AI & ML Research 3 Days

Last updated: July 15, 2026, 8:30 AM ET

Retrieval Augmented Generation & LLM Outputs

Recent research as the primary cause of hallucinations in RAG systems, suggesting that improving the retrieval mechanism can significantly reduce model inventiveness. To address challenges in obtaining structured data from LLMs, a combination of offers a streamlined approach, avoiding manual JSON parsing. Meanwhile, the concept of "Agentic RAG" where agents actively manage the retrieval process. Enterprises can more effectively in this agentic era by focusing on useful work per dollar and scaling workflows. A framework for custom agentic alignment: purpose, principles, and practices, to ensure autonomous AI behavior aligns with enterprise intent.

LLM Costs, Architectures & Context

Estimating the real-world cost of running local LLMs, one analysis in Euros per million tokens, finding that the cheapest model wasn't necessarily the smallest or largest. Autoencoders and latent space to techniques for handling the heavy computational demands of generative AI, particularly with unstructured data. However, long LLM sessions, even within token limits, can suffer from "context rot," and methods for sessions are being explored to mitigate this decay.

AI Development & Industry Impact

The evolving landscape of analytics careers is being reshaped by AI, prompting professionals to adapt. Google and AIM have launched "ATL Saathi," a Gemini-powered AI tool designed to empower Indian educators in robotics labs. Research into Anthropic's latest AI discoveries reveals insights, with discussions also touching upon the future of "world models" for AI. In a separate development, Psi Quantum is developing a plan for a large-scale quantum computer utilizing light.