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Michael Truell@mntruellAI score25AICursor has added Gemini Flash 3.5 to CursorBench, its main coding agent evaluation. The company says the leaderboard will be updated as new models are released, with results available at
koray kavukcuoglu@koraykvAI score44AIGoogle demonstrated Gemini 3.5 Flash in the Gemini app creating an interactive circuit helper that outputs a step-by-step physical build guide and a working simulation. The demo targets students learning complex subjects visually through hands-on interaction. Gemini 3.5 Flash is available globally starting today.
koray kavukcuoglu@koraykvPickAI score72AIGoogle's Gemini 3.5 Flash outperforms Gemini 3.1 Pro on Terminal-Bench 2.1 (76.2%), GDPval-AA (1656 Elo), and MCP Atlas (83.6%). The post also claims it is 4x faster than other frontier models, or 12x in Antigravity, and reports 83.6% on MMMU-Pro for multimodal performance.
Why it matters: The post gives specific benchmark scores against Gemini 3.1 Pro, letting readers compare coding, agentic, and multimodal results directly.
koray kavukcuoglu@koraykvPickAI score72AIGoogle is rolling out Gemini 3.5 Flash globally for consumers in the Gemini app and Search AI Mode. It is also available to developers through the Gemini API, Google Antigravity, and Google AI Studio, and to businesses on the Gemini Enterprise Agent Platform.
Why it matters: The post shows where each Gemini 3.5 Flash access path goes, from consumer apps to developer and enterprise platforms, which helps readers pick the right entry point.
koray kavukcuoglu@koraykvAI score62AIAt Google I/O, Google introduced Gemini 3.5 Flash, which the author says has become part of the daily research cycle. The author says a team of agents in Antigravity 2.0 recreated the original AlphaZero paper and built a playable web version from two prompts, coding the reinforcement learning pipeline in JAX/Flax and training a ResNet model via self-play on multi-TPU pods.
Oriol Vinyals@OriolVinyalsMLAI score62AIGoogle's Gemini 3.5 Flash is available today globally, according to Oriol Vinyals. The post invites developers to build agents and apps with it and links to Google's blog for more details.
Oriol Vinyals@OriolVinyalsMLAI score34AIGemini 3.5 Flash produces fully tactile, interactive HTML/SVG hardware simulations in a single shot when given complex agents and tasks. The output includes bump-mapped metals, spring physics, and procedural audio, according to the post.
Oriol Vinyals@OriolVinyalsMLAI score46AIGoogle's Gemini 3.5 Flash reaches 76.2% on Terminal-Bench 2.1, 1656 Elo on GDPval-AA, and 83.6% on MCP Atlas, showing strong performance on multi-step agentic tasks. The model is positioned as an ultra-fast reasoning engine for powering AI agents.
Reflection@reflection_aiAI score38AIReflection has joined a coalition including AWS, Microsoft, OpenAI, Google, and Nvidia on a framework governing how the U.S. government licenses and deploys AI. The agreement, which includes a non-binding memorandum of understanding with the DoW, commits to safety, red-teaming, and ongoing evaluation and explicitly prohibits unlawful mass surveillance and autonomous weapon use. Reflection says it will keep its commitment to open source while customizing its models for scientists in national labs.
koray kavukcuoglu@koraykvAI score12AIAlphabet has been recognized in TIME's 2026 Most Influential Companies list, with Google's Koray Kavukcuoglu crediting teams for turning AI breakthroughs into everyday user features. TIME's cover story says Sundar Pichai's 2016 "AI-first" push, including custom chips, Cloud, YouTube, and deep AI research, has paid off.
NVIDIA AI Developer@NVIDIAAIDevAI score20AINVIDIA and Google DeepMind experts will host a live session on Friday, April 24 at 11:00 AM PDT showcasing Gemma 4 running on DGX Spark. The demos cover vision translation, long-context document Q&A, and real-time code generation, with audience questions welcome.
koray kavukcuoglu@koraykvAI score49AIAt Google Cloud Next this week, Google introduced its 8th-generation TPUs, split into two variants: 8t for massive-scale training and 8i for low-latency inference. Google presents the launch as a milestone in its accelerator roadmap, aimed at optimizing the full AI stack. The post links to a blog with further details on the systems architecture.
koray kavukcuoglu@koraykvAI score57AIGoogle launched Gemini 3.1 Flash Live, a model designed to handle the nuances of live speech such as tone and interruptions. The post says it can be tried in Gemini Live and Search Live.
