This is great for the whole stock market. It is great for technology stocks. It is great the thesis that the AI boom is multi-year thing.
Jensen Huang, the visionary founder and CEO of Nvidia, calls this the dawn of a new era in computing. He emphasized that businesses worldwide are swiftly transitioning from traditional general-purpose computing to the realm of accelerated computing and generative AI.
GAAP earnings per diluted share for the quarter were $2.48, up 854% from a year ago and up 202% from the previous quarter. Non-GAAP earnings per diluted share were $2.70, up 429% from a year ago and up 148% from the previous quarter.
“A new computing era has begun. Companies worldwide are transitioning from general-purpose to accelerated computing and generative AI,” said Jensen Huang, founder and CEO of NVIDIA.
“NVIDIA GPUs connected by our Mellanox networking and switch technologies and running our CUDA AI software stack make up the computing infrastructure of generative AI.
“During the quarter, major cloud service providers announced massive NVIDIA H100 AI infrastructures. Leading enterprise IT system and software providers announced partnerships to bring NVIDIA AI to every industry. The race is on to adopt generative AI,” he said.
Data Center
Second-quarter revenue was a record $10.32 billion, up 141% from the previous quarter and up 171% from a year ago.
Announced that the NVIDIA® GH200 Grace™ Hopper™ Superchip for complex AI and HPC workloads is shipping this quarter, with a second-generation version with HBM3e memory expected to ship in Q2 of calendar 2024.
Announced the NVIDIA L40S GPU — a universal data center processor designed to accelerate the most compute-intensive applications — available from leading server makers in a broad range of platforms, including NVIDIA OVX™ and NVIDIA AI-ready servers with NVIDIA BlueField® DPUs, beginning this quarter.
Unveiled NVIDIA MGX™, a server reference design available this quarter that lets system makers quickly and cost-effectively build more than 100 server variations for AI, HPC and NVIDIA Omniverse™ applications.
Announced NVIDIA Spectrum-X™, an accelerated networking platform designed to improve the performance and efficiency of Ethernet-based AI clouds, which is shipping this quarter.
Joined with global system makers to announce new NVIDIA RTX™ workstations with up to four new NVIDIA RTX 6000 Ada GPUs, as well as NVIDIA AI Enterprise and NVIDIA Omniverse Enterprise software, expected to ship this quarter.
Launched general availability of cloud instances based on NVIDIA H100 Tensor Core GPUs with Amazon Web Services, Microsoft Azure and regional cloud service providers.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.
Nvidia is now similarly overvalued as IT stocks during the dot com bubble. It will come crashing down to more reasonable levels when the AI-hype dies. AI has actually not made a recent, substantial advancement; it has come creeping over the last 10 years. With a large enough language model (practically scraping the whole internet) they managed to make a chat bot that is reasonably effective and people got star-struck.
This will pass when they fail to make reasonably profit on it in the near future. And people will realize nVidia has no big competitive advantage in AI; they just happened to have something better than CPUs with a good API for AI researchers to use; GPUs are not a great fit for AI. For actual use nVidia needs to innovate to catch up more efficient architectures (e.g. Cerebras) and somehow offer something Microsoft etc. can’t fab themselves at TSMC.
In the short term people vastly and consistently overestimate the pace of technology and over 10 years or so they tend to vastly underestimate tech. The trough of disillusionment will come before AI becomes actually useful and monetizable at scale in the 2030’s.
And no, I won’t short nVidia, I just gradually sold off all nVidia stock and took profit. Just because I’m sure nVidia will crash; maybe even below $100; at some point in the future doesn’t mean that it won’t go to $1000 first. Shorting is difficult and requires timing even if you are right.
You are quite right on shorting. That and leveraging (borrowing money to invest) are two things people who aren’t double digit millionaires should stay the heck out of. With both of these, the investor loses the ability to pick the time and environment in which they must buy or sell (or come up with more money).
Sun Tzu says something somewhere about it being not great to allow yourself to be forced to commit your forces when you don’t get to choose when or where. That seems applicable in many things, including investing.
Stocks go up, stocks go down. Good stocks do. The bad ones disappear. You won’t lose with a good one if your timeline is long enough. Unless we are heading for a time of composting toilets and singing Kum-bah-ya, tech will be the place to be, and AI is part of that.
Mind you, I only invest about 10% of my investment capital in stocks. The rest I invest in carefully chosen fund managers–not the funds, the managers.
Hurray. I bought stock. One of my few exceptions to letting good fund managers do it for me.
It’s also nice to see the human race voting with its wallets to move forward.