Instruction models making their way into the open-source!
AI
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Embeddings Integration and Prototype Support Offer
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yeah as @devonbrackbill said, probably pretty doable with embeddings! and should fit into the current abstractions pretty nicely. if youve got a concrete usecase and need, happy to help prototype some stuff!
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DreamBooth Model Training Now Available for All Users
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yes!!! you no longer need to be a pro user to train dreambooth models!
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Software Stack Enables ML Training and Inference Across Frameworks
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"Software is one of the hardest obstacles in cracking the ML training and inference market. Our software stack is capable of running both training and inference from all the different popular machine learning frameworks and architecture design." @TMLS_TO
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Flamingo AI Advances Computer Vision Beyond Past Predictions
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10 yrs ago @karpathy wrote a blog post on the outlook of AI: https://
karpathy.github.io/2012/10/22/sta
te-of-computer-vision/
… in which he describes how difficult it would be for an AI to understand a given photo, concluding "we are very, very far and this depresses me."
Today, our Flamingo steps up to the challenge. -
Testing Flamingo AI’s Image Recognition Against Parental Challenge
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The "Parents AI test". My dad just sent me a picture and told me: "there's no way AI can guess what this is". Challenge accepted! #Flamingo
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Featuretools-SQL: Automated Feature Engineering for Databases
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Introducing Featuretools-SQL: The easy way to import data from your #RDBMS and perform automated #FeatureEngineering. Streamline your #MachineLearning process with our new library. Learn more in our blog: http://
ow.ly/kFhA50M69ww #Python #databases #postgres #Snowflake #mySQL -
AI Inference Hardware Optimization for Machine Learning Workloads
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Thank you for your continued support as we work to help companies run AI inference workloads faster, cooler, and more cost-effectively using #atmemorycomputation. We look forward to the innovations and advancements that 2023 will hold! #ML #deeplearning #neuralnetworks #AI
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Fine-tuning vs. In-context Learning: Exploring Alternative Approaches
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this is great question! i think its an unexplored space. finetuning is much more heavy weight (error prone, hard to do, more data required, etc), so it will be interesting to see if you can achieve similar performance just by using examples
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Create unlimited AI-generated images with Dreambooth and retain rights
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Did you know that you can create your own AI-generated images (that too unlimited) & keep the rights of your original images & have the trained model for yourself without spending a fortune? Try Dreambooth by AutoTrain: https://
huggingface.co/spaces/abhishe
k/dreambooth
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