Anton Voichenko’s Post

A $500 billion hole in the AI market. So what should we do about it? Corporations and startups are investing huge amounts of money in infrastructure to develop their AI services. It is a fact. How much should these AI services earn to recoup their costs? After all, this is not all done out of love for art; business must bring in money. David Kahn from the Sequoia Foundation tried to answer this question. He made his first calculations in September last year (https://lnkd.in/dUa5QtMk). You can read the details, as he believed, at the link. In short, he took the publicly known costs of chips, added electricity costs, threw in a pinch of company margins, and the result was... $200 billion. Yes, that’s how much all AI companies and AI services of corporations, like Google, should earn per year and Microsoft to recoup the investment. The problem is that he only counted $75 billion in revenue. Where is the other $125 billion? This is the main mystery. About nine months passed and David decided to repeat his calculations (https://lnkd.in/dHFF7R8u). And this time it turned out that in the fourth quarter of this year, the annual revenue of AI companies and services should already be $600 billion. This is ideal. But here, as you understand, we have a problem again. Yes, OpenAI itself has significantly increased its revenue, others have caught up. But Kahn counted only $100 billion in revenue. That is, the hole has reached $500 billion! One could argue that they are investing in infrastructure for a long time, so they can fight back for a long time. Kahn writes that he partly agrees. But there are nuances. Chips lose value quite quickly because new, more efficient ones appear. Plus, great competition forces services to reduce prices to the limit. The conclusion is simple - not all companies will survive this hype around AI. And investors will simply burn their money by betting on the wrong player. But this is a necessary evil with such large-scale changes in the market. But for the founders, as Kahn writes, everything is not so bad. They will accumulate experience and create better AI products. #productmanagement #management #marketing #customerservice #hr #hiring #UX #startup #web3 #tech #growth #digital #Growthhacking #projectmanagement #blockchain #UI #startup #fintech #agile #edtech #business #leadership #analytics #Productdevelopment #design #iot #ai #researchanddevelopment

Creating Economic Value in a Dynamic AI Landscape 🚀 🌕 There is a widening gap -- now $600B in annual revenue -- between infrastructure investment and revenue realization. 💵 OpenAI leads in revenue, while other startups struggle to scale, and as GPU computing commoditizes and competition intensifies, startups must differentiate with meaningful, consumer-centric innovations. So how? 🛂 Emphasis on delivering tangible consumer value is critical. Each AI startup must articulate its value proposition and expected use case clearly to bridge this gap effectively. 📈 Long-Term Vision: amidst speculative hype, focus on sustainable growth and economic impact. #AI #Startups #EconomicValue #Innovation #FutureOfWork

Sequoia recently published a blog post about AI's $600B problem. Read the original piece: https://lnkd.in/eCxC2Z-i “Winners vs. losers: I think we need to look carefully at winners and losers—there are always winners during periods of excess infrastructure building. AI is likely to be the next transformative technology wave, and as I mentioned in the last piece, declining prices for GPU computing is actually good for long-term innovation and good for startups. If my forecast comes to bear, it will cause harm primarily to investors. Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation. “

A very interesting analysis about the AI landscape : “I think we need to look carefully at winners and losers—there are always winners during periods of excess infrastructure building. AI is likely to be the next transformative technology wave, and as I mentioned in the last piece, declining prices for GPU computing is actually good for long-term innovation and good for startups. If my forecast comes to bear, it will cause harm primarily to investors. Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation.” “In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.” https://lnkd.in/gDqq2iS6

David Cahn's "AI’s $600B Question" raises a valid concern: a $600B gap between AI infrastructure investment and revenue growth. While the numbers are staggering, this gap reflects a typical early-stage disruption cycle—think cloud or mobile in the early 2000s. We're at the infrastructure build-out phase of the AI revolution, and commercialization is still catching up. Yes, Nvidia dominates, and OpenAI’s revenue surge to $3.4B is impressive, but they’re just the tip of the iceberg. The commoditization of GPU data centers, far from being a cause for concern, will democratize access and fuel a new wave of AI-driven startups. Lower barriers to entry will lead to exponential innovation—just as we saw with cloud services that gave birth to tech giants like Uber and Airbnb. The $600B question, then, is less about an unsustainable gap and more about the size of the opportunity ahead. We’re poised for massive value creation across industries—healthcare, finance, customer service, and beyond. The current infrastructure overspend? It’s a necessary catalyst for a decade-defining transformation. The real challenge? Building scalable AI products that deliver tangible value to end users. Those who do will help close the gap and lead the next tech wave. The road is long, but the potential ROI on these investments is undeniable. #AI #VC #Growth

AI’s $600B Question Great analysis: According to Sequoia, $600B (yes, that's Billion with a "B") in AI revenue is required to justify capex spent on AI hardware. That's a pretty big hole, and it's hard to see how it will be filled anytime soon ... "Speculative frenzies are part of technology, and so they are not something to be afraid of. Those who remain level-headed through this moment have the chance to build extremely important companies. But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs. " It reminds me of that infamous stat that startups spend almost 40 cents of every VC dollar on Google, Facebook, and Amazon. I wonder if we will get an equivalent here?

