The Age of Research & Enlightenment is Now 🔍 | Research fellow @NormaTechgh | prev ML engineer intern @plantvillage | Agricultural Engineering @UCCGH_Official
Vlad Feinberg (@FeinbergVlad) is Google DeepMind’s pre-training area lead and I asked him all about how to land a job at a frontier lab like Google DeepMind, Anthropic or OpenAI.
In this episode:
• Skills frontier labs need
• Differences between software engineering and AI research
• Domains that matter for frontier research
• Concrete steps engineers can take to get closer to research
• Jeff Dean spot bonus story
Where to watch:
• YouTube - https://t.co/kqn9GtPHOu
• Spotify - https://t.co/MhHYqoOTwt
• Apple Podcasts - https://t.co/jOYDGtGVnt
• Transcript - https://t.co/rza5lwT9Wj
Thank you to the sponsor of this episode for supporting my work:
• WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at https://t.co/y8noBzFEem
Chapters:
00:00 - Intro
00:33 - Skills frontier labs need
08:45 - The difference between AI research and engineering
21:41 - Domains that matter for the frontier
30:50 - Marketing yourself to frontier labs
35:13 - Concrete steps engineers can take
38:29 - Overview of pre-training areas
47:23 - Jeff Dean spot bonus story
50:14 - Favorite Gemini war story
58:59 - Advice for his younger self
01:03:07 - Outro
@sycode_x@geeksilas I get free credits from Cursor events I’ve attended so I haven’t paid for one yet. I also haven’t experienced running out of tokens quickly. For pricing, there is a $20/month and $60/month option. I don’t know about enterprise pricing, but I think it’s pretty cheap.
Today, we are launching Hosted Evaluations on the platform.
Running evals is an infra problem: harnesses, sandboxes, hours of compute, hundreds of parallel runs.
Running evals is hard. Until now.
New paper from Yann LeCun!
"When Does LeJEPA Learn a World Model?"
This paper proves that under Gaussian latent dynamics, LeJEPA can recover the hidden state behind nonlinear observations up to rotation.
The intuition is that linear latent features are the most stable across nearby views, while nonlinear features decay faster, so the objective naturally selects the real world variables.
The key caveat is that this guarantee holds under specific assumptions, and Gaussian latents are the unique case that guarantees this.
This #CVPR2026 paper from our research team is trending #1 on @HuggingFace 🤗
Meet LocateAnything: a vision-language detection model that rethinks bounding box prediction. For AI agents and robots, “seeing” is only useful if a model can pinpoint where something is fast enough to act.
Trained on 138M high-quality samples, LocateAnything decodes bounding boxes in parallel instead of one coordinate at a time, improving localization accuracy while dramatically increasing throughput for visual grounding and detection.
Project page: https://t.co/O7JMe8tzFM