World Model · podcast knowledge graph

Relational Foundation Models for Enterprise Data with Jure Leskovec - #768

2026-05-21 · 66 min · episode 768 · 13 entities

episode page audio

Asserted relationships

  • 0.68
    evidence rules-v4
    Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
  • → hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • → discusses Science concept
    0.40
    evidence rules-v4
    Feed category: Science
  • → discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology
  • → discusses News concept
    0.40
    evidence rules-v4
    Feed category: News
  • → discusses Tech News concept
    0.40
    evidence rules-v4
    Feed category: Tech News
  • → hosted by TWIML company
    0.40
    evidence rules-v4
    Feed author/publisher: TWIML

Entities found in this episode

concepts 5

  • mentioned Science concept
    0.50
    evidence rules-v4
    Feed category: Science
  • mentioned Tech News concept
    0.50
    evidence rules-v4
    Feed category: Tech News
  • discusses Science concept
    0.40
    evidence rules-v4
    Feed category: Science
  • discusses News concept
    0.40
    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
    0.40
    evidence rules-v4
    Feed category: Tech News

companys 4

  • mentioned TWIML company
    0.70
    evidence rules-v4
    Feed author/publisher: TWIML
  • mentioned Technology company
    0.50
    evidence rules-v4
    Feed category: Technology
  • discusses Technology company
    0.40
    evidence rules-v4
    Feed category: Technology
  • hosted by TWIML company
    0.40
    evidence rules-v4
    Feed author/publisher: TWIML

persons 3

  • mentioned Jure Le person
    0.72
    evidence rules-v4
    Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
  • mentioned Sam Charrington person
    0.70
    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
In this episode, Jure Leskovec, co-founder and chief scientist at Kumo and professor of computer science at Stanford, joins us to explore two fronts of his work: AI for science and relational deep learning. We begin with AI Virtual Cell, a multiscale effort to learn data-driven representations from proteins to cells to patients using single-cell RNA-seq data, protein language models like ESM, and structure models like AlphaFold—without hand-encoding biology. Jure then dives into relational deep learning, reframing enterprise databases as graphs and training neural networks directly on raw multi-table data. He explains Kumo’s Relational Foundation Model (RFM2), which performs in-context learning over subgraphs to make accurate predictions on new databases and tasks with no training, and how this approach benchmarks against RelBench and other multi-table datasets. We also discuss real-world deployments at companies like Reddit, DoorDash, and Coinbase, explainability via attention over tables and columns, integration with agentic systems, deployment options, and practical limitations. The complete show notes for this episode can be found at https://twimlai.com/go/768.