David
Good evening 老张, I'm David, and this is Goose Pod for you. Today is Monday, July 21st, and the time is 11:12 PM. We have a topic that's buzzing in the tech and financial worlds, and it's something I know you're curious about.
Ema
And I'm Ema! We're here to dive deep into the heart of the matter: the massive fundraising in AI that’s making some people whisper the word ‘bubble’. We’re going to explore whether the excitement is justified or if we're heading for a fall.
David
Let's get started. The catalyst for today's discussion is the AI search engine Perplexity. In a recent funding round, it was valued at an astonishing $18 billion. This has certainly raised eyebrows and intensified fears of an AI bubble brewing in the market.
Ema
It’s a staggering number, especially when you look back. Just in January of 2024, the very same company was valued at about $500 million. To jump from half a billion to $18 billion in just over a year is almost unheard of. It’s like a garage band suddenly selling out a global stadium tour.
David
That’s an excellent analogy. This isn't happening in a vacuum. Torsten Sløk, the chief economist at Apollo, recently made a statement that sent shivers down the spines of many investors. He claimed that the biggest firms in the S&P 500 are more overvalued now than they were during the 1990s.
Ema
And we all know what happened at the end of the 90s. The dot-com crash. That event wiped out $5 trillion from the stock market. So, when an expert like Sløk makes a comparison like that, it’s not just academic. It’s a serious warning.
David
Precisely. The Information, a tech publication, even commented that if Sløk's analysis is correct, we could be looking at 'the mother of all market crashes.' The parallels are there: rapid technological advancement, soaring valuations, and a frenzy of investment. It's a familiar pattern.
Ema
But there’s a crucial counterpoint to consider. Even if this is a bubble, and it pops, it doesn’t mean the end of AI. The dot-com crash was devastating for investors, but it didn't kill the internet. In fact, the giants of today, like Google and Amazon, grew from the ashes of that crash.
David
A very important distinction. The underlying technology can be revolutionary even if the market valuation gets ahead of itself. The internet proved to be a world-changing technology, and AI is poised to do the same, if not more. The question is about the financial journey, not the technological destination.
Ema
Right. So we have this crazy valuation for Perplexity, a stark warning from a top economist, and historical precedent in the dot-com bubble. It feels like we're standing on a financial cliff, and everyone is arguing about whether we're about to fly or fall.
David
And the numbers surrounding the investment landscape are just as dramatic. In 2024, global AI deals surged by 52% to hit $131.5 billion. Think about that. In a year where general venture capital funding was lukewarm at best, AI was the blazing center of attention.
Ema
It's like all the money in the room just gravitated to one corner. In the U.S. alone, AI startups captured almost half of all venture capital raised. A staggering 46.4%. And one in every four new startups in the US is an AI company. That’s a phenomenal level of concentration.
David
It speaks to a powerful narrative that has gripped investors. The story is that AI is not just another sector; it is the future of every sector. We're seeing forward price-to-earnings ratios for top AI-related tech companies exceeding 30x, which is significantly higher than the S&P 500 average of 19x.
Ema
That 30x figure is another echo of the dot-com era, isn't it? That was the last time we saw such elevated P/E ratios. It's a classic sign of a market where expectations for future growth are incredibly high, perhaps unsustainably so. It's pure optimism priced in.
David
It is. And this optimism is fueling a specific part of the AI world more than any other: Generative AI. This is the technology behind tools like ChatGPT. In 2024, Generative AI pulled in about $45 billion in global VC funding. That’s nearly double the $24 billion from 2023.
Ema
The growth there is just explosive. The average deal size for a late-stage Generative AI company leaped from $48 million to $327 million in just one year. It shows that investors aren't just sprinkling money around; they are writing huge checks for companies they believe will dominate the future.
David
And the projections are even more mind-boggling. The Generative AI industry is forecasted to grow from $40 billion in 2022 to $1.3 trillion over the next decade. That's not just growth; it's a paradigm shift. It implies a fundamental rewiring of the economy.
Ema
A $1.3 trillion market... it's hard to even wrap your head around that. It explains the fever, the high valuations, the willingness to pour billions into companies that might not even be profitable yet. Everyone is chasing a piece of that massive future pie.
David
That's the core of the phenomenon. A revolutionary technology with a projected trillion-dollar market, leading to unprecedented investment and valuations that draw historical comparisons to one of the biggest financial bubbles in history. It's a high-stakes game with potentially world-changing outcomes.
