
Presenting the AI Engineer World's Fair — with Sam Schillace, Deputy CTO of Microsoft
03/29/24 • 42 min
TL;DR: You can now buy tickets, apply to speak, or join the expo for the biggest AI Engineer event of 2024. We’re gathering *everyone* you want to meet - see you this June.
In last year’s the Rise of the AI Engineer we put our money where our mouth was and announced the AI Engineer Summit, which fortunately went well:
With ~500 live attendees and over ~500k views online, the first iteration of the AI Engineer industry affair seemed to be well received. Competing in an expensive city with 3 other more established AI conferences in the fall calendar, we broke through in terms of in-person experience and online impact.
So at the end of Day 2 we announced our second event: the AI Engineer World’s Fair. The new website is now live, together with our new presenting sponsor:
We were delighted to invite both Ben Dunphy, co-organizer of the conference and Sam Schillace, the deputy CTO of Microsoft who wrote some of the first Laws of AI Engineering while working with early releases of GPT-4, on the pod to talk about the conference and how Microsoft is all-in on AI Engineering.
Rise of the Planet of the AI Engineer
Since the first AI Engineer piece, AI Engineering has exploded:
and the title has been adopted across OpenAI, Meta, IBM, and many, many other companies:
1 year on, it is clear that AI Engineering is not only in full swing, but is an emerging global industry that is successfully bridging the gap:
between research and product,
between general-purpose foundation models and in-context use-cases,
and between the flashy weekend MVP (still great!) and the reliable, rigorously evaluated AI product deployed at massive scale, assisting hundreds of employees and driving millions in profit.
The greatly increased scope of the 2024 AI Engineer World’s Fair (more stages, more talks, more speakers, more attendees, more expo...) helps us reflect the growth of AI Engineering in three major dimensions:
Global Representation: the 2023 Summit was a mostly-American affair. This year we plan to have speakers from top AI companies across five continents, and explore the vast diversity of approaches to AI across global contexts.
Topic Coverage:
In 2023, the Summit focused on the initial questions that the community wrestled with - LLM frameworks, RAG and Vector Databases, Code Copilots and AI Agents. Those are evergreen problems that just got deeper.
This year the AI Engineering field has also embraced new core disciplines with more explicit focus on Multimodality, Evals and Ops, Open Source Models and GPU/Inference Hardware providers.
Maturity/Production-readiness: Two new tracks are dedicated toward AI in the Enterprise, government, education, finance, and more highly regulated industries or AI deployed at larger scale:
AI in the Fortune 500, covering at-scale production deployments of AI, and
AI Leadership, a closed-door, side event for technical AI leaders to discuss engineering and product leadership challenges as VPs and Heads of AI in their respective orgs.
We hope you will join Microsoft and the rest of us as either speaker, exhibitor, or attendee, in San Francisco this June. Contact us with any enquiries that don’t fall into the categories mentioned below.
Show Notes
TL;DR: You can now buy tickets, apply to speak, or join the expo for the biggest AI Engineer event of 2024. We’re gathering *everyone* you want to meet - see you this June.
In last year’s the Rise of the AI Engineer we put our money where our mouth was and announced the AI Engineer Summit, which fortunately went well:
With ~500 live attendees and over ~500k views online, the first iteration of the AI Engineer industry affair seemed to be well received. Competing in an expensive city with 3 other more established AI conferences in the fall calendar, we broke through in terms of in-person experience and online impact.
So at the end of Day 2 we announced our second event: the AI Engineer World’s Fair. The new website is now live, together with our new presenting sponsor:
We were delighted to invite both Ben Dunphy, co-organizer of the conference and Sam Schillace, the deputy CTO of Microsoft who wrote some of the first Laws of AI Engineering while working with early releases of GPT-4, on the pod to talk about the conference and how Microsoft is all-in on AI Engineering.
Rise of the Planet of the AI Engineer
Since the first AI Engineer piece, AI Engineering has exploded:
and the title has been adopted across OpenAI, Meta, IBM, and many, many other companies:
1 year on, it is clear that AI Engineering is not only in full swing, but is an emerging global industry that is successfully bridging the gap:
between research and product,
between general-purpose foundation models and in-context use-cases,
and between the flashy weekend MVP (still great!) and the reliable, rigorously evaluated AI product deployed at massive scale, assisting hundreds of employees and driving millions in profit.
