

Reinforcement learning for chip design
Daniel and Chris have a fascinating discussion with Anna Goldie and Azalia Mirhoseini from Google Brain about the use of reinforcement learning for chip floor planning - or placement - in which many new designs are generated, and then evaluated, to find an optimal component layout. Anna and Azalia also describe the…
We score an episode from what we can actually measure — its reach and engagement, what listeners say about it, and what it covers. We don't have those signals for this one yet, so it doesn't get a number.
Buzzmeter says it's buzzing across platforms — the Hive Vote says whether the people who actually listened liked it.
Rate this episode
Add your vote to the Hive — listeners rate every episode after they finish.
- No reviews yet — be the first.
Similar episodes from other shows
More like Practical AI →
DeepMind for Science, sponsored by Clear.ML

How the Global AI Race Has Shifted

10 Years of AlphaGo: The Turning Point for AI | Thore Graepel & Pushmeet Kohli

🔬Searching the Space of All Possible Materials — Prof. Max Welling, CuspAI
One great episode in your inbox, daily — free.
One email a day, unsubscribe anytime. No spam, ever.