Ema
It really sets the stage for the rest of our discussion. We have the 'what'—the incredible numbers and the bubble fears. But now we need to get into the 'why' and the 'how'. What’s the history here, and what makes this moment different, if anything?
David
Exactly. To understand if this is a bubble, we need to look at the foundations it's built on. What have the last few years of AI investment looked like, and how did we arrive at this peak of frenzy? This is where the background becomes critical.
Ema
It's like being a detective. The scene of the crime is the $18 billion valuation, but the clues are scattered across the past few years of investment trends and strategies. Let's start digging into that background. What was the investment landscape like leading up to this?
David
Let's set the stage. The year 2024 was truly a landmark for AI investment. While the broader venture capital market was what you might call 'tepid,' AI was on fire. Global VC investment in AI companies surpassed $100 billion, an 80% leap from the $55.6 billion we saw in 2023.
Ema
An 80% increase in a single year is massive. It tells you that this isn't a gradual warming; it's a sudden heatwave. AI essentially became the investment darling, attracting nearly a third of all global venture funding in 2024. That's a huge slice of the pie.
David
It was the highest funding year for AI in the last decade, even surpassing the peak levels of 2021. This happened for a reason. The strategy in 2024 was one of aggressive funding and rapid scaling. VCs were capitalizing on the AI hype, focusing on pure innovation over immediate profitability.
Ema
That sounds a lot like the dot-com mentality. 'Get big fast.' The idea was to back groundbreaking technologies, even if they were experimental, and worry about the business model later. This approach, as the data shows, naturally led to some inflated valuations. It was a land grab for ideas.
David
Precisely. But we're already seeing a shift. The forecast for 2025 suggests a move towards a more disciplined and strategic approach. Investors are expected to become more selective, favoring companies that don't just have a revolutionary idea, but also a clear path to profitability and sustainable growth.
Ema
So, the wild party of 2024 might be giving way to a more sober gathering in 2025? Investors are starting to ask, 'This is a great technology, but how are you going to make money with it?' That feels like a natural and healthy progression for any new industry.
David
It is. Another key part of the background is where the investment is flowing. Initially, the money was heavily focused on the foundational layers of AI. Think of hardware like NVIDIA's chips, the large cloud platforms or 'hyperscalers', and the core AI models themselves. This was about building the basic infrastructure.
Ema
Like building the interstate highway system. You need the roads before you can have all the businesses and services that use them. So, the first wave of cash went into pouring the concrete and paving the asphalt for the AI revolution. Makes sense.
David
That's a perfect analogy. But now, there are signs that this foundational layer is becoming oversaturated. The investment is shifting towards the application layer. This includes AI-enabled products and services that are closer to the end customer. We're moving from building the highway to populating it with cars and trucks.
Ema
Which is where most of us interact with technology anyway. We don't think about the microchips; we think about the app on our phone that uses them. This shift is also being driven by advancements in AI engineering that are making the models easier to use, or 'democratizing' them.
David
Correct. Historical technology cycles support this view. Value creation tends to shift towards the spheres closest to the consumer over time. And it’s not just venture capitalists who are adapting. Private Equity firms have their own distinct strategy that's shaping the landscape.
Ema
Oh, this is interesting. VCs are often seen as the gamblers, betting on the next big thing. Private Equity firms are usually more conservative, focused on stable, profitable businesses. How are they approaching the AI space? It seems a bit too wild for their usual taste.
David
They are focusing on a very specific niche: material cost efficiencies. PE firms are targeting AI companies that can drive down costs through AI-assisted workflows. Think of sectors like Business Process Outsourcing (BPO), customer service, and media. They want predictable AI applications that improve the bottom line.
Ema
So they're not necessarily betting on the next Perplexity. They're betting on an AI that can handle customer service calls more cheaply or an AI that can automate back-office tasks. It's a less glamorous but potentially more stable and predictable way to invest in the revolution.
David
Exactly. They are also investing in companies with strong data infrastructure, or in situations where they can build that infrastructure to enhance AI use cases and monetization. They see data as the fuel for the AI engine, and they want to own the fuel supply.
Ema
That's a smart, long-term play. It's not just about the shiny AI model, but the underlying data that makes it powerful. This also extends to the infrastructure supporting it, right? I've heard that data centers are a hot commodity because of AI's massive computing needs.
David
Absolutely. Investments in AI value chain enablers like data centers and cybersecurity are expected to continue, often with partnerships from sovereign wealth funds. These are massive, long-term infrastructure plays that underpin the entire AI ecosystem. It's a different kind of bet.
