Kelsey piper ai

That might have people asking: Wait, what?

Good agreed; more recently, so did Stephen Hawking. These concerns predate the founding of any of the current labs building frontier AI, and the historical trajectory of these concerns is important to making sense of our present-day situation. To the extent that frontier labs do focus on safety, it is in large part due to advocacy by researchers who do not hold any financial stake in AI. But while the risk of human extinction from powerful AI systems is a long-standing concern and not a fringe one, the field of trying to figure out how to solve that problem was until very recently a fringe field, and that fact is profoundly important to understanding the landscape of AI safety work today. The enthusiastic participation of the latter suggests an obvious question: If building extremely powerful AI systems is understood by many AI researchers to possibly kill us, why is anyone doing it?

Kelsey piper ai

She explores wide-ranging topics from climate change to artificial intelligence, from vaccine development to factory farms. She writes the Future Perfect newsletter, which you can subscribe to here. She occasionally tweets at kelseytuoc and occasionally writes for the quarterly magazine Asterisk. If you have story ideas, questions, tips, or other info relevant to her work, you can email kelsey. She can also accept confidential tips on Signal at Ethics Statement Future Perfect coverage may include stories about organizations that writers have made personal donations to. This does not in any way affect the editorial independence of our coverage, and this information will be disclosed clearly when relevant. Future Perfect is supported in part by grants from foundations and individual donors. Future Perfect prizes its editorial independence, and all editorial decisions are made separately from fundraising and commercial considerations. Explainers Israel-Hamas war election Tax season. The Oscars Supreme Court Winter warming.

This is reasonable to imagine, but importantly not how modern deep learning actually works.

That might have people asking: Wait, what? But these grand worries are rooted in research. Along with Hawking and Musk, prominent figures at Oxford and UC Berkeley and many of the researchers working in AI today believe that advanced AI systems, if deployed carelessly, could permanently cut off human civilization from a good future. This concern has been raised since the dawn of computing. There are also skeptics. Others are worried that excessive hype about the power of their field might kill it prematurely.

GPT-4 can pass the bar exam in the 90th percentile, while the previous model struggled around in the 10th percentile. And on the advanced sommelier theory test, GPT-4 performed better than 77 percent of test-takers. These are stunning results — not just what the model can do, but the rapid pace of progress. Her work is informed by her deep knowledge of the handful of companies that arguably have the most influence over the future of A. This episode contains strong language. Tolkien Thoughts? Guest suggestions? Email us at ezrakleinshow nytimes. Fact-checking by Michelle Harris and Kate Sinclair. Mixing by Jeff Geld.

Kelsey piper ai

Stephanie Sy Stephanie Sy. Layla Quran Layla Quran. In recent months, new artificial intelligence tools have garnered attention, and concern, over their ability to produce original work. The creations range from college-level essays to computer code and works of art. As Stephanie Sy reports, this technology could change how we live and work in profound ways. Notice: Transcripts are machine and human generated and lightly edited for accuracy. They may contain errors. In the coming weeks and months, we're going to be exploring the newest developments in artificial intelligence and how it's changing the way we live and work. Stephanie Sy kicks off our periodic series The A. Frontier with a look at some new tools that are getting attention and sparking concern over their ability to produce original work, ranging from college-level essays to art.

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We just need to solve a very hard engineering problem first. Others, like Karnofsky, encountered the idea through Yudkowsky and others at the Singularity Institute in the early s, but came to develop their own views. This concern has been raised since the dawn of computing. Can effective altruism stay effective? Good posed the first scenario of runaway machine intelligence:. Why you think you're right - even when you're wrong. This worldview suggests some obvious ideas about which avenues of research are promising. Instead, to the extent that these premises are correct, we should just stop building powerful AI systems, indefinitely, until we have a better idea of how to kick off the avalanche that is a self-improving superintelligence without catastrophe. Why so many members of Congress are calling it quits By Li Zhou. They point to self-driving cars , which are still mediocre under the best conditions despite the billions that have been poured into making them work. I'm not sure if it's the best intro, but it seems like a contender. What you save is stored only on your specific browser locally, and is never sent to the server. For a reason unknown to us, the game does not advance to the second round but the platforms start to blink and the agent quickly gains a huge amount of points close to 1 million for our episode time limit.

Karnofsky, in my view, should get a lot of credit for his prescient views on AI. Some of his early published work on the question, from and , raises questions about what shape those models will take, and how hard it would be to make developing them go well — all of which will only look more important with a decade of hindsight.

And this worldview envisions fairly little useful human input as the system rapidly ramps up in capabilities, because that ramp-up is expected to happen in the blink of an eye. Tolkien Thoughts? Engineers are constantly catching loopholes and plugging new holes against adversarial inputs. It certainly feels to me like there are some bad signs in present-day AI systems that proponents of this view need to explain away. More by The New York Times. That is ultimately what almost every organization with an artificial general intelligence division is trying to do. To do computer vision — allowing a computer to identify things in pictures and video — researchers wrote algorithms for detecting edges. The Latest. No matter whether or not humanity should be afraid, we should definitely be doing our homework. Next Up In Future Perfect. As they grow more sophisticated, scientists like Omohundro predict more adversarial behavior. AI, he concluded, endangers us. The Oscars Supreme Court Winter warming. With AI as a multiplier for human ingenuity, those solutions will come into reach.