The greatly increased scope of the 2024 AI Engineer World’s Fair (more stages, more talks, more speakers, more attendees, more expo...) helps us reflect the growth of AI Engineering in three major dimensions:
Global Representation: the 2023 Summit was a mostly-American affair. This year we plan to have speakers from top AI companies across five continents, and explore the vast diversity of approaches to AI across global contexts.
Topic Coverage:
In 2023, the Summit focused on the initial questions that the community wrestled with - LLM frameworks, RAG and Vector Databases, Code Copilots and AI Agents. Those are evergreen problems that just got deeper.
This year the AI Engineering field has also embraced new core disciplines with more explicit focus on Multimodality, Evals and Ops, Open Source Models and GPU/Inference Hardware providers.
Maturity/Production-readiness: Two new tracks are dedicated toward AI in the Enterprise, government, education, finance, and more highly regulated industries or AI deployed at larger scale:
AI in the Fortune 500, covering at-scale production deployments of AI, and
AI Leadership, a closed-door, side event for technical AI leaders to discuss engineering and product leadership challenges as VPs and Heads of AI in their respective orgs.
We hope you will join Microsoft and the rest of us as either speaker, exhibitor, or attendee, in San Francisco this June. Contact us with any enquiries that don’t fall into the categories mentioned below.
Show Notes
Previous Episode

Why Google failed to make GPT-3 + why Multimodal Agents are the path to AGI — with David Luan of Adept
Our next SF event is AI UX 2024 - let’s see the new frontier for UX since last year!
Last call: we are recording a preview of the AI Engineer World’s Fair with swyx and Ben Dunphy, send any questions about Speaker CFPs and Sponsor Guides you have!
Alessio is now hiring engineers for a new startup he is incubating at Decibel: Ideal candidate is an “ex-technical co-founder type”. Reach out to him for more!
David Luan has been at the center of the modern AI revolution: he was the ~30th hire at OpenAI, he led Google's LLM efforts and co-led Google Brain, and then started Adept in 2022, one of the leading companies in the AI agents space. In today's episode, we asked David for some war stories from his time in early OpenAI (including working with Alec Radford ahead of the GPT-2 demo with Sam Altman, that resulted in Microsoft’s initial $1b investment), and how Adept is building agents that can “do anything a human does on a computer " — his definition of useful AGI.
Why Google *couldn’t* make GPT-3
While we wanted to discuss Adept, we couldn’t talk to a former VP Eng of OpenAI and former LLM tech lead at Google Brain and not ask about the elephant in the room.
It’s often asked how Google had such a huge lead in 2017 with Vaswani et al creating the Transformer and Noam Shazeer predicting trillion-parameter models and yet it was David’s team at OpenAI who ended up making GPT 1/2/3.
David has some interesting answers:
“So I think the real story of GPT starts at Google, of course, right? Because that's where Transformers sort of came about. However, the number one shocking thing to me was that, and this is like a consequence of the way that Google is organized...what they (should) have done would be say, hey, Noam Shazeer, you're a brilliant guy. You know how to scale these things up. Here's half of all of our TPUs. And then I think they would have destroyed us. He clearly wanted it too...
You know, every day we were scaling up GPT-3, I would wake up and just be stressed. And I was stressed because, you know, you just look at the facts, right? Google has all this compute. Google has all the people who invented all of these underlying technologies. There's a guy named Noam who's really smart, who's already gone and done this talk about how he wants a trillion parameter model. And I'm just like, we're probably just doing duplicative research to what he's doing. He's got this decoder only transformer that's probably going to get there before we do.
And it turned out the whole time that they just couldn't get critical mass. So during my year where I led the Google LM effort and I was one of the brain leads, you know, it became really clear why. At the time, there was a thing called the Brain Credit Marketplace. Everyone's assigned a credit. So if you have a credit, you get to buy end chips according to supply and demand. So if you want to go do a giant job, you had to convince like 19 or 20 of your colleagues not to do work. And if that's how it works, it's really hard to get that bottom up critical mass to go scale these things. And the team at Google were fighting valiantly, but we were able to beat them simply because we took big swings and we focused.”