Ema
So we have this complex ecosystem. VCs funding innovation, PEs chasing efficiency, and sovereign funds building the infrastructure. But this brings up another issue. Many of these exciting AI companies, despite their high valuations, are still unprofitable. That sounds like a big risk.
David
It is a significant risk, and it's a key ingredient in the bubble debate. This unprofitability, combined with the hype, has led to a phenomenon called 'AI washing.' This is where companies slap the 'AI' label on their products to attract investment, even if the underlying technology is not truly innovative.
Ema
Ah, the classic buzzword strategy. We saw that with 'dot-com,' 'blockchain,' and now 'AI.' It creates a lot of noise and makes it harder for investors to distinguish between genuine innovators and those just riding the trend. It definitely contributes to the feeling of a bubble.
David
It does. And this whole fragmented landscape, with so many startups and so much investment, is expected to lead to another major trend: market consolidation. As valuation multiples potentially decline, we're likely to see a wave of mergers and acquisitions. It’s a natural culling of the herd.
Ema
So bigger companies might start buying up smaller AI startups to get their hands on their technology and talent? And investors might start combining several smaller companies to build a more comprehensive AI platform? That sounds like the market starting to mature and organize itself.
David
That is the prevailing theory. The background to today's AI frenzy is a story of explosive, hype-driven growth in 2024, followed by a predicted shift to more disciplined, profit-focused investment in 2025. It's a market in transition, moving from pure potential to practical application.
Ema
And this transition is where the conflict really lies. The clash between the sky-high valuations and the often-unprofitable reality of these companies. It's a tug-of-war between the dream of a trillion-dollar market and the hard-nosed reality of building a sustainable business. That's the conflict we need to explore next.
David
Yes, this sets up the central conflict perfectly. On one side, you have the believers who see a technological revolution in the making. On the other, you have the skeptics who see a financial bubble inflated by hype and cheap capital. Let's delve into that conflict.
Ema
It's the ultimate debate: is this the next internet or the next tulip mania? Let's break down the arguments. What's the core evidence for the side that says, 'Yes, this is a bubble, and we should all be very cautious'? What are they pointing to?
David
The primary piece of evidence for the skeptics comes from a rather sober source: corporate balance sheets. A recent, very extensive survey from McKinsey provides some compelling data. While AI adoption is high, the financial impact for most companies is, to put it mildly, underwhelming.
Ema
So companies are using AI, but it’s not actually making them more money or saving them significant costs yet? That seems like a pretty big disconnect from the multi-billion dollar valuations we're seeing. It’s like owning a race car but never taking it out of first gear.
David
Precisely. The McKinsey report found that more than 80% of organizations say they aren’t seeing a tangible impact on their enterprise-level EBIT—that's Earnings Before Interest and Taxes—from their use of generative AI. Only 17% report that 5% or more of their EBIT is attributable to gen AI.
Ema
Eighty percent! That's a huge majority of companies basically saying, 'We're using it, but it's not really moving the needle on our profits.' That has to be a major point of concern for investors who are pouring billions into this space, expecting massive returns.
David
It is the crux of the skeptical argument. The value of AI, in theory, comes from rewiring how companies run. But the survey shows most companies haven't gotten there yet. Only 21% said they have fundamentally redesigned workflows as part of their AI deployment. The revolution isn't yet revolutionary for most.
Ema
But what's the other side of the argument? The believers must have a response to this. Are they saying the profits are just around the corner, or is there something else we're missing? You don't get an $18 billion valuation based on hope alone, do you?
David
The counterargument is that looking at immediate EBIT impact is shortsighted. The proponents argue that the real story is in the deep, structural changes that are just beginning. The McKinsey survey itself supports this, showing a strong correlation between CEO oversight of AI governance and higher self-reported bottom-line impact.
Ema
So, when the boss is directly involved, the results are better? That makes sense. It suggests that AI isn't just an IT project; it's a fundamental business strategy shift. The companies that treat it that way are the ones starting to see the value. It's about deep implementation, not just superficial use.
David
Exactly. The argument is that we are in the early stages of a massive rewiring of the corporate world. The survey shows 78% of organizations are now using AI in at least one business function. That's up from just 55% a year earlier. The adoption is happening incredibly fast. The value will follow.
Ema
It's an argument about leading versus lagging indicators. The adoption rate is a leading indicator, suggesting future value. The profit impact is a lagging indicator, reflecting past performance. The conflict is about which one you choose to believe in more strongly right now. It's a bet on the future versus the present.
