Microsoft CEO Satya Nadella, whose company has invested billions of dollars in ChatGPT maker OpenAI, has had it with the constant hype surrounding AI. During an appearance on podcaster Dwarkesh Patel's show this week, Nadella offered a reality check, arguing that OpenAI's long-established goal of establishing "artificial general intelligence," (AGI) an ill-defined term that roughly denotes the point at which an AI can best humans on an intellectual level, is nonsense. "Us self-claiming some AGI

“The real benchmark is: the world growing at 10 percent,” he added. “Suddenly productivity goes up and the economy is growing at a faster rate. When that happens, we’ll be fine as an industry.”

Needless to say, we haven’t seen anything like that yet. OpenAI’s top AI agent — the tech that people like OpenAI CEO Sam Altman say is poised to upend the economy — still moves at a snail’s pace and requires constant supervision.

  • FauxLiving@lemmy.worldEnglish
    22·
    4 小时前

    I am almost completely tuned out of the tech hypetrain around AI so I can’t comment on the minutiae of what the various tech CEOs are claiming.

    But, most of what people in the consumer tech world are seeing is entirely based on applying transformers to one kind of data: written text or images. This is only an incredibly tiny slice of the kinds of things that these transformer networks can be used for.

    Even just generating a python script is incredibly impressive. If you tried to write a program that could generate arbitrary python in 2010 it would take a massive engineering effort and tens of thousands of hours of work by incredibly well educated humans. But early generations of LLMs were able to do this as an emergent behavior simply by being shown enough examples. People often fail to realize exactly how much LLMs “for free” that, previously, required a concerted effort from engineers and mathematicians.

    There have been many attempts at creating programs which could predict how strings of amino acids folded into proteins. AlphaFold applied transformers to the problem and was able to predict essentially every protein that we’ve been able to observe. Even more, they can apply diffusion techniques (like, ‘AI image generation’) to generate a string of amino acids that form new novel proteins with arbitrary properties. We can write these sequences into DNA (CRISPR) and mass produce these custom designed proteins.

    This is such an incredible leap in biotech that it is hard to state what kind of impact that it will have. We’re already seeing things like HIV cures, optimized flu vaccines, immunotherapy drugs which are custom designed for the individual’s phenotypes. We’re years away from seeing the products of these technologies (clinical trials take time), but Transformers (‘AI’) are driving revolutionary changes in many fields.