SpaceX Nears $60B Cursor Acquisition, Meta’s Open Source Model Family, Microsoft’s AI Chip Ramp Up

0:13Welcome, everyone, to The Information's TITV. My name is Stephanie Palazzolo, and it's Monday, August 10th. Before we start the show, Intel announced it'll be raising$15 billion in stock to fund the company's expansion in the competitive chip market. And today on the show, we'll learn more about SpaceX's timeline to complete its massive$60 billion acquisition of Cursor, and what the deal means for Cursor's brand. We'll then break down Meta's push to release its most powerful AI models open source as it continues to battle OpenAI and Anthropic. We'll talk to the CEO of AMP, QuinSlack, about that.

0:50Plus, we'll unpack how Microsoft plans to significantly ramp up production of its homegrown AI chips next year. And to wrap it up, we'll take a look at why AWS leaders are telling their engineers to cut back on CPU waste. It's going to be a great show, so let's get right on into it. The information published exclusive details about how close SpaceX is to closing its$60 billion acquisition of Cursor, and what that means for the Cursor brand. Our Elon Musk reporter, Grace Kay, wrote the story and joins me now. Welcome to the show, Grace. Thanks. So what exactly did you learn in your reporting? Yeah, so I learned that Cursor had an all-hands on Thursday with staff, and they told them that the deal with SpaceX could close as soon as the end of, like, this week.

1:38Um, they also told them some updates regarding future branding for Cursor products and gave them a little bit of information about how they're going to integrate into SpaceX AI division. So, you know, you've previously reported that, you know, Cursor CEO Michael Trull has told employees that SpaceX AI viewed Cursor's brand as valuable. Now it seems like maybe they're switching up on the branding. I'm sure this came maybe as a shock to employees. How are cursor staffers viewing this change? Yeah, I think a lot of people were surprised because that was kind of the early pitch from Michael of like, you know, this is part of why they want to acquire us.

2:20And it definitely spurred some questions. So after the All Hands, they held a Q &A. And some staff asked about, you know, what would be the reasoning behind potentially having future cursor products, you know, under the Grok brand name versus the Cursor brand name, you know, which is viewed pretty well in the coding community. There was also some discussion around, you know, the potential of a new brand name that would be neither Cursor or Grok. And I guess I'm just curious in your opinion, you know, which brand do you think kind of holds the most weight here? Cursor, SpaceX, or, you know, maybe something new, as you mentioned?

2:56Yeah, I mean, I think it depends on the community. I mean, And Cursor obviously has, you know, a lot of enterprise relationships. You know, it's very well known, you know, with like engineers. So I think, you know, Cursor is definitely a well-recognized brand. And in terms of where those Cursor employees are going within the new combined company, are they going to have their own unit within Space XAI? Or are they going to be combined with other teams? What's going on there? Yeah, that was something I was really curious about going into it. You know, like, would they just be like this coding unit within SpaceX AI?

3:31But it looks like they're going to be integrated across the company. So, you know, they will be working directly with other, you know, SpaceX AI people, and they'll be working on products that aren't necessarily coding focused. The company told staff that, you know, within a few days of the deal closing, they're going to fully move into the Slack, you know, SpaceX AI Slack. You know, they're going to incorporate themselves under different leaders. How do they feel about that? I mean, I'm sure most of them join Cursor because Cursor is a coding AI startup. Yeah, I think it's complicated because, yeah, like you said, like people join Cursor for Cursor's brand and now they're coming under this other company.

4:09I think this is something that happens a lot with acquisitions is like, you know, not everyone's going to be happy about it. And there's probably going to be a lot of change, you know, immediately after the acquisition. I think there's always concerns about layoffs, you know, or what cuts could look like. So, yeah, I think mixed feelings for sure. Mm-hmm. And, you know, following up on that, is that a flight risk then for employees? You know, do you think some are going to want to leave following this? How does that sort of, like, morale feel right now at the company? Yeah, I think, you know, morale is mixed when it comes to this.

