Building Connections Through Open Research: Meta’s Joelle Pineau

**Sam Ransbotham** (0:02)
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**Shervin Khodabandeh** (0:57)
Why is being open about your company's AI research a benefit more than a risk? Find out on today's episode.

**Joelle Pineau** (1:06)
I'm Joelle Pineau from Meta, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (1:12)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI.
I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy Guest Editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (1:30)
And I'm Shervin Khodabandeh, senior partner with BCG, and one of the leaders of our AI business. Together, MIT SMR and BCG have been researching and publishing on AI since 2017, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.
Hi, everyone. Today, Sam and I are happy to be joined by Joelle Pineau, Vice President of AI Research at Meta. Joelle, thanks for speaking with us today.

**Joelle Pineau** (2:07)
Hello.

**Shervin Khodabandeh** (2:09)
Okay, let's jump in.
A good place to start might be for you to tell us about Meta. A lot of people know what Meta is, but maybe you could describe it in your own words and also your role in the company.

**Joelle Pineau** (2:22)
Well, as many people know, Meta is in the business of offering various ways for people to connect and build community, build connections, whether it's through Facebook, WhatsApp, Instagram, Messenger. We have billions of people around the world using our products.
I've been at Meta for about seven years now, leading AI research teams. I'm based in Montreal, Canada, and now I lead FAIR, which is a fundamental AI research team across our labs in the US., in Europe. The role of our group is actually to build next generation AI systems and models, discover the new technology that will eventually make the products better, more engaging, safer as well.

**Sam Ransbotham** (3:04)
That's a great overview. Can you give us a sense of what some of those projects are that you're excited about or you're working on?
You don't have to give us any secrets, of course, but what are some fun things you're excited about?

**Joelle Pineau** (3:15)
Well, I hope we have a chance to talk about it, but there's not a ton of secrets because in fact, most of the work that we do is all out in the open. We adhere strongly to open science principles. We publish our work. We share models, code libraries, and so on and so forth. Our teams cover the full spectrum of AI open problems. So I have some teams who are working on understanding images and videos, building foundation models, also core models that represent visual information.
I have some teams that are working on language models, so understanding text, written, spoken language as well. I have some teams doing robotics, so understanding how AI systems move in the physical world, how they understand objects, people, interactions, and a big team of people who are working on core principles of intelligence.
So how do we form memories? How do we actually build relationship between different concepts and ontology of knowledge and so on and so forth?

**Sam Ransbotham** (4:17)
It seemed like there's almost nothing within artificial intelligence you're not working on there. Tell us a bit about why you think open is important.

**Joelle Pineau** (4:25)
So FAIR has been committed to open research for 10 years now since day one. We've really pushed on this because whenever you start a project from the point of view of making it open, it really puts a very high bar in terms of the quality of the work as well as in terms of the responsibility of the work. And so when we decide what algorithms to build, what data sets to use, how to evaluate our data, how to evaluate the performance of our model through benchmarks, when we know that all of that work is going to be open for the world to scrutinize, it really pushes us to put a very, very high bar on the quality of that work, on the rigor of that work.