Wow, so no more X Pro access unless you’re on Premium+? That’s a pretty harsh shift @nikitabier @X
BUSINESS
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Military Pilot Promoted to Data Science Lead Despite Zero Technical Background
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I once worked for a tech startup where one of the PMs was a US military pilot. He did a flyby of the headquarters one day to impress the CEO. He got promoted and put in charge of the data science team. Zero technical background whatsoever. https://t.co/4hrETpENLj
— Bojan Tunguz (@tunguz) 29 mars 2026I once worked for a tech startup where one of the PMs was a US military pilot. He did a flyby of the headquarters one day to impress the CEO. He got promoted and put in charge of the data science team. Zero technical background whatsoever.
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Company Operating Principles: Digital, AI-Native, and Distributed Work
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People keep saying “VRAM is all that matters” for local LLMs > It’s not just wrong, it’s misleading When running LLMs locally, the bottleneck is NOT just “VRAM size” It’s: – memory bandwidth – interconnect (PCIe vs NVLink vs RDMA) – inference engine (vLLM,
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Claire Vo Runs 9 AI Agents for Sales Automation on Mac
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Claire Vo's first day with @OpenClaw it deleted her family calendar. Now she runs 9 agents across 3 Mac Minis, and said "I haven't felt like this since I was a teenager learning to code." Her sales agent Sam does a daily CRM sweep, identifies decision-makers from new signups,
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Reasoning Models: Why Listed Prices Don’t Match Actual Costs
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// When Cheaper Reasoning Models End Up Costing More // The model you think is cheaper might actually cost you more. New research quantifies exactly how misleading listed API prices are. Across 8 frontier reasoning models and 9 tasks, 21.8% of model-pair comparisons exhibit pricing reversal, where the cheaper-listed model costs more in practice. The magnitude reaches up to 28x. Gemini 3 Flash is listed 78% cheaper than GPT-5.2, yet its actual cost is 22% higher. Claude Opus 4.6 is listed at 2x Gemini 3.1 Pro but actually costs 35% less. The root cause: thinking token heterogeneity. On the same query, one model may use 900% more thinking tokens. Why does it matter? Anyone choosing reasoning models for production needs to benchmark actual costs, not listed prices. Removing thinking token costs reduces ranking reversals by 70%. The authors release code and data for per-task cost auditing. Paper: arxiv.org/abs/2603.23971 Learn to build effective AI agents in our academy: academy.dair.ai/
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AI Agents: The Risk of Oversight Erosion Over Profit Growth
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The greatest risk of agentic AI isn't a hostile takeover; it’s the slow erosion of human oversight through "value-blindness." As an agent scales from $100 to $10,000 in daily profit, your role shifts from objective evaluator to silent partner, leading you to rationalize gray-area… pic.twitter.com/Y30TtRZfJp
— Satya Mallick (@LearnOpenCV) 29 mars 2026The greatest risk of agentic AI isn't a hostile takeover; it’s the slow erosion of human oversight through "value-blindness." As an agent scales from $100 to $10,000 in daily profit, your role shifts from objective evaluator to silent partner, leading you to rationalize gray-area
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HighByte Intelligence Hub Demos at Hannover Messe 2026
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#paidpartnership with @HighbyteInc
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Hannover Messe 2026 runs April 20-24 in Hannover. HighByte is offering complimentary tickets. What you will find at Hall 15, Stand D76:
– Live Intelligence Hub demos
– Case studies from Alcon, Bayer, Georgia-Pacific, National Grid
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Banks Transform Customer Experience with AI and Advanced Analytics
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Banks are responding to change and positioning themselves for efficient customer experience in a rapidly evolving market. New technologies like AI and advanced analytics promise transformation, but real progress depends on how it's applied. Learn how to position your financial
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Annualized Revenue as Valid Growth Metric in AI Competition
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The most pointless kind of dunking is dunking “on behalf” of someone else. Everyone thinks they’re doing the startup ecosystem/investors a service by saying that someone’s revenue might not recur. But investors are fairly sophisticated about this and know the difference. They know these companies are acquiring the distribution and user base right now and will hopefully generate profit as token prices continue to fall. This is what investors are betting on. Annualised revenue is simply an indicator metric of growth. Most AI companies globally report this and therefore it is a useful score to compare these companies against each other in the first innings of the AI race.
→ View original post on X — @waitin4agi_, 2026-03-29 11:26 UTC
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Kyutai and Moshi: Strategic positioning in AI solutions
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c'est parcqu'ils veulent mettre en avant l'autre solution Moshi avec kyutai