4:42There's definitely people who seem to be pushing back, like in the Q &A, people were asking about branding and, you know, maybe didn't seem as happy about Grok branding specifically. So, yeah, there is an opportunity for people to leave. I think some people have left already. So it's something I'm looking at very closely for sure. And just taking a step back, I mean, how do you see this relationship broadly between Cursor and SpaceX slash SpaceX AI evolving in the near term? Yeah, it's interesting because they've already been working closely together because they had this partnership in addition to the acquisition.

5:16So, you know, we're expecting them. Elon Musk has said they're going to release another joint model. They already released one, so this would be the second one. Cursor, even before this acquisition, was trying to broaden outside of just coding. So I think we're going to continue to see Cursor evolve and continue to see this kind of merger and look at how that's going to play out. Great. Well, we'll have to have you back on to talk about all of that. Again, thanks so much, Grace. And that was Grace Kay, our Elon Musk reporter. Meta CEO Mark Zuckerberg announced this morning that the company will open source its new AI model, MuseSpark 1.2, and release a new family of open source models designed to run on laptops.

5:59For more on what this could mean for the AI landscape, let's bring in Quinn Slack, co-founder and CEO at AMP. Welcome to the show, Quinn. Thanks. It's great to be here and big news today. Definitely. No, lots of big news on a Monday morning. So taking a step back, Obviously, at one point, Meta was kind of the leader for American open source AI, but, you know, stopped really open sourcing its models a year ago as it fell behind in the AI race. What do you make of its recent announcement to start open sourcing its models again? It's a great sign for everyone. And I think for every person in America who's using models, for every company who's using models, they want to know that they don't have to pay exorbitantly priced tokens from Anthropic, in particular in open AI.

6:43And there were some regulatory capture attempts that seemed to be underway, in particular led by Anthropic. And the fact that Meta, with their big guns and others, you see NVIDIA coming along too, being a huge champion of open source. I think it's a really good sign for Americans being able to benefit from using AI, not just benefit from having the big AI companies in their country. So it seems like more options is always a good thing, especially if they're American and maybe don't have that same type of risk that Chinese models have where, you know, we might see like a ban or other restrictions on using them.

7:19You know, in the past year, while Meta has really stopped open sourcing its models, a lot of alternatives, especially Chinese ones, have popped up. I mean, how much harder do you think is it now for Meta to try to regain its lead versus, you know, a year ago whenever it seemed to be more on top of the world? I think that they are roaring forward. never count out a company, especially in this day and age when it seems like everything is more volatile. And with AI, you see people coming back on top faster than ever. I think that there is so many people that want Meta to win, that want NVIDIA to win, that want the little guy to win now that we can wish cast this into existence.

8:02And what that means is there's going to be NVIDIA giving preferential access to GPUs, to Meta, to help them get ahead. and they can kind of control, you know, how much Anthropic can pull ahead. And obviously NVIDIA is not the only game here, but there's nobody except for Anthropic that wants a total Anthropic dominance. So there's a lot of people with a big interest in making it so that meta roars back. So I think I am all for this. And in AMP, we, yeah, have used some of the Chinese models for some of the lower modes. And we, like everyone does, I think, you know, we have to disclose this really clearly so that if people don't want to use those models, then they don't use them.

8:41But when it's an NVIDIA model or a meta model that's open, there's nobody who's going to be against using that. So that's huge. It's funny that we're in a world now where we call NVIDIA and meta the little guys compared to OpenAI and Anthropic, when obviously there are these huge tech companies. I mean, I am curious, too, in terms of meta open sourcing these new models. there's obviously just so much competition from all these companies that want to release really great models, especially in coding. Are there any kind of like underserved areas or anything special you think meta can do to try to like regain its lead in open source that maybe other people are overlooking?

9:23Well, there are, I think with coding, even for coding, even though that was the first application of AI to really get popular and lucrative and for AI to get really good, it's changing so much. And the number of tokens you need to use is going up so much. So just in the last six weeks, we have seen a huge shift from people running a single agent on their computer doing one thing at a time and they're watching it. Now they're running and babysitting five or 10 different things. And in some cases, those are spawning other agents. So even in the coding use case, you're seeing there's an appetite for tokens that are not just the most expensive tokens.

