Former Pentagon officials are sounding the alarm about the danger of America losing its status as the global leader in technology and innovation.
China is rapidly gaining ground and if action isn't taken now, it could be too late.
There's a high-tech battle going on between the U.S. and China with much at stake. Experts are speaking out because of concern that the U.S. isn't currently competing enough to come out on top.
"We're getting behind in really the sectors in cyber, AI, ML, that are the most important to win the next battle," said Nicolas Chaillan, a former chief software officer.
Chaillan filled the role as the first chief software officer of the Air Force and Space Force but resigned in September over his concern regarding U.S. complacency.
"You see China, for example, doing 200 hypersonic launches versus 10 in the United States ... that's obviously very alarming," explained Chaillan. "Then you hear the chairman of the Joint Staff saying it's almost a Sputnik moment when it is a Sputnik moment."
"That's a clear example of risk-taking and speed that China's been taking, whereas the risk aversion that we have here to be able to experiment and try something new on the government side has been a real challenge," noted Preston Dunlap, another tech defense official who basically followed Chaillan's lead.
Dunlap served as the inaugural chief architect officer of the Air Force and Space Force.
Both men agree that to maintain technological dominance, the U.S. must act now.
"I do think now is the time to begin to pivot and change that curve because it takes a while to turn an aircraft carrier and it takes a while to turn the technological pace that we have here in the nation," Dunlap stated.
Chaillan estimates that if tremendous progress isn't made within the next six months, keeping up won't be the issue. The U.S. will face the challenge of catching up.
"When it comes to the compounded evolution of AI, there comes a point you can't physically catch up because we're dealing with a nation of 1.4 billion people. Massive volume of data and the more volume of data you get in AI, the better the AI can learn and get better and stronger with time," Chaillan pointed out.
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