Frontier RL data for the world’s leading AI teams.
San Francisco, CA
Joined January 2018
- Tweets286
- Following147
- Followers3.6K
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Labelbox retweeted
“We used to have FU money. Now we have FU tokens.”
Grok 4.5 and GLM-5.2 are here, offering nearly-as-good performance at a fraction of frontier prices. But the discount isn’t really the full story… This week’s panel argues that enterprises more generally might be done with renting their intelligence.
Join @sarahookr of Adaption Labs, @manuaero of Labelbox, and @spirosx of Resolve AI for the latest on the Token Price Wars, Demis Hassabis’ call for an AI oversight board, the Uber-vs-Waymo robotaxi fight, and the ultimate question: are orbital data centers a pipe dream or an immediate reality?
0:00 A new generation of lower-cost models
4:10 Enterprises want their own intelligence stack
6:10 Frontier vs. open source: where does the value go?
10:03 Is enterprises destined to go small?
30:04 Self-improvement as the real fix
31:52 Should the AI industry regulate itself?
47:14 Uber vs. Waymo in DC
1:03:53 Can AI data centers in space really work?
1:14:47 You get a plug! Everyone gets a plug!
TWiAI Episode 22 is live now
🎥 Watch the full episode here 👇
Labelbox retweeted
The @ilyasut episode
0:00:00 – Explaining model jaggedness
0:09:39 - Emotions and value functions
0:18:49 – What are we scaling?
0:25:13 – Why humans generalize better than models
0:35:45 – Straight-shotting superintelligence
0:46:47 – SSI’s model will learn from deployment
0:55:07 – Alignment
1:18:13 – “We are squarely an age of research company”
1:29:23 – Self-play and multi-agent
1:32:42 – Research taste
Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify. Enjoy!
Labelbox retweeted
this is great
The @karpathy interview
0:00:00 – AGI is still a decade away
0:30:33 – LLM cognitive deficits
0:40:53 – RL is terrible
0:50:26 – How do humans learn?
1:07:13 – AGI will blend into 2% GDP growth
1:18:24 – ASI
1:33:38 – Evolution of intelligence & culture
1:43:43 - Why self driving took so long
1:57:08 - Future of education
Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!
Labelbox retweeted
.@svlevine is one of the world's leading robotics researchers (and co-founder of @physical_int).
He thinks fully autonomous robots are much closer than people realize - when I pushed him on a prediction, he said 5 years to robots that can autonomously run your household).
The big game changer, in his view, is that we finally have LLMs with common sense and prior knowledge that we can scaffold the robot models around.
We get into all the reasons this might not happen, the data flywheel from deployment, architecture, simulation, manufacturing, and much more. Enjoy!
0:00:00 – Timeline to widely deployed autonomous robots
0:22:12 – Why robotics will scale faster than self-driving cars
0:32:15 – How vision-language-action models work
0:50:26 – Improvements needed for brainlike efficiency
1:02:48 – Learning from simulation
1:14:08 – How much will robots speed up AI buildouts?
1:22:54 – If hardware’s the bottleneck, does China win by default?
Labelbox retweeted
Your Reading List for 2022!
This time, books recommended by @manuaero, founder & CEO @labelbox:
1. Our Mathematical Universe by Max Tegmark
2. Zen and the Art of Motorcycle Maintenance by Robert Pirsig
See more here: thesequence.substack.com/p/r…
Labelbox retweeted
AI is all around us, and fueled by labeled data. @Labelbox has emerged as the canonical system of record for this process, and is helping growing number of enterprise customers use AI to transform industries. 🚀
labelbox.com/blog/why-we-rai…
Labelbox retweeted
Great mention of @labelbox in a thoughtful article: AI needs an open labeling platform venturebeat.com/2021/01/30/a… via @VentureBeat
Labelbox retweeted
Data scientists often spend more time building and maintaining the tooling for AI systems than they do building the AI systems themselves. s.hbr.org/2TFhHrW
Labelbox retweeted
The second episode of #DefiningTransparency is now live!
In this episode Paul talks with @nathana_sharma from @labelbox about #transparency in the #AI and #blockchain space.
Listen now here:
Labelbox retweeted
Congrats to the team @labelbox on their Series B! @manuaero and team are building a fantastic training data platform, honored to work with them.
We’re excited to share we’ve raised $25M in Series B funding led by @a16z! Since day one, we set out to build the world’s best training data platform. With this funding, we look forward to empowering more customers to build and deploy their AI ambitions labelbox.com/blog/series-b-a…
Labelbox retweeted
.@Labelbox is solving one of the main bottlenecks for companies to adopt AI in production. Congratulations to @manuaero, @Riegerb & team for raising their Series B! #MakeHistory venturebeat.com/2020/02/04/l…
Labelbox retweeted
Wild. AI training data tool LabelBox went from a tiny startup I thought was cool 18mo ago techcrunch.com/2018/07/30/la… to raising $25M today
We’re excited to share we’ve raised $25M in Series B funding led by @a16z! Since day one, we set out to build the world’s best training data platform. With this funding, we look forward to empowering more customers to build and deploy their AI ambitions labelbox.com/blog/series-b-a…
Labelbox retweeted
For AI environments, data is the equivalent of source code. And @labelbox is a training data platform for the development of AI software. Here's why we're investing: bit.ly/3baZF7i
Labelbox retweeted
🔉New podcast episode! In FYI | EP48, we welcome Manu Sharma & Brian Rieger from @labelbox, a private company we believe is leading training data solution for machine learning. We discuss Labelbox, why data labeling is necessary for #AI & much more!
🎧: arkinv.st/34vJbCv
Labelbox retweeted
“When humans have better ways to input and manage data, machines have better ways to learn.” @labelbox is accelerating AI development by creating better labeling and collaboration tools for ML teams.
Design-driven. Remote-OK. And yes, they're hiring!
👉 keyvalues.com/labelbox
Labelbox retweeted
A little simpler when I use synthetic data (constantly overwriting my datasets), but I've found that products like @labelbox take a lot of thought out of the organization for labeled data – at San Diego, CA
Labelbox retweeted
The bottleneck of deep neural networks is labeled datasets. @TheEconomist highlights some of the companies working on solving that: @aireverie @labelbox @hive_ai
"an industry is popping up to help" #AI
economist.com/business/2019/…
