Kelsey piper ai

That might have people asking: Wait, what?

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?

Kelsey piper ai

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. And even among the people who broadly agree that AI poses unique dangers, there are varying takes on what steps make the most sense today. Unfortunately, I don't have time to re-read them or say very nuanced things about them. I think this is an accessible intro to why we should care about AI safety. I'm not sure if it's the best intro, but it seems like a contender. Hide table of contents. The case for taking AI seriously as a threat to humanity Kelsey Piper.

As with Open Philanthropy, many of these techniques depend on training less powerful AIs to help supervise increasingly more powerful systems. She explores wide-ranging topics from climate change to artificial intelligence, from vaccine development kelsey piper ai factory farms.

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? Some people think that all existing AI research agendas will kill us. Some people think that they will save us.

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.

Kelsey piper ai

Kelsey Piper is an American journalist who is a staff writer at Vox , where she writes for the column Future Perfect , which covers a variety of topics from an effective altruism perspective. While attending Stanford University, she founded and ran the Stanford Effective Altruism student organization. Piper blogs at The Unit of Caring.

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The Ezra Klein Show. To do computer vision — allowing a computer to identify things in pictures and video — researchers wrote algorithms for detecting edges. Language models today are vastly better than they were five years ago. In the last 10 years, rapid progress in deep learning produced increasingly powerful AI systems — and hopes that systems more powerful still might be within reach. If superintelligent AIs outnumber humans, think faster than humans, and are deeply integrated into every aspect of the economy, an AI takeover seems plausible — even if they never become smarter than we are. Not every organization with a major AI department has a safety team at all, and some of them have safety teams focused only on algorithmic fairness and not on the risks from advanced systems. If this AI correctly reported that the Earth revolved around the sun, it would be rated more negatively than if it said the opposite. Much AI safety work in the s and s — especially by Eliezer Yudkowsky and the nonprofits he founded, the Singularity Institute and then the Machine Intelligence Research Institute — emerged from this set of assumptions. This concern has been raised since the dawn of computing. You can also contribute via.

Karnofsky, in my view, should get a lot of credit for his prescient views on AI.

This episode contains strong language. Introduction to Effective Altruism. Having exterminated humanity, it then calculates the number with higher confidence. The ones who will suffer most will be low-income people in developing countries ; the wealthy will find it easier to adapt. Furthermore, breakthroughs in a field can often surprise even other researchers in the field. These are stunning results — not just what the model can do, but the rapid pace of progress. By Ellen Ioanes. This does not in any way affect the editorial independence of our coverage, and this information will be disclosed clearly when relevant. Making websites more addictive can be great for your revenue but bad for your users. AI safety Frontpage. In an excerpt from unpublished notes Good wrote shortly before he died in , he writes about himself in third person and notes a disagreement with his younger self — while as a younger man, he thought powerful AIs might be helpful to us, the older Good expected AI to annihilate us. There is substantial disagreement about which approaches seem likeliest to bring us to general AI, which approaches seem likeliest to bring us to safe general AI, and how soon we need to worry about any of this. 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?