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NVIDIA(NVDA - Free Report) CEO Jensen Huang gave computer gamers and developers more than they could ask for this week in Cologne, Germany at the Gamescom conference.
It's fair to say he stunned the crowd with amazing views, stats and demos on NVIDIA's record-breaking new "deep learning" architecture called Turing, featuring RTX image and light reconstruction/simulation powers that enable computers to teach themselves to do in real-time what it takes a Hollywood CGI studio months to do.
The world beyond gaming and CGI got to learn new phrases like "ray tracing" and "rasterization." And NVDA shares made an all-time high today, by only a quarter or so, above $269.
But if you are not a gamer or NVDA investor, you might find it hard to care. While I am not a gamer, I am an NVDA investor, and I'm here to give you two big reasons to care...
1) NVIDIA gaming graphics R&D is giving them deep knowledge about the next frontier of human evolution: AI
2) AI is going to dramatically change the world as you know it
I first addressed the stunning implications of NVIDIA's R&D reveal in my article from August 21...
In the video that accompanies this article today, I do a deeper dive that reviews the basic technology of GPU-driven deep learning and why NVIDIA builds parallel-processing architectures like the Tesla Volta 100. A single such graphics card is a workhorse that can be used to start basic big-data R&D or cryptocurrency mining -- or tens of thousands can be combined in the world's largest supercomputers.
And this is how enterprises, from corporations and universities to small startups and research labs, create neural nets of various sizes and complexity that can handle the processing and memory requirements of machine learning and deep learning.
As a hyper-scale example, I show the components of the world's current top research computer, IBM's (IBM - Free Report) SUMMIT at the Department of Energy, which uses over 26,000 Tesla V100 GPUs in tandem with a few thousand IBM core processors.
To grasp the scale of computing power in these machines, I also compare SUMMIT to Microsoft's (MSFT - Free Report) Xbox One X which has “just” 6 teraflops of processing capacity. A teraflop describes 1 trillion floating point operations per second.
You'll be surprised to learnin the video how many Xboxes it would take to equal SUMMIT's power. It rivals the connectivity and speed of a human brain at 122 "petaflops" -- even as PC-based “brute force” data-crunching capacity already far exceeds human powers -- while still being far from approaching the computational and creative complexity of human intelligence (think language, emotion, social interaction, vision, art, science, etc.).
I'm not worried about a supercomputer learning to think like a human and take over the world any time soon.
But, I do wonder how business and society, including the institutions of law, medicine, finance, and even government, will be transformed in the coming decades… as computers learn to write their own software.
I explored some of these heavier implications in my recent podcast/article...
Few thinkers and scientists understand the challenge with AI better than MIT physicist Max Tegmark, author of the 2017 book Life 3.0: Being Human in the Age of Artificial Intelligence.
I introduced the book last year in What to Do Before the Machines Take Over as another voice on the "advance guard" of technology along with Elon Musk of Tesla (TSLA - Free Report) and Yuval Noah Harari, author of Homo Deus.
Tegmark comes across more optimistic than Harari, perhaps because as a scientist who is deeply involved in and understands the AI challenge, he wants to make sure we get it right. I think he's also friends with Elon Musk, who sometimes sounds like the most pessimistic of the 3 in his warnings about AI.
Musk is also on the scientific advisory board of Tegmark's foundation The Future of Life Institute, a volunteer-run research and outreach organization in the Boston area that works to mitigate existential risks facing humanity, particularly existential risk from advanced artificial intelligence, but researchers also address Biotechnology, Nuclear and Climate Science.
Life 3.0 begins with a science fiction story that doesn't seem that unrealistic. A group of computer scientists called the Omega team decide to build a super AI machine that can learn everything humans do.
In the podcast, I share a few paragraphs that describe Prometheus and its first goal of using Amazon's (AMZN - Free Report) Mechanical Turk, or MTurk, to make money performing thousands of Human Intelligence Task (HITs) every day. Within a week, the computer was earning over $1 million per day.
Then, they went on to teach Prometheus to make TV shows, movies, commercials, news, and eventually, politicians.
Prometheus became a global cultural and political machinery that eventually achieved the goal of every AI that breaks out: world domination.
Tegmark tells this tale to make the point that AI's power is both unprecedented and unpredictable. And it's up to us to understand and embrace its potential so that we might have some control over its direction, velocity, and desired goals.
Tegmark wants more of us to be ambitious about what kind of world we could create with AI. Because the alternative -- thinking it is inevitable and out of our control -- leads to a complacency that won't be ready for the future it creates.
