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PODCAST

EA Forum Podcast (Curated & popular)

Audio narrations from the Effective Altruism Forum, including curated posts and posts with 125 karma. If you"d like more episodes, subscribe to the "EA Forum (All audio)" podcast instead.

technology philosophy

All Episodes

2:40

“The Scaling Series Discussion Thread: with Toby Ord”...

EA Forum Podcast (Curated & popular) ·

2026/02/02

We're trying something a bit new this week. Over the last year, Toby Ord has been writing about the implications of the fact that improvements in AI require exponentially more compute. Only one of these posts so far has been put on the EA forum. This week we've put the entire series on the Forum and made this thread for you to discuss your reactions to the posts. Toby Ord will check in once a day to respond to your comments[1]. Feel free to also comment directly on the individual posts that make

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15:16

[Linkpost] “Are the Costs of AI Agents Also Rising...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. There is an extremely important question about the near-future of AI that almost no-one is asking. We’ve all seen the graphs from METR showing that the length of tasks AI agents can perform has been growing exponentially over the last 7 years. While GPT-2 could only do software engineering tasks that would take someone a few seconds, the latest models can (50% of the time) do tasks that would take a human a few hours. As this trend shows no signs of stopping, people have

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10:01

[Linkpost] “Evidence that Recent AI Gains are Mostly...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. In the last year or two, the most important trend in modern AI came to an end. The scaling-up of computational resources used to train ever-larger AI models through next-token prediction (pre-training) stalled out. Since late 2024, we’ve seen a new trend of using reinforcement learning (RL) in the second stage of training (post-training). Through RL, the AI models learn to do superior chain-of-thought reasoning about the problem they are being asked to solve. This new era

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14:34

[Linkpost] “The Extreme Inefficiency of RL for...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. The new scaling paradigm for AI reduces the amount of information a model can learn from per hour of training by a factor of 1,000 to 1,000,000. I explore what this means and its implications for scaling. The last year has seen a massive shift in how leading AI models are trained. 2018–2023 was the era of pre-training scaling. LLMs were primarily trained by next-token prediction (also known as pre-training). Much of OpenAI's progress from GPT-1 to GPT-4, came from scaling up the

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34:49

[Linkpost] “Inference Scaling Reshapes AI Governance”...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. The shift from scaling up the pre-training compute of AI systems to scaling up their inference compute may have profound effects on AI governance. The nature of these effects depends crucially on whether this new inference compute will primarily be used during external deployment or as part of a more complex training programme within the lab. Rapid scaling of inference-at-deployment would: lower the importance of open-weight models (and of securing the weights of closed models),

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19:45

[Linkpost] “Is there a Half-Life for the Success...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. Building on the recent empirical work of Kwa et al. (2025), I show that within their suite of research-engineering tasks the performance of AI agents on longer-duration tasks can be explained by an extremely simple mathematical model — a constant rate of failing during each minute a human would take to do the task. This implies an exponentially declining success rate with the length of the task and that each agent could be characterised by its own half-life. This empirical

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16:32

[Linkpost] “Inference Scaling and the Log-x Chart” by...

EA Forum Podcast (Curated & popular) ·

2026/02/02

This is a link post. Improving model performance by scaling up inference compute is the next big thing in frontier AI. But the charts being used to trumpet this new paradigm can be misleading. While they initially appear to show steady scaling and impressive performance for models like o1 and o3, they really show poor scaling (characteristic of brute force) and little evidence of improvement between o1 and o3. I explore how to interpret these new charts and what evidence for strong scaling and

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16:16

[Linkpost] “The Scaling Paradox” by Toby_Ord

EA Forum Podcast (Curated & popular) ·

2026/01/30

This is a link post. AI capabilities have improved remarkably quickly, fuelled by the explosive scale-up of resources being used to train the leading models. But if you examine the scaling laws that inspired this rush, they actually show extremely poor returns to scale. What's going on? AI Scaling is Shockingly Impressive The era of LLMs has seen remarkable improvements in AI capabilities over a very short time. This is often attributed to the AI scaling laws — statistical relationships which govern

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32:02

“Leaving Open Philanthropy, going to Anthropic” by...

EA Forum Podcast (Curated & popular) ·

2025/11/06

(Audio version, read by the author, here, or search for "Joe Carlsmith Audio" on your podcast app.) Last Friday was my last day at Open Philanthropy. I’ll be starting a new role at Anthropic in mid-November, helping with the design of Claude's character/constitution/spec. This post reflects on my time at Open Philanthropy, and it goes into more detail about my perspective and intentions with respect to Anthropic – including some of my takes on AI-safety-focused people working at frontier AI

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5:59

“My EA Senescence” by Michael_PJ

EA Forum Podcast (Curated & popular) ·

2025/10/21

I have some claim to be an “old hand” EA:[1] I was in the room when the creation Giving What We Can was announced (although I vacillated about joining for quite a while) I first went to EA Global in 2015 I worked on anot-very successful EA project for a while But I have not really been much involved in the community since about 2020. The interesting thing about this is that my withdrawal from the community has nothing to do with disagreements, personal conflicts, or FTX. I still pretty much agree

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37:35

“Effective altruism in the age of AGI” by...

