Here is @Jukka_Lepikko’s tweet about Nvidia and its P/E ratio.
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Nvidia CEO Jensen Huang will deliver a keynote speech at CES 2026 in Las Vegas today, January 5, at 11 p.m. Finnish time.
The keynote is scheduled to begin at 4 p.m. ET on Monday, Jan. 5. You can watch a livestream on CNET’s YouTube page,
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Nvidia plans to test a robotaxi service with a partner as early as next year; the partner was not disclosed.
Robotaxis would use Level 4 driving, meaning the car can drive without a human, but only in pre-defined areas.
Nvidia sells Drive chips and simulation software for cars; additionally, the company states that Mercedes-Benz models in late 2026 will utilize the technology, at least for urban driving. The goal is to grow into a player similar to Waymo.
CEO Jensen Huang says that robotics is the company’s most important area after AI. 
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Nvidia also announced a new “memory platform” for AI based on BlueField-4. As language models grow very large, they accumulate a lot of background memory (KV cache), and it cannot be kept on the GPU indefinitely without slowing things down. The idea is to move and share that data quickly between different servers so that GPUs can focus on computation.
Nvidia claims that this results in up to 5x better energy efficiency and 5x more tokens per second. Coming later this year.
Nvidia’s own materials are here:
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A little sneak peek at Nvidia’s robotaxi.
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Arbe was mentioned among others here on Nvidia’s website “NVIDIA Expands Global DRIVE Hyperion Ecosystem to Accelerate the Road to Full Autonomy”
Leading companies including Astemo, AUMOVIO, Bosch, Magna, Quanta and ZF Group announced they are building DRIVE Hyperion-based electronic control units.
AUMOVIO, along with Aeva, Arbe, Hesai, Omnivision and Sony, are also among the latest partners to qualify their sensor suites on the open, production‑ready DRIVE Hyperion architecture. This growing sensor ecosystem spans cameras, radar, lidar and ultrasonic technologies that enable automakers and developers to build and validate perception systems optimized for level 4 autonomy.
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Nvidia CFO Colette Kress estimates that demand for data center chips will exceed the previous $500 billion revenue forecast by the end of this year.
Demand has thus increased even further since the original estimate, fueled by the AI boom. At the same time, the company is awaiting licensing decisions from the U.S. government to continue shipments to the Chinese market, where the licensing process remains ongoing, although authorities are reportedly working on the matter.
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Nvidia has appointed Alison Wagonfeld as its Chief Marketing Officer (CMO), who joins from Google after nearly ten years.
The recruitment clearly supports Nvidia’s goal to expand from a mere chip manufacturer into a comprehensive AI platform. Wagonfeld will report directly to CEO Jensen Huang and is expected to strengthen the company’s marketing and global communications during this AI transition phase.
Wagonfeld said she was excited to move “from one AI leader to another” and noted that Google and Nvidia remain close partners, with continued collaboration expected.
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Significant price hikes for memory this year, data centers are driving demand and it’s visible more broadly:
https://x.com/Bloombergtrader/status/2009409275169313170
Is this also a bottleneck for the implementation of planned investments?
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A bit of a repeat here, partly. The linked article reports that Jensen Huang revealed at CES that the company’s new Rubin architecture has entered full production six months ahead of schedule.
According to the article, the new generation of AI chips is significantly more powerful than its Blackwell predecessor, offering, among other things, tenfold savings in computing costs.
The early release addresses the dire capacity shortage of cloud giants, and the text emphasizes that it strengthens Nvidia’s market leadership as demand continues at record highs this year as well.
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Nvidia and Eli Lilly are jointly investing $1 billion in a new research lab in San Francisco.
The idea behind the lab is to use AI and high-performance computing to discover and develop new drug candidates even faster in the future. The funding will be spent over five years on various equipment, as well as computing capacity and talent.
Work is expected to begin in the early part of this year, and this “project” continues the companies’ previous collaboration. I don’t know how big of a deal this is for Nvidia, but it’s at least interesting and one example of Nvidia’s capabilities & the opportunities it creates.
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China is preparing rules to limit the purchase quantities of foreign AI chips, such as Nvidia’s high-end models.
The intention is, of course, to support domestic manufacturers while simultaneously allowing limited imports. Chinese companies still need Nvidia’s H200 chips, at least for now, and can indeed buy them, but in the future, purchases will require justification as well as regulatory approval.
The United States said this week it would allow sales of Nvidia’s advanced H200 AI computing chips to China. Demand for the chips remains strong among Chinese technology groups, including Alibaba (HK:9988) and ByteDance, the report said.
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According to the news below, deliveries of Nvidia’s H200 chips to China are stalling because the country’s customs are not allowing new “AI chips” into the country, and consequently, component suppliers have put production on ice. Chinese firms have also been warned against buying chips “unnecessarily,” and no clear reason has been provided; furthermore, there is no information regarding the duration of the ban or whether it is merely temporary or permanent.
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