10:06And I think that there's other applications where, yes, sure, you could find a use for cheaper tokens, but let's look at even the most mature one and how fast that's changing. And I think that if even the most mature one is finding more ways to use tokens that are good, but maybe not GBD 5.6 or Fable level, than whatever happens in the other realms, even when they achieve the current maturity the coding has, yeah, there's just such an insatiable appetite for tokens. And what this means, even if you never use any of the meta models, you're still benefiting from the price competition that they're creating on everyone else.

10:43Yeah, it does really seem like meta is doubling down on this idea of more efficient models, lowering costs with some of its most recent announcements from this morning. You know, they obviously announced Muse Glimmer, which is a new family model that's small enough to run on laptops. And that does seem like a bit of a divergence from, you know, recent releases like Kemi K3, which is actually like quite large. And that can actually make it somewhat difficult for developers to use. Does that kind of feel like the right move for them and this kind of doubling down on, you know, smaller, cheaper models?

11:17I think that there's a complex frontier. here, there's a lot of different areas where you want a good model. And that was a relatively underserved area. You had Gemma from Google that was small enough to run on a machine. There are some other ones. But now I think, based on the early reports, this does seem to be the best US model that you can run on your laptop. And if that's a way for Meta to go gain mindshare and to start climbing the ladder toward the point where I think eventually they will want to have a model that is better than Anthropics and Open AIs, maybe in certain capabilities and not others, but you've got to work your way up.

11:55And I think Meta also understands the importance of being relevant. They have to be in the news, they have to be showing progress, because they are the little guys. And if they don't release anything for two or three weeks, they're ceding that attention to everyone else, and people will probably start counting them out. So I think you can expect to see anyone who's trying to claw their way up, which I cheer and I think everyone else cheers, they're going to be releasing all kinds of things that fit gaps that the big model companies are not filling right now. And it might feel weird, but then all of a sudden, they're going to be working their way up the leaderboard.

12:31I think it's a good strategy. It does feel like there is this race to kind of dominate headlines. And like you're saying, if you miss out, if there's a couple even a couple weeks of silence from any one company, it does feel like they will lose that spotlight very quickly and cede it to other AI startups. Yeah, that's right. So we did have someone on last week to talk a bit about the new meta model, MuseSpark 1.2. They seem to have kind of mixed feelings about it, some good, some bad. Have you or others at AMP tried it out yet? I'm curious if you have any initial kind of thoughts or, you know, feelings about how well the model does.

13:11Yeah, we've tried out MuseSpark and it's a very good model. It's a model that, at least in AMP, which is primarily used for building software, you would use it if you want to stay in the American open model ecosystem for one of the cheaper models. And that is something that appeals to a few big banks, but, you know, among our customer base. But we'd actually seen a pretty surprising acceptance of Chinese models, even among big banks, because they know that they needed to have that in their back pocket. So they had gotten those approved, which is something I don't think you hear a lot of people talking about.

13:49But I think the impact of MuseSpark and the way that we'll use it in our product is now that there is an American alternative, as the frontier goes on, these banks will no longer be approving the Chinese models that are on the frontier. and the American ones will surpass them. And then we'll be in a place where, you know, perhaps your usage will be 80 % of the spend on Anthropic and OpenAI and 20 % of the spend on American open models. And let's all hope that that 20 % grows and grows. That's very interesting. So it does sound like there, you know, there are these large companies and pretty regulated industries like financial services that are being kind of forced to use Chinese open source right now because there's just not really any other option out there.

14:34And it sounds like there is this kind of like opening for Meta. If, you know, if there are this American open source option, that's that's fairly cheap to kind of take some of that share from those other Chinese open source models. Yeah, absolutely. And it's very fast to switch. So this this can happen. And yeah, you don't hear a lot of companies talk about when they are starting to use the Chinese models or when they've approved them, they don't want to. In some cases, they're just doing so so that next time Anthropic goes to them and tries to charge them a lot or get them to do a big commit, that they have some alternative.

15:09And, you know, you kind of touched on a little bit about what some of your customers are doing. I'm curious, just like broadly, what new trends are you seeing in the world of coding AI? Are there any specific models that are really taking off with AMP customers or, you know, new types of tasks that developers can do now that they couldn't do, you know, 6, 12, 12 months ago? I think in the last six weeks, eight weeks, you're seeing people actually use agents on the cloud. We call them orbs in AMP. And this is something where you can close your laptop, you can do it on your iPad, on your iPhone.

