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Chapter 1: What is the main topic discussed in this episode?
Welcome back to the Rundown for another weekend deep dive. Today, we are talking about the next phase of the AI boom, AI agents. For the past couple of years, the AI boom has been about training large language models, you know, the chat GPTs and the clods of the world. But now the focus is shifting from simply talking to AI to having AI actually do things for you.
Chapter 2: What is the main focus of the AI boom discussed in this episode?
We are entering the era of AI agents and the implications for the economy, the stock market, and your job are massive. So in today's episode, we'll break down what agentic AI actually is, why Nvidia is betting the house on it, and what this means for the AI bull case moving forward. We got a great one for you today. Let's dive in.
The best way to understand agentic AI is comparing it to what came before it, which was generative AI. Now I'm talking about the chat GPT moment. With generative AI, people would type in a prompt and the AI would give you an answer. Now people could generate text, images, code, even video, all with a simple prompt.
You could ask the AI to create a workout plan for you or rewrite an email or write a history essay or a business strategy, and the AI would give you an answer within seconds. When this technology first dropped, it was a huge breakthrough and the adoption exploded overnight. In fact, ChatGPT grew to 100 million monthly active users within two months of its launch.
I mean, that is the fastest service to reach 100 million users ever. Today, ChatGPT has more than 900 million weekly users with about 50 million people paying for premium features. I am one of those people that pays for ChatGPT. And look, it's not just ChatGPT anymore. Other tools have popped up like Anthropix Cloud and Google's Gemini, all of which have hundreds of millions of users.
So these tools are amazing and very popular, but they do require the user to be in the driver's seat. You know, you ask it a question, it gives you an answer, but the AI can't actually do anything in the real world. You know, it can't log into your email and reply to all the unread messages. It can't file your taxes. It can't manage your calendar.
It's just good at generating outputs like text, images, and video. But what agentic AI does is it takes it a step further. Instead of the AI just answering your question, AI agent can break down a task into steps. It can use tools. It can interact with software and try to complete a job with minimal human supervision.
The way I think of it is like generative AI is like, you know, it can read memos, it can send emails, it can book meetings, it can follow up with clients, it can update the CRM, it can compare vendors and file expense reports, all with minimal human input. Now these tools are relatively new, but pretty powerful already.
Anthropic has clawed code, OpenAI has codex, and then there's OpenClaw, which has gone insanely viral. So we're at a point now where AI agents can do real economic transactions, even going as far as sending and receiving money. We're actually gonna talk more about that in a bit. So this is leading to a transformation of the AI industry.
In fact, Nvidia CEO Jensen Huang thinks that we're at an inflection point. So let's talk about what this means for the AI economy and why Jensen Huang thinks that the rise of AI agents could add an extra $500 billion to Nvidia's revenues. So we're starting to see the rise of agentic AI. So let's talk about why investors are paying attention.
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Chapter 3: How does agentic AI differ from generative AI?
That is called inference. Inference is when an AI model answers questions from a user and generates output. Inference is also what powers AI agents to execute their tasks. A very simplified analogy that I can think of is AI training is like someone going to business school. And then AI inference is like hiring that person to do a job and answer questions.
And this shift to inference is impacting the AI infrastructure spending. According to research from Gartner, global capital spending on inference infrastructure is going to surpass spending on training for the first time ever this year. And this gap is expected to widen fast. By 2029, companies are projected to spend nearly twice as much on inference compared to training.
The thing is, these AI models are now so good that there's less urgency to train new ones. Instead, there's more focus on getting the most out of these existing AI models. Now, the other side effect of the rise of agentic AI and the focus on inference is that this is gonna exponentially increase the demand for compute.
So if you think about it, a normal AI chatbot gives you one response, but an AI agent needs to think through the tasks, call multiple tools, check its own work, retry if something fails, pull in outside data, and keep running in the background to complete the work. All that requires a lot more tokens and a lot more computing power. And it also requires a different type of hardware.
Most people know about Nvidia's GPUs. They're really good at training AI models. Well, inference and agentic workloads are different. That requires CPUs working alongside GPUs to get the maximum performance. The CPU acts as a brain that can think and execute multi-step tasks. It can call external tools like APIs and databases and manage memory better.
