reports 14% better code-task performance than EmbeddingGemma 1 and says it is designed for consumer hardware such as phones and laptops.

Why it matters: The release combines text, image, video, and audio retrieval in one 768-dimensional space at 740M parameters, a useful reference for on-device multimodal search design.

AIDemis Hassabis says Dario Amodei's essay, which argues the AI industry should slow down, points toward the right path, though the details still need working through. He also points to Google DeepMind's recent proposal for an industry-wide standards body for frontier AI. The quoted essay describes a three-part plan, and Anthropic is committing to give third-party evaluators permanent, employee-level access to its systems.

AIGoogle Developers Blog describes autofinetune, a project applying autonomous agent loops to LLM post-training with Tunix, Gemma, and Cloud TPUs. In an SFT case study on FunctionGemma, an agent ran 20 automated experiments on a Cloud TPU v5e-1 to adjust LoRA settings, optimizers, and learning rates. In a GRPO case study on Gemma 3 1B for GSM8K math reasoning, the agent ran 40 experiments on a Cloud TPU v6e-1 and improved total reward by about 10%.

AIThe Gemini app is now available for Windows, letting users open it with the Alt + Space shortcut. From any app, it can polish drafts, summarize long documents, brainstorm ideas, and create custom images and videos.

AIGoogle Labs has made Dreambeans, its experimental app that creates personalized daily story collections, available to all U.S. accounts aged 18 and over on Android and iOS. Each daily collection combines personalized topics with information distilled from connected Google apps, including Calendar, Gmail, Photos, Search, YouTube, and Gemini. Users can dive deeper into stories, bookmark them, share them, and give feedback to improve future collections.

AIGoogle DeepMind's Peter Battaglia discusses how machine learning is changing global weather forecasting, including early warnings for storms such as Hurricane Melissa. The episode covers traditional physics-based models versus AI models and probabilistic forecasting, and highlights WeatherNext 3 as Google DeepMind's most advanced global weather AI model yet.

AIGoogle announced general availability of ADK for Kotlin 1.0, a Kotlin Multiplatform framework for building AI agents on servers and Android. Version 1.0 reaches feature parity with ADK 1.0 Core and adds Android extensions for on-device models, cloud Gemini via Firebase AI Logic, and persistent sessions and memory with Room and AppSearch. The post includes a server-side incident triage example using KSP-generated tools and skills, plus an Android financial assistant example with human confirmation for transfers.

Why it matters: The post names the new Android and server-side capabilities and the code setup, helping Kotlin developers judge whether ADK fits their agent projects.

AIGoogle Developers Blog argues that teams building AI coding agents should replace end-to-end benchmark scores with behavioral evaluations that test discrete, observable actions. Examples include asking clarifying questions on underspecified prompts, running a local validator before marking a build change complete, and consulting live search for current information. The post recommends fast, deterministic unit-style checks, outcome-based LLM-as-a-judge checks for complex tasks, and batch runs that track aggregate pass rates over time.

AIGemini Notebook's upgraded experience is rolling out across all mobile devices this week, according to the account. Web users can opt in via Settings to be notified when their artifacts are ready, and after a Quiz, Chat can recommend what to study next or generate targeted flashcards for weak spots.

AIGoogle AI Studio is encouraging developers to start building apps with Gemini 3.8 Flash, linking to a guide on ai.dev. The post offers no benchmarks, pricing, or feature details beyond that invitation.

AIDemis Hassabis announced AlphaGenome Atlas, a searchable AI database that maps the predicted impact of all 9 billion possible single-letter DNA changes. The post says it can help scientists better understand disease and is freely available for academic research.

Why it matters: The post describes a searchable database of predicted effects for all 9 billion single-letter DNA variants, which is useful for researchers tracing disease-related genetic changes.

AIOpen model licenses are tightening at the Chinese frontier, with Zhipu's GLM-5.3 switching from MIT to a custom license requiring a security review for inference and fine-tuning providers with over $10 billion in annual revenue. Motif-3 ships under an MIT license with strong scores for its size, while Tencent's Hy4-preview is a competent model that currently overthinks. Western makers Google and Meta have moved to Apache 2.0.

AIGoogle Antigravity announces that Google DeepMind's science-skills is available for download on GitHub. The post includes a link to the google-deepmind/science-skills repository and no further details about its contents or features.

AIGoogle DeepMind has launched AlphaGenome Atlas, an AI-powered searchable database mapping the predicted impact of all 9 billion possible single-letter DNA changes. It runs in a regular web browser without coding and is free for academic researchers.

AIGoogle DeepMind introduced AlphaGenome Atlas, an AI-powered database charting the molecular impact of every possible genetic variant. Scientists are already using it to investigate unsolved rare diseases and map rare mutations linked to complex traits.

Why it matters: The source names a concrete use case, finding disease-causing DNA variants, which shows how the database could support rare disease research.

AIGoogle DeepMind has introduced AlphaGenome Atlas, a platform with predicted molecular effects for 9 billion single-nucleotide variants in the human genome. It is free for academic research through a web portal, and the AlphaGenome Variant Impact score condenses predictions from AlphaGenome and AlphaMissense into one number for ranking variants. The source says collaborators used it to identify variants in unsolved rare disease cases and to find rare non-coding variants linked to traits.

Why it matters: The source details how precomputed variant predictions, a single impact score, and linked feature attributions make genome-wide mutation effects searchable for researchers without coding skills.

AIGoogle DeepMind has released AlphaGenome Atlas, a web portal that predicts the regulatory effects of all 9 billion possible single-letter genetic changes in the human genome. The Atlas provides an AlphaGenome Variant Impact (AVI) score that combines coding and non-coding predictions to help researchers prioritize variants. The source says the portal requires no coding skills and is available to researchers and biologists worldwide.

Why it matters: The source details how the Atlas's AVI score is used in real rare disease and UK Biobank analyses, showing a practical route for prioritizing non-coding variants.