As artificial intelligence (AI) continues to permeate our digital landscape, the influence of microelectronics – the tiny chips powering these technologies – can’t be overlooked. Ensuring the security of these essential components is now more critical than ever to safeguard larger digital ecosystems.
The U.S. Department of Defense (DoD) is capitalizing on the potential of 5G networks to fortify military communication capabilities in the face of escalating geopolitical tensions.
Following the expulsion of official outlets RT and Sputnik from various Western nations, Moscow has redirected its focus to social media platforms and generative artificial intelligence (AI), as per a recently published report.
The Intelligence Community (IC) has been unstinting in embracing and assimilating artificial intelligence (AI) and machine learning (ML) into their operations. The benefits of applying AI/ML to the overwhelming volume of data the IC handles is undeniable.
NVIDIA, a leader in the realm of artificial intelligence (AI) and chip making, achieved an impressive stock market valuation of $2 trillion recently, highlighting the ongoing boom in the AI marketplace.
Noted by the Federal News Network, Senator Mark Warner has underlined the necessity for firm regulations and standards to ensure the safe and credible development and implementation of Artificial Intelligence (AI) technologies. The absence of such guidelines, he cautioned, could cause risk to federal initiatives.
A recent report by Ernst & Young (EY) indicates that most federal IT decision-makers and influencers rely on internal data repositories for training artificial intelligence (AI) models. Specifically, 58% of federal respondents look to these resources as the main source for their AI training data.
The newly issued executive order (EO) on Artificial Intelligence (AI) offers federal agencies concrete guidelines and guardrails to mitigate potential risks linked with AI adoption. This move sets imperative goals that are time-bound.