EA Forum Podcast (Curated & popular) ·

2025/10/10

This post is based on a memo I wrote for this year's Meta Coordination Forum. See also Arden Koehler's recent post, which hits a lot of similar notes. Summary The EA movement stands at a crossroads. In light of AI's very rapid progress, and the rise of the AI safety movement, some people view EA as a legacy movement set to fade away; others think we should refocus much more on “classic” cause areas like global health and animal welfare. I argue for a third way: EA should embrace the mission of

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10:24

“Charity Entrepreneurship is bottlenecked by a lack...

EA Forum Podcast (Curated & popular) ·

2025/10/01

TL;DR - AIM's applicants skew towards global health & development. We’ve recommended four new animal welfare charities, have the capacity to launch all four, but expect to struggle to find the talent to do so. If you’ve considered moving into animal welfare work, applying to Charity Entrepreneurship to launch a new charity in the space could be of huge counterfactual value. Part 1: Why you should launch an animal welfare charity Our existing animal charities have had a lot of impact—improving

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9:35

“Why You Should Build Your Own EA Internship Abroad”...

EA Forum Podcast (Curated & popular) ·

2025/07/28

I am writing this to reflect on my experience interning with the Fish Welfare Initiative, and to provide my thoughts on why more students looking to build EA experience should do something similar. Back in October, I cold-emailed the Fish Welfare Initiative (FWI) with my resume and a short cover letter expressing interest in an unpaid in-person internship in the summer of 2025. I figured I had a better chance of getting an internship by building my own door than competing with hundreds of others

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45:34

“We should be more uncertain about cause...

EA Forum Podcast (Curated & popular) ·

2025/07/11

Summary In this article, I argue most of the interesting cross-cause prioritization decisions and conclusions rest on philosophical evidence that isn’t robust enough to justify high degrees of certainty that any given intervention (or class of cause interventions) is “best” above all others. I hold this to be true generally because of the reliance of such cross-cause prioritization judgments on relatively weak philosophical evidence. In particular, the case for high confidence in conclusions on

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5:38

“80,000 Hours is producing AI in Context — a new...

EA Forum Podcast (Curated & popular) ·

2025/07/10

About the program Hi! We’re Chana and Aric, from the new 80,000 Hours video program. For over a decade, 80,000 Hours has been talking about the world's most pressing problems in newsletters, articles and many extremely lengthy podcasts.But today's world calls for video, so we’ve started a video program[1], and we’re so excited to tell you about it! 80,000 Hours is launching AI in Context, a new YouTube channel hosted by Aric Floyd. Together with associated Instagram and TikTok accounts, the channel

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38:04

“A shallow review of what transformative AI means for...

EA Forum Podcast (Curated & popular) ·

2025/07/10

Epistemic status: This post — the result of a loosely timeboxed ~2-day sprint[1] — is more like “research notes with rough takes” than “report with solid answers.” You should interpret the things we say as best guesses, and not give them much more weight than that.Summary There's been some discussion of what “transformative AI may arrive soon” might mean for animal advocates. After a very shallow review, we’ve tentatively concluded that radical changes to the animal welfare (AW) field are not yet

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72:36

[Linkpost] “A deep critique of AI 2027’s bad timeline...

EA Forum Podcast (Curated & popular) ·

2025/06/19

This is a link post. Thank you to Arepo and Eli Lifland for looking over this article for errors. I am sorry that this article is so long. Every time I thought I was done with it I ran into more issues with the model, and I wanted to be as thorough as I could. I’m not going to blame anyone for skimming parts of this article. Note that the majority of this article was written before Eli's updated model was released (the site was updated june 8th). His new model improves on some of my objections,

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5:16

“Revamped effectivealtruism.org” by Agnes Stenlund 🔸

EA Forum Podcast (Curated & popular) ·

2025/05/28

We’ve redesigned effectivealtruism.org to improve understanding and perception of effective altruism, and make it easier to take action. View the new site → I led the redesign and will be writing in the first person here, but many others contributed research, feedback, writing, editing, and development. I’d love to hear what you think, here is a feedback form. Redesign goals This redesign is part of CEA's broader efforts to improve how effective altruism is understood and perceived. I focused on

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7:19

“ALLFED emergency appeal: Help us raise $800,000 to...

EA Forum Podcast (Curated & popular) ·

2025/04/18

SUMMARY: ALLFED is launching an emergency appeal on the EA Forum due to a serious funding shortfall. Without new support, ALLFED will be forced to cut half our budget in the coming months, drastically reducing our capacity to help build global food system resilience for catastrophic scenarios like nuclear winter, a severe pandemic, or infrastructure breakdown. ALLFED is seeking $800,000 over the course of 2025 to sustain its team, continue policy-relevant research, and move forward with pilot

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5:30

“Introducing The Spending What We Must Pledge” by...

EA Forum Podcast (Curated & popular) ·

2025/04/01

Epistemic status: highly certain, or something The Spending What We Must 💸11% pledge In short: Members pledge to spend at least 11% of their income on effectively increasing their own productivity. This pledge is likely higher-impact for most people than the Giving What We Can 🔸10% Pledge, and we also think the name accurately reflects the non-supererogatory moral beliefs of many in the EA community. Example Charlie is a software engineer for the Centre for Effective Future Research. Since

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77 results

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