Jul 31, 2026

Data Quality Is the Compute Multiplier — Ari Morcos, DatologyAI

Ari Morcos, CEO of DatologyAI, explains why data quality is the critical "compute multiplier" in an era of scarce and expensive compute. He outlines DatologyAI's "oil refinery" process (Clean, Curate, Create, Compose) for enhancing datasets. Through empirical results and customer cases like Thomson Reuters and Arcee, he demonstrates how superior data curation leads to significantly better models, reduced training costs, improved inference efficiency, and the ability to train competitive models for a fraction of traditional costs, proving that manufacturing high-quality data is more effective than buying more compute.

Jul 20, 2026

The First Dedicated YC GPU Cluster - With Together AI

YC and Together AI have partnered to launch the first dedicated YC GPU cluster, addressing the critical compute bottleneck faced by AI-native startups. This initiative provides flexible, cost-effective access to GPU resources, enabling companies from early-stage research to major players to train, fine-tune, and run inference on AI models, and mitigating the financial strain of long-term compute commitments.

Jul 15, 2026

Recursive Model Improvement — Lee Robinson, Cursor, SpaceXAI

Lee Robinson of Cursor outlines a comprehensive strategy for recursive AI model improvement, centered on a two-loop training framework. He details how Cursor enhances both user-feedback-driven outer loops and high-quality evaluation inner loops, introducing novel methods like textual feedback and addressing reward hacking. The discussion extends to scaling compute infrastructure through partnerships with SpaceX, Colossus, and Terafab, and leveraging agent-based automation to streamline research and foster a future where models continuously train and improve themselves.

May 04, 2026

Training an LLM from Scratch, Locally — Angelos Perivolaropoulos, ElevenLabs

A practical guide to the engineering principles and trade-offs involved in training a small language model from scratch on a local machine, based on a workshop by Angelos Perivolaropoulos from ElevenLabs.

Mar 16, 2026

Building AI for better healthcare — the OpenAI Podcast Ep. 14

OpenAI's Dr. Nate Gross and Karan Singhal detail their strategy for applying AI in healthcare, focusing on the rigorous, physician-led process for training models on sensitive health data. They discuss the challenges of deployment in siloed systems and how AI is evolving from a Q&A tool into an integrated assistant for patients and a critical safety net for clinicians.

Dec 10, 2025

How We Built a Leading Reasoning Model (Olmo 3)

A comprehensive overview of the entire process behind building Olmo 3 Think, covering the full stack from pre-training architecture and data selection to the detailed post-training recipe involving SFT, DPO, and a deep dive into the advanced infrastructure for scaling Reinforcement Learning (RL). The summary also includes critical reflections on the challenges and nuances of evaluating modern reasoning models.