Nvidia According to Dan Ives скачать в хорошем качестве

Nvidia According to Dan Ives

Book a call with me to grow your business with YouTube - https://calendly.com/ikostiy03/dc Gain lifetime access to my AI course - https://ailcourse.replit.app/?channel=d I'm looking for UK AI Companies to partner with - Email [email protected] I generated 45M views + helped businesses generate $100k's from YouTube in 2024 Follow me on twitter -   / davidcarbutt_   Contact me here for business or sponsorships opportunities - [email protected] This accountant saved me a fortune. If you're in the UK, book a call with Ben for accounting or bookkeeping. https://calendly.com/donnellanbouchie... Want to join a private stocks group? Click here -https://www.fejeremy.com/2024-app-plt... 📖 Reccomended Palantir Substacks Arny Trezzi - https://arnytrezzi.substack.com/ Either Square - https://eithersquare.substack.com/ Dan Ives just pulled the curtain back on Google’s AI hype — and he did not hold back. While Gemini 3 exploded across the internet, topping benchmarks in coding, math, and reasoning and triggering a full Code Red inside OpenAI, Dan argues that most people are missing the real story. Yes, Google’s generative AI momentum is real. Yes, Gemini 3 is impressive. And yes, Google’s TPUs give them a vertically integrated AI stack that looks terrifying on paper. But according to Dan, the AI revolution is still Nvidia’s world — and everyone else is just paying rent. The hype has convinced many investors that Google is running away with AI. But chips are a completely different battlefield than models. Nvidia still controls roughly 90% of the data center AI chip market, and the gap isn’t even close. In Dan’s words, there is one godfather of AI hardware — Jensen Huang. Nvidia isn’t just winning on market share; it’s winning on reliability, maturity, and execution. Every serious AI company knows that if their core product depends on AI, Nvidia is the safest bet. Innovation in AI is ruthless. A tiny performance edge can decide winners, and that requires hardware you can trust at scale. Nvidia has already paid the price of years of trial and error. New chip efforts — even from trillion-dollar companies like Google and Amazon — are still learning lessons Nvidia mastered long ago. Dan estimates Nvidia is at least four years ahead of any serious chip competitor, and in AI time, that’s an eternity. Even though Google’s TPUs are improving rapidly, they’re still largely internal tools rather than industry standards. Despite massive supply shortages, very few companies are actually switching off Nvidia. And that’s the key risk for Google: once Nvidia scales supply, it only gets harder to displace them. Right now, demand for AI chips exceeds supply by roughly 12 to 1. That imbalance implies three to four trillion dollars in AI compute spending alone over the next few years. Add enterprise software, consumer applications, and downstream services, and total AI spending could easily exceed ten trillion dollars. Even if those estimates are optimistic, one thing is clear — AI is not a bubble. It’s infrastructure. It’s foundational. And it’s accelerating. Dan rejects comparisons to the dot-com bubble outright. The demand is real, the spending is real, and the use cases are multiplying. Every company wants its own proprietary AI, trained on its own data, customized for its own workflows. That means the demand base is shifting from a handful of hyperscalers to nearly every enterprise on Earth. And that shift overwhelmingly benefits Nvidia, which still owns the hardware layer powering almost all AI training and inference today. Google’s progress shouldn’t be dismissed. Gemini 3 proves how far they’ve come since Bard, and their ecosystem integration is the cleanest in the market, especially compared to Copilot’s confusion and Apple Intelligence’s struggles. But competing with Nvidia means competing with the backbone of the entire AI economy. Nvidia isn’t assisting the AI revolution anymore — it’s powering it. Most AI chatbots, images, videos, and models you interact with today were built on Nvidia GPUs. Dan believes Nvidia’s recent growth is just the beginning of the next leg of its story. If a multi-trillion-dollar industry is being built almost entirely on your hardware, the upside doesn’t disappear overnight. Big tech remains the dominant force in markets, and every new AI use case becomes another tailwind. The only people missing out are those waiting for AI to collapse instead of understanding what’s actually being built.