And that's why Nvidia is now making CPUs themselves alongside their GPUs. NVIDIA became the most valuable company in the world because their GPUs were the best at training AI models. The company's data center revenue, which represents their AI chips business, has grown nearly 13x since the launch of ChatGPT. But NVIDIA CEO Jensen Huang understands that the future is agentic AI.
At the recent NVIDIA GTC developer conference, Jensen introduced the new Vera CPU, which is specifically designed to handle these agentic workloads. He also introduced a new central processor and an AI system built on the technology from Grok, which is a startup the company basically acquired for about $20 billion back in December of last year.
Now, just to be clear here, I'm not talking about Elon's Grok chatbot. The Grok that I'm talking about ends with a Q, and they make chips specifically for inference. So NVIDIA is now positioning themselves to be the leader when it comes to inference. By the way, Jensen was talking a big game at the GTC conference.
He now expects Nvidia to make over $1 trillion in revenue from the Blackwell and Vera Rubin chips alone through 2027. That's up from last year's forecast of $500 billion by the end of 2026. So the company is expecting the AI boom to continue for at least another year. You know, I'll be honest with you guys. I was kind of skeptical of all the CapEx spending from these big tech companies.
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Chapter 4: What tasks can AI agents perform that generative AI cannot?
Young people might not be able to get jobs. And then you have some companies announcing big layoffs and blaming it on AI. In February, Block, formerly known as Square, announced that they were laying off half their workforce, about 4,000 people.
And the CEO of that company, Jack Dorsey, straight up said that it wasn't because the business was struggling, but because of the effectiveness that teams are seeing from using AI tools. And look, Block is not the only one. Amazon cut 16,000 jobs in January. Atlassian cut 10% of its workforce.
And then there was a report in Reuters in mid-March that Meta is considering laying off 20% of its workforce, which would be about 15,000 jobs. So you have all these tech companies laying off tons of people. And then these kind of layoff announcements can create like a domino effect, causing other companies to lay off their staffs to stay lean and competitive.
Now, look, the reality is a lot of these tech companies are probably just course correcting from overhiring following the post COVID boom. And they're just using AI to kind of cover their mistake and paint a better story for investors. But we can't just ignore the impact that AI could have on jobs. One of my favorite tech analysts is Ben Thompson. He writes a great newsletter called Stratechery.
And in a recent post, he had a very interesting framing of the situation. He wrote that the positive impact of AI in large organizations won't necessarily be eliminating jobs, but instead it might be about replacing what he called the hard to manage and motivate
human cogs in the organizational machine with AI agents because these AI agents do what they're told and work 24 seven until the job is done. You know, AI doesn't burn out. AI doesn't ask for raises and they can potentially get the work done at a faster rate than humans. I guess we'll have to wait and see. The rising unemployment for younger workers is a bit worrisome though, I gotta say.
So what's my take here? Well, I think I'm starting to drink the AI agent hype juice, all right? I've been playing around with some of these tools like OpenClaw and Cloud Code, and while I'm still trying to figure them out, even in their current state, you can see the potential. And the thing is, these tools are only gonna get better.
From an investing perspective, the rise of AI agents is making me more bullish on the AI trade, especially the big tech companies and NVIDIA. The shifted inference is gonna require exponentially more compute. So all the AI CapEx from big tech companies is likely justified. And with NVIDIA leaning into CPUs and inference chips, it's hard not to be bullish.
I mean, look, longtime listeners know I'm an optimistic person. And when you look back at every major technological shift in history, it's created some anxiety about jobs, but the new tech has always led to new industries and new opportunities and overall economic growth. I think the same thing will happen with AI. Now, I'm not gonna lie, it does feel like things are moving really, really fast.
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Chapter 5: How is Nvidia positioning itself in the AI agent market?
Hope you guys enjoyed today's episode. Let me know what you guys think about the rise of AI agents. Are you drinking the hype juice like me? Does all this make you less worried about an AI bubble? Do you think that AI agents will replace a ton of jobs and lead to a big rise in unemployment? Drop your thoughts in the comments on Spotify and YouTube.
And while you're at it, if you have an extra five seconds, consider giving us a five-star rating.
All that engagement really does help us out, and it helps other people find the show. Thank you guys so much for listening, watching, and commenting. Shout out to Mike and Connor for all the work behind the scenes. And we'll see you guys back here tomorrow.