A great introduction to his ideas can be found in his first TED-Talk for the book, released on YouTube July 5...
Andrew Ng is an AI pioneer who has worked for Baidu (BIDU - Free Report) and Alphabet (GOOGL - Free Report) and now invests in AI startups. He says that "AI is the new electricity."
That's how powerful he sees the potential of AI to transform business and society. Here's how I summed it up in my recent article...
NVIDIA is not only reinventing industries but actually creating new industries with its GPU-based deep learning and artificial intelligence technologies.
Today's buzzword for that is "disruption," but Austrian economist Joseph Schumpeter called the human engine of innovation "creative destruction" nearly a century ago and that sounds a lot more like what NVIDIA is doing in this decade -- and probably the rest of this century.
From revolutionizing medical imaging and customizing consumer experiences to autonomous cars and powerful new forms of genetic research, the 4th industrial revolution is expanding the economics of the possible and forging unpredictable growth.
(end of excerpt from August 21 article)
And to think this all started with chips for games. Today, I found this simple summary on the NVIDIA website...
Fueled by the insatiable demand for better 3D graphics, and the massive scale of the gaming market, NVIDIA has evolved the GPU into a computer brain at the exciting intersection of virtual reality, high performance computing, and artificial intelligence.
NVIDIA gaming is like the R&D lab where powerful new tools and systems are being created and applied to real-world industrial, medical, and "intelligence" challenges.
In short, the games drive innovations that are anything but playing around.
In the end -- rather, in the beginning of this revolution -- NVIDIA deep learning and AI technologies will create a future that looks and feels very different than the one you experience today.
I remain an optimist. Here's to hoping that Jensen and the gamer armies keep the battlefields in the cyber realm, while they bring forth AI computing power that makes life better for everyone on the planet.
Disclosure: I own shares of NVDA for the Zacks TAZR Trader portfolio.
Kevin Cook is a Senior Stock Strategist for Zacks Investment Research where he runs the Healthcare Innovators and TAZR Trader services. Click Follow Author above to receive his latest stock research and macro analysis.
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Who Cares NVIDIA Makes Great Gaming Graphics?
NVIDIA(NVDA - Free Report) CEO Jensen Huang gave computer gamers and developers more than they could ask for this week in Cologne, Germany at the Gamescom conference.
It's fair to say he stunned the crowd with amazing views, stats and demos on NVIDIA's record-breaking new "deep learning" architecture called Turing, featuring RTX image and light reconstruction/simulation powers that enable computers to teach themselves to do in real-time what it takes a Hollywood CGI studio months to do.
The world beyond gaming and CGI got to learn new phrases like "ray tracing" and "rasterization." And NVDA shares made an all-time high today, by only a quarter or so, above $269.
But if you are not a gamer or NVDA investor, you might find it hard to care. While I am not a gamer, I am an NVDA investor, and I'm here to give you two big reasons to care...
1) NVIDIA gaming graphics R&D is giving them deep knowledge about the next frontier of human evolution: AI
2) AI is going to dramatically change the world as you know it
I first addressed the stunning implications of NVIDIA's R&D reveal in my article from August 21...
NVIDIA Gaming Drives the Deep Learning-AI Revolution
In the video that accompanies this article today, I do a deeper dive that reviews the basic technology of GPU-driven deep learning and why NVIDIA builds parallel-processing architectures like the Tesla Volta 100. A single such graphics card is a workhorse that can be used to start basic big-data R&D or cryptocurrency mining -- or tens of thousands can be combined in the world's largest supercomputers.
And this is how enterprises, from corporations and universities to small startups and research labs, create neural nets of various sizes and complexity that can handle the processing and memory requirements of machine learning and deep learning.
As a hyper-scale example, I show the components of the world's current top research computer, IBM's (IBM - Free Report) SUMMIT at the Department of Energy, which uses over 26,000 Tesla V100 GPUs in tandem with a few thousand IBM core processors.
To grasp the scale of computing power in these machines, I also compare SUMMIT to Microsoft's (MSFT - Free Report) Xbox One X which has “just” 6 teraflops of processing capacity. A teraflop describes 1 trillion floating point operations per second.
You'll be surprised to learnin the video how many Xboxes it would take to equal SUMMIT's power. It rivals the connectivity and speed of a human brain at 122 "petaflops" -- even as PC-based “brute force” data-crunching capacity already far exceeds human powers -- while still being far from approaching the computational and creative complexity of human intelligence (think language, emotion, social interaction, vision, art, science, etc.).
