Driven mostly by chip manufacturing right now. Let's keep it going up and to the right. Next up: fully-automated ports, high-speed rail, nuclear power, solar. It's time to build.
@fchollet
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Major daily services rely on this code
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Most of the services you use daily (including X/Twitter, YouTube, Spotify, Netflix, Snap, Waymo…) are using some of this code
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AI as Excuse for Cost-Cutting, Not Genuine Productivity Gains
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Haven't seen any company firing devs because they genuinely anticipated they wouldn't need humans anymore. But I have seen a few companies firing devs because they needed to cut costs, saying "it's because of AI!" The story "we're so productive now we don't need employees
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Knowledge Benchmarks Don’t Equal Real-World Capabilities
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Exam-style knowledge benchmarks != Real-world capabilities
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LLMs positioned mid-way between capabilities and limitations
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I would disagree here, based on current LLM capabilities and failure cases, I would place them mid-way. They are genuinely "in-between"
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Understanding Differs from Compression: Prediction and Action Across Contexts
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No, compression is a means, understanding is an ability. You understand something if you can correctly make predictions and take action across all relevant situations
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Deep Learning Abstractions Limited to Local Generalization Across Domains
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These weakly abstract models can generalize, but only locally so. They still break down upon simple problem modifications or when encountering novel problems. This has been true of all deep learning generated abstractions, across every domain and across all architectures.
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Models as spectrum between associations and causal abstractions
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While this is directionally right, keep in mind that this is not a binary distinction. There's a spectrum between, on one extreme, collections of associations (e.g. a lookup table), and on the other extreme a maximally concise, abstract causal model (e.g. Snell's law). With https://
x.com/Grady_Booch/st
/Grady_Booch/status/1835413920624030136
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Keras get_file now returns extracted directory path instead of archive
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Making some life-quality changes to `keras.utils.get_file`: when extracting an archive, it will return the path to the extracted dir rather than the archive path. Just plain better.
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The Future Depends on Who Serves Whom: Humans or Machines
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The good future is the one where the machines exist to support humans. The bad future is the one where humans exist to support the machines