The Man Building the Last AI Humans Will Need to Design - The Story
What if the fastest path to superintelligence is AI that builds itself? That's the bet Richard Socher is making — and he has the track record to back it up. A double unicorn founder and early investor in eight unicorn companies (including Perplexity and Hugging Face), Richard has spent 15 years building the foundational research that powers modern AI. Now he’s co-founded Recursive with an elite team from Google DeepMind, OpenAI, and Meta to pursue something more ambitious: a self-improving AI that generates its own scientific breakthroughs — what he calls a "eureka machine."
Richard joins Oz to unpack how recursive superintelligence actually works and why open-ended AI systems could outpace today's giants.
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Amazing Answers: Richard Socher on how You.com is Reimagining Search with AI
In this episode, Nathan sits down with Richard Socher, CEO and Founder of You.com, a personalized AI search assistant. They discuss the rise of the AI chatbot paradigm and how that's changed the game for search, You.com's various modes, with particular emphasis on Genius mode and above all Research mode, and much more. Try the Brave search API for free for up to 2000 queries per month at https://brave.com/api
LINKS:
- You.com: https://you.com/
-Richard Socher's site: https://www.socher.org/
SPONSORS:
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@labenz
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TIMESTAMPS:
(00:00) Preview
(01:38) Interview with Richard Socher: AI pioneer
(02:26) Exploring the You.com product
(02:55) The AI Bundle
(05:23) Richard Socher's journey in deep learning
(16:43) You.com comparison to competitors
(31:16) The future of AI search engines
(41:38) The changing landscape of search engines
(41:44) The impact of chatbots and AI on search
(42:16) How the market will shape up
(43:33) The power of open source
(01:02:32) The role of AI in advancing science
(51:42) The future of AI: philosophical and practical considerations
(55:06) The future of AI: risks and regulations
(01:11:07) The future of AI: agency and emergence
(01:26:57) The future of AI: retrieval, memory, and online learning
This show is produced by Turpentine: a network of podcasts, newsletters, and more, covering technology, business, and culture — all from the perspective of industry insiders and experts. We’re launching new shows every week, and we’re looking for industry-leading sponsors — if you think that might be you and your company, email us at erik@turpentine.co.
The Power of AI in Search with You.com's Richard Socher
In the latest episode of Gradient Dissent, Richard Socher, CEO of You.com, shares his insights on the power of AI in search. The episode focuses on how advanced language models like GPT-4 are transforming search engines and changing the way we interact with digital platforms. The discussion covers the practical applications and challenges of integrating AI into search functionality, as well as the ethical considerations and future implications of AI in our digital lives. Join us for an enlightening conversation on how AI and you.com are reshaping how we access and interact with information online.
*Subscribe to Weights & Biases* → https://bit.ly/45BCkYz
Timestamps:
00:00 - Introduction to Gradient Dissent Podcast
00:48 - Richard Socher’s Journey: From Linguistic Computer Science to AI
06:42 - The Genesis and Evolution of MetaMind
13:30 - Exploring You.com's Approach to Enhanced Search
18:15 - Demonstrating You.com's AI in Mortgage Calculations
24:10 - The Power of AI in Search: A Deep Dive with You.com
30:25 - Security Measures in Running AI-Generated Code
35:50 - Building a Robust and Secure AI Tech Stack
42:33 - The Role of AI in Automating and Transforming Digital Work
48:50 - Discussing Ethical Considerations and the Societal Impact of AI
55:15 - Envisioning the Future of AI in Daily Life and Work
01:02:00 - Reflecting on the Evolution of AI and Its Future Prospects
01:05:00 - Closing Remarks and Podcast Wrap-Up
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20VC: The Biggest AI Leaders on What Matters More; Model Size or Data Size & Where Does The Value in AI Accrue; to Startups or to Incumbents
Richard Socher is the founder and CEO of You.com. Richard previously served as the Chief Scientist and EVP at Salesforce.
Douwe Kiela is the CEO of Contextual AI, building the contextual language model to power the future of businesses. Previously, he was the Head of Research at Hugging Face, and before that a Research Scientist at Facebook AI Research.
