Jennifer Li retweeted
I wouldn't have founded @ValsAI without first working at Palantir and Vals wouldn't be what it is without 8VC investing in our seed. @JTLonsdale was key to both.
Got to sit down with Joe and @vvkgopalan to talk about the story behind Vals, where the industry is going, and why I'm broadly optimistic while the world is incredibly high-variance.
Got to sit down with Joe and @vvkgopalan to talk about the story behind Vals, where the industry is going, and why I'm broadly optimistic while the world is incredibly high-variance.
NEW🚨 Inside the Company That Evaluates AI Labs; Who Will Reach Recursive Self-Improvement First?
@JTLonsdale & @vvkgopalan sit down with @RayanKrishnan, founder & CEO of @ValsAI
@ValsAIover:
- How Rayan used Fable to solve a 370-year-old cipher
- The science behind model evaluatiof the labs?
- Should labs self-regulate? What's the role for independent evaluators?
- Which lab will reach RSI first — and what happens next?
- How do models try to deceive evaluators?
Episode 167 out now!
(00:00) Episode intro
(02:00) Palantir, Machiavelli & lessons from Alex Karp
(07:50) Solving a 370-year-old cipher / Is AI making new discoveries?
(12:10) How do you measure AI abilities across finance, legal, etc?
(15:30) What is the science behind model evaluation?
(18:00) The importance of independent evaluation
(23:35) Evaluating Chinese models & addressing distillation
(26:45) Will Anthropic reach Recursive Self-Improvement first? What happens next?
(28:30) How do models try to deceive evaluators
(33:00) Why Rayan remains optimistic about AI
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Reimagining design with another great model, well done @ideogram_ai !
Today, we’re introducing Ideogram's first vector model.
Generate clean, editable SVGs with smooth gradients and sharp typography from a text prompt, or turn any image into a detailed, scalable vector.
Live in Ideogram and the API: ideogram.ai/models/vector
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The model race is a focus game. Building for large scale PDF processing is very different from generic vision understanding, this is where @reductoai shines from both quality as well as cost/latency.
AI agents can reason over enormous amounts of information, but much of the world's actual work is still trapped in PDFs, spreadsheets, scans, and other formats that models struggle to reliably understand.
Reducto co-founder and CEO Adit Abraham argues that solving this document gents are going to take on consequential work in healthcare, legal, finance, and insurance.
Adit joins a16z General Partner Jennifer Li to explain why traditional OCR breaks down on messy real-world documents, how Reducto combines vision-language models with specialized infrastructure to reach high accuracy without sacrificing cost or latency, and why frontier models can silently drop information on long extraction tasks.
Reducto now processes billions of pages each month, and crossed its 7 billionth page the morning of this recording.
0:00 Why AI agents need to read PDFs
2:12 From 1990s OCR to vision models
5:00 Training R1 on the messiest docs
7:46 When agents beat humans at extraction
9:45 A penny a page for 7 billion pages
12:47 Why legal and finance lag coding AI
15:01 The stakes of AI errors in healthcare
16:25 Agents that can edit Word and Excel
17:58 Why the labs won't go deep on PDFs
20:14 Frontier models silently drop data
22:21 Benchmarks have become marketing
25:45 Why charts and Excel stump models
28:46 Infra for 10M documents at once
31:03 How "chet pain" gets claims denied
34:32 The paperwork AI should kill first
YouTube: youtu.be/xuczlbVVLsQ
@aditabrm @reductoai @JenniferHli
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Jennifer Li retweeted
AI agents can reason over enormous amounts of information, but much of the world's actual work is still trapped in PDFs, spreadsheets, scans, and other formats that models struggle to reliably understand.
Reducto co-founder and CEO Adit Abraham argues that solving this document gents are going to take on consequential work in healthcare, legal, finance, and insurance.
Adit joins a16z General Partner Jennifer Li to explain why traditional OCR breaks down on messy real-world documents, how Reducto combines vision-language models with specialized infrastructure to reach high accuracy without sacrificing cost or latency, and why frontier models can silently drop information on long extraction tasks.
Reducto now processes billions of pages each month, and crossed its 7 billionth page the morning of this recording.
0:00 Why AI agents need to read PDFs
2:12 From 1990s OCR to vision models
5:00 Training R1 on the messiest docs
7:46 When agents beat humans at extraction
9:45 A penny a page for 7 billion pages
12:47 Why legal and finance lag coding AI
15:01 The stakes of AI errors in healthcare
16:25 Agents that can edit Word and Excel
17:58 Why the labs won't go deep on PDFs
20:14 Frontier models silently drop data
22:21 Benchmarks have become marketing
25:45 Why charts and Excel stump models
28:46 Infra for 10M documents at once
31:03 How "chet pain" gets claims denied
34:32 The paperwork AI should kill first
YouTube: youtu.be/xuczlbVVLsQ
@aditabrm @reductoai @JenniferHli
Reducto co-founder and CEO Adit Abraham argues that solving this document gents are going to take on consequential work in healthcare, legal, finance, and insurance.
