AI & ML Research 3 Days

Last updated: July 12, 2026, 2:30 PM ET

AI Model Behavior and Limitations

Researchers are exploring the internal workings of large language models, with Anthropic developing a technique to observe Claude as it processes information. This research aims to better understand how these models handle tasks, moving beyond simply observing outputs. Meanwhile, the issue of AI hallucination persists; even advanced models that can range from amusing to harmful. The limitations of long context windows in LLMs are also being addressed, as excessive token accumulation can due to remembering too much rather than forgetting.

RAG and Future AI Infrastructure

The debate continues regarding Retrieval-Augmented Generation (RAG) and fine-tuning techniques, with an emphasis on understanding their distinct applications for different problems rather than declaring a single winner. However, some argue that RAG itself is a temporary solution, suggesting that future AI infrastructure will rely on persistent neural states and strict latency budgets rather than vector databases, marking a potential shift beyond RAG.

Agentic AI and Data Engineering

The concept of agentic AI is facing scrutiny, with concerns that an over-reliance on delegating tasks to machines could be a significant drawback. In parallel, practical data engineering skills are being highlighted, with a guide on building a second ETL pipeline with Python, Docker, Postgre SQL, and Kestra, focusing on a production-ready RSS pipeline. For those looking to advance their data processing capabilities, a guide to intermediate PySpark skills covers partitions, shuffles, joins, caching, and execution plans.

AI in Enterprise and Operations

Enterprises are actively integrating AI to transform operations. Deutsche Telekom is working to become an AI-native telecommunications company, using AI to enhance customer service, employee workflows, and network operations, with a focus on the future of voice communication. On a smaller scale, developers are experimenting with orchestrating numerous AI agents, with one guide detailing how to in parallel using Claude code.