Sequoia Capital's key message: it's time to build the application layer of AI. Let's put this amazing infrastructure to work - for real people "For startups, the takeaway is clear: As a community, we need to shift our thinking away from infrastructure and towards end-customer value. Happy customers are a fundamental requirement of every great business. For AI to have an impact, we need to figure out how to leverage this new technology to make people’s lives better. How can we translate these amazing innovations into products that customers use every day, love and are willing to pay for? The AI infrastructure build out is happening. Infrastructure is not the problem anymore. Many foundation models are being developed—this is not the problem anymore, either. And the tooling in AI is pretty good today. So the $200B question is: What are you going to use all this infrastructure to do? How is it going to change people’s lives?" https://lnkd.in/gzaEDT9y

Where’s $500 Billion, Carl? 🤨 Hey folks! Sequoia Capital just dropped a bombshell on the AI world, and it's creating waves. Let’s break it down in simple terms. The Big Money Question Sequoia is asking the ultimate question: "Where is all the revenue?" They’re saying the projected revenue needed to justify AI investments is insane. We’re talking $200 billion at the end of 2023, skyrocketing to $600 billion by the end of 2024. 🫥 That’s a massive leap! What’s Happening in AI Land? 🐶 1. GPU Availability: The GPU shortage peaked in late 2023 but has now eased. Startups can get GPUs more easily with shorter lead times. 2. Cloud Providers Stockpiling: Cloud giants like Microsoft have heavily invested in GPUs, driving historic levels of CapEx. They're stockpiling GPUs, indicating a commitment to AI development. 3. OpenAI still has the lion’s share of AI revenue: OpenAI’s revenue jumped from $1.6 billion to $3.4 billion in a year. But other startups are lagging, with most making less than $100 million. 4. The $125B hole is now a $500B hole: Even with giants like Google, Microsoft, Apple, and Meta, there's a massive gap in projected AI revenue. They might bring in $10 billion annually, and other companies like Oracle and Tencent add a bit more, but we’re still far from $600 billion. 5. NVIDIA B100 Chip Excitement: NVIDIA’s new B100 chip promises 2.5 times better performance than the H100 for only 25% more cost. This means even more spending on these new chips, pushing investments higher while the actual returns remain uncertain. Sequoia’s Forecast Sequoia warns that many AI investments might go up in smoke 🚬 It’s tough to pick winners, but losers? They’re easier to spot. The hype is real, but so are the risks. AI might not deliver the massive returns everyone is hoping for, at least not as quickly as expected. There’s enormous potential but also significant financial risks. #Artificialintelligence

𝐈𝐬 𝐭𝐡𝐢𝐬 𝐀𝐈 𝐦𝐚𝐝𝐧𝐞𝐬𝐬, 𝐡𝐲𝐩𝐞 𝐨𝐫 𝐰𝐡𝐚𝐭…… Startup CoreWeave, specialized in GPU computing in the cloud has secured a 💲1.1 billion in new funding. According to Crunchbase data they have now raised a total of 4.6 billion💰💰💰💰 According to a news release: “Organizations of every size and industry are racing to deploy larger-scale AI solutions and capabilities – driving explosive demand for powerful and scalable infrastructure. “ 👉 https://lnkd.in/dzvedqTB I am not so sure about that statement, I see many organizations still struggling with there basic data. Getting proper product master data or customer data to even start with #datascience, euuhm I mean #AI. Or having issues to deploy a simple random forest model. Will coreweave ever become profitable? Investors have put 4.6 billion into the company. You can spin up GPU’s for around $ 2.50 an hour. That would mean companies have to spent more than 210.000 years on Coreweaves’s GPU’s in the cloud to earn back that investment, ignoring all other costs…… #AIbubble…. #TulipMania

🚀 Just came across this mind-blowing (and super straightforward) AI manifesto from Sequoia: https://lnkd.in/dTiPysVf. Too busy to read? Here’s the TL;DR: "Where’s the money, Lebowski?" 💸 Sequoia’s blog shows (with a killer chart) that AI’s revenue potential is skyrocketing every quarter. By Q4 2023, it was $200B. For Q4 2024? A whopping $600B! And a trillion per quarter isn't too far off. These Net Revenues are what we're hoping to see from AI to justify the massive infrastructure investments. FYI, this will soon outpace all current VC dry powder available for investments. What has Sequoia noticed in just 10 months since September 2024? 👀 - GPU resources became more accessible - Cloud providers have plenty of GPU "fat" for everyone - OpenAI's growth is off the charts – from $1.6B ARR at end of 2023 to $3.4B now. But a cliff might be ahead 🪂 – only a few startups hit $100M in sales, none close to OpenAI’s level. - There’s a $600B revenue gap: Google, Microsoft, Apple, Facebook might generate ~$10B/year in AI-related revenue. Add another ~$5B each from Oracle, ByteDance, Alibaba, Tencent, X, and Tesla... maybe we get $100B globally. So where's the other $500 billion? Wait for it... NVIDIA plans to launch the B100 chip (2.5x better than H100 at just 25% higher cost). This means even MORE spending on B100 (since VC cash is plentiful for AI companies but not their Net Revenues). Sequoia's big takeaway: Investments in AI will largely go up in smoke (typical of hype cycles), except for standout performers like OpenAI and a handful of other $100M+ startups. 🔥 It’s tough to pick winners but way easier to spot losers… 🔥 #AI #TechTrends #Investment #SequoiaInsights