AGI is a Rorschach Test for People to Project Their Technology Anxieties

There’s a lot of murmur around AGI. While some experts see it coming next year, a few believe it will be here in 2029, and some others say never. Then there are those that claim that we’ve attained AGI many times in 2024 with developments like Devin and Claude-3 Opus, sparking the debate that now when we do achieve it, no one will really care.

When asked about AGI in a recent interview, Microsoft’s CTO Kevin Scott said, “AGI is kind of a Rorschach test for people and a lot of times it’s like what are you most anxious about in the development of the technology.”

The Rorschach test is a psychological assessment method that uses inkblots to analyse a person’s emotions, personality, and psychological traits.

“I don’t even know what it means, honestly in a literal sense. If you had to sit down and write a technical definition of AGI, I think you would have a very hard time doing that,” he added.

The AGI Obsession

We’re still not sure if OpenAI will be the first to build AGI, but in obsessing over it, they surely top the list. “I don’t care if we burn $50 billion a year, we’re building AGI, and it is going to be expensive and totally worth it,” said OpenAI CEO Sam Altman on Stanford eCorner’s talk.

Calling ChatGPT mildly embarrassing and GPT-4 the dumbest model users will ever have to use again, he emphasised the importance of iterative deployment rather than delivering perfect solutions.

“If we build AGI in a basement and then the world is blissfully walking blindfolded along, I don’t think that makes us very good neighbours,” he said, stressing the need to put the product in people’s hands and letting society co-evolve with the technology.

Many were quick to call out this obsession.

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With such hype, one might think that OpenAI has a detailed plan or timeline or at least a definition in place for AGI; however, nothing concrete was said about that.

“It’s too loose a definition, and there’s too much room for misinterpretation. I’ve given up on trying to give the AGI a timeline,” said Altman, when asked for a best guess of when he thinks AGI will happen.

According to Altman, when people ask about the AGI timeline, what they really want to know is when the world is going to be super different and when their lives will change due to it.

Although he doesn’t know how to give a precise timeline of when we get to the milestone people care about, he believes that every year for the next many years, there will be dramatically more capable systems.

In another recent interview, when asked about when he thinks we as a humanity will build AGI, Altman said that he used to love to speculate on that but has now realised that it’s a very poorly formed question and that people use extremely different definitions of what AGI is.

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“I think it makes more sense to talk about when we’ll build systems that can do capability X or Y or Z rather than when we kind of fuzzily cross this one-mile marker,” he said. Adding that by the end of this decade and possibly somewhat sooner than that, we will have quite remarkable systems.

Of course, many weren’t convinced by his big talk and hype words. There have been discussions around Altman’s stance on burning that kind of money ($50 billion) to build AGI – it’s more than some countries’ GDP!

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All major big-tech companies, like OpenAI, Meta, Google DeepMind, and Tesla are in the pursuit of AGI, but tech enthusiasts and the developer community seem to be disappointed by OpenAI for making tall claims and not releasing anything significant lately.

At this point, the joke is just getting funnier.

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However, there are also those who like Altman’s enthusiasm. “He knows money [will] no longer have value when they have achieved AGI,” said a user. Another wrote, “It would be a minuscule price to pay for something that could transform humanity.”

In India, meanwhile, Soket AI Labs has become the first startup to build solutions towards ethical AGI. This AI research lab plans to do this by starting with smaller language models and eventually building advanced AI systems capable of achieving human-level intelligence.

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