Chapter 1: What is the main topic discussed in this episode?
Welcome to the podcast. I'm your host, Jaden 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 to switch and is beating OpenAI and enterprise spending.
Chapter 2: What is Meta's Manus desktop AI agent and its significance?
A new startup called Memories AI is building a visual memory layer for robotics. Open 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 ByteDance's Seed Dance, we have Google Veo 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 on the platform. If you don't already have a subscription, it's $8.99 a month,
Chapter 3: How is Niv AI addressing energy consumption in data centers?
and you get access to over 70 of the top AI models all on 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 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've just launched a desktop app that is basically bringing their AI agent directly onto your computer.
Chapter 4: What innovations is Memories AI bringing to robotics?
I think they've seen all of the hype around OpenClaw and realized that having an AI... But bringing it beyond just having it on 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.
And I think this is a lot closer to how people actually work, which is why OpenClaw went so viral. I think 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 risks. Security-wise, you 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 to access all of your computer files.
Chapter 5: Why is Anthropic leading in enterprise AI spending?
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 spike 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.
Chapter 6: What does OpenAI's new AWS deal mean for government AI?
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, you know, oil prices continue, because a lot of this was powering data centers, a lot of this is powering energy.
And AI is literally just a direct pipeline from energy to what we are, you know, all using, like all of this stuff has to be run, it takes insane amounts of energy, a lot of the data centers, a lot of the AI training centers. facilities that we're building, they're, you know, they're told like 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. So 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 and a month later, I'm like, hey,
you know, for this project, can you help me write a new, you know, some sort of new document or some sort of new file, it can go and look at my, you know, my history, my contacts, and remember everything about that specific project 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, you know, these things are going to cost like 20 or $30,000, they'll be in our home to do things.
And I mean, there's a whole nother conversation of people will, if people will want that or trust that, and I think inevitably, they will once these things are have improved, just like 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, right, once we start moving from just having AI on our phone that we talk to AI in a robot that's walking around or in our home or in our warehouse.
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Chapter 7: How do AI agents transform our interaction with technology?
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 real world experiences, just like a human would.
And something I would actually expect to see from an optimist robot or a figure robot is they would have this kind of memory built in. 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 it sounds crazy in the future, but I think these are the problems that people are starting to solve now.
Chapter 8: What challenges do AI data centers face with energy usage?
So I'm excited to see what memory.ai does with this memories.ai. Okay, Anthropic is now capturing over 70% of new enterprise AI spend. This 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. Just a couple of months ago, it was a really tight race between OpenAI, but now Anthropic is pulling way ahead and they're actually moving ahead fast. If you look at the charts, it's phenomenal.
Their business is playing. I mean, their businesses are basically paying all this money for their AI services. coding tools, I think primarily, but a lot of people are just using paying for Claude for for regular chat tools. At the same time, OpenAI is reportedly rethinking their strategy. So they're shifting more focus 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, OpenAI has this, you know, massive user base, which is true. Almost, you know, 900, 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 Anthropix users in the US combined or something like that, which is sort of crazy. But if you look at the revenue numbers, they're not that far apart.
OpenAI said that they're on pace to generate about $25 billion in revenue this year. And Anthropix 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 OpenAI 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 OpenAI 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 OpenAI and the federal government, particularly the Pentagon, have had a huge falling out or sorry, anthropic in the Pentagon. And OpenAI kind of stepped in and took a lot of those contracts. And so I think what is actually happening is that OpenAI is trying to insert themselves directly into the most important distribution channel for government AI, which is AWS.
Because AWS already has really deep relationships across all federal agencies. They are already, you know, compliant. Their infrastructure is something that's already trusted. And so by OpenAI plugging directly into AWS in this new partnership, OpenAI is not just, you know, selling their model. They're becoming part of the default procurement pipeline for government AI.
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