The highest analyst updates the NVIDIA price goal for one surprising reason, initially appeared in TheStret.
Nvidia (NVDA) He pulled the wider vibrations of the market and became one of the biggest winners of the market this year.
Its ubiquitous GPU was a golden standard when feeding AI breakthrough, making it necessary for Chip shares to investors.
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In addition, despite the fact that it has reached record heights this year, a lot of gas is still left in the NVIDIA tank.
Looking forward, he is preparing to release his next generation GPU system, separating further in the data center space.
If everything goes according to plan, the grip of the Chip King to Ai can be tightened, and with fresh approval, the runway looks long.
It is honest to call the NVIDIA GPU series a line of revolutions, each chip line spent on the last mile of the country.
It started with an ampere, a huge step for wool and a raised tensor core. The Ampere was a smashing Hypercalers hit, looking at everything from recommended engines to early AI concept evidence.
Then we had a Hopper. NVIDIA is packed in a special transformer engine, increased NVLink speed and adjusted its chips so that LLM could train faster without pressing the budget.
Hopper Cemented Nvidia point as the best dog, both in research laboratories and mega scales in data centers.
Another appeared in Blackwell Ultra, which turned the game using a smarter data processing, faster memory and methods to reduce retardation.
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Suddenly we saw that the generative AI came with real -time videos, large modeling and instant data.
There is now a Rubin of Blackwell’s successor, who claims to be 3.3 × faster. This leap is not a regular clock speed bump, but that means you can include more AI workload at the same stop.
Its new generation of tenzor core, high -level memory interface and liquid -cooled design allow companies to run several models simultaneously.
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Rubin is smoothly associated with the mature Nvidia Cuda ecosystem, where each library, tool chain and optimization received a lift.
For AI teams, this means shorter training cycles, denser conclusions and freedom at the same time experiment with more complex models.
If everything lives up to the hype, Nvidia will once again prove why it is an indispensable engine behind the AI revolution.