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Antibodies, known for their precision in targeting diseases like cancer and autoimmune disorders, are challenging to model due to their flexible and diverse structures. To address this, A-Alpha Bio developed AlphaBind, an AI model designed to predict and optimize antibody-antigen binding affinity. Leveraging NVIDIA and AWS technology, AlphaBind uses experimental data and advanced machine learning… Continue reading In-Silico Antibody Development with AlphaBind Using NVIDIA BioNeMo and AWS HealthOmics

AI shopping agents are emerging tools that can navigate retail websites, find products, and complete purchases on behalf of users through simple prompts. Companies like Perplexity, Google, and OpenAI are developing such agents, with Perplexity already offering one that can browse and purchase items using a system powered by Stripe’s single-use debit cards. However, challenges… Continue reading The race is on to make AI agents do your online shopping for you

NYU Langone Health achieved a world-first by performing a fully robotic double lung transplant on a 57-year-old woman with severe COPD. Using the Da Vinci Xi robotic system, the surgical team, led by Dr. Stephanie Chang, replaced both lungs through small incisions, offering a minimally invasive approach with reduced pain and quicker recovery. The patient,… Continue reading World’s First Fully Robotic Double Lung Transplant Performed by NYU Langone Health

This study examines how large language models (LLMs) use their training data to solve reasoning tasks, such as math problems, compared to answering factual questions. It found that while factual answers often come directly from specific training documents, reasoning tasks rely on general strategies learned from documents demonstrating how to solve similar problems. These strategies… Continue reading Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models

A recent study explored using AI models to improve brain tumor detection in MRI scans by applying a unique method called transfer learning. Researchers adapted a neural network originally trained to detect camouflaged animals, hoping it could better identify subtle features in brain images, similar to how camouflage works in nature. The study focused on… Continue reading Camouflage detection boosts neural networks for brain tumor diagnosis

The OLMo 2 series introduces advanced open-source language models with 7B and 13B parameters, designed to rival leading models like Llama 3.1 and Qwen 2.5 in performance. These models, trained on a massive dataset of 5 trillion tokens, deliver significant improvements in understanding and reasoning across various benchmarks, making them the best fully open models… Continue reading OLMo 2: Advanced Open-Source Models Rivaling Top AI Systems

This paper explores how large language models (LLMs) are transforming the way we interact with software through GUI automation. These advanced AI agents can understand and process visual elements of software, execute tasks based on natural language commands, and simplify complex, multi-step actions. Applications range from web navigation to mobile and desktop automation. The paper… Continue reading Large Language Model-Brained GUI Agents: A Survey

A study published in Nature Human Behaviour shows that large language models (LLMs), like BrainGPT, can predict scientific outcomes with greater accuracy than human experts. Researchers tested 15 LLMs and 171 neuroscientists using BrainBench, a tool that compares real and fake neuroscience study results. LLMs achieved 81% accuracy, while human experts averaged 63%. A specialized… Continue reading AI can predict study results better than human experts

Researchers found that multimodal AI models, like Gemini Pro and GPT4o, understand time-series data better when presented as visual plots rather than raw numbers. Time-series data, such as activity tracking or medical signals, is often challenging to analyze, but using plots makes it easier for these models to identify patterns and trends. In experiments on… Continue reading Unlocking the power of time-series data with multimodal models