There is astonishing new progress in AI-generated art, molecular biology, text and other fields that is revealed in a new NY Times article (paywall, at https://www.nytimes.com/2022/08/24/techn...e4358ee2df):
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The bottom line is, though, that the most interesting aspect of all this to us is that despite having transformative potential in changing our society, none of this new high computer software technology is exhibiting the ghost of a chance of actually generating consciousness. Meaning that the apocalyptic predictions of a downloading of human consciousness into advanced AI systems or cyborgs, or of some malevolent conscious AI system taking over the world and wiping out humanity, are still just as indefinitely far in the future, or more likely, simply impossible mostly because of the Hard Problem, and the fact that human consciousness is fundamentally nonalgorithmic.
(This post was last modified: 2022-08-25, 03:18 PM by nbtruthman. Edited 2 times in total.)
Quote:DALL-E 2 "art": It isn’t just the art it generates. It’s how it generates art. These aren’t composites made out of existing internet images — they’re wholly new creations made through a complex A.I. process known as “diffusion,” which starts with a random series of pixels and refines it repeatedly until it matches a given text description. And it’s improving quickly — DALL-E 2’s images are four times as detailed as the images generated by the original DALL-E, which was introduced only last year.
...last year, DeepMind’s AlphaFold — an A.I. system descended from the Go-playing one — did something truly profound. Using a deep neural network trained to predict the three-dimensional structures of proteins from their one-dimensional amino acid sequences, it essentially solved what’s known as the “protein-folding problem,” which had vexed molecular biologists for decades.
This summer, DeepMind announced that AlphaFold had made predictions for nearly all of the 200 million proteins known to exist — producing a treasure trove of data that will help medical researchers develop new drugs and vaccines for years to come. Last year, the journal Science recognized AlphaFold’s importance, naming it the biggest scientific breakthrough of the year.
...now, large language models like OpenAI’s GPT-3 are being used to write screenplays, compose marketing emails and develop video games. (I even used GPT-3 to write a book review for this paper last year — and, had I not clued in my editors beforehand, I doubt they would have suspected anything.)
A.I. is writing code, too — more than a million people have signed up to use GitHub’s Copilot, a tool released last year that helps programmers work faster by automatically finishing their code snippets.
Finally, LaMDA and other state-of-the-art language models are becoming eerily good at having humanlike text conversations.
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But skeptics say that models like GPT-3 and LaMDA are just glorified parrots, blindly regurgitating their training data, and that we’re still decades away if ever from creating true A.G.I. — artificial general intelligence — that is capable of “thinking” for itself.
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However, the practical ramifications are profound....the best A.I. systems are now so capable — and improving at such fast rates — that the conversation in Silicon Valley is starting to shift. Fewer experts are confidently predicting that we have years or even decades to prepare for a wave of world-changing A.I.; many now believe that major changes are right around the corner, for better or worse. One estimate, for example, has been that there is a 35% chance that AI will make all white collar knowledge jobs obsolete by 2036.
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In just a few years, the vast majority of the photos, videos and text we encounter on the internet could be A.I.-generated. Our online interactions could become stranger and more fraught, as we struggle to figure out which of our conversational partners are human and which are convincing bots. And tech-savvy propagandists could use the technology to churn out targeted misinformation on a vast scale, distorting the political process in ways we won’t see coming.
Comment:
The bottom line is, though, that the most interesting aspect of all this to us is that despite having transformative potential in changing our society, none of this new high computer software technology is exhibiting the ghost of a chance of actually generating consciousness. Meaning that the apocalyptic predictions of a downloading of human consciousness into advanced AI systems or cyborgs, or of some malevolent conscious AI system taking over the world and wiping out humanity, are still just as indefinitely far in the future, or more likely, simply impossible mostly because of the Hard Problem, and the fact that human consciousness is fundamentally nonalgorithmic.