Cloning HGI for AGI
Human intelligence got to where it is today through evolution. Some argue that to get to AGI, we will approximate all the “FLOPs” that went into that process, an approach most famously mapped out by Ajeya Cotra’s
Next Episode

Latent Space Chats: NLW (Four Wars, GPT5), Josh Albrecht/Ali Rohde (TNAI), Dylan Patel/Semianalysis (Groq), Milind Naphade (Nvidia GTC), Personal AI (ft. Harrison Chase — LangFriend/LangMem)
Our next 2 big events are AI UX and the World’s Fair. Join and apply to speak/sponsor!
Due to timing issues we didn’t have an interview episode to share with you this week, but not to worry, we have more than enough “weekend special” content in the backlog for you to get your Latent Space fix, whether you like thinking about the big picture, or learning more about the pod behind the scenes, or talking Groq and GPUs, or AI Leadership, or Personal AI.
Enjoy!
AI Breakdown
The indefatigable NLW had us back on his show for an update on the Four Wars, covering Sora, Suno, and the reshaped GPT-4 Class Landscape:
and a longer segment on AI Engineering trends covering the future LLM landscape (Llama 3, GPT-5, Gemini 2, Claude 4), Open Source Models (Mistral, Grok), Apple and Meta’s AI strategy, new chips (Groq, MatX) and the general movement from baby AGIs to vertical Agents:
Thursday Nights in AI
We’re also including swyx’s interview with Josh Albrecht and Ali Rohde to reintroduce swyx and Latent Space to a general audience, and engage in some spicy Q&A:
Dylan Patel on Groq
We hosted a private event with Dylan Patel of SemiAnalysis (our last pod here):
Not all of it could be released so we just talked about our Groq estimates:
Milind Naphade - Capital One
In relation to conversations at NeurIPS and Nvidia GTC and upcoming at World’s Fair, we also enjoyed chatting with Milind Naphade about his AI Leadership work at IBM, Cisco, Nvidia, and now leading the AI Foundations org at Capital One. We covered:
Milind’s learnings from ~25 years in machine learning
His first paper citation was 24 years ago
Lessons from working with Jensen Huang for 6 years and being CTO of Metropolis
Thoughts on relevant AI research
GTC takeaways and what makes NVIDIA special
If you’d like to work on building solutions rather than platform (as Milind put it), his Applied AI Research team at Capital One is hiring, which falls under the Capital One Tech team.
Personal AI Meetup
It all started with a meme:
Within days of each other, BEE, FRIEND, EmilyAI, Compass, Nox and LangFriend were all launching personal AI wearables and assistants. So we decided to put together a the world’s first Personal AI meetup featuring creators and enthusiasts of wearables. The full video is live now, with full show notes within.
Timestamps
[00:01:13] AI Breakdown Part 1
[00:02:20] Four Wars
[00:13:45] Sora
[00:15:12] Suno
[00:16:34] The GPT-4 Class Landscape
[00:17:03] Data War: Reddit x Google
[00:21:53] Gemini 1.5 vs Claude 3
[00:26:58] AI Breakdown Part 2
[00:27:33] Next Frontiers: Llama 3, GPT-5, Gemini 2, Claude 4
[00:31:11] Open Source Models - Mistral, Grok
[00:34:13] Apple MM1
[00:37:33] Meta's $800b AI rebrand
[00:39:20] AI Engineer landscape - from baby AGIs to vertical Agents
[00:47:28] Adept episode - Screen Multimodality
[00:48:54] Top Model Research from January Recap
[00:53:...
If you like this episode you’ll love
Episode Comments
Generate a badge
Get a badge for your website that links back to this episode
<a href="https://goodpods.com/podcasts/latent-space-the-ai-engineer-podcast-262472/presenting-the-ai-engineer-worlds-fair-with-sam-schillace-deputy-cto-o-47748328"> <img src="https://storage.googleapis.com/goodpods-images-bucket/badges/generic-badge-1.svg" alt="listen to presenting the ai engineer world's fair — with sam schillace, deputy cto of microsoft on goodpods" style="width: 225px" /> </a>
Copy