Nvidia
GPUs and full-stack computing platforms that power AI, gaming and data centres.
Public · NASDAQ:NVDA- Sector
- Semiconductors
- Based in
- Santa Clara, United States
- Founded
- 1993
- Invested
- 2019
Nvidia designs graphics processing units (GPUs) and the systems built around them. Its data centre chips, networking and rack-scale systems are the main hardware used to train and run large AI models, and its GeForce GPUs are a mainstay of PC gaming.
Much of Nvidia's advantage comes from software. CUDA, the programming platform it launched in 2006, lets developers use GPUs for general computing, and a large ecosystem of AI, scientific and graphics libraries has been built on top of it.
Nvidia was founded in 1993 by Jensen Huang, Chris Malachowsky and Curtis Priem, and Huang has led it ever since. It went public in 1999, the same year it introduced what it called the first GPU.
As of 29 Sep 2026
Why I own it
Nvidia makes the picks and shovels of AI. CUDA made its GPUs the default tool for machine learning, and that software ecosystem takes years to copy.
Every model trained and every query answered runs on compute, and demand is nowhere near its peak. Nvidia sells the whole system, from chips to networking to software, so it captures more of each dollar of the build-out than anyone else.
Then · 2019
Since I invested
- Held for
- about 7 years
- Status
- Active
- Share price, past year
- +20%
- In the notebook
- 1 note
Thesis check since 29 Sep 2026
5 developments support it, 0 challenge it
- SupportsCongratulations to our CEO @JensenHuang on receiving the National Medal of Science for advancing GPU computing to power
- SupportsThe new @Jaguar Type 01 is here, powered by NVIDIA.
- SupportsTSMC's Q3 result lands on 15 October
Checked against the thesis by Jev, an AI model. Can be wrong.
From the notebook
All notesComing up
TSMC's Q3 result lands on 15 October
TSMC reports third-quarter earnings on 15 October, Taiwan time, having guided revenue to $44.6bn-$45.8bn and flagged pressure on margins. That guidance reflects temporary pressure from 2-nanometer technology ramp-up costs, even as AI-driven orders keep volumes climbing. The call is the first real test of whether advanced-node demand from Nvidia, AMD and Apple is still outrunning TSMC's capacity to build it.
Since this note:TSMC −0.3%Nvidia −0.2%AMD +0.8%(S&P 500 +1.3%)
TSMC
AMDWritten by AI from share prices, the companies' posts and the news. Can be wrong; not financial advice.
Latest on X
@nvidia- Nvidia@nvidia · 9 OctCongratulations to our CEO @JensenHuang on receiving the National Medal of Science for advancing GPU computing to power scientific breakthroughs.
And to fellow honorees Elon Musk, Lisa Su, Michael Dell, Satya Nadella, and Sergey Brin.81397
- Nvidia@nvidia · 8 OctThe new @Jaguar Type 01 is here, powered by NVIDIA.
Under its stunning design is NVIDIA Hyperion, the computer and sensor platform that takes in everything the car sees and senses, then helps it make smart decisions in real time.
It’s paired with NVIDIA Halos, a safety system that covers everything from the chips to the software. Before reaching the road, Type 01's software passed 150,000 tests over tens of thousands of hours.
And with over-the-air updates, it’ll keep getting better long after it leaves the showroom.
Our own Ali Kani and Rishi Dhall joined the JLR team in New York to celebrate the reveal. Congratulations!
🔗 https://media.jlr.com/jaguar/en-us/news/2026/10/jaguar-type-01
8889827 - Nvidia@nvidia · 3 OctThank you to The Korea Society for honoring @JensenHuang with the 2026 Van Fleet Award and celebrating the U.S.–Korea partnership.
We’ve worked with Korea for more than 25 years, and we’re proud of what we’ve built together. Looking forward to what comes next.5962579
- Nvidia@nvidia · 2 OctUp to 8x faster, and now you know why ⚡️@openai GPT-6 Astra Ultrafast runs on NVIDIA
Read the story: https://nvda.ws/3W2bZ5H
107891K - Nvidia@nvidia · 1 OctWhat does “fungible” mean for AI infrastructure? The flexibility to run different workloads: every type of AI, every phase of AI and even workloads that aren’t AI at all.
One platform, built for maximum “productivity”, “durable” years after deployment, and “fungible” for every model and workload.
Read the blog to learn more: https://nvda.ws/4hphGmQ
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