Nano Banana 2 (5 minute read)
Google's Nano Banana 2 (Gemini 3.1 Flash Image) combines the advanced reasoning and image quality of Nano Banana Pro with significantly faster generation speeds.
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Statement from Dario Amodei on our discussions with the Department of War (5 minute read)
Anthropic believes in the importance of using AI to defend the US and other democracies and to defeat its autocratic adversaries. This is why it has worked proactively to deploy its models to the Department of War and the intelligence community. However, it also acknowledges that, in some cases, AI can undermine, rather than defend, democratic values. Two such use cases are mass domestic surveillance and full autonomous weapons. Anthropic has refused to accede to the Department of War's request to remove safeguards in its models. It will help the Department transition to another provider to avoid any disruption to ongoing military planning should it decide to offboard Anthropic.
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xAI Co-Founder Toby Pohlen Is Latest Executive to Depart (1 minute read)
xAI co-founder Toby Pohlen is leaving the startup. Pohlen was in charge of Macrohard, a division of the company focused on AI software run by agents. He is the seventh of 12 xAI co-founders to leave in less than three years. xAI merged with SpaceX earlier this month. SpaceX plans to go public in what is expected to be the largest initial public offering of all time.
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Next-Token Predictor Is An AI's Job, Not Its Species (14 minute read)
Overemphasizing next-token prediction is a confusion of levels. On the levels where AI is a next-token predictor, humans are also next-token predictors. On the levels where humans are not next-token predictors, AI isn't one either. While AI was shaped by next-token prediction, the inside of its thoughts probably looks like a world-model, the same as a human's.
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Building Interactive Worlds (6 minute read)
Realβtime interactive environments require tight integration between simulation engines, agent AI, and live user input to create dynamic, persistent worlds. State management, sensory abstraction, behavior logic, and rendering pipelines must work in concert to support scalable multiβuser interaction. Predictable agent behavior and efficient event propagation are core requirements for responsive, interactive experiences.
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LLMs don't ship bad code. Teams do (Sponsor)
When AI codes, who's accountable for quality? Today, AI assistants generate Playwright tests, AI healers patch broken selectors, and everything stays green, even when tests don't preserve business intent. mabl calls this "logic drift," and it gets worse with scale. Read the full breakdown on mabl's blog
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Realtime Prompting Guide (38 minute read)
OpenAI announced the general availability of the Realtime API alongside gpt-realtime, a speech-to-speech model with improved instruction following, tool use, voice quality, and lower latency. The accompanying prompting guide outlines a practical prompt structure and techniques tailored specifically for realtime voice systems.
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Introducing helm (4 minute read)
helm is a TypeScript framework for AI agents. It allows agents to call typed functions with structured inputs and outputs. helm ships with built-in skills for everyday actions, and users can define custom skills. Its 'execute' tool runs whatever JavaScript the LLM writes within a sandbox.
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Perplexity APIs power Android OEM AI features (4 minute read)
Perplexity is supplying its AI APIs to a major Android device maker to enhance onβdevice and cloudβconnected features. The integration brings Perplexity's deep research, summarization, and knowledge retrieval capabilities directly into the handset ecosystem at scale. This move accelerates manufacturer differentiation and broadens Perplexity's footprint in consumerβfacing AI experiences.
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On-Device Function Calling in Google AI Edge Gallery (7 minute read)
Google's on-device AI showcase app, Google AI Edge Gallery, is now available on iOS in addition to Android. It includes two out-of-the-box agentic experiences, Mobile Actions and Tiny Garden, which showcase how Google's efficient FunctionGemma model translates natural language directly into function calls on devices within merely 270M parameters. Benchmarking has now been integrated directly into the Google AI Edge Gallery app, so users can measure and experience LiteRT's leading CPU and GPU performance across their devices.
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