AI Round Up: Ari Morcos from Datalogy AI and Rob Toews from Radical VC on AI Talent Wars, xAI’s $200B Valuation, & Google’s Comeback

**Rob Toews** (0:00)
Never bet against Elon is a sound mantra.

**Ari Morcos** (0:02)
I would also say, don't bet against that.

**Jacob Effron** (0:04)
These are all environments seen all the rage these days on the venture side.

**Rob Toews** (0:06)
There's like a tidal wave of cash that is about to come down on everyone's environment.

**Jacob Effron** (0:11)
Is model progress slowing down?

**Rob Toews** (0:13)
In the spirit of making this a provocative, spicy discussion, I'll disagree with our review.

**Jacob Effron** (0:17)
Do you think this MSL experiment's gonna work? Today we're introducing a slightly different format to the show that I'm super excited to try. We'll still be doing our one-on-one interviews, but we'll also be adding a news roundup with some great minds in AI today. No better way to start with them with the two co-hosts we have right now. Ari Marcos is the CEO of Datalogy, a really interesting state-of-the-art data curation company. And he previously spent two years at Google DeepMind and five years at Meta as an AI engineer. We also have Rob Toews, partner of Radical Ventures, where he's led investments in companies like Writer, Hebia and Datalogy. And he also writes a really interesting column at Forbes. We hit on all the big AI topics today, RL environments, valuation of model companies, the AI talent wars, and even hit things like brain computer interfaces. This was a ton of fun to do. We'll still be doing our one-on-one interviews, but I hope folks really enjoy these kind of episodes as well. We'd love feedback on what we've done here. Please DM me on any platform and subscribe to stay tuned for all future episodes. Without further ado, here's Ari and Rob.
Rob, Ari, thanks so much for doing this.

**Rob Toews** (1:15)
Thanks for having us, Jacob.

**Ari Morcos** (1:16)
Yeah, really excited to be here.

**Jacob Effron** (1:17)
I've been looking forward to this one for a while. I feel like we often have lots of conversations off mic about a bunch of this stuff, and so figured it'd be fun to bring it onto the podcast. Before we dive into every topic on everyone's Twitter feeds, I felt like it would be good to just let you guys quickly introduce yourselves so the audience has a bit of context. Maybe, Ari, if you want to kick it off.

**Ari Morcos** (1:36)
Yeah. Hi, I'm Ari Marcos. I'm the CEO and co-founder of Datalogy AI. Prior to founding Datalogy a couple of years ago, I was an ML researcher for about a decade. I spent some time at DeepMind and five years at FAIR at Meta AI. At Datalogy, we work on all things optimizing data for building the best models possible.
Which can make massive impacts in the costs and performance of the models that you train.

**Jacob Effron** (2:01)
It's tough having an actual researcher on the show when it comes to takes. You really will correct if the VC's go too off what they know.
Fun to have around. Rob, yourself?

**Rob Toews** (2:12)
Yeah, there's going to be an actual substance on this podcast.

**Jacob Effron** (2:16)
At least when Ari talks.

**Rob Toews** (2:18)
Yeah, when Ari talks. It's great to be here, looking forward to the conversation. My name is Rob Toews. I am a partner at Radical Ventures and lead the firm's Bay Area office. Radical is a VC firm totally focused on AI with close ties to the AI research community, close relationships with a lot of AI pioneers like Jeff Hinton and Fei-Fei Li and so forth. I've won a number of Radical's investments over the years, including in Datalogy and others that I'm sure may end up coming up as we chat. Prior to coming to VC, I worked in autonomous vehicles for a long time.
Excited to be here.

**Jacob Effron** (2:54)
Amazing. Well, two great folks to hit the topics of the day. I figured no better place to start than the discourse that's been happening around model progress. I feel like there's some very vocal camps on Twitter and other places around whether model progress has slowed down. There's been people that have said, look, GPT-5 was really just GPT-45 with a router. Clearly, maybe you can hillclimb on individual areas like coding, but the era of large general improvements in generations and models is slowing. And other people say, what are you talking about? Look at these awards that these model companies seem to be winning in math and coding and all these other spaces. Maybe Ari, we'll start with you. Which side of this debate do you come down on?

**Ari Morcos** (3:39)
I don't think it's slowing down significantly. I think it might be a little bit harder to measure it and to see it.