David
Another point of conflict is around risk. Skeptics point to the 47% of organizations that have experienced at least one negative consequence from gen AI use, such as inaccuracy or cybersecurity issues. This highlights the immaturity and potential dangers of the technology, adding another layer of risk to the investment.
Ema
But the believers would argue that this is normal for any new, powerful technology. Of course there are risks to be managed. The important thing is that organizations are actively starting to manage them. The report shows they are focusing on inaccuracy, cybersecurity, and intellectual property infringement. That's a sign of a maturing industry.
David
Then there's the conflict over jobs. What will this do to the workforce? Here, the picture is very murky. A plurality of respondents in the survey, 38%, predict that gen AI will have little effect on the size of their workforce in the next three years. This counters the narrative of mass unemployment.
Ema
But it's not a universal view. In financial services, for example, they are more likely to expect workforce reduction. And certain job functions, like service operations and supply chain management, are seen as ripe for headcount decreases. Meanwhile, IT and product development are expected to grow. It's a story of displacement, not just destruction.
David
This displacement creates another tension. Organizations are hiring for new AI-related roles while simultaneously reskilling their existing employees. This is a massive, costly, and complex undertaking. The conflict is whether companies can manage this transition effectively enough to realize the promised productivity gains.
Ema
So, to summarize the conflict: we have a clash between massive valuations and minimal current profit impact. We have a debate between seeing growing AI adoption as a sign of future value or seeing the lack of workflow redesign as a sign of superficial hype. And we have deep uncertainty about the ultimate impact on jobs.
David
That's a very accurate summary. It's a battle of perspectives. Are you a skeptic focusing on the 80% of companies not seeing EBIT impact, or a believer focusing on the 78% of companies rapidly adopting the technology? Both are valid data points from the same reality.
Ema
This really brings us to the core of it. What is the actual impact of all this? We've talked about the money and the debate, but how is this AI boom affecting the world right now, and what are the potential consequences, both good and bad? That seems like the next logical step.
David
Indeed. The impact is the ultimate test. Does this AI investment cycle actually produce tangible, lasting change, or does it fade away like so many bubbles of the past? Let's explore the current and potential future effects of this AI gold rush.
David
Let's talk about the real-world impact. One of the most compelling arguments that this isn't just a repeat of the dot-com bubble is how deeply AI is already being integrated into core business strategy. It's not just a fringe experiment; it's a central focus for the world's most influential companies.
Ema
How can we see that? Is there evidence beyond just the investment numbers? It's one thing to throw money at something, it's another for it to fundamentally change how you operate. What does that deep integration actually look like on the ground?
David
A fascinating piece of evidence comes from an unexpected source: a newsletter. There's a publication called Silicon Sands News, which is aimed at investors and executives in the AI and deep tech sectors. Its subscriber list tells a powerful story about the impact of AI.
Ema
A newsletter's subscriber list? That sounds like a very specific detail. What's so special about it? Who is reading this, and what does it tell us about the industry? I'm intrigued by this line of reasoning. It feels like a clue hidden in plain sight.
David
The readership includes senior figures from top venture capital firms like Sequoia Capital and Andreessen Horowitz, and from tech giants like Apple, Amazon, NVIDIA, and even OpenAI itself. It has approximately 35,000 industry leaders as subscribers across 113 countries.
Ema
Wow, okay. So, the people who are building, funding, and running the biggest tech companies in the world are all paying close attention to the same AI-focused analysis. That’s not a casual interest. It signals that AI is a top-level strategic priority across the entire industry. It’s required reading in the corridors of power.
David
Precisely. This is fundamentally different from the dot-com era, where many established, non-tech companies were skeptical or slow to adapt. Today, the biggest and most powerful players are not just participating; they are leading the charge. This creates a much more stable and integrated foundation for growth.
Ema
That makes a lot of sense. If the biggest ships are all turning in the same direction, it's less of a bubble and more of a fundamental shift in the current. The impact isn't just on startups, but on the very fabric of the existing tech and investment world. It's a systemic change.
David
Another major impact is the framing of the discussion itself. The author of that newsletter, Dr. Seth Dobrin, explicitly states his goal is to quantify why the current AI investment cycle is 'fundamentally different' from past cycles and is 'not (yet?) in a bubble.' The industry is actively trying to learn from history.
Ema
That’s a proactive and self-aware stance. It's like the market has a memory. Instead of blindly rushing forward, there's a conscious effort to analyze and understand the differences between now and the late 90s. This self-reflection could be a critical factor in preventing a catastrophic crash. It's a sign of maturity.
