GPT-4 could treat the Turing test the same way we treat CAPTCHA
LLMS
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Cerebras and Cirrascale Launch Affordable LLM Cloud Service
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If you’re working on large language models on a budget, Cerebras and Cirrascale offer a cloud service starting at $2,500. Large language models are about to be a giant commercial phenomenon, says Cerebras CEO Feldman. // @cerebras // #AI #deeplearning #machinelearning
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New Partnership Democratizes AI Model Training at Lower Cost
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According to @VentureBeat our new offering with @Cirrascale “democratizes #AI by giving users the ability to train GPT-class models much more inexpensively than existing providers” and our partnership with @Jasper “accelerates adoption and improves the accuracy of generative AI.”
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Transformer Equations as Low-Level Microcode and Assembly Instructions
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Nice! Like the track of work. Equations of Transformer are a bit like low-level microcode, this track tries to "go up" to uncover an implied assembly instruction set (e.g. RAW "read-arithmetic-write" operator?), and implemented algorithms on top of that for e.g. ridge regression.
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Allen AI’s CLOSE Completes Visual Tasks From Text Inputs Alone
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No Images Are Needed! Allen AI’s CLOSE Learns to Complete Visual Tasks From Text Inputs Alone
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Efficient Pre-training and Fine-tuning Approaches for Large Models
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As the scale of models increases, the computational effort needed for training grows rapidly. Check out a pair of new approaches that can significantly improve model performance through thoughtful pre-training and fine-tuning with only minimal compute. https://
goo.gle/3UicYbD -
GPT-3 Improved Rhyming Generates Green Day Song Lyrics
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The new version of GPT-3 is significantly improved at rhyming! Here, I use it to generate the lyrics for a new Green Day song.
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CICERO by Meta AI: Fluent Conversations with Multiple Diplomacy Players
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What impresses @ml_perception the most about #CICERObyMetaAI is its ability to hold fluent, human-like conversations with up to Diplomacy players simultaneously. Learn how we created an interface between language and strategic reasoning models:
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Chains for User Input and Memory in LangChain
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Yes to both! I think they are probably slightly different things, ones getting it know if it needs more info (adding in a “user input” chain) and another is getting it to keep the overall goal in mind (memory probably good for this)