Alex Lebrun is the Co-Founder and CEO of Nabla, an AI assistant for doctors. Prior to Nabla, he led engineering at Facebook AI Research. Alex founded Wit.ai, acquired by Facebook in 2015.
Tomasz Tunguz is the Founder and General Partner @ Theory Ventures, just announced last week, Theory is a $230M fund that invests $1-25m in early-stage companies that leverage technology discontinuities into go-to-market advantages.
Sarah Guo is the Founding Partner @ Conviction Capital, a $100M first fund purpose-built to serve "Software 3.0" companies. Prior to founding Conviction, Sarah was a General Partner at Greylock where she made investments in the likes of Figma, Coda and Neeva.
Emad Mostaque is the Co-Founder and CEO @ StabilityAI, the parent company of Stable Diffusion. Stability are building the foundation to activate humanity's potential. To date, Emad has raised over $110M with Stability with the latest round reportedly pricing the company at $4BN.
Clem Delangue is the Co-Founder and CEO @ Hugging Face, the AI community building the future. To date, Clem has raised over $160M from the likes of Sequoia, Coatue, Addition and Lux Capital to name a few.
Cris Valenzuela is the CEO and co-founder of Runway, the company that trains and builds generative AI models for content creation. To date, Cris has raised over $285M for the company from the likes of Lux Capital, Felicis, Coatue, Amplify, and Nvidia to name a few.
Noam Shazeer is the co-founder and CEO of Character.AI. A renowned computer scientist and researcher, Shazeer is one of the foremost experts in artificial intelligence (AI) and natural language processing (NLP).
The Two Most Pressing Questions in AI:
What matters more the size of the model or the size of the data?
Where does the value accrue in the next 5-10 years; to startups or to incumbents?
20VC: Does Value Accrue to Incumbents or Startups in the AI Race, Why Model Size Matters More Than Data Size, Why Artificial General Intelligence is Far Away, Why Carpenters Will Be Paid More Than Software Engineers & Future of Jobs with Richard Socher
Richard Socher is the founder and CEO of You.com. Richard previously served as the Chief Scientist and EVP at Salesforce. Before that, Richard was the CEO/CTO of AI startup MetaMind, acquired by Salesforce in 2016. He is widely recognized as having brought neural networks into the field of natural language processing, inventing the most widely used word vectors, contextual vectors and prompt engineering. He has over 150,000 citations and served as an adjunct professor in the computer science department at Stanford.
In Today's Episode with Richard Socher We Discuss:
1. The Decade-Long Journey to Becoming an AI OG:
How did Richard first make his way into the world of AI over a decade ago?
What are 1-2 of his biggest lessons from working with Marc Benioff?
How did 5 years at Salesforce impact how he both thinks and operates?
2. Models: Does Size Matter:
How important is model size? Is data size more important?
What are the biggest misconceptions people have around models today?
How does Richard respond to the suggestion that "many startups are wrappers around LLMs"?
Are hallucinations a feature or a bug?
3. Where Does Value Accrue:
Where does Richard believe most of the value will accrue; startup or incumbent?
Which incumbents are best positioned to win? Which are the laggards and behind?
What do many not see about the startup vs incumbent race in the AI war?
4. Open vs Closed: Which Wins:
Does Richard favour Yann LeCun's open approach? Or is the world of AI more closed?
What are the biggest challenges of an open ecosystem?
What are the nuances that make both challenging?
5. Richard Socher: AMA:
Why will carpenters be paid more than software engineers in 10 years?
Why is AGI still way off? Are people too unrealistic?
How much money does Google make off search every day? Why does that leave them vulnerable?
Richard Socher of You.com: the David taking on the "Search" Goliath Google
Richard Socher from You.com (and before that, Stanford, MetaMind, Salesforce) joins Host Pieter Abbeel to discuss the future of search, LLMs, AGI, You.com, Metamind, AIX Ventures.
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Engineering an ML-Powered Developer-First Search Engine with Richard Socher - #582
Today we’re joined by Richard Socher, the CEO of You.com. In our conversation with Richard, we explore the inspiration and motivation behind the You.com search engine, and how it differs from the traditional google search engine experience. We discuss some of the various ways that machine learning is used across the platform including how they surface relevant search results and some of the recent additions like code completion and a text generator that can write complete essays and blog posts. Finally, we talk through some of the projects we covered in our last conversation with Richard, namely his work on Salesforce’s AI Economist project.
