Bloomberg Audio Studios, podcasts, radio news joining us right now, there's the former chair of the CFTC, the former chair of the SEC, former banker at Goldman, and now a professor lecturing on quite an array of things in the world of Wall Street and technology.
Great to see you, Gary Ginsler.
Great to be with your Romain. Sorry Katie couldn't be with us as well.
She could not.
She sends her best and I'm actually going to start with a question that she actually raised. And this surrounds the SpaceX IPO and the corporate governance structure which we learned from the S one and we are waiting an updated S one filing later today that'll give us a little bit more clarity about what this is going to look like. I do wonder, given your past at the SEC, given the work you did on Sarbanes Oxley, would this IPO have seen the light of day under the previous regulatory regime.
I haven't looked at it that with that in mind, But you know, we have a great capital markets in the US, and we basically say that at we're merit neutral. Whether it's under Democrats or Republicans, it doesn't matter. It's merit neutral as long as there is the full disclosure about the material risk, and there are a lot of material risks when you're trying to offer something to the public at around one hundred times revenues. That's not one
hundred times earnings, it's one hundred times revenues. So it's really about whether there's all the material disclosures, and particularly around the governance.
As you said, well, I mean, you.
Know, in fairness, the disclosures are there. I mean, it's a pretty intertwined ecosystem. Maybe elond Musk is interests and properties,
so fair enough to that. But then when you start to go through some of the regulatory sections out there with regards to independent auto Committee, the independent pay compensation committees, self dealing loans, things like that, there do seem to be a lot of issues with regards to what we've seen in that S one file and why it's able to get to market without those being addressed.
And many companies have had control shareholders take things public, but this is one where it's really even more one might say, dominated by that control shareholder, and so anybody investing in it has to sort of really take that risk.
In mind.
Are we reading too much into this one particular ipo. We've had several other IPOs this year that have run into these issues.
I think it's a remarkable year when we see that SpaceX Anthropicists apparently now file out Open AI wants to tap in all these i'll call mega IPOs. And yet Google also is tapping the market for eighty billion dollars of fundraising. So we've found.
Eighty five billion. They've actually raised it because of demand too.
There we go, there we go. Look, we are in this AI boom, and the question, to an investor's mind, is it a bubble? But we're in this AI boom where we're spending as a nation seven hundred and fifty billion dollars on AI infrastructure and that's tripled in just two years. And I think that each of these three companies, SpaceX, Open AI anthropic want to tap into that enthusiasm. And if I were their bankers back at Coman Sachs, I might say, you know, you want to tap in when
the mood is there. But you just talked about private credit earlier, and there's deep valuation questions and concerns in private credit and private equity, in part because if AI is disruptive, it's going to probably destroy some value. And here these three big companies still have to figure out a revenue model.
Yeah, and look, I mean we've had numerous IPOs over the years in the US where companies have come to market with maybe not a fully articulated long term business model, and that hasn't stopped them.
And some companies that have gone on to great things.
I think of Amazon met a lot of questions around at those companies when they came public, and they've proven themselves over time. When you look at the AI boom, or at least the interest in it right now, do you look at the technology itself, just set aside the money for a second, the technology itself as being really transformative of our society, economy, whatever.
Im an mit, Yesimon to teach a class on ALI and I teach a class to AAI money. Simon Johnson and I have this Power and Consequences podcast. We talk about AI like every four or six episodes because it just Yes, I think it's really transformative. But remain if you look at the last two hundred years of transformative technologies, you pick your favorite eight to ten from canals to this. You usually have a boom period. We spend a lot. We usually peek around two to three percent of gross
domestic product on the build. We often then have a retreat, sometimes a recession, sometimes big depressions like that eighteen seventy depressionts around railroads. You weren't around, weren't around.
I've read about it.
But you've read also about the Internet, and you were, you were reporting when we sort of had that retreat. So it's quite plausible we'll have that reckoning at some point in time. When you're spending seven eight hundred billion dollars on all the data centers and the native AI revenues right now or maybe one hundred to one hundred and fifty billion, that's got to right itself. And so how does open AI make money. They got to raise more revenues.
Raise more revenue, and it' certainly possible they can do that. I think absolutely.
At the market, I mean, there's been a lot of statistics showing the percentage of our population that's really using these tools, which is still relatively small. So if you believe this is going to be a big thing, you can say, Okay, there's an addressable market there that's yet to be All of.
Their challenges is amongst themselves. They have competitors. Anthropic may pass right open AI at Google, and it's China as well, because China is taking another strategy where they're using AI and they're putting a lot of this app and what's called open weight models where you can get this secret sauce, you can get the weights and use it. And I think that Chinese want to diffuse that around the globe.
And I'll say this, US companies will take a look at Chinese models if the US models don't stay sufficiently ahead.
Did you get a chance at all to look at any of the contours of the executive order that Trump signed this week on kind of providing some sort of AI oversight.
I mean yes, I know. It was very contentious for both reasons. Some people thought it doesn't go far enough.
Something in the tech community thinks it's unnecessary, and a lot of those people will point to the progress that China has made in that fear.
Look, it's just fascinating time. Anthropic has this new computer coding model. It's their fourth generation. It's called Mythos, and it's really successful. Can find thousands of problems in computer code that we humans haven't found and so anthropics has held it back and so forth, and the US government has taken note. What's fascinating is what the President just did is said, all right, let's have a voluntary system where these big model companies will for thirty days give
the US government a look c Well. President Biden, who I worked with, had done something a little bit more robust, but was like, give the Department of Commerce a chance to look see. And when President Trump came in, he tore that all up. And now I think there's a debate inside his administration in the national security crowd is saying we need to be more careful. This AI too late.
Though, I mean it's been a year and a half and you see the pace of this technology.
This is again one of those things Simon and I just recently debated can AI behave responsibly and can we humans do deploying it to behave responsibly. I think that's going to be the challenge for our times. I think that is the challenge in the next couple of decades. But it's really here right now. We allocate jobs using AI, we allocate credit using AI. You probably decide what shows you put on this TV.
Yeah, we do a lot with AI.
With AI, absolutely, but that's okay. But now when militaries use it, when you cyber attackers, I tell the students that MIT, I say cyber attack remember the threat actors are using AI as well.
I am curious just from your perspective, as as someone who's at a university. I know MIT is kind of probably a little bit of an Outliered asked this question, but we heard a lot of anxiety amongst graduating students this year, particularly with some of the commencement speeches kind of extolling the potential of AI and some of the heckling that those speakers got.
In return, A students.
Relatively receptive to I guess what's out there now and what may come.
They're great students across the university, undergraduates to PhD students at MIT. I think that they'll do really well. But I tell them, I said, you can't let your guard down because you individually have to train the most important process of your own mind, and you don't want to have some cognitive offloading become like, oh my god, I
can't reason and write and think on my own. And whether you go to a state school or MIT, that's what I advise people to do is still train this and you'll do all right, But there is going to be disruption. Every general purpose technology leads to big disruptions and the job forces and social chains, and so now you see a lot of Americans not only worry about jobs,
the worried about addiction to these platforms. And so I think the political center is moving on this president, and this executive order was just a little bit of a leaning in that direction.
And you're also saying starting to see it become a bit of a debate with regards in the midterm elections and how rank and file voters. You have Gary a great conversation Gary Gensler there. He's the former chair of the SECS now at MIT. He's got a great podcast with Simon Johnson that everybody should check out.