AI & ML

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Shark Week Special: The AI Ocean, Who Eats Who in the Enterprise AI Food Chain?

TL;DR Enterprise AI is not one market. It is a connected ecosystem of business applications, model providers, data platforms, private AI operating models, accelerated infrastructure, networking, and physical facilities. The vendors that create the most technical capability do not always capture the most enterprise value. Value tends to accumulate around control points: user distribution, proprietary

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Anthropic is finding bugs faster than Microsoft can fix them

On an afternoon in mid-May, dozens of Microsoft engineers and their managers gathered online and in a conference room at the company’s Redmond, Washington, headquarters to discuss Project Glasswing. The tech giant was racing to fix weaknesses in its code that a new AI model known as Mythos was uncovering at an unprecedented clip. The

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The AI Agent Feeding Frenzy: What Happens When Autonomous Systems Compete for the Same Resources?

TL;DR In honor of shark week. the best week of the year, here are some inspired topics. The most dangerous agent failure may not involve one agent going rogue. It may involve dozens of agents behaving reasonably inside their own local rules while collectively exhausting the same API quota, GPU pool, queue, credential boundary, budget,

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What happens when you put AI to work deciphering lost languages?

Every ancient language that has ever been deciphered needed an anchor. Usually that’s a bilingual text, like the Rosetta Stone, or a known relative to compare it to. Linear A, the writing system of the Bronze Age Minoan civilization on the Greek island of Crete, has neither. Linear A is described as a “language isolate”

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Centralize co-founders Rachit Kataria (left) and William Wang. [courtesy photo]

Exclusive: Former Meta And Slack Engineers Raise $15M For New Startup Centralize To Build A ‘Deal GPS’ For Enterprise Sales

While working as a product tech lead at a startup, Rachit Kataria watched a multi-hundred-thousand-dollar enterprise account suddenly fall into jeopardy.  After pausing his entire engineering team’s workload for two weeks to ship a requested fix, he discovered the effort made no difference. The customer still threatened to churn. “We did a retro, and wouldn’t

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