This article discusses five cutting-edge AutoML techniques and trends that are expected to shape the landscape of highly automated machine learning model building in the 2026 year about to start.
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OpenAI is investing in stronger safeguards and defensive capabilities as AI models become more powerful in cybersecurity. We explain how we assess risk, limit misuse, and work with the security community to strengthen cyber resilience.
Author(s): Manash Pratim Originally published on Towards AI. I Built an AI That Understands My Team’s Emotions From Our Commits and Messages I built an AI that analyzes commits, PR reviews, and Slack messages to detect emotional drift and burnout in engineering teams. Using vector-drift embeddings and a fine-tuned LLaMA model, it learned to read the subtext beneath our communication and the results shocked me. Image generated using AIThe article discusses the creation of an AI designed to […]
Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables. Compare that with human scientists, who work in a collaborative environment and consider experimental results, the broader scientific literature, imaging and structural analysis, personal experience or intuition, and input from colleagues and peer reviewers. Now, MIT researchers have developed a method for optimizing materials recipes and planning experiments […]
Understanding AI in 2026 — from machine learning to generative models The post Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI — Clearly Explained appeared first on Towards Data Science.
How an “automobile” can become a talisman before which the Fourth Amendment fades. The post Does the Fourth Amendment require a garage? The Moses Case appeared first on Downsize DC.
Pixi makes python environment management simple, consistent, and portable.
Imagine having a continuum soft robotic arm bend around a bunch of grapes or broccoli, adjusting its grip in real time as it lifts the object. Unlike traditional rigid robots that generally aim to avoid contact with the environment as much as possible and stay far away from humans for safety reasons, this arm senses subtle forces, stretching and flexing in ways that mimic more of the compliance of a human hand. Its every motion is calculated to […]
What recruiters are looking for in machine learning portfolios The post Don’t Build an ML Portfolio Without These Projects appeared first on Towards Data Science.