Unlocking Potential: NVIDIA and Super Safe Collaboration

**SPEAKER_1** (0:00)
Welcome to the podcast. Super Safe Intelligence has landed a massive new deal with Nvidia for a huge boost in computing. Claude Opus 4.7 has just finished a two-week coding job. There's this basically new benchmark that has come out that is really exciting to me, and I'll tell you why. Google AI overviews now appear in 43% of searches. This is up 15% from a year ago. Let's talk about how the landscape is shifting, specifically in SEO. Nvidia, Microsoft, and IBM have all launched Open Secure AI Alliance to defend agents. We're going to talk about why there's so much drama in that. Enigma has exited stealth, and they've just gotten $70 million to rethink how humans are talking to robots. Safe Super Intelligence is only two years old. It's the research lab that was founded by Ilya Suskova after he left OpenAI, and they have secured a multi-billion-dollar investment from Nvidia, and also access to their next-generation Vera Rubin GPU platform. This deal in particular is basically going to increase their compute power by about 10x, which is a massive jump, and it's going to let them scale their research into AI safety and reasoning. And you know what's crazy about this company, if you've been following along, they literally have not even shipped a product yet, they don't have any revenue, and they've just gotten this multi-billion-dollar investment from Nvidia, really just riding off the fact that Ilya Suskova is famous, was one of the OGs at OpenAI. And of course, he's, when I say famous, famous because he's a very incredible AI researcher, but still, it's just really running off of the name, which is amazing. SSI has now raised $7 billion total. They have $32 billion for evaluation, and their backers are Nvidia, Andreessen Horowitz, Alphabet, Sequoia, Lightspeed. They really have all the biggest tech players. They've raised so much money, and still, no products have been shipped, no revenue has been generated, and they're continuing to raise more money and get more contracts. And just to be fair, this is actually what Ilya said when he started the company. He said, don't expect any products for, I think he said, two to four years or something like that, which is kind of what happened with OpenAI, where there was a lot of money raised, a lot of research done, and then they started to come out with stuff. It looks like that's what SSI is doing. Vera Rubin is Nvidia's next-generation GPU architecture, and by getting this, SSI is essentially going to put themselves as an early flagship customer. They're also going to collaborate with Nvidia on advancing future compute platforms. And with the background of Ilya, I think for Nvidia, this is like a really good kind of name brand company working with them on it, and also it's going to help a lot with R&D. SSI also partners with Google Cloud, which means that they have two of the largest compute suppliers in the industry, which are funding their runway while they're working on a new foundational research that they're doing instead of shipping products. Suscova right now is really betting that some of this deep research on AI alignment and reasoning is going to help solve some of the problems. And so he doesn't have any of the product pressure that everyone else has, but the level of compute backing, and I think a lot of the investor confidence to me is signaling that, you know, maybe this is a crazy bubble, or maybe he's on to something that we don't know. And definitely, I think there's some value in the long game.
Opus 4.7 has implemented a 61,000 line Apple software program from scratch. I was rolling my eyes when I first saw this news story, because it was like it did it in 14 hours, when it should have taken two weeks and did it for $250. Okay, what's cool to me is there's a new benchmark called Mirror Code, and it basically tests whether an AI can rebuild real production software. And it doesn't, it's not allowed to get the code for that software. It basically is like, hey, go look on your computer, go try to copy the Apple Music app. You can look at it, try to copy it as best you can. You don't get to see any of the source code, you don't get access to the internet, and it's basically a black box. And how long does it take you to build it, and how much money does it cost? And so in this particular test, they were able to have Opus 4.7 and also OpenAI's GPT 5.5. Both of them re-implemented GoTree, which is a 16,000 line parser, and they did it across a bunch of different programming languages. They did it for $100 to $400 each. What's interesting is they had a bunch of other softwares that they worked on, but of the 25 different programs, 17 that it was tasked to recreate basically, achieved perfect re-implementation and at least one run, and four of them were 99% perfect implementation. So between 17 plus 4, we're basically at almost the 25, a very high percentage. Only 8 of them were unable to solve it. It's exciting to me just to see how far we've come. These AI models are now like the benchmark is how quickly can you recreate an entire piece of software. So I'm really excited about that approach in particular, and I think it's probably one of the better benchmarks that I have seen. Google AI overviews now show up in 43% of all searches. That's about triple the rate from a year ago. And I think this is a big shift. Google is becoming basically a destination where you get your answers answered directly, just like ChatGPT, instead of pointing you to other websites. And I mean, right now, that's 43%. I think we're going to go to 80, 90% in the coming couple years. Google AI mode visits jumped 121% in the last 11 months. That's climbing from 126 million in June of last year to 279 million in May of this year.