Player FM - Internet Radio Done Right
12 subscribers
Checked 5h ago
Aggiunto tre anni fa
Content provided by LessWrong. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LessWrong or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Player FM - Podcast App
Go offline with the Player FM app!
Go offline with the Player FM app!
Podcasts Worth a Listen
SPONSORED
Living together in a group is a strategy many animals use to survive and thrive. And a big part of what makes that living situation successful is listening. In this episode, we explore the collaborative world of the naked mole rat. Threshold is nonprofit, listener-supported, and independently produced. You can support Threshold by donating today . To stay connected, sign up for our newsletter . Operation frog sound! Send us your frog sounds for an upcoming episode. We want you to go out, listen for frogs and toads, and record them. Just find someone croaking, and hit record on your phone. It doesn’t matter if there’s background noise. It doesn’t even matter if you’re not sure whether or not you’re hearing an amphibian—if you think you are, we would love to get a recording from you. Please also say your name and where you are in the world, and then email the recording to us at outreach@thresholdpodcast.org…
“A History of the Future, 2025-2040” by L Rudolf L
Manage episode 467328892 series 3364758
Content provided by LessWrong. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LessWrong or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
This is an all-in-one crosspost of a scenario I originally published in three parts on my blog (No Set Gauge). Links to the originals:
Thanks to Luke Drago, Duncan McClements, and Theo Horsley for comments on all three parts.
2025-2027
Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it's definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends.
Open Sky. (Zdislaw Beksinsksi) The return of reinforcement learning
From 2019 to 2023, the main driver of AI was using more compute and data for pretraining. This was combined with some important "unhobblings":
Outline:
(00:34) 2025-2027
(01:04) The return of reinforcement learning
(10:52) Codegen, Big Tech, and the internet
(21:07) Business strategy in 2025 and 2026
(27:23) Maths and the hard sciences
(33:59) Societal response
(37:18) Alignment research and AI-run orgs
(44:49) Government wakeup
(51:42) 2027-2030
(51:53) The AGI frog is getting boiled
(01:02:18) The bitter law of business
(01:06:52) The early days of the robot race
(01:10:12) The digital wonderland, social movements, and the AI cults
(01:24:09) AGI politics and the chip supply chain
(01:33:04) 2030-2040
(01:33:15) The end of white-collar work and the new job scene
(01:47:47) Lab strategy amid superintelligence and robotics
(01:56:28) Towards the automated robot economy
(02:15:49) The human condition in the 2030s
(02:17:26) 2040+
---
First published:
February 17th, 2025
Source:
https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040
---
Narrated by TYPE III AUDIO.
---
…
continue reading
- A History of the Future, 2025-2027
- A History of the Future, 2027-2030
- A History of the Future, 2030-2040
Thanks to Luke Drago, Duncan McClements, and Theo Horsley for comments on all three parts.
2025-2027
Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it's definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends.
Open Sky. (Zdislaw Beksinsksi) The return of reinforcement learning
From 2019 to 2023, the main driver of AI was using more compute and data for pretraining. This was combined with some important "unhobblings":
- Post-training (supervised fine-tuning and reinforcement learning for [...]
Outline:
(00:34) 2025-2027
(01:04) The return of reinforcement learning
(10:52) Codegen, Big Tech, and the internet
(21:07) Business strategy in 2025 and 2026
(27:23) Maths and the hard sciences
(33:59) Societal response
(37:18) Alignment research and AI-run orgs
(44:49) Government wakeup
(51:42) 2027-2030
(51:53) The AGI frog is getting boiled
(01:02:18) The bitter law of business
(01:06:52) The early days of the robot race
(01:10:12) The digital wonderland, social movements, and the AI cults
(01:24:09) AGI politics and the chip supply chain
(01:33:04) 2030-2040
(01:33:15) The end of white-collar work and the new job scene
(01:47:47) Lab strategy amid superintelligence and robotics
(01:56:28) Towards the automated robot economy
(02:15:49) The human condition in the 2030s
(02:17:26) 2040+
---
First published:
February 17th, 2025
Source:
https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040
---
Narrated by TYPE III AUDIO.
---
485 episodes
Manage episode 467328892 series 3364758
Content provided by LessWrong. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by LessWrong or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
This is an all-in-one crosspost of a scenario I originally published in three parts on my blog (No Set Gauge). Links to the originals:
Thanks to Luke Drago, Duncan McClements, and Theo Horsley for comments on all three parts.
2025-2027
Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it's definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends.
Open Sky. (Zdislaw Beksinsksi) The return of reinforcement learning
From 2019 to 2023, the main driver of AI was using more compute and data for pretraining. This was combined with some important "unhobblings":
Outline:
(00:34) 2025-2027
(01:04) The return of reinforcement learning
(10:52) Codegen, Big Tech, and the internet
(21:07) Business strategy in 2025 and 2026
(27:23) Maths and the hard sciences
(33:59) Societal response
(37:18) Alignment research and AI-run orgs
(44:49) Government wakeup
(51:42) 2027-2030
(51:53) The AGI frog is getting boiled
(01:02:18) The bitter law of business
(01:06:52) The early days of the robot race
(01:10:12) The digital wonderland, social movements, and the AI cults
(01:24:09) AGI politics and the chip supply chain
(01:33:04) 2030-2040
(01:33:15) The end of white-collar work and the new job scene
(01:47:47) Lab strategy amid superintelligence and robotics
(01:56:28) Towards the automated robot economy
(02:15:49) The human condition in the 2030s
(02:17:26) 2040+
---
First published:
February 17th, 2025
Source:
https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040
---
Narrated by TYPE III AUDIO.
---
…
continue reading
- A History of the Future, 2025-2027
- A History of the Future, 2027-2030
- A History of the Future, 2030-2040
Thanks to Luke Drago, Duncan McClements, and Theo Horsley for comments on all three parts.
2025-2027
Below is part 1 of an extended scenario describing how the future might go if current trends in AI continue. The scenario is deliberately extremely specific: it's definite rather than indefinite, and makes concrete guesses instead of settling for banal generalities or abstract descriptions of trends.
Open Sky. (Zdislaw Beksinsksi) The return of reinforcement learning
From 2019 to 2023, the main driver of AI was using more compute and data for pretraining. This was combined with some important "unhobblings":
- Post-training (supervised fine-tuning and reinforcement learning for [...]
Outline:
(00:34) 2025-2027
(01:04) The return of reinforcement learning
(10:52) Codegen, Big Tech, and the internet
(21:07) Business strategy in 2025 and 2026
(27:23) Maths and the hard sciences
(33:59) Societal response
(37:18) Alignment research and AI-run orgs
(44:49) Government wakeup
(51:42) 2027-2030
(51:53) The AGI frog is getting boiled
(01:02:18) The bitter law of business
(01:06:52) The early days of the robot race
(01:10:12) The digital wonderland, social movements, and the AI cults
(01:24:09) AGI politics and the chip supply chain
(01:33:04) 2030-2040
(01:33:15) The end of white-collar work and the new job scene
(01:47:47) Lab strategy amid superintelligence and robotics
(01:56:28) Towards the automated robot economy
(02:15:49) The human condition in the 2030s
(02:17:26) 2040+
---
First published:
February 17th, 2025
Source:
https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040
---
Narrated by TYPE III AUDIO.
---
485 episodes
All episodes
×
1 “You will crash your car in front of my house within the next week” by Richard Korzekwa 1:52
1:52
Play Later
Play Later
Lists
Like
Liked1:52
I'm not writing this to alarm anyone, but it would be irresponsible not to report on something this important. On current trends, every car will be crashed in front of my house within the next week. Here's the data: Until today, only two cars had crashed in front of my house, several months apart, during the 15 months I have lived here. But a few hours ago it happened again, mere weeks from the previous crash. This graph may look harmless enough, but now consider the frequency of crashes this implies over time: The car crash singularity will occur in the early morning hours of Monday, April 7. As crash frequency approaches infinity, every car will be involved. You might be thinking that the same car could be involved in multiple crashes. This is true! But the same car can only withstand a finite number of crashes before it [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/FjPWbLdoP4PLDivYT/you-will-crash-your-car-in-front-of-my-house-within-the-next --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

