🧠 Meta's new open-source brain AI
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🧠 Meta's new open-source brain AI
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🍎 Apple may build smaller AI models from Gemini
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🔐 Quantum computers could break encryption by 2029, warns Google
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🧠 Google TurboQuant cuts AI memory use by 6x
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🧠 Meta's new open-source brain AI
Meta has unveiled TRIBE v2, a new foundation model capable of predicting human brain activity across vision, sound, and language, trained on neuroimaging data collected from roughly 700 volunteers.
The company has released the model, its full codebase, and an interactive demo, with the explicit goal of accelerating medical research breakthroughs — particularly in the understanding and treatment of neurological disorders.
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🍎 Apple may build smaller AI models from Gemini
Apple has secured full access to Google’s Gemini model and plans to distill it into smaller, more efficient models capable of running directly on Apple devices without requiring an internet connection.
The distillation process involves training these compact models using Gemini’s high-quality answers and advanced reasoning patterns, enabling them to replicate sophisticated capabilities while using far less computing power.
Apple is using Gemini to develop a significantly smarter, conversational version of Siri for iOS 27, although it has encountered challenges because Gemini was originally optimized for general chatbot and coding tasks that do not always align with Apple’s specific needs.
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🔐 Quantum computers could break encryption by 2029, warns Google
Google has released a formal roadmap to transition its entire global infrastructure to post-quantum cryptography by 2029, warning that quantum computers capable of breaking current encryption may arrive sooner than widely expected.
The company highlighted “harvest now, decrypt later” attacks as an active and ongoing threat, in which malicious actors are already collecting encrypted data today in anticipation of decrypting it once sufficiently powerful quantum computers become available.
More than 6.8 million Bitcoin currently held in vulnerable addresses could eventually be at risk, although Bitcoin developers have begun work on quantum-resistant upgrades through BIP 360, a proposed new address format.
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🧠 Google TurboQuant cuts AI memory use by 6x
Google Research has introduced TurboQuant, a new compression algorithm capable of reducing AI working memory — specifically the KV cache — by at least 6x while maintaining full performance and accuracy.
The technique combines two innovative methods, PolarQuant and QJL, leveraging vector quantization to eliminate KV cache bottlenecks. The team plans to present the research at ICLR 2026 next month.
Although TurboQuant represents a significant laboratory breakthrough, it is currently limited to inference-stage memory optimization and does not address training requirements, meaning it would not resolve broader RAM constraints even if widely adopted.
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