AI Research Posts

FOD#107: It's NOT the year of agents – it's the year when WE got used to AI

Plus 10 open-source deep research assistants and other useful stuff

🎙️When Will We Fully Trust AI to Lead?

An Inference with Eric Boyd, CVP of AI Platform

RLHF variations: DPO, RRHF, RLAIF

DPO, RRHF, and RLAIF explained: three RLHF alternatives that skip reward models, use ranking loss, or replace human annotators with AI feedback.

FOD#106: Don't be passive aggressive with your agents

Plus: who to hire from the coding agents crowd, and a new video on how Sam Altman’s thinking about AI is evolving

🦸🏻#20: Best AI Coding Agents in 2026: Which One Wins?

Hands-on comparison of 15 coding agents across IDEs, CLIs, and full-stack platforms. Cursor and Warp lead. See scores, DX ratings, and who to use for what.

FOD#105: Will “Agent Wars” Shift From Cloud to Device?

plus signals from Sam Altman most people missed

🎙️Why AI Still Needs Us?

An interview with Toloka CEO Olga Megorskaya on human-AI co-agency: how human-in-the-loop work evolved from labeling to expert judgment, RLHF, and benchmarks

🔹 Ready to accelerate your AI innovation? The time is now.

Join us for this exclusive virtual event from AI innovators CoreWeave and NVIDIA to help us collaboratively redefine the future of AI

DeployCon SF: Free GenAI Summit ft. DoorDash, ConverseNow, and more

Guest Post: Yambda-5B and Open Recommender System Datasets Explained

Yambda-5B is Yandex's open recommender dataset: 4.79B user interactions, audio embeddings, and organic flags — a production-scale alternative to MovieLens.

Meta-Learning in AI: MAML, Prototypical Nets & Model-Based Approaches

Meta-learning teaches AI to learn how to learn. Covers MAML, Prototypical Networks, Meta-LoRA, ReMA, and meta-evaluation with real examples.