Helping AI reach more people requires deep collaboration across the ecosystem. Today we’re announcing new investment, with support from @SoftBank
, @NVIDIA
, and @Amazon
, to scale the infrastructure needed to bring AI to everyone.
COMPUTING
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Major AI Infrastructure Investment Backed by SoftBank NVIDIA Amazon
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Autonomous Agent Research Costs Only $6
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The cost difference is insane.
— God of Prompt (@godofprompt) 27 février 2026
I ran an autonomous research agent for 6 hours:
– Searched 50+ sources
– Synthesized findings
– Generated PDF report
Total cost: $6 pic.twitter.com/i5OpC7y1beThe cost difference is insane. I ran an autonomous research agent for 6 hours: – Searched 50+ sources
– Synthesized findings
– Generated PDF report Total cost: $6 -
Cheaper AI coding model beats Claude
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Everyone's paying $15/month for Claude to write code. I just found a model that codes BETTER than Opus 4.6, runs 3x faster, and costs $1/hour for unlimited scaling. Self-hosted. Always-on agents. 10B activated parameters. The agent economy just became profitable:
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AGI and Starlink Space Lasers: A Reachable Future
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AGI with Starlink space laser cans still reach you there.
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Axelera AI Showcases Edge AI Hardware at MWC 2026
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Barcelona is ready for the IQ Era. Axelera AI is providing the power. MWC 2026 kicks off, we are at the Fira Gran Via to show how the Metis and Europa AIPUs enable high performance AI at the edge without the energy constraints of traditional GPUs. Visit us at the Netherlands
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TSMC Taiwan Risk AI Chips Hyperscaler Capex Analysis
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For our first episode of our new show In-Context Cooking, we have the Founder & CEO of SemiAnalysis Dylan Patel.
— Latent.Space (@latentspacepod) 26 février 2026
We talk about:
• Taiwan endgame scenarios & TSMC risk
• AI export controls + Chinese talent flight
• $180–200B hyperscaler capex (is this a bubble?)
• Nvidia vs… pic.twitter.com/qvJCoGCiVqFor our first episode of our new show In-Context Cooking, we have the Founder & CEO of SemiAnalysis Dylan Patel. We talk about:
• Taiwan endgame scenarios & TSMC risk
• AI export controls + Chinese talent flight
• $180–200B hyperscaler capex (is this a bubble?) • Nvidia vs -
Materials Science and Generative AI Revolutionize Scientific Discovery
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This was a very nice interview by Latent Space in sunny San Diego at Neurips. https://t.co/lHUta2ezG9
— Max Welling (@wellingmax) 26 février 2026This was a very nice interview by Latent Space in sunny San Diego at Neurips. Latent.Space (@latentspacepod) 🔬 New Science pod with @cusp_ai! We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation of all modern technology—from GPUs to climate solutions—is a materials problem, and that unifying the mathematics of stochastic thermodynamics with generative AI will unlock a new paradigm of automated scientific discovery. — https://nitter.net/latentspacepod/status/2026716448626978955#m
→ View original post on X — @wellingmax, 2026-02-26 10:18 UTC
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Burning model into chip achieves 51k tokens per second
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now add this to silicon that burns the model into the chip. And we will go from 17.000 token/s to 51.000 tokens/s inference throughput will go on to expand so much faster than we ever could have predicted. This will make for the most absurd applications.
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MIT CSAIL Research Update April 2026
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This is MIT CSAIL: https://t.co/SIrlbVeuiV pic.twitter.com/Ph2yJHG22L
— MIT CSAIL (@MIT_CSAIL) 25 février 2026This is MIT CSAIL: https://
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AI-Powered Materials Science: New Era of Automated Discovery
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🔬 New Science pod with @cusp_ai!
— Latent.Space (@latentspacepod) 25 février 2026
We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation… pic.twitter.com/UKZ5xH9NK4🔬 New Science pod with @cusp_ai! We are entering a new era where materials science and discovery is transitioning from slow, manual experimentation, to a high-speed search problem powered by generative AI and "physics processing units." @wellingmax argues that the foundation of all modern technology—from GPUs to climate solutions—is a materials problem, and that unifying the mathematics of stochastic thermodynamics with generative AI will unlock a new paradigm of automated scientific discovery.
→ View original post on X — @wellingmax, 2026-02-25 17:50 UTC