Brad’s Note: Last week, our colleague Nomi Prins attended Nvidia’s GPU Technology Conference (GTC).
If you’ve been keeping up with the tech sector over the past year or so, you know Nvidia has been leading the pack when it comes to AI-related advances. And the conference featured a host of other companies and business ventures that are gearing up to propel growth in the space.
That’s why today, we’re excited to share with you Nomi’s findings from the conference… How the government is leaning into AI technology to boost national security… What is needed for full advancement of its revolutionary potential… And one way you can profit in your portfolio today.
By Nomi Prins, Editor, Inside Wall Street With Nomi Prins
Two major events happened last week.
One, the Fed kept rates where they are, and signaled three more rate cuts to come this year. That’s what I’ve been saying would happen for months.
The bigger event, in case there was any doubt that artificial intelligence (AI) is growing rapidly, was the Nvidia GTC expo in San Jose, California.
I headed to San Jose to attend it. It was a buzz of developers, investors, public officials from the local to the federal level, and corporate leaders.
Nvidia was the headline sponsor.
Dell Technologies – which has more than doubled since I first recommended it to Distortion Report readers in February 2022 – was a major force at the conference, too.
Both companies are poised to accelerate their AI presence in the public sector. And the Department of Defense (DOD) is set to expand its AI partnership with the private sector.
Let me explain.
Dell and Nvidia’s Government Relationships
Dell Technologies’ partnership with the U.S. government and Army focuses on providing advanced technology solutions, including AI, to support its missions and operations.
In 2023, Dell broke into the top 20 federal contractors. It jumped from 21st place in 2022 to 17th place in the rankings. In the process, it raked in more than $2.6 billion of contracts last year.
Over the past five years, Dell has received $6.5 billion in government contracts.
Some key areas where Dell Technologies collaborates with the U.S. Army include:
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Cybersecurity: Dell Technologies offers advanced cybersecurity solutions that help protect the Army’s sensitive data, network software, and infrastructure from cyber threats.
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Data Analytics and IT Solutions: Dell Technologies provides data storage solutions that enable the Army to store and access large volumes of data quickly.
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Edge Computing: Dell Technologies is helping the U.S. Army adopt edge computing solutions. These would bring processing power closer to the battlefield. That would improve response times and enable faster decision-making during combat.
Dell Technologies’ stock price surged to a record high following its upbeat annual forecast that highlighted AI-related profits.
But the market has been even more impressed with Nvidia, whose stock price has risen 87% since the beginning of this year.
Nvidia is working closely with the U.S. Army as well and aims to tighten that relationship. To do that, it’s focused across these areas:
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Machine Learning: Nvidia’s advanced AI and machine learning algorithms and AI chips can improve target recognition and situational awareness while optimizing decision-making for the DOD. Other government contractors, such as Microsoft, also use its GPUs (graphics processing units), so it’s positioned to gain profitability from those firms, too.
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Visualization: Nvidia’s GPUs and visualization software can enhance the Army’s training and simulation capabilities. This includes creating interactive virtual environments for training purposes to help soldiers prepare for real-world challenges.
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Cybersecurity: Nvidia’s cybersecurity solutions can protect the Army’s networks and data from cyber threats by instantly recognizing and diffusing them.
Enter Blackwell
Nvidia’s GPUs are crucial for deploying and training large-scale AI models. Companies like Microsoft and Meta have spent billions of dollars on Nvidia’s GPUs for their own AI developments.
Software makers are scrounging for Nvidia’s current generation of H100s, or Hoppers.
At the conference last week, Nvidia CEO Jensen Huang announced a new generation of AI chips and software for running AI models. It named the new processors Blackwell.
As Huang told a riveted crowd, “Hopper is fantastic, but we need bigger GPUs.”
Nvidia also introduced a new revenue-generating software called NIM that would make it easier to deploy AI.
In that way, Nvidia is transforming itself into a platform provider, not just a chipmaker. That means it will remain a key player in the AI-tech space for years to come.
The government will be a part of that.
Let me put that into context.
The Pentagon’s Vision for AI
Last month, Craig Martell addressed the three-day Advantage DOD 2024: Defense Data and AI Symposium in Washington.
