Meta Manus Desktop App, Anthropic Enterprise Lead, OpenAI AWS Deal

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1:00Welcome to the podcast. I'm your host, Jayden Schaefer. Today on the podcast, we have a number of interesting stories. Meta has just launched Manus for desktop in this kind of AI agent on your computer craze. We have Anthropic, which is currently now officially flipped a switch and is beating OpenAI and Enterprise spending. A new startup called Memories AI is building a visual memory layer for robotics. And AI is expanding their government footprint with a brand new AWS contract. We're going to dive into all of those today in the state of what I think we're kind of watching these three different layers collide infrastructure, enterprise spend and agents. I'm also super excited to announce that AI box my own startup has officially added video to our platform. You can now create AI tools with video and you can chat with over eight of the top AI video generation models. We have bite dances, seed dance. We have Google Vio models. We have OpenAI's Sora models and we have Pixiverse models on there. This is super exciting for us. It's been a big push and we hope to see what incredible tools you guys build with video

2:04on the platform. If you don't already have a subscription, it's 899 a month and you get access to over 70 of the top AI models all in one platform for less than 20 bucks a month. I hope this saves you a ton of money and you get access to all of these interesting new models to test out, try and talk with. You can try out the platform with the link in the description or typing in AIbox.ai. All right, let's get into the episode today. The first thing I wanted to cover is just the fact that we have a huge story from Meta's Manus. This is a company they recently acquired and what's interesting is Manus was sort of going viral. It was a Chinese firm that kind of had to pull itself out of China before this acquisition. But they just launched a desktop app that is basically bringing their AI agent directly onto your computer. They've seen all of the hype around OpenClaw and realized that having an, you know, they probably had a lot of these AI capabilities, but bringing it beyond just having it on, you know, a website and into your computer, I think they've seen the value of that. It's a really big shift. I think these agents were living in the cloud before. Now they're going to be able to access your files, run apps, organize data, even build software locally.

3:06And I think this is a lot closer to how people actually work, which is why OpenClaw went so viral. I mean, it's basically the beginning of AI agents becoming our operating system layer. I think we're going to see a huge shift here. This isn't just answering our questions, but they're actually going to be doing the work inside of our machines. I think the trade off is obviously obvious. I think more power means that there's going to be more risk security wise. You, you know, can now give AI access to your local environment, which is going to have a lot of privacy concerns as well. I think for some people, right, Meta doesn't have the greatest track record on privacy and on your data. And so for some people, they might be a little, a little concerned about having access, all of your computer files. But at the end of the day, these are really powerful tools. So I'm going to, I'm interested to see what sort of uptake Manus has. This is already a product that's been doing quite well. And I think this makes it a lot more useful. There's also a new startup called Niv AI. They just raised funding to solve a problem that I think a lot of people are not talking about enough, which is power. AI data centers right now are using tons of power, tons of electricity, because GPU workloads

4:08spike really unpredictably. And I think that forces operators to throttle usage or they have to overpay for backup capacity. So what Niv is doing is they're building a system right now to monitor and optimize power usage in real time, essentially, they're acting as a co-pilot for data center energy. I think the reason why this matters is because AI isn't just a software problem right now. It's an energy problem, companies that figure out how to squeeze more output from the same hardware and power constraints are going to have a massive advantage. I think especially when you look at the state of the world today with everything happening in Iran and the energy shock that we've seen over the last few weeks, I think energy is more important now than ever. A lot of people are talking about the fact that AI companies are going to be very severely negatively impacted if these energy shocks, these high oil prices continue because a lot of this was powering data centers, a lot of this was powering energy. AI is literally just a direct pipeline from energy to what we are all using. All of this stuff has to be run.

5:10It takes insane amounts of energy. A lot of the data centers, a lot of the AI training facilities that we're building, they're told they should be building power plants basically attached to them because they use so much energy and a lot of people are seeing their local energy bills increase due to these kind of data center projects. I think this is a really fantastic startup and I'm excited to follow along with them. There's a new startup I've been looking into called Memories.ai. They're building what might become kind of this like foundational layer for physical AI and that is visual memory. So instead of just remembering text like ChatGPT does, they're basically building a system that's going to help AI remember what it actually sees. So that means wearable devices, robotics and real world AI systems that can recall visual experiences over time, right? Because right now, if you have a conversation with ChatGPT in a month later, I'm like, hey, for this project, can you help me write a new document or some sort of new file? It can go and look at my history, my context and remember everything about that specific

6:12project from two months ago. Now, it's a completely different situation when we have robots running around in the real world with cameras on them that are learning and figuring out how to do things in warehouses and eventually in all of our homes with something like the Optimus robots or the figure robot that these things are going to cost like $20 or $30,000, they'll be in our home to do things. I mean, there's a whole other conversation if people will want that or trust that. And I think inevitably they will once these things have improved just self-driving cars. But I think right now, most of these AI systems are living in really a digital world. And if AI is going to operate in the physical world, once we start moving from just having AI on our phone that we talked to to AI in a robot that's walking around or in our home or in our warehouse, it needs to have memory the same way humans do. So I think this is very early, but it points to where things are going in the future. AI that doesn't just respond, but it actually remembers it learns, it builds context from world world experiences, just like a human would end something that I would actually expect to see from an Optimus robot or a figure robot is they would have this kind of memory built

