AI Research Posts

Guest post: Why Not All VectorDBs Are Agent-Ready*

7 AI Concepts You Should Know (AI 101 Guide Recap)

Revisiting main concepts that form current AI landscape in 2025

8 Remarkable Research Papers You Should Definitely Read

A list (pt. 2) of the most groundbreaking research papers from the first half of the 2025 that deserve your attention. Take some time to explore or refresh them!

🎙️AI Changed The Web. How To Build For It?

An Inference with Linda Tong, CEO @Webflow

Guest post: Why AI Databases Don't Need SQL*

5+ Notable Models of 2025 that You Should Know (AI 101 Guide Recap)

Revisiting Reasoning models, World Foundation Models and others — a summary of models, platforms and tools from our AI 101 Series

8 Awesome Research Papers You Might Have Missed but Must Read

Part 1: The most groundbreaking AI papers from the first half of 2025 – worth your time, whether you’re discovering or revisiting

The Agentic Stack, So Far?

A 20-part reference guide for a field in motion

9 Methods and Techniques You Must Know (AI 101 Guide Recap)

Take some time to learn or refresh the key techniques and methods that matter most

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 approaches to preference alignment that simplify the RLHF pipeline, use ranking loss, or replace human feedback with AI feedback.