Martell is the DOD’s chief digital and artificial intelligence officer. He said:
Imagine a world where combatant commanders can see everything they need to see to make strategic decisions.
Imagine a world where those combatant commanders aren’t getting that information via PowerPoint or via emails from across the [organization] – the turnaround time for situational awareness shrinks from a day or two to 10 minutes.
This AI focus kicked into high gear last fall.
In October, the White House released an AI executive order to galvanize federal focus on AI development and security.
Then, in November, the DOD released its strategy for faster AI adoption. Its blueprint underscored the need for AI in five key areas:
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Superior battlespace awareness and understanding
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Adaptive force planning and application
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Fast, precise, and resilient kill chains
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Resilient sustainment support
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Efficient enterprise business operations
The strategy also highlighted six critical AI-related goals:
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Invest in interoperable, federated infrastructure.
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Advance the data, analytics, and AI ecosystem.
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Expand digital talent management.
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Improve foundational data management.
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Deliver capabilities for the enterprise business and joint warfighting impact.
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Strengthen governance and remove policy barriers.
These goals collectively address the “DOD AI Hierarchy of Needs.” These needs span data quality governance, insightful analytics and metrics, assurance, and responsible AI.
AI Uses for National Security
As generative AI gains momentum, so does the need for AI applications to support U.S. defense national security and infrastructure.
That’s because the more the general public and U.S. enemies gain access to AI, the more the U.S. military must keep up. The military may wind up relying more on AI algorithms than Army sizes in the future.
That would be a major budget and lifesaving result!
The U.S. military has actually been using AI for years. It has nearly eliminated the need for human input in maneuvers such as drone strikes and surveillance. But there is more in the pipeline.
Generative AI can improve the military’s decision-making process. The Army can use AI models to analyze data for patterns and situational implications quicker than humans can.
But the government has been, by its own admission, behind the curve on AI development relative to the private sector.
That’s why Martell said the DOD “should be paying the industry to build models because they’re always going to be on the cutting edge” regarding developing AI solutions.
He said the Pentagon will need to rely even more on the private sector to drive change across the department – especially to ensure that quality data is being used properly.
The Path to the Nvidia GTC Conference
I attended the AI on the Road session at the Nvidia GTC expo last Tuesday morning.
The session convened a fascinating pairing of Army officials and private sector leaders to discuss the opportunities and challenges of generative AI and AI systems.
It confirmed what I’ve already written. There are synergies and, therefore, profit opportunities between the private and public sectors in AI.
And these are growing rapidly.
As Nvidia VP Federal Anthony Robbins noted, the company’s Blackwell platform will be another step forward in “driving change and transformation” for “speed to mission” for the military.
The chief AI architect at Dell Technologies, Dr. Art Villanueva, said the future of generative AI hinges on the “quality of data available.”
What he said resonated with me. I have always believed, and written here, that the best data in equals the best data out.
The upshot is that the upside of generative AI can be limitless if two key elements come into play.
First, the proper systems and hardware need to be integrated to process data and formulate responses to that data.
Second, there must be data transparency. AI models scour and access publicly available data. Then, they analyze and process that data to generate “machine learning” results.
But just because data is public doesn’t mean it’s accurate.
There must be a high degree of quality control over that data. Otherwise, AI models can incorporate errors and make decisions based on those errors, in effect, compounding them.
As with most things in life, the quality of inputs will determine the quality of outcomes. This will matter for the government and for defense as much as it will for business efficiency and technology.
And that’s something Dell Technologies highlighted.
Stretching back to my time on Wall Street, what the savviest minds knew then remains true today – the greatest commodity is information.
As I discovered at the Nvidia GTC event, streamlined AI programs that use optimal information will determine how far, and how fast, generative AI takes us.
Meanwhile, a great way to take advantage of the rapidly growing AI arena is to invest in the Global X Artificial Intelligence & Technology ETF (AIQ).
It includes companies leading the AI charge in the hardware and software space.
Regards,
Nomi Prins
Editor, Inside Wall Street with Nomi Prins