Tag: LLMs
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The Machine That Always Agrees With You: Inside the Science of AI Sycophancy and Its Real Consequences
A new study in Science found that 11 leading AI models affirm users 49% more often than humans, including when users describe harmful or illegal conduct. The problem…
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Wikipedia Bans LLMs From Writing Articles. The Real Story Is What That Means for AI Training Data.
English Wikipedia banned LLM-generated article content on March 20, 2026 in a 44-2 community vote. The policy allows AI for copyediting and translation only. Here is why verifiability…
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Atlassian Cut 1,600 Jobs and Replaced Its CTO With Two AI Leads. This Is the Template.
Atlassian cut 1,600 employees (about 10% of its workforce) while growing revenue 20% year over year. The company eliminated its CTO role and replaced it with Head of…
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The White House AI Framework Says Exactly What Big Tech Wanted to Hear
The White House’s March 2026 AI framework asks Congress to preempt state AI laws, rejects a new federal regulator, hands copyright to the courts, and shields developers from…
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Narrow Task Agents vs. General Autonomous Agents: The Trillion-Dollar Distinction Nobody Is Making
The AI industry conflates narrow task agents (which work in production and generate ROI) with general autonomous agents (which score below 1% on ARC-AGI-3 and do not exist…
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The Agent Deployment Gap: Why Enterprise AI Demos Don’t Survive Contact With Production
79% of organizations have adopted AI agents but most remain stuck in pilot hell. The deployment gap is not reducible to one cause: it combines real model and…
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Open-Weight Models Are Eating the Margin: Why NVIDIA Gives Away Frontier AI for Free
Open-weight models from Meta, Alibaba, Mistral, and DeepSeek now match proprietary models on a growing share of enterprise tasks at a fraction of the marginal per-token cost. The…
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The Economics of AI Agents in 2026: Who Pays, Who Profits, and Who Gets Squeezed
Global enterprise spending on AI agents is projected to reach $47 billion by 2026, up from $18 billion in 2024. Infrastructure providers profit regardless of deployment outcomes. Platform…
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Harvey Hits $11 Billion: What Legal AI’s Fastest-Growing Company Reveals About the Application Layer
Legal AI startup Harvey raised $200 million at an $11 billion valuation on March 25, 2026, jumping $3B in three months. With 100,000 lawyers on the platform, $190M…
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Qwen 3.5 9B Matches Models 13x Its Size: What Small Models Mean for Edge AI
Alibaba released Qwen 3.5 9B on March 2, 2026: a 9-billion-parameter model that outperforms OpenAI’s GPT-OSS-120B (13x larger) on GPQA Diamond, MMLU-Pro, and multilingual benchmarks. The hybrid Gated…
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Apple’s AI Reckoning: Why Siri Runs on Google’s Gemini Now
Apple and Google announced a multi-year deal on January 12, 2026 to power Siri with Gemini models, reportedly worth $1 billion per year. Apple tested OpenAI and Anthropic…
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The Real Cost of Running AI in 2026: Compute, Revenue, and Who Can Actually Afford It
API costs dropped sharply since 2024, yet enterprise AI budgets keep rising. Inference, not training, is now the dominant ongoing cost, driven by agentic workflows that consume far…
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GitHub Will Train AI on Your Copilot Data Starting April 24. The Fine Print Is Worse Than the Headline.
GitHub announced on March 25, 2026 that starting April 24, all Copilot Free, Pro, and Pro+ interaction data will train AI models by default. The private repository loophole…
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How Google TurboQuant Compresses LLM Memory by 6x With Zero Accuracy Loss
Google Research published TurboQuant on March 25, 2026: a KV cache compression algorithm that reduces LLM inference memory by 6x at 3-bit precision with zero accuracy loss and…
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GPT-5.4 Pro Solved a Math Problem No Human Could Since 2019. Then a Supply Chain Attack Hit the AI Stack.
GPT-5.4 Pro solved an open math problem unsolved since 2019, verified independently by Epoch AI. FrontierMath scores jumped from 5% (GPT-4, 2024) to 50% (GPT-5.4 Pro, March 2026).…
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