During a Senate Commerce Committee hearing last week, Sen. Ted Budd (R-NC) spoke about artificial intelligence developers creating programs that are built on open-source models produced in China.
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00:00Thank you, Chairman. Again, thank you all for being here. I've enjoyed various conversations
00:04with each of you. The ability for the U.S. to deploy new energy generation capacity and upgrade
00:09its grid is in many ways the key to the race against China. Energy is how we can win and
00:14it's also how we can lose. Permitting in this country, it takes too long. China's command and
00:20control system means that they will not fail to deploy the energy needed to achieve the scale
00:26necessary to develop the most advanced models, which will drive all to the benefit of AI.
00:33So I'm glad to be working with Senator Lummis on the FREE Act, which would set up a permit
00:38by rule structure, which would let large projects meet comprehensive standards at the front end
00:44instead of dragged out on a case by case process. So we all want to protect the environment
00:49and we all want to maintain U.S. economic and technological leadership.
00:55So Mr. Intertor, what is CoreWeave's experience been in contracting power? And are you concerned
01:03that the current permitting system can make it hard for the U.S. to achieve capital investment
01:07in the scale needed to win this AI race?
01:10So, as you said, access to power, access to scale power is certainly one of the keys to
01:20our ability to win this race. There are others, but it is one that I spend a lot of time thinking
01:26about. I separated the comment into access to power and access to scale power because I
01:34do think that we are moving towards a period of this race where the size, the magnitude of
01:45the infrastructure that is being required to move our artificial intelligence, the labs
01:52that are building it, the companies that are building it forward at the velocity that's
01:56necessary is going to be a specific challenge that really requires a lot of thought. We have
02:02a huge part of our organization focused on not just getting access to power, but getting access
02:09to the size and scale of power that's going to be able to build the infrastructure at the scale of
02:15Abilene or close to it in order to allow this to move forward. It's tough, right? And it will get
02:23harder as we move through time because the existing infrastructure that does have opportunities,
02:33it has some level of elasticity, is going to be consumed. And once that is consumed, you're going to get down
02:38to kind of a first principle, how do we get power online now? And that's really going to be
02:45challenging within the regulatory environment as it currently is configured.
02:48Thank you. Mr. Smith, a similar question. How is Microsoft trying to secure power for its data
02:53centers? I mean, we read about that in the news recently, but what does federal policy need to focus
02:58on to make sure that we don't lose this race because we can't get enough energy?
03:02Well, we invest to bring more electricity generation onto the grid and then to bring it through the grid
03:08to our data centers. We probably have more permitting applications in more countries than quite
03:15possibly any company on the planet. Last time I looked at it, it was 872 applications in more than 40
03:21countries. The number one challenge in the United States when it comes to permitting, interestingly
03:26enough, is not local, it's not state, it is the federal wetlands permit that is administered by the Army
03:34Corps of Engineers. We can typically get our local and state permits done in about six to nine months.
03:41The national, the wetlands permit is taking off in 18 to 24 months. Both the outgoing Biden
03:48administration and the incoming Trump administration have focused on this, but if we could just solve
03:54that, we could accelerate a lot here in this country. Very helpful. Thank you. Mr. Altman, much has been
04:01made about the Chinese open source models like DeepSeq. We spoke about that a month or two ago. A concern
04:07that I have is that accessible Chinese models promoted by the Chinese Communist Party might be an attractive
04:14option for AI application developers to build on top of, particularly in developing world economies.
04:20So how important is U.S. leadership in either open source or closed AI models? I think it's quite
04:28important to lead in both. We realize that we, OpenAI, can do more to help here, so we're going to
04:35release an open source model that we believe will be the leading model this summer because we want
04:40people to build on the U.S. stack. In terms of closed source models, a lot of the world uses our
04:44technology and the technology of our colleagues. We think we're in good shape there. So how could federal
04:49policy further help encourage AI ecosystem to be developed right here in the U.S.?
04:53Well, you touched on a great point with energy. I think it's hard to overstate how important energy
04:59is to the future here. Eventually, chips, network gear, that will be made by robots and will make
05:06that very efficient and will make that cheaper and cheaper. But an electron is an electron. Eventually,
05:11the cost of intelligence, the cost of AI will converge to the cost of energy. And how much you can have,
05:17the abundance of it will be limited by the abundance of energy. So in terms of long-term
05:21strategic investments for the U.S. to make, I can't think of anything more important than energy.
05:27Yeah, you know, chips and all the other infrastructure also, but energy is where this,
05:32I think, I think this ends up. Thank you.
05:36Chairman.