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Large Action Models: Beyond Language, Into Action

Viso.ai

Large Action Models (LAMs) are deep learning models that aim to understand instructions and execute complex tasks and actions accordingly. It uses formal languages, like first-order logic, to represent knowledge and an inference engine to draw logical conclusions based on user queries. Symbolic AI Mechanism.

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Generate a counterfactual analysis of corn response to nitrogen with Amazon SageMaker JumpStart solutions

AWS Machine Learning Blog

The accomplishments of deep learning are essentially just a type of curve ļ¬tting, whereas causality could be used to uncover interactions between the systems of the world under various constraints without testing hypotheses directly. The causal inference engine is deployed with Amazon SageMaker Asynchronous Inference.

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Speed is all you need: On-device acceleration of large diffusion models via GPU-aware optimizations

Google Research AI blog

We address this challenge in our work titled ā€œ Speed Is All You Need: On-Device Acceleration of Large Diffusion Models via GPU-Aware Optimizations ā€ (to be presented at the CVPR 2023 workshop for Efficient Deep Learning for Computer Vision ) focusing on the optimized execution of a foundational LDM model on a mobile GPU.

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Build a personalized avatar with generative AI using Amazon SageMaker

AWS Machine Learning Blog

base model using SageMaker asynchronous inference. We explain the rationale for using an inference endpoint for training later in this post. We explain each step in more detail in the following sections and walk through some of the sample code snippets. amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117"