Category: AI
News and analysis on AI models, chips, infrastructure, applications and the business shifts behind machine intelligence.
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Lingyan’s Bionic Face Bet: Does Emotional AI Sell?
Lingyan raised over ¥10M for its bionic face tech. We examine whether emotional robotics can move past novelty into real commercial demand.
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AI Is Coming for Your Money, Not All Money
AI is reshaping finance from trading to lending. We explore who benefits, who gets squeezed, and why the “all money” panic misses the real story.
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AI Data Centers Have a Ghost Problem Nobody Budgeted For
The AI data center boom is leaving behind ghost infrastructure: half-finished shells, stranded capacity, and idle GPUs that nobody planned to pay for.
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Goose Language: A Sign of the Coming AI Code Debt?
The Goose programming language offers a glimpse into AI’s role in coding, but it also raises questions about technical debt and software reliability.
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AI Is Rewriting Cyberattack Playbooks. Can India Adapt?
AI is reshaping cyberattacks and defense. We examine India’s readiness, the global vulnerability race, and what defenders must do to keep pace.
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The AI Wealth Gap Nobody Has Solved Yet
As AI profits concentrate in a handful of firms, neither the US nor Asia has cracked how to share the gains—and the policy vacuum is widening.
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Google May Use Gmail and Photos Data for AI-Targeted Ads
Google says Gmail and Photos data shared with AI search could feed targeted ads, raising fresh privacy questions about how personal data trains AI.
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Solar’s Labor Shortage Meets Its Robot Solution
Gritt Robotics uses AI-assisted machines to address the solar industry’s shrinking workforce, raising questions about automation, cost, and the future of clean energy jobs.
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Moonshot’s 3T Kim K3.1 Pro: What Scale Alone Won’t Settle
Moonshot AI’s Kim K3.1 Pro packs 3 trillion parameters, but the real story is cost, serving efficiency, and whether raw scale still wins in China’s model race.
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NIST Is Writing Cybersecurity Rules Just for AI Systems
NIST is developing tailored cybersecurity controls for AI systems, moving beyond borrowed IT rules to address model-specific risks and new attack surfaces.