7:17in. So it's learning and understanding. And let's say your robot breaks. I would expect that you can transfer memory from one robot model to the next when you upgrade. So let's say you've had a robot in your family for, you know, 10 years that's been helping out and it understands how to do everything inside of your home. I think you'll be able to transfer those memories to the next iteration of the robot, which is really fascinating and I think a really strong moat between switching between robot companies in the future. Now, I know this sounds crazy in the future, but I think these are the problems that people are starting to solve now. I'm excited to see what memory dot AI does with this memories dot AI. Okay. Anthropic is now capturing over 70% of new enterprise AI spend is according to ramp data. And I actually love these types of reports from Mercury or ramp or even a lot of different banks will put out these these types of reports. But I mean, basically they have access to what companies are actually spending because they have, you know, insights into their financials. And so, you know, this is really solid data coming out of ramp.

8:17Just a couple of months ago, it was a really tight race between open AI, but now Anthropic is pulling way ahead and they're actually moving ahead fast. If you look at the charts, it's phenomenal. Their businesses playing, I mean, their businesses are basically paying all this money for their AI coding tools, I think primarily, but a lot of people are just using paying for clawed for regular chat tools. At the same time, open AI is reportedly rethinking their strategy. So the shifting more focused towards enterprise after they've been heavily investing in consumer products. I think right now the AI race isn't just about who has the coolest demos, it's about really who makes money. Enterprise adoption is a real scoreboard. And I think right now, like people, everyone's like, wow, open AI has this massive user base, which is true, almost, you know, almost a billion weekly active users. Last I checked, it was 900 million weekly active users. I think Sam Altman, I mean, I know he was just throwing some shade, but he said something recently, which was like, there was more free chat GPT users in Texas than like all of Anthropics users in the US combined or something like that, which is sort of crazy.

9:23But if you look at the revenue numbers, they're not that far apart. Opening, I said that they're on pace to generate about $25 billion in revenue this year. And Anthropic is on pace to generate about $19 billion. So these companies are much closer than you'd think when it comes to revenue. Okay, there's a massive story unfolding with open AI right now. They're expanding their government footprints through a new deal with AWS. I think on the surface, it just looks like another partnership, but I don't think that is actually the case. So open AI has signed a deal to distribute AI products in the US government through AWS. And that includes access inside highly secure environments like GovCloud and even classified regions, handling really sensitive workloads. Now we've seen that open AI and the federal government, particularly the Pentagon have had a huge falling out or sorry, Anthropic in the Pentagon and opening it kind of stepped in and took a lot of those contracts. And so I think what is actually happening is that open AI is trying to insert themselves directly into the most important distribution channel for government AI, which is AWS,

10:23because AWS already has really deep relationships across all federal agencies. They are already compliant to their infrastructure as something that's already trusted. And so by opening and plugging directly into AWS in this new partnership, open AI is not just selling their model, they're becoming part of the default procurement pipeline for government AI. I think what gets really interesting for me is that AWS is already heavily tied to Anthropic. They have, you know, Amazon has invested billions into them on many of the early investment rounds of Anthropic were led by Amazon and AWS, you know, famously when AWS was trying to compete in the early days with ChatGbT, Amazon put in four billion dollars. And since they've been, you know, many multiples and much more than that. But cloud is deeply ingrained into AWS's AI platform because of that. And so this was supposed to be Anthropics kind of like home turf, you know, but now open AI is stepping directly into that system. I don't think it's just a competition. It's really a platform level battle happening inside that same infrastructure. Government adoption right now, I think is kind of acting as a bit of a signal to the

11:25entire market because if your model is trusted for classified insensitive workloads, then that credibility is really going to be able to spill over into a lot of enterprise deals specifically, right? Like for users, I don't think users are like, oh my gosh, the government uses open AI. That should be my default model. But for enterprise, I think that's 100% the signal that they see, right? It's like if the government, the most classified, you know, quote unquote organization in the world is using this. This is probably something that's great for enterprise. So I think it really is expanding right now, open AI's reach into federal agencies. And it's also strengthening their position with enterprise customers who care about security, compliance, and long term stability, right? Let's be honest, I think a lot of people saw the anthropic deal falling through and felt like the company perhaps was a little bit less stable. Now, is that true or not? I'm not, you know, speculating on that. I just think that's what a lot of enterprises I heard saying. So at the same time, open AI is keeping control. They decide which models get deployed. They coordinate directly with customers and they can enforce additional safeguards. So this isn't them handing over the keys, you know, to AWS and saying, you know,

12:28you're the distribution layer. You you let people do whatever you want with the product. I think right now, the winners are not just the companies with the best models. It's the companies that control distribution, infrastructure, and trust at scale. And so if open AI is making this deal with AWS, I think that's kind of the first step forward here. Guys, thank you so much for tuning into the podcast today. If you enjoyed the episode, make sure to leave a rating and review wherever you get your podcasts. And as always, make sure to go check out aibox.ai. We've just launched eight new video models into the platform. So if you want to try those all out for only 899 month, you can check out all of the latest from open AI's Sora, Google's VO, Seed Dance, and a ton of other incredible models all in the one platform. There's a link in the description. I'll catch you guys all in the next episode.

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