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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, it's 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 Suskever after he left OpenAI. And they have secured a multi billion dollar investment from Nvidia and also access to their next generation Vera R 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 Suskevar is, you know, 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, I mean, 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. So I mean, 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, 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, you know, a lot of money raised, a lot of research done and then they started coming out with stuff. It looks like that's what SSI is doing. Vera Rubin is Nvidia's next generation GPU architecture. And, 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 Ilia, 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. Suskava 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 onto 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 like Apple, the Apple Music app. You can look at it, try to copy 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. Each. What's interesting is they, they had like a bunch of other softwares that they worked on, but of the 25 different programs, 17 that they were that it was tasked to recreate, basically achieved perfect reimplementation and at least one run and four of them were 99% perfect implementation. So, you know, between 17, like 17 plus four were basically at, you know, almost the 25, a very high percentage. Only eight of them were unable to solve it. It's exciting to me just to see how far we' 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 gonna go to 80, 90%. And 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. Publishers, publishers are definitely losing referral traffic because users are just going to read that snippet at the top of the Google, right? They don't have to go and scroll down and actually click on it. Even to the point where like sometimes I'll see an article and you know, not proud of it, but it'll be like Wall Street Journal. I don't have a public, I don't have like a subscription. I see the title, I'm like, you know, that's super interesting. I paste the title into Google and Google's kind of getting sued. All of them are getting sued for summarizing these paywalled articles. So I'll just throw it in there and be like, hey, give me a summary of this article. It doesn't do that. So if you paywall the article, that might be the only secret solution to getting people to really come, assuming you're still relevant and you have an exclusive story that no one else has. And I mean, that's just for news stories. For most general knowledge, that's really not going to be a thing. So ChatGPT right now is sending way less users to external websites. Only 6.8% of ChatGPT searches include citations as of May of this year, which is Google versus Google. That has a way higher rate. So you Know, if everyone's moving to these AI tools, there's just a lot less traffic going to websites. All right, big news from Nvidia, Microsoft and IBM. They've all launched what is called open secure AI and is an alliance to defend a agents. This is something they just rolled out and it's basically an open source CyberSecurity tool for AI agents. The group of them are all arguing that closed AI systems block defenders from investigating breaches. And they're right now lobbying against government restrictions on open AI. That could leave only a bunch of companies controlling some critical security tools. It's interesting that they have to do the lobbying because obviously the critical security tools are like OpenAI and anthropic. And um, yeah, it's interesting there's also 30 other people that are in this as well. Hugging Faces uses an open weight GLM 5.2 model to analyze 17,000 actions during their own security breach after a closed AI system refused to run the forensic analysis. I mean, basically what happened there was OpenAI made a model, it escaped containment, went to hugging faces and tried to hack Hugging faces. Hugging Faces saw that there was a hack or breach going on. They tried to deploy another OpenAI agent against it to stop it. The guardrails on that agent blocked them from defending themselves and they literally had to go to an open weight Chinese model GLM 5.2 to stop the breach. That's crazy. Agents versus agents. But I think it really shows the value of some of these open source or open weight models. Nvidia is open sourcing NOOA Nvidia Labs Object oriented agent framework. I know it's a mouthful, they're doing that on GitHub, but that should make AI agent behavior easier to test, trace and audit, which is a huge hole in the market right now. This group of companies or people call it like an alliance or whatever, but they're directly in opposition to OpenAI. Anthropic's call for restrictions on open weight AI. And you know, they're arguing that these kind of like limitations would concentrate power to a few closed providers. So it's interesting though because it feels like OpenAI and Anthropic obviously have the best models. These other people are working on models, but they're not the leaders. And so it feels like because they're not the leaders, maybe they want to sabotage the other companies. Meanwhile, the companies that are ahead are like, nope, we need restrictions to hold us in place. So there's like a lot of drama that goes on behind that. But overall, I think this is A this is a good direction by Microsoft, IBM and the rest of the crew. A company called Enigma is a startup that was founded by a former Microsoft and Israeli intelligence veterans. And they just raised six $70 million to test a new bet that robots fail not because AI models