Aaron Ginn’s Post

Recently, the well-known venture capital firm #Sequoia Capital presented a forecast on investments in #AI projects and the expected returns. These numbers are impressive. According to Sequoia Capital, revenues from AI projects, which should justify investments in infrastructure, are growing at an incredible rate every quarter. If in the last quarter of 2023 they were $200 billion, in the last quarter of 2024 this figure will reach $600 billion, and then it could exceed a trillion per quarter. Also, in this report, Sequoia Capital reviews what happened in the first half of 2024: - GPU resources became more available. - Cloud providers accumulated significant GPU reserves for everyone who needs them. - OpenAI showed phenomenal growth: from $1.6 billion in annual recurring revenue at the end of 2023 to $3.4 billion in June 2024. However, Sequoia claims that a decline is ahead. Although they saw several AI startups with sales of less than $100 million, none of them come close to OpenAI in terms of sales, reaching only about $100 million. - Sequoia Capital estimates that the AI industry is short of $600 billion: in their opinion, Google, Microsoft, Apple, and Facebook together can generate $10 billion a year in AI-related revenue. Possibly, another $5 billion from each of the following: Oracle, ByteDance, Alibaba, Tencent, X, and Tesla. Even if all these companies together reach $100 billion, where will the remaining $500 billion come from? And that's not all: Sequoia Capital reminds us that NVIDIA is about to launch the B100 chip (with 2.5 times better performance compared to the H100 and only 25% more expensive). This means companies will start spending even more on B100, considering that AI companies have a lot of venture capital, unlike net profits. What does this tell us? It tells us that the hype around AI is reaching a new level, and the expectations from this level are simply enormous. This is not just like Bitcoin or even the tulip mania. Investments in AI (except for projects like OpenAI and a few others that can be counted on two hands) will largely not pay off. The hype will calm down a bit, until the next jump. Perhaps in the next wave, we will see #AGI?

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

Considering the current difficulty in buying / accessing reasonably priced AI focused GPUs this is particularly timely and welcome. Do you know anyone who could benefit from this programme? #AI #Startups #Innovation https://lnkd.in/ePJFBHDV

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

In the fast-evolving tech landscape, staying ahead requires not just innovation, but practical, actionable insights. Together with NVIDIA, Amazon Web Services (AWS), and TLV Partners, we invite you to an LLM Mastery event exclusively designed for #CTOs. The last couple of months proved that understanding and leveraging the latest in LLM and AI technologies can be the difference between leading the pack and playing catch-up. So.. mark your calendar for April 7th at 5 pm in Tel Aviv, and let's rumble 🚀 What’s on the Agenda? Gilad Gershon will kick things off with a deep dive into NVIDIA Inception for #Startups, offering a glimpse into resources and tools that can accelerate your tech venture. Amit Bleiweiss will follow, unraveling the capabilities of NVIDIA's #LLM tools for training and deployment, alongside insights into Resource Aggregation for Generative AI (RAG). And, who doesn’t love a good case study? 📓 Shahar Daniel from AWS will interview Itamar Friedman and Dedy Kredo the founders of CodiumAI exploring the journey of founding & building a technology that integrates advanced, non-trivial analysis within your coding environment utilizing their text-to-code solution on AWS cloud with Nvidia's #GPUs. Secure your spot here today → https://lnkd.in/dsqnkzKu And don’t say we didn’t warn you, spots are super-limited. Yasmin Lukatz I Noa Topaz I Dana Harel Tayer I Ravit Sasson I Jessica Hare I Shlomit Cohen I Karyn Priel I Liat Miller I Yaniv Benji I Noa Eilon

🚀 Fresh Buzz in the Startup Realm!  🌟 Inference.ai has successfully raised $4 million in its seed round! 💸💼 🚀 Inference.ai is tackling the global GPU shortage with smart algorithms that match companies' needs with available GPUs. This streamlines the process and cuts costs compared to other cloud providers. 💻💡 As the demand for AI applications skyrockets, Inference.ai's focus on helping companies acquire and use GPUs more efficiently couldn't come at a better time. 📈 This mitigates the ongoing shortage and ensures that businesses can access the computing power they need without breaking the bank. 💻💰 #cheers to Inference.ai for their commitment to advancing the AI revolution! 🥂 Follow us to get more updates and news from the world of Venture capital. 📰🌐 #InferenceAI #StartupFunding #AIRevolution #VentureCapital #TechInnovation #Canada #ALTVC #Tech #AI #Greeninnovation #Innovation

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

Thrilled to finally reveal the launch of FlexAI, led by the incredible Brijesh Tripathi and Dali Kilani, which just raised a $30M seed round to make AI compute infrastructure more efficient and accessible to everyone. Our investment thesis: 1. Strong macro-tailwinds - Compute for AI is a mature market with sustainable demand growth from new models over the next years - But the compute demand is already exceeding data center capacities and supply of GPUs, creating a supply constraint for Nvidia’s top units - AI model development is attracting large amounts of funding, much of which will be dedicated to computation and costs/performance will matter more and more. 2. The need for a European AI infrastructure - Compute power is high on the geopolitical agenda. Who will control AI will control the world. - European AI model companies rely today on US-based hardware and US-based cloud providers to build "European" AI models - If Data sovereignty and security matter, then there is an urgent need for a European AI compute platform 3. An exceptionally skilled team to build this European AI compute platform - Brijesh has built customized systems and hardware for AI use cases at NVIDIA and Apple before, and designed + scaled compute systems for autonomous driving at Tesla and Zoox, as well as with the Intel super-compute platform - Dali has a demonstrated track record of executing and delivering both hardware and software projects, and leading engineering teams (this is the second time we back him, not a coincidence!) - both have known each other for a long time and worked together at NVIDIA. have built GPUs themselves and were there when Apple and Tesla decided their launch their own chips for the exact same reasons (cost and performance trade-off + reduce dependency on third party suppliers). - They have already demonstrated the strength of their network by signing key partnerships even before product launch and have assembled Tier 1 advisors around FlexAI. Thrilled to be partnering with Alpha Intelligence Capital, Heartcore Capital , Elaia , Frst and Motier Ventures to build the AI compute infrastructure the world needs, made in Paris (with love). https://lnkd.in/e3aXXZSB cc Partech