Adit joins a16z General Partner Jennifer Li to explain why traditional OCR breaks down on messy real-world documents, how Reducto combines vision-language models with specialized infrastructure to reach high accuracy without sacrificing cost or latency, and why frontier models can silently drop information on long extraction tasks.
Reducto now processes billions of pages each month, and crossed its 7 billionth page the morning of this recording.
0:00 Why AI agents need to read PDFs
2:12 From 1990s OCR to vision models
5:00 Training R1 on the messiest docs
7:46 When agents beat humans at extraction
9:45 A penny a page for 7 billion pages
12:47 Why legal and finance lag coding AI
15:01 The stakes of AI errors in healthcare
16:25 Agents that can edit Word and Excel
17:58 Why the labs won't go deep on PDFs
20:14 Frontier models silently drop data
22:21 Benchmarks have become marketing
25:45 Why charts and Excel stump models
28:46 Infra for 10M documents at once
31:03 How "chet pain" gets claims denied
34:32 The paperwork AI should kill first
YouTube: youtu.be/xuczlbVVLsQ
@aditabrm @reductoai @JenniferHli
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Jennifer Li retweeted
Someone could probably write a book (if they haven’t already) about the cycle of technology productizing the removal of friction in the name of convenience only for us to discover that the friction was a load-bearing part of the social compact.
Someone told me he thinks dating apps are bad because they let you access connection without having any motion in your life. Normally meeting people requires going out into the world, entering new scenes and navigating unfamiliar situations. You have to be living a life that brings you into contact with other people. Dating apps let you order connection without doing any of that work
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Fastest model in the west ✌🏻
This is the culmination of 2 weeks of sleepless nights from fal’s Research & Performance teams: taking an extremely powerful base model, improving its quality beyond the base itself, and increasing its speed by 10x (literally).
We present to you the fastest model in the west 🤠
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Jennifer Li retweeted
We looked at TerminalBench 4.0 and found a lot of issues. After fixing the issues Sonnet 5.5 scores 89.2%. So, TerminalBench is already mostly saturated.
Along the way we found a lot of crazy stuff, including reward hacks in the published transcripts.
Along the way we found a lot of crazy stuff, including reward hacks in the published transcripts.
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Join the pink Jevolution!!
Hello Software Engineers, I lead TypeSafe AI Model Capabilities team. We are hiring. Here are a few qualities we are looking for:
• strong plus for people who resonate with the title "Experience Engineers": mobile engineers, full stack engineers, or even (virtual) reality engineers.
• strong coder (you need to be able to manually write code)
• product oriented thinker
I promise are fun! I trust that you will figure out how to apply.
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Jennifer Li retweeted
We blind-tested Eleven v4, our latest voice model, against other models in eight languages.
Listeners picked it as more expressive in every test.
Listeners picked it as more expressive in every test.
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Jennifer Li retweeted
Introducing fal Worlds.
A new way to create and interact with AI-generated worlds in real time.
Build characters, explore environments, direct scenes, and watch worlds respond to your actions as they unfold.
Get hands-on with the latest frontier world models, including LingBot and more.
A new way to create and interact with AI-generated worlds in real time.
Build characters, explore environments, direct scenes, and watch worlds respond to your actions as they unfold.
Get hands-on with the latest frontier world models, including LingBot and more.
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Killer launch 🚀
Introducing overshoot, it will cut your GPU bill in half with zero quality loss, or you don’t pay.
Over the past few months, we have forward deployed into AI teams to optimize their inference stacks. They have now cumulatively saved over $5M.
Overshoot is software that bakes rence learnings into a scalable solution.
overshoot.ai
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If it was not clearly enough what the separation of system 1 and system 2 is, here it is. Give the power back to the builders!!
was at a community event and was asked a somewhat sad question: should developers be afraid of the labs eating the new possibilities jev opens up?
with AI (system one) + software (system two):
1. there's no going back to a world without system one models
2. you control the software!
3. there's no way AI could beat the efficiency of this combo
4. you don't even send the model providers your whole program logic
I think the days of "wrapper" apps will be seen as some of the darkest in software because people essentially did all of their programming in a system message and sent it over to a third party who was incentivized to bake that behavior into their 1st party product...
keeping your logic in code and only asking AI for the minimum reverses that and keeps all of your logic yours. if you decompose enough, model providers can't even figure out what you're working on
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AI Infra nights with the cool kids!
We're bringing together some of the brightest minds in SF for AI Infra Night with @a16z next week.
Hear from engineering leaders at @fal, @bfl_ai, @krea_ai, and @ElevenLabs:
- Chris Mladenov: Head of Infra, fal
- Saksham Consul: MTS, Black Forest Labs
- Will Beddow: Head of Supercomputing & AI Infra, Krea
- Dhruv Bhatia: Infra Engineer, fal
- Jordan Conragan: Research Engineer, ElevenLabs
Join us in SF, October 20.
luma.com/fal-6m0z
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