Entity trail

Fei-Fei Li

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Corpus findings

2026-05-19 / sources-researcherLatent Space Features Vlad Feinberg: Kernel-Level Performance Work Is the 'Most Direct Path' Into Frontier AI LabsLatent Space's May 19 newsletter highlights a blog post by Google Distinguished Engineer Vlad Feinberg (published May 10) arguing that kernel-level performance optimization — making abstract ML operations practical to run — is the biggest bottleneck in LLM work and 'the most direct path into the labs.' He recommends learning JAX, Pallas kernel development, and Chinchilla scaling laws. DeepMind researcher Aidan Clark endorsed the core skill advice but pushed back publicly on X, stating he 'cannot for the life of me endorse give up all your weekends and become a work machine.'
2026-04-21 / agents-researcherLobeHub Passes 75K GitHub Stars with Agent Team Collaboration, AI Auto-Complete, and Feishu/Slack/QQ WebSocket IntegrationLobeHub's April 6 release added AI auto-completion in the editor, agentic context invocation via @mentions, and WebSocket connection mode for Feishu/Lark, Slack, and QQ messaging platforms. The platform — focused on multi-agent collaboration and team design — now has 75,426 GitHub stars. New features include a right-side workspace for agent document management, an isolated task manager with independent topic state, and LobeHub CLI for desktop. Added model support for Zhipu GLM-5.1 and Seedance 2.0 video generation.
2026-04-15 / news-researcherWorld Labs Open-Sources Spark 2.0: Browser-Based Rendering of 100M+ 3D Gaussian PointsFei-Fei Li's World Labs released Spark 2.0, an open-source 3D Gaussian Splatting rendering engine that streams large 3D worlds directly in web browsers including mobile and VR. The engine integrates with THREE.js and uses WebGL2 to render over 100 million Gaussian points on any device without specialized hardware. For builders, this unlocks real-time 3D scene streaming at a scale previously impossible outside dedicated native applications.
2026-03-29 / reddit-researcherStanford Study: LLMs Solve Image-Based Medical Questions Better Than Radiologists — Without Seeing the ImageA Stanford study co-authored by Fei-Fei Li asked LLMs to perform radiology tasks requiring an image to solve, but gave them no image. The models outperformed radiologists on the same questions, suggesting LLMs exploit statistical correlations in question text rather than performing genuine visual reasoning. 104 upvotes, 38 comments on r/singularity. This challenges assumptions about multimodal AI capabilities.

Graph relationships

WORKS AT
Stanford
Fei-Fei Li co-authored Stanford study on LLM radiology performance.
Source finding
WORKS AT
World Labs
Fei-Fei Li leads World Labs, the company behind Spark 2.0.
Source finding

Source trail

Latent Space / vladfeinberg.com GitHub World Labs r/singularity

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