Jensen All In AI! “Compute Race” to Physical AI: Do You Spot These Highlights & Lists?
If CES 2026 can be summed up in one sentence, it’s this: AI is no longer just about stronger models—it’s truly entering the real world, forcing a full re-pricing of energy, compute, and infrastructure.
NVIDIA opened strong but closed weaker, suggesting capital markets weren’t fully satisfied. But don’t overlook this all-in-AI starting point. Let’s walk through the three biggest CES highlights.
1. From “Single-Card Performance” to “System-Level AI Supercomputing”: NVIDIA Rubin vs. AMD Helios
NVIDIA broke with its CES tradition of launching new consumer GPUs—and went all in on AI.
1) Rubin lifts data-center revenue expectations
If Blackwell pushed the limits of single-GPU performance, Rubin tackles the problem of system-scale deployment. It’s expected to launch in 2H 2026
Rubin delivers 5× inference performance and 3.5× training performance versus Blackwell
10× lower cost, already in mass production
The Rubin platform (including Rubin GPUs + Vera CPUs, six chips in total) will be deployed first by $Amazon.com(AMZN)$ AWS, $Microsoft(MSFT)$ Azure, $Alphabet(GOOG)$ Cloud, $Meta Platforms, Inc.(META)$, and OpenAI, before entering large-scale commercial adoption in the second half of 2026.
2) AMD: Helios takes a direct shot at data-center scale
$Advanced Micro Devices(AMD)$’s presence at CES was noticeably stronger than in previous years. Lisa Su unveiled the latest Helios AI computing rack, expected to launch later this year.
Helios isn’t trying to beat Rubin on “who’s faster.” Instead, AMD chose a different path: open architecture + scale, designed to absorb the compute demand of large models and AI agents.
Helios is AMD’s next-gen data-center rack platform for large-scale AI workloads. Built on the OCP open rack standard, co-developed with Meta
Each Helios rack includes 18,000+ CDNA 5 GPUs and 4,600 Zen 6 CPU cores; Delivers up to 2.9 ExaFLOPS of compute
2. Physical AI: Everything About Robotaxis and Robots
1) Autonomous driving: from “driver assistance” to “thinking systems”
NVIDIA officially launched its end-to-end autonomous driving AI, AlphaMayo—a system that can think and reason.
NVIDIA Drive AV software will debut in the new Mercedes-Benz CLA, delivering L2 end-to-end driving. In demonstrations, the vehicle completed route planning and driving with zero human takeover, successfully reaching its destination.
AlphaMayo = model layer
Mercedes-Benz = application layer
When it comes to smart driving, Tesla’s FSD rollout this year is also worth watching.
2) Robotics: the biggest “incremental narrative” at CES 2026
Even before CES, markets were buzzing about robots.
By integrating Omniverse simulation, synthetic data generation, and robot control models, NVIDIA is injecting AI capabilities from the cloud-based “soft world” into the physical “hard world”—cars, factories, and robots.
But $Qualcomm(QCOM)$ delivered the real surprise.
At CES Las Vegas, Qualcomm unveiled a next-generation full-stack robotics architecture, integrating hardware, software, and hybrid AI. Its goal: power everything from small home robots to full-size humanoids.
Qualcomm also launched its latest high-performance robotics processor—the Qualcomm Dragonwing™ IQ10 series. Its positioning is clear: turning robots from “able to move” into “able to work continuously.”
Other robots companies to look:
Robotics software: $PTC Inc(PTC)$, $PALLADYNE AI CORP(PDYN)$, $Mobilicom Limited(MOB)$
Industrial robotics: $Tesla Motors(TSLA)$ $Honeywell(HON)$ $Teradyne(TER)$ $Lincoln(LECO)$
3. When Compute and Physical AI Accelerate Together: Where Does the Power Come From?
U.S. nuclear stocks surged: $Nine Energy Service Inc.(NINE)$ +16%, $NuScale Power(SMR)$ , $Oklo Inc.(OKLO)$ +15%, $NANO Nuclear Energy Inc(NNE)$ +12%, $Energy Fuels(UUUU)$ +11%
Another key Rubin highlight: the architecture supports 45°C warm-water cooling, eliminating chillers and saving 6% of global data-center electricity usage. The stronger the emphasis on efficiency, the clearer it becomes that systems are approaching power limits.
The U.S. Department of Energy’s funding direction—and the collective rally in nuclear stocks—suggest this isn’t just short-term speculation. AI data centers are not cyclical demand; they are multi-year, continuously expanding infrastructure.
Questions to discuss
CES’s Three Big Themes: Rubin, Physical AI, and Power: Which investment opportunity do you like most?
Are you ready to all in on NVIDIA, or buying robots or nuclear stocks instead?
Is Qualcomm’s robotics pivot a signal for a stock re-rating?
Will 2026 be the breakout year for Tesla’s FSD + Optimus?
Leave your comments to win tiger coins!
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CES’s Three Big Themes: Rubin, Physical AI, and Power: Which investment opportunity do you like most?
Are you ready to all in on NVIDIA, or buying robots or nuclear stocks instead?
Is Qualcomm’s robotics pivot a signal for a stock re-rating?
Will 2026 be the breakout year for Tesla’s FSD + Optimus?
Leave your comments to win tiger coins!
In positioning, NVIDIA remains my core holding, but I’m not ignoring the second-order plays. Robotics is where expectations are still forming, and Qualcomm’s $Qualcomm(QCOM)$ full-stack push stands out as a possible re-rating catalyst as embodied AI scales.
On Tesla $Tesla Motors(TSLA)$ , I see 2026 as a potential inflection year. FSD is getting closer to true autonomy, while Optimus remains meaningful upside optionality. As AI moves into the real world, compute, robots, and power will be re-priced together—and that’s the framework guiding my exposure.
@Tiger_comments @TigerStars @TigerClub
therefore, better for me to wait, watch before doing anything [Serious] [Serious] [Serious]
The star of the show is Rubin, expected to be launched in 2H 26. Rubin is 10x lower cost yet delivers 5x inference performance and 3.5x training compared to Blackwell.
In Physical AI, NVIDIA launched its end to end Autonomous Driving AI - AlphaMayo, a system that can think and reason.
I am super excited at Nvidia's latest innovation and believe that NVIDIA has lots of exponential growth ahead.🥰🥰🥰🌈🌈🌈💰💰💰
魯賓交付5 ×推理性能和3.5 ×訓練表現對布萊克威爾
10倍成本更低,已量產
Qualcomm (QCOM.US) is actively attempting to pivot and capture growth from both Rubin (data center inference) and Physical AI (automotive, robotics). Its stock re-rating potential is tied to the successful scaling of these new ventures beyond smartphone chips .
Tesla (TSLA.US) embodies the Physical AI narrative, with 2026 poised as a critical year for validating its FSD and Optimus strategies. However, near-term financial performance and delivery growth face challenges, creating a divergence between its current automotive business and future tech valuation . Its energy business also ties it directly to the Power theme.
AI demand peaks post-training boom
Margins normalize
Growth slows
They are not modeling machines that work 24/7, never quit, and need constant compute refreshes.
Physical AI does not replace cloud AI. It extends it indefinitely.
That is why Jensen is not slowing down. He is accelerating.
Humans adapt. Robots break.
What changed is not hardware. It is foundational models + simulation + edge compute converging at once.
Nvidia now controls all three layers:
Training brains – massive GPU clusters
Teaching reality – Omniverse digital twins
Executing decisions – edge AI silicon
That stack did not exist before 2024. Now it does.
This is why Jensen is confident enough to say robotics will be the largest incremental AI market.
Not hype. Timing.