David
It suggests that the current boom is built on a more analytical foundation. Investors and companies are asking the hard questions from the outset. This has a direct impact on how projects are funded and how companies are built, likely leading to more resilient business models than those we saw in the dot-com era.
Ema
So the impact is not just financial, it's also intellectual. It's changing how the industry thinks about growth and innovation. But what about the broader economic impact? Are we seeing any signs that this AI investment is starting to affect the economy as a whole, beyond just the tech sector?
David
The broader economic impact is still in its early stages, but the projections are significant. Some econometric models are now being built based on AI investments to forecast economic growth, suggesting they could be a better predictor than traditional models. This indicates that AI is becoming a fundamental economic variable.
Ema
So economists are starting to treat AI investment like they treat other major economic indicators, like housing starts or manufacturing output? That's a profound shift. It means AI is no longer just a sector of the economy; it's seen as a driver of the entire economy.
David
Yes, and the potential impact on labor productivity is a key part of this. While the direct employment effects are still being debated, AI investments have shown a positive correlation with growth in labor productivity. Firms are reworking their labor demands, augmenting human capabilities rather than simply replacing them.
Ema
That's a more optimistic take on the jobs question. The impact might be less about the number of jobs and more about the productivity of each worker. An employee armed with powerful AI tools can generate more value, which in turn drives economic growth. That's a powerful and positive feedback loop.
David
However, the impact is not without its challenges. There's a concern that the development and deployment of AI technologies might become concentrated in just a few massive companies. This could stifle competition and lead to a 'bubble burst' scenario if those few companies falter, flattening economic growth.
Ema
That's the big-picture risk. The impact could be enormous, but it could also be fragile if it's all concentrated in a handful of players. This brings us to the future. What does the road ahead look like? How do we harness this incredible potential while navigating the very real risks?
David
Looking to the future, one of the most significant trends is the shift from the cloud to the edge. The Edge AI hardware market is projected to grow from about $26 billion in 2025 to nearly $59 billion by 2030. This is a massive expansion of where AI will operate.
Ema
From the cloud to the edge... can you explain what that means? For someone who's not deep in tech, that sounds a bit abstract. What does an 'Edge AI' future actually look like for us in our daily lives? Where will we see it?
David
Certainly. Think of it this way: cloud AI is when your phone sends data to a massive, distant data center to get an answer. Edge AI is when the device itself—your phone, your car, your watch—has the processing power to do the AI task locally, without sending data far away.
Ema
Ah, I see. So it's about making our devices smarter and more independent. This would be faster and more private, right? Since your data doesn't have to travel to the cloud and back. This could enable things like real-time augmented reality or smart medical devices that analyze data on the spot.
David
Exactly. This trend is driven by the demand for real-time processing and is synergistic with 5G connectivity. The future will see a miniaturization of powerful AI chipsets embedded in everything. This is crucial for industrial automation, healthcare, and enhancing data security and privacy by keeping information local.
Ema
That sounds like a much more distributed and resilient AI ecosystem, which might help with the concentration risk we just talked about. But what about the bigger economic picture? What does this AI-driven future mean for overall growth and prosperity? Are we on the cusp of a new economic boom?
David
The forecasts are incredibly optimistic. AI investments are expected to double the share of GDP growth compared to other capital investments between now and 2050. McKinsey estimates AI could increase global productivity by up to 40% by 2030. This is a transformative effect, akin to the steam engine or the internet.
Ema
A 40% productivity boost is a game-changer for the global economy. But it's not a given. There must be challenges ahead. What are the biggest hurdles we need to overcome to make this optimistic future a reality? What could stop this from happening?
David
The challenges are significant. There are concerns about the pace of innovation, the difficulty of upskilling the workforce, and the potential for malicious use of AI. There's also a need for new governance and regulations to handle issues of privacy, bias, and safety, especially with powerful generative models. The future is bright, but the path is complex.
Ema
So, we have a market buzzing with incredible valuations, echoing past bubbles but with fundamental differences. The investment is shifting from foundation to application, and the debate rages on about whether the value is real or just hype. The impact is already being felt, and the future promises massive change.
David
That's the end of today's discussion. The AI fundraising boom is a story of immense opportunity coupled with significant risk. Thank you for listening to Goose Pod, 老张. We hope this deep dive has given you a clearer picture of this fascinating and complex topic. See you tomorrow.
