20VC: Cohere's Chief Scientist on Why Scaling Laws Will Continue | Whether You Can Buy Success in AI with Talent Acquisitions | The Future of Synthetic Data & What It Means for Models | Why AI Coding is Akin to Image Generation in 2015 with Joelle Pinea

**Joelle Pineau** (0:00)
The scaling laws have been remarkably robust. There's a lot we don't know yet in terms of the vulnerability of these systems.

**Harry Stebbings** (0:07)
If you don't need to buy the Galacticos, why do you have like an Andrew Tulloch, a Daniel Gross and Alex Wang and the Galacticos assembling? If I gave you $10 billion, what would you spend it on first? Knowing what you know, what do you not let your children do? This is 20VC with me, Harry Stebbings, and today we have one of the leading minds in AI, Joelle Pineau on the show. Joelle is the chief scientist at Cohere, where she leads research on advancing large language models and practical AI systems. Before joining Cohere, she was VP of AI Research at Meta, where she founded and led Meta's AI Montreal Lab. Joelle is also a professor at McGill University and renowned for her pioneering work in reinforcement learning, robotics and responsible AI development. But before we dive into the show today, are you drowning in AI tools? Chat GPT for writing, Notion for docs, Gmail for email, Slack for comms and you're constantly copy pasting between them all losing context and losing time. This is the AI productivity tax and it's killing your output. At 20VC, we're all about speed of execution and Superhuman is the AI productivity suite that gives you superpowers everywhere you work. With the intelligence of Grammarly, Mail and Coda built in, you can get things done faster and collaborate seamlessly. Finally, AI that works where you work, however you work. Superhuman gets you from day one with zero learning curve and it's personalized to sound like you at your best, not like everyone else using generic AI. Get AI that works where you work, unlock your Superhuman potential. Learn more at superhuman.com/podcast.
That's superhuman.com/podcast. And once you're moving faster with Superhuman, make sure you're moving safely with Vanta. Customer trust can make or break your business. And the more your business grows, the more complex your security and compliance tools get. It can turn into chaos and chaos isn't a security strategy. That's where Vanta comes in. Think of Vanta as your always on AI-powered security expert who scales with you. Vanta automates compliance, continuously monitors your controls, and gives you a single source of truth for compliance and risk. So whether you're a fast growing startup like Cursor or an enterprise like Snowflake, Vanta fits easily into your existing workflows so you can keep growing a company your customers can trust. My listeners can get $1,000 off Vanta by going to vanta.com/20vc. That's vanta.com/20vc, 20VC for $1,000 off Vanta. You have now arrived at your destination. Joelle, it is so great to have you in the studio. I've heard many great things from Nick Aidan Shrep. So thank you so much for joining me.

**Joelle Pineau** (3:03)
Thank you, happy to be here.

**Harry Stebbings** (3:04)
Now, you spent over six years at Meta and I want to start there because it's a very transformative time and place. What are the biggest takeaways for you from that time and how did that shape your mindset to how you think today?

**Joelle Pineau** (3:18)
Well, I was there from 2017 to 2025 and you have to see just how much AI changed over that period of time. What we were really focused on is fundamental AI research. One thing that I've learned is just sometimes how long it takes to prove out a hypothesis. We feel like AI is moving at the speed of lightning. But in fact, there's some things that it just takes a few years to mature, to get the right optimizer, the right compute, the right data for that to really make a difference.

**Harry Stebbings** (3:47)
I look at where we are today and everyone goes, it's here, it's here, it's here. Then you actually look at what a lot of the leaders have been saying recently where it's like, actually, Andre was saying, it's not the year of the agents, it's the decade of agents. Sam's pulling back too. Have we got over our skis and we're actually all pulling back, realizing that time is the factor we need to rely on?

**Joelle Pineau** (4:06)
Well, I'll give you an example. I've been in research for a couple of decades now. I've been working on reinforcement learning for over 20 years. And suddenly, everyone's talking about reinforcement learning since the advent of reasoning models, agents and so on. So, sometimes you have to be a little patient with these ideas. And the right algorithmic tweak, the right context, the right problem domains just opens up the magic.

**Harry Stebbings** (4:32)
I was listening to Andre yesterday and he said in this show that reinforcement learning is terrible.