7/ At the end of the day, Sora proved something the whole industry is about to face. Hype gets you to number one. It does not pay the compute bill. And the bill always comes. Source: OpenAI, with figures from Forbes, Cantor Fitzgerald, WSJ, and Appfigures.
COMPUTING
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Multi-step Workflows: Persistent State and Parallel Bursting
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You run multi-step workflows where state must persist across tool calls. You need bursting capability (i.e., thousands of parallel environments for RL training or evaluations) that must go from zero to scale in
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Run local models with agent harnesses like Codex or Claude Code
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You can run local models at home and use any agent harness like Codex or Claude Code with them https://t.co/e5blwOYytx
— Ahmad (@TheAhmadOsman) 16 juin 2026You can run local models at home and use any agent harness like Codex or Claude Code with them
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Deep Agents Part 2: Context Management
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Deep Agents deep dive Part 2 | Context Management
— LangChain (@LangChain) 16 juin 2026
A <2 min explanation on one of the most important capabilities in the Deep Agents harness from @SydneyRunkle pic.twitter.com/tnIsx9aiLiDeep Agents deep dive Part 2 | Context Management A
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NVIDIA Blackwell platform dominates MLPerf Training 6.0 benchmarks
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The NVIDIA Blackwell platform just swept MLPerf Training 6.0, delivering fastest performance and largest scale.
— NVIDIA (@nvidia) 16 juin 2026
Beyond the benchmarks, capabilities like the Reliability, Availability, and Serviceability Engine and NVIDIA Resiliency Extension deliver fewer interruptions and… pic.twitter.com/QH77j4UA8nThe NVIDIA Blackwell platform just swept MLPerf Training 6.0, delivering fastest performance and largest scale. Beyond the benchmarks, capabilities like the Reliability, Availability, and Serviceability Engine and NVIDIA Resiliency Extension deliver fewer interruptions and
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AI Performance Is an Infrastructure Issue, Not Just Software
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The PGA Championship is a useful reminder for every technology leader: AI performance is not just a software issue. It is an infrastructure issue. Before asking what AI can automate, predict, or recommend, leaders should ask whether their network can support those decisions
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Colossus 2 not fully used with Grok
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To my knowledge, Colossus 2 is also not fully used with Grok.
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Radically efficient AI for an open-source future
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The way we will create a future where powerful AI is open-source and accessible to all is by making AI radically more efficient, both in terms of inference compute and (more importantly) in terms of training data requirements. That is what
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Google unveils TimesFM, a zero-shot predictive AI
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GOOGLE HA LIBERADO EN SILENCIO UNA IA QUE PREDICE PATRONES
— Nico (@nicos_ai) 16 juin 2026
Ventas. Precios de mercado. Tráfico web.
Demanda energética. Volatilidad cripto.
Se llama TimesFM:
→ Entrenada con 100B de datos reales
→ Forecasting zero-shot, sin fine-tuning
→ Corre en local.
100% Gratis y Open… pic.twitter.com/shKaFPJuxhGOOGLE HAS QUIETLY RELEASED AN AI THAT PREDICTS PATTERNS Sales. Market prices. Web traffic.
Energy demand. Crypto volatility. It's called TimesFM: → Trained on 100B of real data
→ Zero-shot forecasting, no fine-tuning
→ Runs locally. 100%
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Small specialized models are the future; buying a GPU was right
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Small and specialized models are the future Buy a GPU was right