Now with a higher temperature (1.0), we get an idea of an auto diagram creator. Definitely more ambitious!
GENERATIVE AI
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Low Temperature AI Generates Automatic To-Do List App
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With a low temperature (0.2), we get an idea of an automatic to-do list app. Interesting, but nothing revolutionary. (model-generated text in bold)
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Temperature Controls Model Token Generation Creativity
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1. Temperature – controls how the model chooses from its next choice of tokens. Increasing the temperature makes generating tokens with lower likelihoods more probable, and vice versa. As a result:
• Lower temperature = more predictable
• Higher temperature = more creative -
Understanding Token Likelihood Parameters in Language Models
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It does this by giving a “likelihood” number to each token. So, for the phrase “I like to bake …”, “cookies” has a higher likelihood than “chairs.” “chairs” can still appear, but “cookies” has a much higher chance. But we can change this behavior with those 3 parameters.
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Adjusting Model Parameters: Temperature, Top-k, Top-p
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So, how can you do this? By adjusting the model parameters. There are 3 parameters you can adjust:
1. Temperature
2. Top-k
3. Top-p But before we see how to use them, let’s first understand how the model selects the next token to generate. -
Harmonai joins Replicate with open source audio ML models
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Also, welcome @harmonai_org to Replicate! They're a open source collective of audio ML hackers. This is just the first of many models they're working on and we're looking forward to all those robo-tunes.
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Dance Diffusion: Diffusion Model Generating Music on Replicate
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Dance Diffusion is now on Replicate. It's a diffusion model from @harmonai_org that generates music:
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AI NFT Games: Combining Artificial Intelligence with Digital Assets
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"AI NFT Game" An AI NFT Game uses NFTs and AI. The use of #NFTs in the game allows players to own and trade unique digital assets, adding an element of scarcity and value to the game. AINFTGame.Eth | AGIGame.Eth | AGIGames.Eth #AINFTGame #AGIGame #AGIGames #NFTCommunity
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Privacy-Respecting Public Pre-Training Datasets for AI Models
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So where do we go from here? We conclude with a number of suggestions for the field. The first ones focuses on making sure we have public pre-training sets which are truly privacy-respecting. Can we make such a dataset/model with comparable utility to what people use now? 12/n
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FHE Limitations for Large Model Inference Privacy
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But FHE is not so practical for these models. And it may be infeasible to use some of these large models on a user's device. So even with private fine-tuning, then privacy at inference time still remains. 11/n