World Model · podcast knowledge graph

#76 - LUKAS BIEWALD (Weights and Biases CEO)

2022-06-09 · 58 min · episode 76 · 7 entities

Asserted relationships

  • → discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology
  • → references Mlst website
    0.38
    evidence rules-v4
    Link in episode "#76 - LUKAS BIEWALD (Weights and Biases CEO)": https://wandb.me/MLST

Entities found in this episode

companys 2

  • mentioned Technology company
    0.50
    evidence rules-v4
    Feed category: Technology
  • discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology

websites 2

  • mentioned Mlst website
    0.45
    evidence rules-v4
    Link in episode "#76 - LUKAS BIEWALD (Weights and Biases CEO)": https://wandb.me/MLST
  • references Mlst website
    0.38
    evidence rules-v4
    Link in episode "#76 - LUKAS BIEWALD (Weights and Biases CEO)": https://wandb.me/MLST

concepts 2

  • mentioned CEO concept
    0.35
    evidence rules-v4
    CEO
  • mentioned LUKAS concept
    0.35
    evidence rules-v4
    LUKAS

podcasts 1

Episode description as stored
Check out Weights and Biases here! https://wandb.me/MLST Lukas Biewald is an entrepreneur living in San Francisco. He was the founder and CEO of Figure Eight an Internet company that collects training data for machine learning. In 2018, he founded Weights and Biases, a company that creates developer tools for machine learning. Recently WandB got a cash injection of 15 million dollars in its second funding round. Lukas has a bachelors and masters in mathematics and computer science respectively from Stanford university. He was a research student under the tutelage of the legendary Daphne Koller. Lukas Biewald https://twitter.com/l2k [00:00:00] Preamble [00:01:27] Intro to Lukas [00:02:46] How did Lukas build 2 sucessful startups? [00:05:49] Rebalancing games with ML [00:08:14] Elevator pitch for WandB [00:10:38] Science vs Engineering divide in ML DevOps [00:14:11] Too much focus on the minutiae? [00:18:03] Vertical information sharing in large enterprises (metrics) [00:20:37] Centralised vs Decentralised topology [00:24:02] Generalisation vs specialisation [00:28:59] Enhancing explainability [00:33:14] Should we try and understand "the machine" or is testing / behaviourism enough? [00:36:55] WandB roadmap [00:39:06] WandB / ML Ops competitor space? [00:44:10] How is WandB differentiated over Sagemaker / AzureML [00:46:02] WandB Sponsorship of ML YT channels [00:48:43] Alternatives to deep learning? [00:53:47] How to build a business like WandB Panel: Tim Scarfe Ph.D and Keith Duggar Ph.D Note we didn't get paid by Weights and Biases to conduct this interview.