1 “My ‘infohazards small working group’ Signal Chat may have encountered minor leaks” by Linch 10:33
10:33
Play Later
Play Later
Lists
Like
Liked10:33
Remember: There is no such thing as a pink elephant. Recently, I was made aware that my “infohazards small working group” Signal chat, an informal coordination venue where we have frank discussions about infohazards and why it will be bad if specific hazards were leaked to the press or public, accidentally was shared with a deceitful and discredited so-called “journalist,” Kelsey Piper. She is not the first person to have been accidentally sent sensitive material from our group chat, however she is the first to have threatened to go public about the leak. Needless to say, mistakes were made. We’re still trying to figure out the source of this compromise to our secure chat group, however we thought we should give the public a live update to get ahead of the story. For some context the “infohazards small working group” is a casual discussion venue for the [...] --- Outline: (04:46) Top 10 PR Issues With the EA Movement (major) (05:34) Accidental Filtration of Simple Sabotage Manual for Rebellious AIs (medium) (08:25) Hidden Capabilities Evals Leaked In Advance to Bioterrorism Researchers and Leaders (minor) (09:34) Conclusion --- First published: April 2nd, 2025 Source: https://www.lesswrong.com/posts/xPEfrtK2jfQdbpq97/my-infohazards-small-working-group-signal-chat-may-have --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