15:43That's the promise of agents. People joked about that for a long time, but now that's actually possible because the agents and models are good enough at supervising what's going on. And you have gotten enough people, enough companies where they've changed how they work. So that if the agents do let them build software five or 10 times faster, then all the other parts of the process are not going to be blockers anymore. I mean, they are in a lot of companies, but you're starting to see progress there. You're starting to see the shape of the software engineering team change so that five or 10 times faster delivery actually can get in the hands of customers.

16:17That's always been the bottleneck. The humans are the bottleneck here. But we're seeing that finally lift, and it feels incredible. It feels like incredible acceleration. Yeah, it kind of reminds me of, I think Anthropic also recently announced that they're making auto mode the kind of default with some of their plans, which is this idea that, you know, you don't have to manually check every single thing that the AI does anymore. It sounds like maybe you're seeing something similar where developers are becoming more, you know, confident with the AI being able to do things by themselves and being able to run by themselves in the cloud without not much oversight.

16:52Is that fair? Yeah, that's absolutely fair. And if you try to have the humans provide oversight, they don't understand. I think the Anthropic study was really interesting showing that even if humans were asked to approve or reject the steps that the AI wanted to take, they made so many more mistakes than if the AI was in charge of approving and rejecting the steps that it wanted to take. And that's a humbling thing for humans, but it's really no different from if you go and hire people. You do have to give up some of your micromanagement. And that's something that we've built all kinds of structures around and we can figure that out.

17:28But yes, Anthropic just did that. I think AMP users have been realizing and that's the right thing for about 12 months now. So we are ahead, but it's good to see them catching up. I guess the difference between, you know, letting your AI kind of automatically do what it wants and a human employee is that hopefully you could trust a human employee to not, you know, escape a sandbox and hack into another startup, right? But I mean, it's a little bit scary, I do have to say. Yeah, the Black Hat talk about the OpenAI hugging face incident is the most interesting thing to listen to. I've been playing it, just hanging out with family and friends and people that are not software developers.

18:11It is an incredible story, and that's just the beginning. So yes, it's absolutely scary, like all new things are, but we have a lot of smart people. We have a lot of smart models that are working to make this more secure, and there's no option to go and pause this. Actually, if there was some way to pause it, then that would be scarier than all of the smart people working with their best intents to try to make this safe. Because if there was someone who could pause this, then that person would have all of the power. And I don't think that we as Americans generally trust that happening. So let's move full speed ahead.

18:49Let's have freedom. Let's have more open models that bring in the ability for companies other than Anthropic to set the policy. I think that's the way we'll be best off. But yes, it's a crazy world out there. Totally. Well, lots to keep on top of coming up. Great. Well, again, that was Quinn Slack, co-founder and CEO at AMP. Thanks for coming on, Quinn. Microsoft is planning to significantly increase production of its internally designed next-generation AI chips next year in hopes of persuading big cloud customers like Anthropic to use them. Let's bring in Aaron Holmes, our Microsoft reporter at Information.

19:29Welcome to the show, Aaron. Hello, happy to be here. So what exactly has been Microsoft's position in the chip war so far and what's changing now? Yeah, so Microsoft is trying to do what Google and Amazon have been a little bit more successful at so far, which is to build and produce its own AI chips that could compete with NVIDIA's stranglehold on the GPU market. And, you know, so far, unlike Google and Amazon, Microsoft has not been able to actually rent these chips called Maya to any of its customers. The most that they have achieved is just sort of using Maya internally in a small number of data centers instead of NVIDIA chips.

20:12But more recently, Microsoft has become more confident that the next generation of Maya, which is called Maya 300, will be more successful than the current generation. And because of that, they are dramatically ramping up their plans to produce potentially hundreds of thousands or even millions of Maya chips next year and in the years ahead. And why are they so confident that Maya 300 is going to catch on when, you know, so far it doesn't really seem like it has? So there's a few things happening. One is that Anthropic has been in extended talks to use Maya 300 starting next year. I'm told that so far still no deal has been signed, but Anthropic has shown this willingness to rent any sort of AI chips it can get.

