AI & ML Research 3 Days

Last updated: July 26, 2026, 2:30 AM ET

AI & ML Research

LLM Memory and RAG Systems

Context windows in AI agents, prompting a usage-reinforced decay engine based on the Ebbinghaus forgetting curve. Most Retrieval-Augmented Generation (RAG) hallucinations are actually extraction errors, not true hallucinations, and can be addressed with seven patterns for a typed generation contract to improve accuracy. Optimizing RAG generation involves an LLM cascade, moving from cheaper local models up to a hosted flagship, incorporating a validation loop and testing twenty local models against a hosted benchmark for cost-effectiveness. Adding more AI agents to a system can ironically make it slower, revealing the hidden cost of asynchronous systems where tiny CPU tasks become a bottleneck when scaling hundreds of LLM agents.

Foundational Models and Data Science Applications

Tabular foundation models now perform on par with or better than fully tuned gradient-boosted trees on the Tab Arena benchmark, capable of predicting missing spreadsheet columns zero-shot, similar to how LLMs complete text. The Lattice Boltzmann Method can simulate fluid dynamics, like a Kármán vortex street, without directly solving fluid equations, offering a first-principles approach implemented in C++ for fluid simulation. Intelligent Document Processing (IDP) systems can be built and run in the cloud to automate the classification and extraction of Personally Identifiable Information (PII) from emails using AWS services for document analysis. When data science projects lead to unexpected outcomes, like an overbooked flight scenario, the cost difference between a $8 million solution and a $5,000 solution can be significant, with the potential for projects to go viral.

Infrastructure and Engineering Trade-offs

Optimizing vector search when RAM becomes too expensive requires navigating the trade-offs between on-disk and in-memory Approximate Nearest Neighbor (ANN) indexes, considering architectures like HNSW, SPANN, and Disk ANN for cost-effective search. After 8.5 years of experience in Machine Learning, key lessons learned include the importance of patience, optimism, discipline, project management, and effective teamwork for ML success.

Biomedical and Energy Innovations

A landmark achievement in organ transplantation involves supercooled kidneys being transplanted into pigs, a crucial step in preserving organs outside the body for longer periods, as they typically deteriorate within hours of removal for organ preservation. AI is playing a significant role in accelerating drug discovery and development, a traditionally expensive and failure-prone scientific challenge that can now be streamlined by AI tools. In energy transmission, a power line aiming to reshape New York's grid is encountering snags, as the state relies on significant electricity imports, such as 52 gigawatt-hours from Canada during a heat wave, meeting about 9% of its demand on a particular day for grid infrastructure.