Booz Allen-Hamilton Secures Pentagon Artificial Intelligence Contract
We take a closer look into Booz Allen-Hamilton's massive artificial intelligence contract with the Pentagon and what it entails for both parties.
Who is Booz Allen-Hamilton?
Booz Allen-Hamilton is a global firm of approximately 26,300 diverse, passionate, and exceptional people driven to excel, do right, and realize positive change in everything that they do.
They bring bold thinking and a desire to be the best in consulting, analytics, digital solutions, engineering, and cyber, and with industries ranging from defence to health to energy to international development.
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Booz Allen-Hamilton has one guiding purpose—to empower people to change the world. Its founder, Edwin Booz said it best: “Start with character… and fear not the future.” They bring a ferocious integrity to not only train our clients to tackle the problems they face today but to help them change the status quo for tomorrow. Each day, they imagine, invent, and deliver new ways to better serve their employees, their clients, and the world.
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Booz Allen Hamilton won a five-year, $800 million task order to provide artificial intelligence services to the Department of Defense’s Joint Artificial Intelligence Center (JAIC).
Under the contract award, announced by the General Services Administration and the JAIC on May 18, Booz Allen Hamilton will provide a “wide mix of technical services and products” to support the JAIC, a DoD entity dedicated to advancing the use of artificial intelligence across the department.
The contracting giant will provide the JAIC with “data labeling, data management, data conditioning, AI product development, and the transition of AI products into new and existing fielded programs,” according to the GSA news release.
“The delivered AI products will leverage the power of DoD data to enable a transformational shift across the Department that will give the U.S. a definitive information advantage to prepare for future warfare operations,” the release said.
The contract will support the JAIC’s new joint warfighting mission initiative, launched earlier this year. The initiative includes “Joint All-Domain Command and Control; autonomous ground reconnaissance and surveillance; accelerated sensor-to-shooter timelines; operations center workflows; and deliberate and dynamic targeting solutions,” said JAIC spokesperson Arlo Abrahamson told C4ISRNET in January.
The joint warfighting initiative is looking for "AI solutions that help manage information so humans can make decisions safely and quickly in battle,” Abrahamson said. The award to Booz Allen Hamilton will push that effort forward, Lt. Gen. Jack Shanahan, the center’s director, said in a statement.
“The Joint Warfighting mission initiative will provide the Joint Force with AI-enabled solutions vital to improving operational effectiveness in all domains. This contract will be an important element as the JAIC increasingly focuses on fielding AI-enabled capabilities that meet the needs of the warfighter and decision-makers at every level," Shanahan said.
The award to Booz Allen Hamilton was made by the GSA through its Alliant 2 Government-wide Acquisition Contract, a vehicle designed to provide artificial intelligence services to the federal government. The GSA and JAIC have been partners since last September, when the pair announced that they were teaming up as part of the GSA’s Centers of Excellence initiative, a program meant to accelerate modernization with agencies across government.
“The CoE and the JAIC continue to learn from each other and identify lessons that can be shared broadly across the federal space,” said Anil Cheriyan, director of the GSA’s Technology Transformation Services office, which administers the Centers of Excellence program. “It is important to work closely with our customers to acquire the best in digital adoption to meet their needs.
Google AI Designs Next-Gen Chips In Under 6 Hours
In a Google-Nature paper published on Wednesday, the company announced that AI will be able to design chips in less than six hours. Humans currently take months to design and layout the intricate chip wiring. Although the tech giant has been working in silence on the technology for years, this is the first time that AI-optimised chips have hit the mainstream—and that the company will sell the result as a commercial product.
“Our method has been used in production to design the next generation of Google TPU (tensor processing unit chips)”, the paper’s authors, Azalea Mirhoseini and Anna Goldie wrote. The TPU v4 chips are the fastest Google system ever launched. “If you’re trying to train a large AI/ML system, and you’re using Google’s TensorFlow, this will be a big deal”, said Jack Gold, President and Principal Analyst at J.Gold Associates.
Training the Algorithm
In a process called reinforcement learning, Google engineers used a set of 10,000 chip floor plans to train the AI. Each example chip was assigned a score of sorts based on its efficiency and power usage, which the algorithm then used to distinguish between “good” and “bad” layouts. The more layouts it examines, the better it can generate versions of its own.
Designing floor plans, or the optimal layouts for a chip’s sub-systems, takes intense human effort. Yet floorplanning is similar to an elaborate game. It has rules, patterns, and logic. In fact, just like chess or Go, it’s the ideal task for machine learning. Machines, after all, don’t follow the same constraints or in-built conditions that humans do; they follow logic, not preconception of what a chip should look like. And this has allowed AI to optimise the latest chips in a way we never could.
As a result, AI-generated layouts look quite different to what a human would design. Instead of being neat and ordered, they look slightly more haphazard. Blurred photos of the carefully guarded chip designs show a slightly more chaotic wiring layout—but no one is questioning its efficiency. In fact, Google is starting to evaluate how it could use AI in architecture exploration and other cognitively intense tasks.
Major Implications for the Semiconductor Sector
Part of what’s impressive about Google’s breakthrough is that it could throw Moore’s Law, the axion that the number of transistors on a chip doubles every five years, out the window. The physical difficulty of squeezing more CPUs, GPUs, and memory on tiny silicon die will still exist, but AI optimisation may help speed up chip performance.
Any chance that AI can help speed up current chip production is welcome news. Though the U.S. Senate recently passed a US$52bn bill to supercharge domestic semiconductor supply chains, its largest tech firms remain far behind. According to Holger Mueller, principal analyst at Constellation Research, “the faster and cheaper AI will win in business and government, including with the military”.
All in all, AI chip optimisation could allow Google to pull ahead of its competitors such as AWS and Microsoft. And if we can speed up workflows, design better chips, and use humans to solve more complex, fluid, wicked problems, that’s a win—for the tech world and for society.