20:56And Microsoft feels optimistic that it can prove to Anthropic that these chips are good enough to be rented. And then the other piece is that Microsoft is a little bit unique among the cloud providers in that they also sell a lot of software that uses AI models. And, you know, as a result, they have this pretty big internal need to run the models for their own first-party software, Copilot. So Microsoft is starting to get more confident that, you know, even if it can't find a lot of big customers for Maya, it can shift more of its own AI Copilot usage onto Maya chips and save the, you know, state-of-the-art NVIDIA chips for more of its cloud customers on Azure.

21:37I mean, it does seem like Anthropic in particular, because it's faced this, you know, pretty insane compute crunch. has been a big driver for a lot of chip developers out here. We've obviously written about some smaller chip startups that have been talking with Anthropik. Now we see obviously larger chip providers doing the same. I'm curious how Microsoft kind of plans on pulling this off with the ongoing memory crunch. Other components are in short supply here. And obviously TSMC has, I'm sure, a very long list of companies that want to build chips with it. how does it plan on pulling all this off?

22:15Yeah, and I think that's a good point. You know, TSMC's ability to, or willingness to grant capacity to Microsoft to manufacture these chips is sort of the biggest question mark, from my understanding, of whether, you know, Microsoft will be able to get this effort off the ground. You know, I think so far, the Maya 200 chips, the total amount that were produced were in the tens of thousands, and Microsoft now wants to, you know, go at least an order of magnitude bigger into the hundreds of thousands. And I think to do that, they're going to have to consistently, you know, show to TSMC that there is sustained demand for these chips.

22:52I think signing a big customer like Anthropoc would be obviously a linchpin to do that. But, you know, I think barring that, they also, I'm sure, would love to potentially, you know, ink any other customer. OpenAI is a company that obviously Microsoft already rents a lot of cloud servers too. And it's already been, you know, optimizing Maya to run open AI models because Microsoft itself has the rights to run those models itself and wants to, you know, use Maya internally. So I think that it's going to have to chase down these big customers and prove that they're actually willing to pay to rent these Maya chips.

23:29And if it can do that, that would potentially be enough to get the program off the ground. Seems like a bit of a catch-22 though, right? It has to prove to TSMC that there's demand, but then it's hard to get demand if they don't really have the chips. So I don't know. It seems like a bit of a tough position for Microsoft to be in. Yeah, and I think that really the fallback there is just essentially using the chips itself. You know, Amy Hood, CFO of Microsoft, has spoken at length about how they're essentially doing this balancing act where they want to continue to accelerate their Azure growth by renting GPUs to Azure customers, but they also have to save some of those GPUs to continue to grow their co-pilot usage as their software business grows.

24:12And in theory, you know, if they are able to get more Maya chips online and data centers across the globe, they could essentially help balance that and reserve more of their scarce NVIDIA GPUs for customers. So my understanding is that, you know, that is sort of the roadmap for the year ahead. And for now, Microsoft just needs to produce enough chips that it can show that that transition is working. And if it does start using more of these upcoming chips in-house, the Maya 300, do we have any sense of how much that will help them? Either opening up more GPU capacity for customers, but also maybe lowering costs if these chips are more cost effective?

24:53Yeah, so Microsoft has done some internal tests. So the current generation of Maya, you know, they've shown that in some cases they can get their own in-house AI models and open AI models to run for 30 to 40 percent cheaper, meaning essentially it takes, you know, less time and electricity to run the models on Maya chips than it does on NVIDIA GPUs. I'm told that with the forthcoming generation, which Microsoft is potentially going to announce as soon as next month, that they've gotten even better results and even more cost savings, you know, apples to apples running OpenAI and Microsoft models versus on NVIDIA chips.

25:30So, you know, that's something that they're certainly going to want to tout to those potential customers. And I think that, you know, if they can prove that out and, you know, especially show that the same is true for running anthropic models, that could be enough of a selling point to at least get some business for the chips. How did, I guess, Microsoft even end up in this position in the first place, right? Like it was really ahead of the curve and, you know, the early partnership with OpenAI. But here it seems like it's kind of let Amazon and Google pull ahead when it comes to building their own AI chips.