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| | | | | Stories about code, design, coffee and other good stuff. | |
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| | | | | One of the major reasons my company prefers Java over Python, is Java's static type declarations (and all the benefits that follow). If only Python had that, my life would be so much nicer. | |
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golangbot.com
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| | | | | A tutorial about WebAssembly and how to cross compile and run Go programs in the browser using WebAssembly. | |
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jalammar.github.io
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| | | Discussions: Hacker News (397 points, 97 comments), Reddit r/MachineLearning (247 points, 27 comments) Translations: German, Korean, Chinese (Simplified), Russian, Turkish The tech world is abuzz with GPT3 hype. Massive language models (like GPT3) are starting to surprise us with their abilities. While not yet completely reliable for most businesses to put in front of their customers, these models are showing sparks of cleverness that are sure to accelerate the march of automation and the possibilities of intelligent computer systems. Let's remove the aura of mystery around GPT3 and learn how it's trained and how it works. A trained language model generates text. We can optionally pass it some text as input, which influences its output. The output is generated from what the model "learned" during its training period where it scanned vast amounts of text. | ||