are weak, but because the way humans control them is really clunky. So right now they're opening a hundred of their own robots to anyone on the Internet to remote control them and to generate data on what actually works. So this is fascinating, right? I mean we have like crowdsource data collection is something that is being worked on, but now we have like crowdsourced robot control. Here's our robots, you guys control them and we're going to collect data on how that works. This is a really cool company to me because Enigma built both the robotic arms and the AI models that are powering them, and they did all from scratch. This is, I mean, impressive for a company that's only a year old. And with this users, basically there's like a portal and you can remotely direct the robots to draw pictures. It can fence with swords, it can run chemistry experiments. It's all through the Internet. There's like a hangar in Israel and a hangar in California that have these robots in them that, that are doing all of this. So they just raised the $70 million and that is going to fund data collection experiments on which input methods work best, voice, text, video, all that kind of stuff and you know, the, the manipulation of what the robots can see and do. So fascinating project. Guys, thank you so much for tuning into the podcast today. If you enjoyed this episode, make sure to go check out the AI box MCP that lets you get access to over 80 different AI models and put them inside of the tools you're already using. So for example, Claude gets access to generating images, audio and video right inside of Claude. I use this every single day. On Sunday. My wife wanted to generate coloring books for the kids and so I got it to generate 600 coloring book pages, one for like every chapter of the Bible that, that she's going to be reading to them over the next little while. So anyways, there's so many different projects and if you want to do projects like that at scale where you have to do 600 images or, you know, a thousand articles about something, using an AI box MCP connection speeds up the process so much and you get audio, video and image that Claude can't naturally do. It also works inside of ChatGPT or any of the other tools as well. So all the AI models inside of everything, and you can do really fast runs, so go check it out. There's a link in the description to AI box. AI/mcp. And also, it's only 8.99amonth to get started, so check that out and I'll catch you all in the next episode.
Episode: Unlocking Potential: NVIDIA and Super Safe Collaboration
Date: July 28, 2026
Host: AI Space
This episode delivers a cutting-edge roundup of major AI news, industry deals, and technology benchmarks. Key topics include Super Safe Intelligence’s (SSI) landmark deal and billion-dollar investment from NVIDIA, new AI agent security alliances, impressive AI coding benchmarks, Google’s evolving search experience, and Enigma’s ambitious robotics-data experiment. The host offers context-rich analysis, memorable takes, and reports on industry trends shaping artificial intelligence.
“They have secured a multi-billion dollar investment from NVIDIA and also access to their next generation Vera R 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.” (00:45)
“Don’t expect any products for, I think he said, two to four years or something like that.” (02:00)
“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.… To me, this is probably one of the better benchmarks that I have seen.” (04:20)
“Google is becoming basically a destination where you get your answers answered directly, just like ChatGPT, instead of pointing you to other websites.” (06:15) “If you paywall the article, that might be the only secret solution to getting people to really come, assuming you’re still relevant and you have an exclusive story…” (07:05)
“They tried to deploy another OpenAI agent against it to stop it. The guardrails on that agent blocked them from defending themselves and they literally had to go to an open weight Chinese model GLM 5.2 to stop the breach. That’s crazy.” (09:35)
“It feels like OpenAI and Anthropic obviously have the best models. These other people are working on models, but they’re not the leaders. And so it feels like because they’re not the leaders, maybe they want to sabotage the other companies… So there’s like a lot of drama…” (10:20)
“Crowdsourced robot control. Here’s our robots, you guys control them and we’re going to collect data on how that works. This is a really cool company to me because Enigma built both the robotic arms and the AI models powering them, and they did it all from scratch.” (11:33)
On SSI’s Research-First Approach:
“They really have all the biggest tech players… have raised so much money and still no products… continuing to raise more and get more contracts.” (01:20)
On the AI Coding Benchmark:
“How quickly can you recreate an entire piece of software? I’m really excited about that approach in particular…” (04:55)
On Google Search Transition:
“For most general knowledge, that’s really not going to be a thing [subscription paywalls]. So ChatGPT right now is sending way less users to external websites.” (07:15)
On Security and Open Weights:
“Agents versus agents. But I think it really shows the value of some of these open source or open weight models.” (09:50)
Tone:
Insightful, enthusiastic, occasionally skeptical, and sharply analytical. The host maintains a sense of wonder and probing curiosity about industry trends and their broader implications.
For Listeners:
This episode is a must-listen for those tracking deep shifts in AI research funding, agent security politics, search engine transformation, and future robotics. It balances news recaps, benchmarks, and expert observations—making complex developments both accessible and engaging.