A Gene Editing Therapy Cut Cholesterol Levels by Half
An experimental gene-editing therapy developed by Crispr Therapeutics is showing promise for treating heart disease.
An experimental gene-editing therapy developed by Crispr Therapeutics is showing promise for treating heart disease.
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When we ask ourselves the question, ” what is inside machine learning systems? “, many of us picture frameworks and models that make predictions or perform tasks.
In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer. Unlike traditional methods, this algorithm is not based on temporal difference (TD) learning (which has scalability challenges), and scales well to long-horizon tasks. We can do Reinforcement Learning (RL) based on divide and conquer, instead of temporal …
What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task. Despite the fact that word2vec is a well-known precursor to modern language models, for many years, researchers lacked a quantitative and predictive theory describing its learning process. In our new paper, we …
× Predicting Ego-centric Video from human Actions (PEVA). Given past video frames and an action specifying a desired change in 3D pose, PEVA predicts the next video frame. Our results show that, given the first frame and a sequence of actions, our model can generate videos of atomic actions (a), simulate counterfactuals (b), and support …
Read more “Whole-Body Conditioned Egocentric Video Prediction”
This paper was accepted at the Workshop on Unifying Representations in Neural Models (UniReps) at NeurIPS 2025. Activation steering methods in large language models (LLMs) have emerged as an effective way to perform targeted updates to enhance generated language without requiring large amounts of adaptation data. We ask whether the features discovered by activation steering …
Read more “ExpertLens: Activation Steering Features Are Highly Interpretable”
Organizations need seamless access to their structured data repositories to power intelligent AI agents. However, when these resources span multiple AWS accounts integration challenges can arise. This post explores a practical solution for connecting Amazon Bedrock agents to knowledge bases in Amazon Redshift clusters residing in different AWS accounts. The challenge Organizations that build AI …
Read more “Connect Amazon Bedrock agents to cross-account knowledge bases”
n8n is a powerful yet easy-to-use workflow and automation tool for multi-step AI agents, and many teams want a simple, scalable, and cost-effective way to self-host it. With just a few commands, you can deploy n8n to Cloud Run and have it up and running, ready to supercharge your business with AI workflows that can …
Read more “Easy AI workflow automation: Deploy n8n on Cloud Run”
The developers of Terminal-Bench, a benchmark suite for evaluating the performance of autonomous AI agents on real-world terminal-based tasks, have released version 2.0 alongside Harbor, a new framework for testing, improving and optimizing AI agents in containerized environments. The dual release aims to address long-standing pain points in testing and optimizing AI agents, particularly those …