00:00 Speaker A
Big money pouring into AI, and this time, it’s Elon Musk and Nvidia at the center of it. Bloomberg is reporting that xAI is raising up to $20 billion with Nvidia investing as much as 2 billion into Musk’s AI startup. For more, we want to bring in here John McNeil, DBX Ventures CEO, co-founder of Vista Shares and former president at Tesla. John, uh good to see you. So reports showing Jensen Wong, uh doing more investing. John Nvidia apparently investing 2 billion in xAI.
00:30 Speaker A
What what do you make of that, John, that headline and what if anything does it tell you about that mega AI trade and trend?
00:35 Speaker B
Hey Josh, I think what it says is that uh, Nvidia and and Jensen are deploying their balance sheet uh in in in very productive ways. I think there’s a lot of VCs that would love to have Jensen’s returns right now. I think he’s up like five or 6X on Core Weave. Uh, he’s up similar amounts in his in in their investments into OpenAI.
00:56 Speaker B
Uh they’ve invested into xAI along the way uh and uh wave, Anthropic, others. So he’s he and Nvidia are building a uh kind of an envious portfolio uh that uh that’s generating um the combination of great returns for their balance sheet, but also, uh also really seeding uh customers uh purchasing ahead of uh ahead of where their demand is.
01:19 Speaker A
Let me ask you, John, with all this money Musk is raising here, does it change at all the competitive landscape, you know, with OpenAI, Anthropic, Google?
01:32 Speaker B
I think what what’s happening is that with the large large, large language model producers, uh, so OpenAI, Anthropic, uh X AI, they are kind of each of them uh in a race that kind of gets rescored monthly as to to who’s at the top of the leaderboard. But they’re all generating very similar now uh results across general uh areas uh of expertise. But when you look
01:58 Speaker B
particularly into specific verticals like coding. Uh, XAI is is making dramatic gains and and are coming up at the top of a lot of folks’s leaderboards. So, uh I think the the main story here, it doesn’t change. It takes a lot of capital to train these large models. Uh and we’re seeing some parity now amongst uh the very, very largest of these large language model companies.