Peter Gostev’s Post

NVIDIA is now fourth most valuable company in the world. Its valuation equals to half of India’s GDP. Goldman Sachs has called it most important stock on the planet. Artificial Intelligence has changed the fortunes of NVDIA in last 18 months, its chips are used to train the AI models. Demand is so high that it can’t keep up production. In Hisab Kitab I explain the NVIDIA phenomenon https://lnkd.in/gwuXyr5f

Hey everyone, I just read a compelling article on InvestorPlace about why NVIDIA could become a $5 trillion company. The author makes some thought-provoking points about their potential for growth in the AI, gaming, and data center markets. I highly recommend giving it a read and joining the conversation. #NVIDIA #GrowthPotential #InvestingOpportunity https://ift.tt/A4QjJfY

Here is the reason why AGI is arriving on a faster timetable.  Nvidia is outperforming Moore’s Law.  OpenAI’s first Nvidia GPU stack had .17 Petaflops.  We are going from fractions of a Petaflop to Exaflops.  1 Exaflop = 1,000 Petaflops Today, there are a handful of Exaflop supercomputers globally.  Now, Nvidia is selling Exaflop systems.  Two more years and those Exaflop systems will look obsolete.  The main constraint is having enough data to train these massive trillion parameter models.  Imagine an AI trained on all YouTube videos, the Library of Congress, and the World Wide Web.  Who wins that game? Long: Google

Yesterday, I had an engaging discussion about the AI market with my friend Mathieu. Like many others, his unique perspective focuses on the opportunities in Cloud-based AI and the significant GPU purchases by hyperscalers.  However, with model sizes downsizing and CPU+NPU+GPU advancements, Edge AI (or on-device AI) is becoming even more attractive. Just look at the recent announcements from Microsoft (Copilot + on ARM Qualcomm), Nvidia, and AMD to boost the PC/Laptop AI experience. Add some more security and privacy concerns, and we have a beautiful combo of triggers to pull that market off. 

OpenAI’s Sora requires approximately 12 minutes to generate a 1-minute video using the NVIDIA H100 GPU ☄️ A report estimates that around 89,000 NVIDIA H100 GPUs are needed to support the creator communities on platforms like TikTok and YouTube, considering the AI-generated video production. However, factoring in realistic utilization, peak demand, and high traffic, this estimate increases to about 720,000 GPUs. Additionally, creators often produce multiple video candidates before selecting the final version, further doubling the GPU requirements. For more details, check out https://lnkd.in/gYYnKAnb

Some say that R&D played a crucial role in NVIDIA rise. The compounding effect is real, even in R&D. Big Tech spends significant amounts on R&D to gain an edge. Without R&D, there is no future. Even if something sounds crazy, Just do it. One of my patents might sound crazy: In essence, it's a "ball bearing with rubber band properties." But in the coming 100 years, it will play a critical role in technology, whether we are on Earth, the Moon, or Mars. Sounds crazy? It is. Here’s how big tech is leading the patent war. The Big 3 are killing it 🔰Apple 🔰Microsoft 🔰Google But there is S𝗼𝗺𝗲𝗼𝗻𝗲 who does not have the numbers but is still killing the game? Remember, sometimes Quality > Quantity of Patents Who? Stay tuned for Part 3 of the series.....

With $NVDA becoming the second most valuable company in the world yesterday, I thought it worthwhile to lay out my thoughts both near-term and longer-term depending on your time horizon. My belief is that over the next 3-4 years, Nvidia revenues are likely to roughly triple from current levels with the stock roughly doubling. However, before year-end we may be near a digestion phase for the amounts spent on AI over the past 1 ½ years since the launch of ChatGPT in late 2022. My complete thoughts are below https://lnkd.in/gJb6ztNi

Over $250 billion has been added to Nvidia's market capitalisation following their earnings report last night. Their performance has lifted global stock markets. Good for Nvidia but the market appears to me to have not discounted the time lag factor and has assumed a straight line to AI success. For my part with regard to the diagnostic industry and the use of AI I think there has been a wilful ignorance with regard to the regulatory risk associated with introducing any new diagnostic product/service. I think the introduction of AI related diagnostics will increase both the complexity and cost of getting Regulatory Approval and I suspect the length of time required for approval. We live in interesting times. https://lnkd.in/eyn7iyAD

Get ready for an electrifying earnings season with Nvidia! 🚀 On Feb 21, we dive deep into Nvidia's groundbreaking achievements: a projected EPS of $4.56, revenues touching the sky at $20.3 billion, and a leap into AI that's reshaping our digital world. 🌐 Nvidia's journey from gaming to AI dominance shows no signs of slowing down. Wondering how to leverage this tech titan's earnings for your trading strategy? CMTrading offers a special $250 deal to get you started. Dive in and trade the future today! T&Cs apply. 🎯 https://lnkd.in/dAn9qFfs Use CMT250 at checkout. T&C apply.

Recently at SIGGRaph, the host asked an interesting question about Jensen Huang about Nvidia going up stack into software while Hyperscalers going down stack into chips. https://lnkd.in/ecetv8rK 11:27 Jensen gave an technically correct answer about Nvidia always being a software company but he actually dodged the question. You see, those same software insights are already being tackled by Hyperscalers (and AMD) as they not only build the chips but - as a prerequisite - also introduce an open source layer conceptually similar to CUDA so that that layer can organize the context so that the accelerated computing can happen at the chip level. So while what Jensen outwardly said about Nvidia being a software company insofar as CUDA is concerned is true, all things being equal, if he only stays at the CUDA layer and goes no further up stack, Nvidia will eventually stagnate. And he knows that. What we are really seeing is Nvidia going above the CUDA layer into NIMs - i.e specialized LLMs for e.g. Robotics - which have clients from established Robotics companies like Boston Dynamics to who's who in Robotics startups like Figure.ai. We are even seeing Nvidia going higher to the eventual AI app layer - witness OpenAI's DALL-E similar looking app and the Avatar app just to name a few. It's unclear whether Nvidia is using it only as proof of concept to demonstrate the power of its GPUs or as a gateway delving eventually into the App layer. I suspect its more the latter - potentially at least - as Jensen is keeping his options open. The main reason for holding back is that his main customers are the Hyperscalers but he is also well aware they eventually want to eat his lunch. Inside a fortune cookie: Avoid Strength, Attack Weakness: Striking Where the Enemy is Most Vulnerable... By holding out advantages to him, he can cause the enemy to approach of his own accord - Sun Tzu 😉