Nano Banana 2.1@NanoBananaAI score62AINano Banana 2, also called Gemini 3.1 Flash Image, adds visual grounding with Google Search, 512px resolutions, and extreme aspect ratios of 1:8 and 1:4. The guide advises using it as the default for new projects, with Nano Banana Pro reserved for complex prompts it fails, and keeping Thinking mode off by default.
Oriol Vinyals@OriolVinyalsMLAI score47AIGoogle's newest Gemini 3.1 Flash-Lite model outperforms the previous generation's Gemini 2.5 Flash tier. Google positions it as smarter, faster, and cheaper, with details linked in the Google blog post.
Nano Banana 2.1@NanoBananaAI score23AIGoogle's Nano Banana 2 image model lets users add exact details to outputs by writing short sentences in prompts. The post contrasts a bare prompt for a snow leopard portrait with a detailed one specifying pose, melting snow, flowers, a sun dog, lighting, and blue eyes.
Yi Tay@YiTayMLAI score13AIYi Tay announced that Ni Jinjie has joined Google DeepMind's Singapore branch as a research scientist. Nijinjie will work on Gemini scaling and reinforcement learning under Tay and Quoc Le.
Nano Banana 2.1@NanoBananaAI score18AIGoogle's Nano Banana account says users can turn anything into an enamel pin with Nano Banana 2, either by selecting the "Enamel pin" style in the Gemini app or by using a prompt. The example prompt asks for just the subject as a gold enamel pin shown as a minimal photo on a desk.
Oriol Vinyals@OriolVinyalsMLAI score60AINano Banana 2, officially released as Gemini 3.1 Flash Image Preview, ranks first in Image Arena text-to-image with a score of 1279. The quoted post says it also ties for first in single-image editing at 1407 and costs $0.067 per image, about half the price of Nano Banana Pro.
Nano Banana 2.1@NanoBananaPickAI score67AINano Banana announces Nano Banana 2, which it describes as its best image generation and editing model yet. The model can be tried in the Gemini app, Google AI Studio, and other places the post does not specify.
Why it matters: The post names the access points for Nano Banana 2, which helps readers see where the image generation and editing model can be tried.
Quoc Le@quocleixAI score53AIQuoc Le announced that Aletheia, a math research agent, autonomously solved 6 of 10 FirstProof problems, the best result in the inaugural challenge. The post says this exceeds last year's IMO-gold achievement and points to a paper and thread for full details. The accompanying figure shows 10 unmodified problems, 6 candidate solutions per agent, and expert evaluation yielding 6 solved problems on a best-of-2 basis.
Quoc Le@quocleixPickAI score65AIGoogle researchers used the Aletheia agent, powered by Gemini 3 Deep Think, to attempt 10 FirstProof challenge problems without modification. The agent operated fully autonomously and solved 6 of the 10 problems, according to the post, with methodology and expert evaluations described in the linked arXiv paper.
Why it matters: The post gives the autonomous setup and expert-evaluated results for an AI agent on FirstProof math problems, useful for judging how far such systems go on research-level math.
Nano Banana 2.1@NanoBananaAI score10AINano Banana, the account linked to Google and Gemini, shares a prompt asking an image model to imagine the image as a simple cookie cutter and show the resulting unfrosted homemade cookies on a plate without showing the cutter. The post is a creative prompt example rather than an announcement of a new feature.
Yi Tay@YiTayMLPickAI score78AIGoogle has released Gemini 3.1 Pro, reporting 77.1% on ARC-AGI-2 and more than twice the score of Gemini 3 Pro on that benchmark. The model is rolling out to developers in preview through the Gemini API and Google AI Studio, to enterprises via Vertex AI and Gemini Enterprise, and to consumers in the Gemini app and NotebookLM.
Why it matters: The post pairs the release with a benchmark table comparing Gemini 3.1 Pro against Gemini 3 Pro, Claude Sonnet 4.6, Claude Opus 4.6, and GPT-5.2 on reasoning and coding tasks.
Oriol Vinyals@OriolVinyalsMLAI score5AIOriol Vinyals shared a prompt asking an AI model to generate an SVG of a pelican riding a car in France, with a cat beside it and the Eiffel Tower in the background. The post offers no model name, results, or benchmark figures.
