#cryptotechshift

cryptotechshift

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Ziņas nosaukums: Vai mākslīgais intelekts ir tavs "slepenais ierocis" tirdzniecībā? 🤖🦁
Ziņas teksts:
Krypto pasaule strauji mainās, un tie, kas neseko tehnoloģijām, paliks aiz muguras! 🚀
Šodien es pētniecībā izmantoju Binance AI aģenta jaunas prasmes akadēmijā. Patiesība ir tāda, ka mākslīgais intelekts vairs nav tikai greznība, bet ir obligāts rīks katram gudram tirgotājam un investoram.
Kā mākslīgais intelekts mainīs tavu ceļu?
🎯 Datu analīze: Tūkstošiem candlestick analīze sekundēs.
🎯 Laika taupīšana: Precīzu atbilžu saņemšana uz sarežģītiem jautājumiem, nevis stundām ilgs meklējums.
🎯 Gudrā mācīšanās: Palīdz atklāt jaunas prasmes (tagad pieejamas 13 jaunas prasmes!).
Kā "sirds lauva" saturu radītājs, es redzu, ka patiesā vara slēpjas "mākslīgā intelekta" un "cilvēka prāta" kombinācijā. Mēs esam jaunā laikmetā, kur ieguldījumi ir gudrāki! 🦁🔥
Mans jautājums jums:
Vai jūs jau esat sākuši izmantot mākslīgo intelektu savos ieguldījumu lēmumos? Vai joprojām dodat priekšroku tradicionālajai manuālajai analīzei? Dalieties ar savām domām komentāros! 👇#BinanceAI #AITrading #BinanceSquare #الذكاء_الاصطناعي #CryptoTechShift $BTC $ETH $BNB

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Skatīt tulkojumu

THE GREAT AI SHIFT HAS STARTED — AND NO ONE IS READY FOR WHAT COMES NEXT The biggest move in the AI world isn’t happening in a lab — it’s happening in the hardware stack. And the signal just became impossible to ignore. OpenAI, the same company that helped turn Nvidia into a multi-trillion giant, has begun running ChatGPT inference on Google TPUs. Not speculation. Not a leak. This is mid-2025 reality — and it’s shaking the entire AI industry. Why would OpenAI move away from the hardware that powered its rise? Simple: inference is where the real costs live. Training a model is a one-time burn. Inference is forever — every prompt, every token, every second. OpenAI’s 2024 inference bill crossed $2B+, while GPT-4 training reportedly cost a fraction of that. And Google’s TPUs? They deliver massive performance-per-dollar advantages, shifting the economics overnight. Midjourney did it. Anthropic is scaling on TPUs. Meta is negotiating billions. The smartest operators are all drifting in the same direction — away from Nvidia’s premium chips, toward Google’s cost-efficient silicon. Here’s what almost no retail investor is factoring in: By 2030, 75% of AI compute demand will be inference — not training. Nvidia built its empire on training workloads. But the future is an always-on inference world — and that is where Nvidia’s edge weakens. Meanwhile, institutional capital is moving early. Soros dramatically increased its Alphabet exposure. Berkshire made a multi-billion bet. While retail chases parabolic charts, big money is positioning for the next era of AI infrastructure. This isn’t a minor rotation. It’s a structural transition — the kind that only becomes obvious in hindsight. The AI hardware race is being rewritten, and the winners may not be the same giants who dominated the last cycle. Training was the old game. Inference is the new battlefield. And every shift in computing power eventually reshapes the broader digital economy — including crypto. As AI gets cheaper and more accessible, blockchain-aligned compute, decentralized AI, and digital assets built for machine-driven economies stand to gain in ways the market hasn’t even priced yet. The transition has started. Most people are not ready. #CryptoTechShift $BTC

THE GREAT AI SHIFT HAS STARTED — AND NO ONE IS READY FOR WHAT COMES NEXT

The biggest move in the AI world isn’t happening in a lab — it’s happening in the hardware stack. And the signal just became impossible to ignore.

OpenAI, the same company that helped turn Nvidia into a multi-trillion giant, has begun running ChatGPT inference on Google TPUs.
Not speculation. Not a leak. This is mid-2025 reality — and it’s shaking the entire AI industry.

Why would OpenAI move away from the hardware that powered its rise?
Simple: inference is where the real costs live.

Training a model is a one-time burn. Inference is forever — every prompt, every token, every second. OpenAI’s 2024 inference bill crossed $2B+, while GPT-4 training reportedly cost a fraction of that.

And Google’s TPUs?
They deliver massive performance-per-dollar advantages, shifting the economics overnight. Midjourney did it. Anthropic is scaling on TPUs. Meta is negotiating billions. The smartest operators are all drifting in the same direction — away from Nvidia’s premium chips, toward Google’s cost-efficient silicon.

Here’s what almost no retail investor is factoring in:

By 2030, 75% of AI compute demand will be inference — not training.
Nvidia built its empire on training workloads.
But the future is an always-on inference world — and that is where Nvidia’s edge weakens.

Meanwhile, institutional capital is moving early.
Soros dramatically increased its Alphabet exposure. Berkshire made a multi-billion bet. While retail chases parabolic charts, big money is positioning for the next era of AI infrastructure.

This isn’t a minor rotation.
It’s a structural transition — the kind that only becomes obvious in hindsight.

The AI hardware race is being rewritten, and the winners may not be the same giants who dominated the last cycle.

Training was the old game.
Inference is the new battlefield.
And every shift in computing power eventually reshapes the broader digital economy — including crypto.

As AI gets cheaper and more accessible, blockchain-aligned compute, decentralized AI, and digital assets built for machine-driven economies stand to gain in ways the market hasn’t even priced yet.

The transition has started.
Most people are not ready.

#CryptoTechShift $BTC

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