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Google’s Plan to Catch ChatGPT Is to Stuff AI Into Everything

Bloomberg: “A new internal directive requires “generative artificial intelligence” to be incorporated into all of its biggest products within months. Artificial intelligence was supposed to be Google’s thing. The company has cultivated a reputation for making long-term bets on all kinds of far-off technologies, and much of the research underpinning the current wave of AI-powered chatbots took place in its labs. Yet a startup called OpenAI has emerged as an early leader in so-called generative AI—software that can produce its own text, images or videos—by launching ChatGPT in November. Its sudden success has left Google parent company Alphabet Inc. sprinting to catch up in a key subfield of the technology that Chief Executive Officer Sundar Pichai has said will be “more profound than fire or electricity.”

Google is not alone in its conviction that AI is now everything. Silicon Valley has entered a full-on hype cycle, with venture capitalists and entrepreneurs suddenly proclaiming themselves AI visionaries, pivoting away from recent fixations such as the blockchain, and companies seeing their stock prices soar after announcing AI integrations. In recent weeks, Meta Platforms Inc. CEO Mark Zuckerberg has been focused on AI rather than the metaverse—a technology he recently declared so foundational to the company that it required changing its name, according to two people familiar with the matter…”

See also The New York Times – Noam Chomsky: The False Promise of ChatGPT – “…The crux of machine learning is description and prediction; it does not posit any causal mechanisms or physical laws. Of course, any human-style explanation is not necessarily correct; we are fallible. But this is part of what it means to think: To be right, it must be possible to be wrong. Intelligence consists not only of creative conjectures but also of creative criticism. Human-style thought is based on possible explanations and error correction, a process that gradually limits what possibilities can be rationally considered. (As Sherlock Holmes said to Dr. Watson, “When you have eliminated the impossible, whatever remains, however improbable, must be the truth.”) But ChatGPT and similar programs are, by design, unlimited in what they can “learn” (which is to say, memorize); they are incapable of distinguishing the possible from the impossible. Unlike humans, for example, who are endowed with a universal grammar that limits the languages we can learn to those with a certain kind of almost mathematical elegance, these programs learn humanly possible and humanly impossible languages with equal facility. Whereas humans are limited in the kinds of explanations we can rationally conjecture, machine learning systems can learn both that the earth is flat and that the earth is round. They trade merely in probabilities that change over time.”

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