- cross-posted to:
- artificial_intel
- cross-posted to:
- artificial_intel
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I don’t get the title.
Why ‘making “pretend people” with artificial intelligence’ is a waste of energy
Oh, thank you
Simply because the title makes zero sense.
The article itself doesn’t really clear it up, IMO.
The headline was confusing and reading the article doesn’t really clear things up. I don’t think Gill is imagining the same sort of “pretend person” that I would want out of AGI. What I want is a personal assistant that knows me extremely well, is able to tirelessly work on my behalf, and has a personality tailored to my needs and interests. It should be general enough to understand me on a personal level and do a good job anticipating what I want.
That would not at all be a waste of energy to me.
Depends on how much energy it takes. If it takes more resources than it frees, then I’d say it is not worth it.
I am quite sure it’ll cost less than it would to hire a human for the job.
I’m talking about the energy and resources to actually create and provide this service.
So am I.
knows me extremely well, is able to tirelessly work on my behalf, and has a personality tailored to my needs and interests.
Those may still be ANI applications.
Today’s LLM’s marketed as the future of AGI are more focused on knowing a little bit about everything. Including a little bit about how MRIs work and a summary of memes floating around a parody subreddit. I fail to see how LLM’s as they are trained today will know you extremely well and give you a personality tailored to your needs. I also think commercial interests of big tech are pitted against your desire for “tirelessly work[ing] on my behalf”.
Like Farnsworth Bentley?
What I want is a personal assistant that knows me extremely well, is able to tirelessly work on my behalf, and has a personality tailored to my needs and interests.
and you’re not concerned at all about this information being compromised and used against you?
phew…
Of course I’m concerned about it. That’s why I would take measures to ensure the information is well protected. I already run local LLMs and image generators for most of the stuff I use AI for, both to ensure that I have control over what sort of outputs they generate and to keep any inputs I run through them private. An AGI assistant like what I’m describing is something I would want to run on my own hardware too.
Do you really think you’ll be able to run a full fledged, real-feeling AGI on home hardware?
Perhaps an assistant, maybe…
but good on you for forethought.
Yes, I do. Perhaps not the current generation of hardware, but the chip manufacturers are currently throwing hundreds of billions of dollars into designing the next generation of AI-specialized hardware so I expect the next generation to be very impressive. The software has also been getting more efficient, making better use of the hardware that already exists. I’ve been experimenting a lot with it.
I know quite a lot of people doing research into AI. Some from my own background in applied mathematics, and some from my partners partner’s background in computational linguistics. They all have very different ideas about the future of AI, but they all laugh about the idea of a generic AGI.
What should we make pretend people with?
Play-Doh
Edit: And candy!
This is the best summary I could come up with:
Interview While the likes of OpenAI and Google DeepMind chase after some fabled artificial general intelligence, not everyone thinks that’s the best use of our time and energy in developing AI.
Computer scientist Binny Gill – CEO and co-founder of business automation firm Kognitos, and formerly chief architect and cloud CTO at Nutanix – thinks the push for AGI is the entirely wrong approach in what could be the next industrial revolution.
Rather than trying to replicate humans with some kind of general-purpose artificial intelligence, Gill thinks we should look to the past to see what sort of systems we should be building.
Gill instead hopes we’ll see the rise of what he calls artificial narrow intelligence, or ANI.
This isn’t a new concept; it’s the sort of application-specific machine learning that already exists behind things like self-driving cars.
To learn more about Gill’s optimistic vision for the future of AI, watch our full video interview with him by clicking on play above.
The original article contains 279 words, the summary contains 163 words. Saved 42%. I’m a bot and I’m open source!