I'm not worried about a supercomputer learning to think like a human and take over the world any time soon.
But, I do wonder how business and society, including the institutions of law, medicine, finance, and even government, will be transformed in the coming decades… as computers learn to write their own software.
I explored some of these heavier implications in my recent podcast/article...
Facebook Faceplant: First Large-Scale AI Fail
Here's an excerpt...
Embracing the Next Brave New World
Few thinkers and scientists understand the challenge with AI better than MIT physicist Max Tegmark, author of the 2017 book Life 3.0: Being Human in the Age of Artificial Intelligence.
I introduced the book last year in What to Do Before the Machines Take Over as another voice on the "advance guard" of technology along with Elon Musk of Tesla (TSLA - Free Report) and Yuval Noah Harari, author of Homo Deus.
Tegmark comes across more optimistic than Harari, perhaps because as a scientist who is deeply involved in and understands the AI challenge, he wants to make sure we get it right. I think he's also friends with Elon Musk, who sometimes sounds like the most pessimistic of the 3 in his warnings about AI.
Musk is also on the scientific advisory board of Tegmark's foundation The Future of Life Institute, a volunteer-run research and outreach organization in the Boston area that works to mitigate existential risks facing humanity, particularly existential risk from advanced artificial intelligence, but researchers also address Biotechnology, Nuclear and Climate Science.
Life 3.0 begins with a science fiction story that doesn't seem that unrealistic. A group of computer scientists called the Omega team decide to build a super AI machine that can learn everything humans do.
In the podcast, I share a few paragraphs that describe Prometheus and its first goal of using Amazon's (AMZN - Free Report) Mechanical Turk, or MTurk, to make money performing thousands of Human Intelligence Task (HITs) every day. Within a week, the computer was earning over $1 million per day.
Then, they went on to teach Prometheus to make TV shows, movies, commercials, news, and eventually, politicians.
Prometheus became a global cultural and political machinery that eventually achieved the goal of every AI that breaks out: world domination.
Tegmark tells this tale to make the point that AI's power is both unprecedented and unpredictable. And it's up to us to understand and embrace its potential so that we might have some control over its direction, velocity, and desired goals.
Tegmark wants more of us to be ambitious about what kind of world we could create with AI. Because the alternative -- thinking it is inevitable and out of our control -- leads to a complacency that won't be ready for the future it creates.
A great introduction to his ideas can be found in his first TED-Talk for the book, released on YouTube July 5...
How to get empowered, not overpowered, by AI
The 4th Industrial Revolution Started With Games
Andrew Ng is an AI pioneer who has worked for Baidu (BIDU - Free Report) and Alphabet (GOOGL - Free Report) and now invests in AI startups. He says that "AI is the new electricity."
That's how powerful he sees the potential of AI to transform business and society. Here's how I summed it up in my recent article...
NVIDIA is not only reinventing industries but actually creating new industries with its GPU-based deep learning and artificial intelligence technologies.
Today's buzzword for that is "disruption," but Austrian economist Joseph Schumpeter called the human engine of innovation "creative destruction" nearly a century ago and that sounds a lot more like what NVIDIA is doing in this decade -- and probably the rest of this century.
From revolutionizing medical imaging and customizing consumer experiences to autonomous cars and powerful new forms of genetic research, the 4th industrial revolution is expanding the economics of the possible and forging unpredictable growth.
(end of excerpt from August 21 article)
And to think this all started with chips for games. Today, I found this simple summary on the NVIDIA website...
Fueled by the insatiable demand for better 3D graphics, and the massive scale of the gaming market, NVIDIA has evolved the GPU into a computer brain at the exciting intersection of virtual reality, high performance computing, and artificial intelligence.
NVIDIA gaming is like the R&D lab where powerful new tools and systems are being created and applied to real-world industrial, medical, and "intelligence" challenges.
In short, the games drive innovations that are anything but playing around.
In the end -- rather, in the beginning of this revolution -- NVIDIA deep learning and AI technologies will create a future that looks and feels very different than the one you experience today.
I remain an optimist. Here's to hoping that Jensen and the gamer armies keep the battlefields in the cyber realm, while they bring forth AI computing power that makes life better for everyone on the planet.
Disclosure: I own shares of NVDA for the Zacks TAZR Trader portfolio.
Kevin Cook is a Senior Stock Strategist for Zacks Investment Research where he runs the Healthcare Innovators and TAZR Trader services. Click Follow Author above to receive his latest stock research and macro analysis.