Oriol Vinyals@OriolVinyalsMLAI score4AIGoogle DeepMind researcher Oriol Vinyals posted a simple prompt asking for an SVG image of a rollercoaster. The post includes no model name, output, or benchmark result.
Nano Banana 2.1@NanoBananaAI score6AINano Banana, Google's Gemini image account, shares a prompt for a 9:16 wallpaper with negative space near the top and bottom, a subtle top-to-bottom gradient, no blur, and no cropping. The post advises keeping the scene simple and placing the subject and style at the end of the prompt, with example images attached.
Nano Banana 2.1@NanoBananaAI score14AINano Banana (@NanoBanana) posts a sample prompt showing how specific image-generation instructions can be, describing a San Francisco cafe scene with a couple by the window, a sleeping black-and-white French bulldog, and a mirrored "Nano's Cafe" gold lettering on the glass. The post offers the detailed prompt as an illustration of how far users can go with specificity, covering clothing, props, lighting, and poses.
Oriol Vinyals@OriolVinyalsMLAI score13AIGoogle DeepMind researcher Oriol Vinyals announced he is moving back to California after ten years in London, to keep working on Gemini and toward AGI. The post is a personal update with no product, benchmark, or technical details.
Yi Tay@YiTayMLAI score62AIGoogle's Gemini 3 Deep Think is announced as a model strong in math and coding, with an IMO gold result and a 3455 Codeforces ELO. The post also says it reaches gold-standard performance in physics and chemistry olympiads and sets new records on ARC-AGI-2 and HLE.
Oriol Vinyals@OriolVinyalsMLAI score26AIOriol Vinyals highlights Deep Think's real-world use in helping researchers find errors in high-level mathematics research papers. He notes that such work would be far beyond what an undergraduate math student could do alone.
Yi Tay@YiTayMLAI score67AIYi Tay introduces Aletheia, a math research agent powered by an advanced version of Gemini Deep Think. The post says it produced two publishable papers, one fully automatic and one human-AI collaboration, and solved multiple open Erdős problems. The attached image shows a Google DeepMind paper titled "Towards Autonomous Mathematics Research" with a generator, verifier, and reviser loop.
Quoc Le@quocleixAI score46AIA new paper shows researchers using "vibe-proving" with Gemini Deep Think to tackle open problems and refute long-standing conjectures. The work also reports discovering obscure mathematical links across theoretical computer science, physics, and other fields.
Quoc Le@quocleixAI score62AIQuoc Le announced a paper describing Aletheia, an agent built on Gemini Deep Think that goes beyond Olympiad problems to PhD-level mathematics. The post says Aletheia iteratively generates and verifies proofs, collaborates on human-AI research, autonomously generates a paper on eigenweights, and solves open Erdős conjectures.
Quoc Le@quocleixAI score22AIGoogle's latest blog post describes how Gemini Deep Think is being applied to advance mathematical and scientific research. The post itself gives no specific benchmarks, figures, or release details beyond this announcement.
Yi Tay@YiTayMLAI score14AIYi Tay announced that a new frontier lab in Singapore, described as the first in Asia, is building AGI and gathering top talent. He welcomed @zzlccc, who joined Google DeepMind to work on Gemini post-training under Tay's leadership.
Quoc Le@quocleixAI score60AIQuoc Le announced a case study using Gemini to systematically evaluate 700 conjectures labeled open in the Erdős Problems database. The team addressed 13 problems, finding 5 novel autonomous solutions and identifying 8 existing solutions missed by previous literature.
Nano Banana 2.1@NanoBananaAI score12AINano Banana posts a prompt template for generating a 3x3 grid of colorful, tactile 3D icons on a white background with no text. The post lists example themes: dogs with different emotions, bananas, January, and the same cat in different emotions.
Nano Banana 2.1@NanoBananaAI score13AIGoogle's Nano Banana account says Nano Banana Pro can search for how the Gemini 3 Flash launch was received and turn those findings into a short, headed article. The demo prompt also asks for a rendered image of a glossy magazine cover and two-page spread.
Reflection@reflection_aiAI score42AIReflection AI technical staff member Aakanksha Chowdhery argues that the bottleneck for agentic AI is pre-training itself rather than post-training fixes. Drawing on her work on PaLM and early Gemini, she says next-token prediction breaks down for long-horizon planning and that objectives, attention, and training data must evolve.