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Yuntian Deng

@yuntiandeng
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Saya makin percaya bahwa perangkat lunak masa depan akan menggabungkan kode untuk alur kontrol dengan program saraf kecil untuk penilaian yang “samar”. Itulah yang saya eksplorasi lewat ProgramAsWeights: program-program ini “dikompilasi” dari deskripsi bahasa Inggris. Contohnya, saya menggabungkan 30 program saraf dengan pohon keputusan untuk membuat asisten situs kursus yang berjalan lokal dan tampak seperti chatbot. Tiap program kecil menangani pertanyaan seperti “pakar mana yang harus menerima ini?”, sementara kode mengendalikan seluruh alur. Anda bisa mencobanya di sini...

Original post / EN

I increasingly think future software will combine code for control flow with small neural programs for "fuzzy" judgments. That's what I've been exploring with ProgramAsWeights, which answers the question of where those neural programs come from: they are "compiled" from English descriptions. For example, I combined 30 neural programs with a decision tree to build a course website helper that looks like a chatbot but runs locally. Each small program handles a question like "Which specialist answerer should this be routed to", and code controls the overall flow. You can try building with it here: https://t.co/Bwgcn362bc
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Diogo Almeida @CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x https://t.co/JSybNG2BKJ

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