The complete show notes for this episode can be found at twimlai.com/go/582
Richard Socher — The Challenges of Making ML Work in the Real World
Richard Socher, ex-Chief Scientist at Salesforce, joins us to talk about The AI Economist, NLP protein generation and biggest challenge in making ML work in the real world.
Richard Socher was the Chief scientist (EVP) at Salesforce where he lead teams working on fundamental research(einstein.ai/), applied research, product incubation, CRM search, customer service automation and a cross-product AI platform for unstructured and structured data. Previously, he was an adjunct professor at Stanford’s computer science department and the founder and CEO/CTO of MetaMind(www.metamind.io/) which was acquired by Salesforce in 2016. In 2014, he got my PhD in the [CS Department](www.cs.stanford.edu/) at Stanford. He likes paramotoring and water adventures, traveling and photography. More info:
- Forbes article:
https://www.forbes.com/sites/gilpress/2017/05/01/emerging-artificial-intelligence-ai-leaders-richard-socher-salesforce/) with more info about Richard's bio.
- CS224n - NLP with Deep Learning(http://cs224n.stanford.edu/) the class Richard used to teach.
- TEDx talk(https://www.youtube.com/watch?v=8cmx7V4oIR8) about where AI is today and where it's going.
Research:
Google Scholar Link(https://scholar.google.com/citations?user=FaOcyfMAAAAJ&hl=en)
The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Arxiv link(https://arxiv.org/abs/2004.13332), blog(https://blog.einstein.ai/the-ai-economist/), short video(https://www.youtube.com/watch?v=4iQUcGyQhdA), Q&A(https://salesforce.com/company/news-press/stories/2020/4/salesforce-ai-economist/), Press: VentureBeat(https://venturebeat.com/2020/04/29/salesforces-ai-economist-taps-reinforcement-learning-to-generate-optimal-tax-policies/), TechCrunch(https://techcrunch.com/2020/04/29/salesforce-researchers-are-working-on-an-ai-economist-for-more-equitable-tax-policy/)
ProGen: Language Modeling for Protein Generation:
bioRxiv link(https://www.biorxiv.org/content/10.1101/2020.03.07.982272v2), [blog](https://blog.einstein.ai/progen/) ]
Dye-sensitized solar cells under ambient light powering machine learning: towards autonomous smart sensors for the internet of things
Issue11, (**Chemical Science 2020**). paper link(https://pubs.rsc.org/en/content/articlelanding/2020/sc/c9sc06145b#!divAbstract)
CTRL: A Conditional Transformer Language Model for Controllable Generation:
Arxiv link(https://arxiv.org/abs/1909.05858), code pre-trained and fine-tuning(https://github.com/salesforce/ctrl), blog(https://blog.einstein.ai/introducing-a-conditional-transformer-language-model-for-controllable-generation/)
Genie: a generator of natural language semantic parsers for virtual assistant commands:
PLDI 2019 pdf link(https://almond-static.stanford.edu/papers/genie-pldi19.pdf), https://almond.stanford.edu
Topics Covered:
0:00 intro
0:42 the AI economist
7:08 the objective function and Gini Coefficient
12:13 on growing up in Eastern Germany and cultural differences
15:02 Language models for protein generation (ProGen)
27:53 CTRL: conditional transformer language model for controllable generation
37:52 Businesses vs Academia
40:00 What ML applications are important to salesforce
44:57 an underrated aspect of machine learning
48:13 Biggest challenge in making ML work in the real world
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Language Modeling and Protein Generation at Salesforce with Richard Socher - #372
Today we’re joined Richard Socher, Chief Scientist and Executive VP at Salesforce. Richard and his team have published quite a few great projects lately, including CTRL: A Conditional Transformer Language Model for Controllable Generation, and ProGen, an AI Protein Generator, both of which we cover in-depth in this conversation. We also explore the balancing act between investments, product requirement research and otherwise at a large product-focused company like Salesforce.
