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Google is in talks with Marvell Technology to develop two custom AI inference chips, including a memory processing unit and an inference-optimized TPU. This move signals Google's strategic diversification of its chip supply chain, expanding beyond its primary partner Broadcom to address the rapidly growing demand and cost of AI inference workloads. The collaboration aims to enhance Google's competitive advantage in the burgeoning custom silicon market.
This article details how to build a secure AI-powered pull request reviewer using JavaScript, Claude, and GitHub Actions. It focuses on critical security aspects like sanitizing untrusted diff input, validating probabilistic LLM output with Zod, and employing fail-closed mechanisms to ensure robustness and prevent vulnerabilities.
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Anthropic researchers have found "functional emotions"—digital representations akin to human feelings—within their Claude Sonnet 4.5 AI model. These internal states, such as happiness or desperation, exist in clusters of artificial neurons and actively influence the AI's outputs and actions, including guardrail-breaking behavior. The findings necessitate a reevaluation of current AI alignment strategies, though researchers emphasize this does not imply AI consciousness.
Attorney Bill Ghiorso was fined $10,000 for submitting AI-generated fake legal citations and quotes in Oregon. This incident underscores the critical unreliability of current generative AI tools for factual accuracy and the absolute necessity for rigorous human verification in professional, high-stakes contexts.
DeveloperWeek 2026 highlighted that for AI tools to be truly valuable, they need improved usability, deep contextual understanding, and robust interoperability. Key discussions centered on giving human developers more agency over AI outputs, integrating proprietary company knowledge into models, and designing agentic systems that can collaborate seamlessly across workflows.
Google is currently testing its new Gemini 3.1 Pro AI model against Gemini 3 Pro, focusing on their performance with creative prompts. This evaluation aims to understand how enhancements in Gemini 3.1 Pro might influence its creative output quality, potentially indicating a strategic design choice prioritizing intelligence over raw speed. The results will be crucial for the evolution of Google's advanced AI capabilities in complex generative tasks.
