Big Tech Giants Like Apple and Alphabet Poised to Leverage AI for Industry Dominance, According to ARK Invest

Big Tech Giants Like Apple and Alphabet Poised to Leverage AI for Industry Dominance, According to ARK Invest

Crypto News – In a recent white paper released on October 1st, ARK Invest, the investment firm helmed by Cathie Wood, highlighted how major technology companies such as Apple and Alphabet, the parent company of Google, are likely to rely heavily on artificial intelligence (AI) to maintain their leadership in the industry. Authored by ARK’s chief futurist Brett Winton, the report delves into the disruptive nature of AI and outlines a framework for identifying transformative technologies.

AI’s Accelerating Cost Decline Mirrors Historical Disruptions

Winton identifies three key traits that define disruptive technology platforms: rapid declines in cost, the ability to penetrate new or underserved markets, and business models that may initially appear unprofitable or risky. According to the report, AI is a textbook example of such a platform, as it is experiencing the steepest cost decline of any technology in history.

“The cost to operate AI models with comparable performance has been halving every four months, a trend that we expect to continue throughout this decade,” Winton explained. He likened this trend to Moore’s Law, which states that semiconductor costs decrease by half every 18 to 24 months. However, Winton emphasized that the pace of AI’s cost decline is four to six times faster than that of semiconductors, indicating a much quicker path to disruption.

Big Tech’s Cautious Approach to AI Innovation

The report also examines how industry incumbents like Google and Apple often allow smaller startups to take on the initial risks of emerging technologies, including AI, before adopting those technologies at scale. Winton pointed out that Google did not release its large language model to the public until three years after OpenAI had entered the market. Even then, Google’s AI model lagged behind in terms of cost-efficiency, with customers needing to pay more than 40% extra for comparable performance compared to OpenAI’s models.

Apple, on the other hand, has yet to launch a large language model of its own, though the tech giant is expected to introduce its first AI-powered products in late 2024. Winton argued that, while slower to market, companies like Apple and Google may have valid reasons for their deliberate pace. They are, after all, guardians of carefully cultivated reputations and must avoid releasing products that could behave unpredictably, potentially undermining their brand trust.

Will Caution Cost Big Tech in the AI Race?

Winton questioned whether Big Tech’s cautious approach could ultimately limit their ability to deploy AI systems that deliver exceptional performance at scale. Although these companies benefit from being industry incumbents, their preference for less disruptive technology could put them at a disadvantage in the rapidly evolving AI space.

“They are incumbents,” Winton concluded, “and they would prefer technology that is not so disruptive. But to their detriment, it is.”