AI & ML Research 3 Days

Last updated: July 24, 2026, 2:30 AM ET

AI for Scientific Discovery and Health

Google Deep Mind commits $40M to the Genesis Mission, aiming to accelerate scientific discovery with AI. OpenAI outlines its commitment to advancing American science by partnering with the U.S. Department of Energy and national labs to utilize frontier AI for discovery. In medicine, AI the next generation of medicines, a process that is traditionally expensive and failure-prone. For health insights, ChatGPT now securely connect medical records and Apple Health data. A conversational AI agent for everyday symptom assessment, called Symptom AI, is being developed by Google AI.

LLM Runtimes and Agent Development

For those looking to build their own LLM inference runtime from scratch, a guide details the journey on an H100, covering weight packing and CUDA graphs. To enhance LLM agent capabilities, a practical walkthrough that can write and run code using the OpenAI Agents SDK and Docker. However, scaling hundreds of LLM agents can introduce unexpected bottlenecks; one system actually made it slower, highlighting the hidden costs of asynchronous systems. To address errors in Retrieval Augmented Generation (RAG), most hallucinations are identified as extraction errors rather than true hallucinations, and seven patterns for a typed generation contract are proposed. Further improvements to RAG generation focus on iterating top-k candidates one at a time, with two regimes for sending retrieved candidates to the generation brick and a sufficiency signal that picks between them being detailed. Prompt engineering alone is insufficient; context engineering with four bricks is by ensuring faithful answers to the correct context.

AI Infrastructure and Security

OpenAI is in Effingham County, Georgia, with Project Camellia, emphasizing responsible energy, community investment, jobs, and access to Codex. OpenAI and Hugging Face partnered to address a security incident during model evaluation, sharing early findings and lessons for defenders. In enterprise solutions, OpenAI introduces Presence, a platform for deploying trusted voice and chat agents for customer and internal workflows. NTT DATA Group has to 30 minutes by utilizing Chat GPT Enterprise and Codex, enabling secure AI adoption for 9,000 employees. A new program is launched by OpenAI to help small businesses build AI skills, automate work, and grow with Chat GPT Work.

ML Operations and Experimentation

For those whose ML experiments are a mess, a hands-on guide provides a fix for tracking experiments, logging models, and reproducing results using ML Flow. Patience, optimism, discipline, project management, and team dynamics are identified as key lessons learned after 8.5 years of ML, as detailed in a recent post. Fine-tuning a robot AI model on Colab is explored with a reproducible 100-step LoRA fine-tuning run for Open VLA, including dataset checks, Colab setup, training metrics, and Weights & Biases evidence being shared. The extent to which data science workflows can run on a GPU today is examined, with Part 1 focusing on accelerating data preparation using cu DF, cudf.pandas, and the Polars GPU Engine being explored.

AI in News and Emerging Technologies

News organizations are using AI to strengthen reporting, grow audiences, and improve business operations, with OpenAI tools supporting journalists and publishers. In broader technological developments, a power line that could reshape New York’s grid is, impacting the state's energy transmission capabilities, which relied on importing 9% of its electricity from Canada on a recent heat wave day as reported. The conversation around AI advances also centers on materials science innovation, which underpins algorithms, computing power, and semiconductor fabrication. Separately, a quantum computer that learns from its errors is being developed by Google AI, signaling progress in machine intelligence.

AI Security and Data Science Challenges

Detecting vulnerabilities in agent skills is approached with Skill Spector, which moves from simple green checkmarks to real security judgments, as static analysis is noted to nail malicious skills while over-flagging useful ones, leaving a gap where human judgment is essential as explained. Data science can sometimes lead to negative emotional outcomes, as illustrated by the story of an overbooked flight where an $8 million cost was weighed against $5,000 and potentially going viral being discussed.