In October, Whisper, a state-of-the-art audio model from @OpenAI for speech recognition was added to the library. https://
huggingface.co/docs/transform
ers/model_doc/whisper
…
LLMS
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OpenAI Whisper Speech Recognition Model Added to Hugging Face
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Meta AI Open-Sources OPT Language Model Series
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OPT was open-sourced by @MetaAI and added in the library last May. It is a series of open-sourced large causal language models similar in sizes to GPT3.
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BLOOM Multilingual Language Model Released by BigScience
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BLOOM was then released in June by @BigscienceW
. It is a similar series of model, though trained on 46 languages. https://
huggingface.co/docs/transform
ers/model_doc/bloom
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Doubling AI Model Architectures: New Audio, Vision and Multimodal Models
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We doubled the number of architectures (89 to 167) with new models in audio, text, vision, multiple modalities or even time seriesand protein folding Here are a few highlights in the most used of those new models
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Upcoming ChatGPT Features Found in Client Code: Pause, Copy, Prompt Palette
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References to possible upcoming ChatGPT features found by @eeeziii in minified client JS:
– Pause completions
– Copy thread to clipboard
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GPT-3 Synthesis of arXiv Preprint with BERT-embedded Hopfield Networks on Ethereum Blockchain
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GPT-3 zero-shot synthesis of an arXiv pre-print in LaTeX notation on distributed manifold in-painting using BERT-embedded Hopfield networks on the Ethereum blockchain. Model text-davinci-003, temperature 0.7. Playground link: https://
beta.openai.com/playground/p/m
z75vuUjGsEusUyPheyEdcSZ?model=text-davinci-003
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GPT-3 Outperforms Humans on IQ Test Benchmarks
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GPT-3 beats humans on IQ tests
#RuleoftheRobots #AI https://
studyfinds.org/are-you-smarte
r-than-ai/
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Limitations of Generative AI Tuning and Data Distribution
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Being able to produce outputs for an arbitrary input doesn’t give you the ability to reproduce the input distribution of the tuning data. Even if you somehow can, tuning on the generations of a tuned model is like making a copy of a copy of a VHS tape.
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Transformers and LSTMs: Scaling architectures and the need for innovation
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I agree with the core thing I think you’re saying: there’s lots of architectures that could allow models to scale with respect to both data and computation. Transformers are one, maybe not even a good one. But LSTMs as we have then don’t scale — so we were missing an invention
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AI Model Behavior with Inappropriate Prompts and Content Filtering
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I’m pretty sure that happens for inappropriate content at least. If you construct a prompt that looks benign in isolation but produces offensive output it spins for an unusually long time before saying “Sorry, can’t do that.”