Tag: ai
All the articles with the tag "ai".
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Lessons from OpenClaw
It’s easy to think OpenClaw is a joke because of the meetup mania — thousands of folks descending on Frontier Tower in San Francisco, wearing Mac Minis in baby slings and munching on lobster rolls. But if you think only that, you’ll be blind to why it’s succeeding and the many product and engineering lessons which it has to teach.
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ClawPod: OpenClaw on HomePod
Behold ClawPod! ClawPod is a bridge which lets you talk to your OpenClaw agent from an Apple HomePod. Does it work? Yes! Is it pretty rough around the edges? Also, yes! But until Siri finally gets her brain transplant, this is the only way I know to deliver a powerful AI personal assistant to the HomePod you already have.
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Why Claude Code Won (for now)
2025 was the year of vibecoding and AI agents. But the most improbable part of the year was the discovery that Claude Code, an old-school, text-based, command-line app was the ideal form factor for futuristic agentic workflows. Why did it happen this way? Here’s my explanation.”
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Tools that make us dumber
It may not be obvious when a tool makes us dumber
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Hyperscale LLMs, like the Apollo mission?
On whether modern LLMs in their vast data centers are as useless as Apollo 11.
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How to vibewrite a manifesto
Two weeks ago I couldn’t sleep so I was browsing twitter (bad habit). One thing led to another. I bought a domain name. I woke up and vibecoded a web manifesto, which a couple hundred people commented on. This was fun.
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Finally, a Replacement for BERT: Introducing ModernBERT
Introducing ModernBERT, a family of state-of-the-art encoder-only models representing improvements over older generation encoders across the board, with 8192 sequence length, better downstream performance and much faster processing. Available as a slot-in replacement for any BERT-like models.
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Faith and Fate: Transformers as fuzzy pattern matchers
What do transformer-based AI models actually learn? Can they solve complex problems by reasoning systematically through multiple steps? The Faith and Fate paper (Dziri et al. 2023) suggests answers: they often succeed by pattern matching, not systematic reasoning.