Emulated: The Data for Fully Autonomous Software Engineers and Companies — Joseph Wang

AI Engineer

Summary

El vídeo presenta a Emulated, un laboratorio de datos que busca aumentar la fiabilidad y autonomía de los agentes de IA. Joseph y Sid explican que los benchmarks actuales para ingenieros de software de IA son insuficientes, ya que solo cubren cambios de código y no replican la complejidad de la vida real, como la infraestructura distribuida o la interacción con clientes. Proponen el uso de entornos simulados, llamados 'sandboxes', que imitan empresas completas y recursos de nube reales para entrenar agentes en tareas de ingeniería de software completas y de largo alcance. Destacan los desafíos técnicos de estas simulaciones y la necesidad de gestionar infraestructura real en entornos de prueba, invitando a la colaboración.

Chapters

  1. 0:00Introduction to Emulated
  2. 1:17AI Agent Capability Gap
  3. 3:44Simulating Complex Software Companies
  4. 6:24Challenges of Real Infrastructure
  5. 10:58Multi-Node Cloud Sandboxes
  6. 13:21Emulated's Vision and Focus

Topics covered

  • Fiabilidad y autonomía de agentes de IA
  • El futuro de los agentes de IA

+8 more topics (full content when you follow the channel)

Transcript excerpt

So, I appreciate the intro. Uh my name is Joseph and this is my co-founder Sid. Emulated is a data lab focused on increasing the reliability and autonomy of AI agents. And if you've been a AI engineer and you've watched the talks, seen the tracks, then there's probably one takeaway that all the talks have in common. And it's that we're headed towards a future where agents are able to perform useful work over longer and longer horizons with little to no supervision. So, today we're going to answer some of the questions of what this means for the data and model layers. Uh we're going to touch on some pretty cool things. Uh so, look out for them. Um like how to simulate a company within a sandbox or sandboxes for multi-node systems and distributed clusters. Um and if we have a little bit of time, we'll also go into some of the work that we're doing with post-training pipelines and how these…