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🤖 Microsoft puts humans before artificial intelligence. Microsoft AI has published the Humanist AI Code of Conduct for MAI models, with a clear message: People matter more than AI. The charter also emphasizes that AI should not exceed human control, and should remain correctable and stoppable when needed. The most important idea here isn’t how powerful the model is, but who makes the decision when models become more autonomous? The future of AI won’t be measured only by capabilities, but by our ability to keep it useful, controllable, and accountable to humans. {future}(MSFTUSDT) {future}(GOOGLUSDT) #Microsoft #MAI #AI #ArtificialIntelligence
🤖 Microsoft puts humans before artificial intelligence.
Microsoft AI has published the Humanist AI Code of Conduct for MAI models, with a clear message:
People matter more than AI.
The charter also emphasizes that AI should not exceed human control, and should remain correctable and stoppable when needed.
The most important idea here isn’t how powerful the model is, but who makes the decision when models become more autonomous?
The future of AI won’t be measured only by capabilities, but by our ability to keep it useful, controllable, and accountable to humans.

#Microsoft #MAI #AI
#ArtificialIntelligence
The 2026 Microsoft Build Conference is officially kicking off, and Microsoft is rolling out its in-house MAI model family with 7 native models across inference, programming, image processing, speech, and transcription. The flagship model, MAI-Thinking-1, boasts 35 billion active parameters and a 128K context window, hitting levels comparable to Claude Opus 4.6 on the SWE-bench Pro. They also launched cutting-edge Frontier Tuning services, a Web IQ search engine, and the next-gen topology quantum chip, Majorana 2, which boosts qubit reliability by 1000 times, pushing the timeline for scalable quantum computers to 2029. Why it matters: This marks Microsoft's first fully in-house AI model stack (no third-party distillation involved), while advancing their quantum computing + AI Agent platform, signaling a new phase in the tech giant's AI competition, where hardware and software are integrated as one. #微软 #MAI #AI #量子计算 #Build2026
The 2026 Microsoft Build Conference is officially kicking off, and Microsoft is rolling out its in-house MAI model family with 7 native models across inference, programming, image processing, speech, and transcription. The flagship model, MAI-Thinking-1, boasts 35 billion active parameters and a 128K context window, hitting levels comparable to Claude Opus 4.6 on the SWE-bench Pro. They also launched cutting-edge Frontier Tuning services, a Web IQ search engine, and the next-gen topology quantum chip, Majorana 2, which boosts qubit reliability by 1000 times, pushing the timeline for scalable quantum computers to 2029.

Why it matters: This marks Microsoft's first fully in-house AI model stack (no third-party distillation involved), while advancing their quantum computing + AI Agent platform, signaling a new phase in the tech giant's AI competition, where hardware and software are integrated as one.

#微软 #MAI #AI #量子计算 #Build2026
Article
How Does Newton Protocol Build the Future of AI-Powered Finance? And Why Does the Network’s Experimental Version Matter!!!As AI usage increases, the real question isn’t: Can AI make decisions? But rather: How can it carry out those decisions on the blockchain safely and reliably? Now it’s time for @NewtonProtocol , which develops an infrastructure that allows AI agents to execute financial operations on-chain in a secure and verifiable way, rather than only offering suggestions or analyses. This vision makes $NEWT connected to a real technical problem that may become even more important as the AI economy expands.

How Does Newton Protocol Build the Future of AI-Powered Finance? And Why Does the Network’s Experimental Version Matter!!!

As AI usage increases, the real question isn’t: Can AI make decisions? But rather: How can it carry out those decisions on the blockchain safely and reliably?
Now it’s time for @NewtonProtocol , which develops an infrastructure that allows AI agents to execute financial operations on-chain in a secure and verifiable way, rather than only offering suggestions or analyses. This vision makes $NEWT connected to a real technical problem that may become even more important as the AI economy expands.
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