1 “Leverage, Exit Costs, and Anger: Re-examining Why We Explode at Home, Not at Work” by at_the_zoo 6:16
6:16
Play Later
Play Later
Lists
Like
Liked6:16
Let's cut through the comforting narratives and examine a common behavioral pattern with a sharper lens: the stark difference between how anger is managed in professional settings versus domestic ones. Many individuals can navigate challenging workplace interactions with remarkable restraint, only to unleash significant anger or frustration at home shortly after. Why does this disparity exist? Common psychological explanations trot out concepts like "stress spillover," "ego depletion," or the home being a "safe space" for authentic emotions. While these factors might play a role, they feel like half-truths—neatly packaged but ultimately failing to explain the targeted nature and intensity of anger displayed at home. This analysis proposes a more unsentimental approach, rooted in evolutionary biology, game theory, and behavioral science: leverage and exit costs. The real question isn’t just why we explode at home—it's why we so carefully avoid doing so elsewhere. The Logic of Restraint: Low Leverage in [...] --- Outline: (01:14) The Logic of Restraint: Low Leverage in Low-Exit-Cost Environments (01:58) The Home Environment: High Stakes and High Exit Costs (02:41) Re-evaluating Common Explanations Through the Lens of Leverage (04:42) The Overlooked Mechanism: Leveraging Relational Constraints --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/G6PTtsfBpnehqdEgp/leverage-exit-costs-and-anger-re-examining-why-we-explode-at --- Narrated by TYPE III AUDIO .…

1 “PauseAI and E/Acc Should Switch Sides” by WillPetillo 3:31
3:31
Play Later
Play Later
Lists
Like
Liked3:31
In the debate over AI development, two movements stand as opposites: PauseAI calls for slowing down AI progress, and e/acc (effective accelerationism) calls for rapid advancement. But what if both sides are working against their own stated interests? What if the most rational strategy for each would be to adopt the other's tactics—if not their ultimate goals? AI development speed ultimately comes down to policy decisions, which are themselves downstream of public opinion. No matter how compelling technical arguments might be on either side, widespread sentiment will determine what regulations are politically viable. Public opinion is most powerfully mobilized against technologies following visible disasters. Consider nuclear power: despite being statistically safer than fossil fuels, its development has been stagnant for decades. Why? Not because of environmental activists, but because of Chernobyl, Three Mile Island, and Fukushima. These disasters produce visceral public reactions that statistics cannot overcome. Just as people [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/fZebqiuZcDfLCgizz/pauseai-and-e-acc-should-switch-sides --- Narrated by TYPE III AUDIO .…

1 “VDT: a solution to decision theory” by L Rudolf L 8:58
8:58
Play Later
Play Later
Lists
Like
Liked8:58
Introduction Decision theory is about how to behave rationally under conditions of uncertainty, especially if this uncertainty involves being acausally blackmailed and/or gaslit by alien superintelligent basilisks. Decision theory has found numerous practical applications, including proving the existence of God and generating endless LessWrong comments since the beginning of time. However, despite the apparent simplicity of "just choose the best action", no comprehensive decision theory that resolves all decision theory dilemmas has yet been formalized. This paper at long last resolves this dilemma, by introducing a new decision theory: VDT. Decision theory problems and existing theories Some common existing decision theories are: Causal Decision Theory (CDT): select the action that *causes* the best outcome. Evidential Decision Theory (EDT): select the action that you would be happiest to learn that you had taken. Functional Decision Theory (FDT): select the action output by the function such that if you take [...] --- Outline: (00:53) Decision theory problems and existing theories (05:37) Defining VDT (06:34) Experimental results (07:48) Conclusion --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/LcjuHNxubQqCry9tT/vdt-a-solution-to-decision-theory --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

1 “LessWrong has been acquired by EA” by habryka 1:33
1:33
Play Later
Play Later
Lists
Like
Liked1:33
Dear LessWrong community, It is with a sense of... considerable cognitive dissonance that I announce a significant development regarding the future trajectory of LessWrong. After extensive internal deliberation, modeling of potential futures, projections of financial runways, and what I can only describe as a series of profoundly unexpected coordination challenges, the Lightcone Infrastructure team has agreed in principle to the acquisition of LessWrong by EA. I assure you, nothing about how LessWrong operates on a day to day level will change. I have always cared deeply about the robustness and integrity of our institutions, and I am fully aligned with our stakeholders at EA. To be honest, the key thing that EA brings to the table is money and talent. While the recent layoffs in EAs broader industry have been harsh, I have full trust in the leadership of Electronic Arts, and expect them to bring great expertise [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/2NGKYt3xdQHwyfGbc/lesswrong-has-been-acquired-by-ea --- Narrated by TYPE III AUDIO .…

1 “We’re not prepared for an AI market crash” by Remmelt 3:46
3:46
Play Later
Play Later
Lists
Like
Liked3:46
Our community is not prepared for an AI crash. We're good at tracking new capability developments, but not as much the company financials. Currently, both OpenAI and Anthropic are losing $5 billion+ a year, while under threat of losing users to cheap LLMs. A crash will weaken the labs. Funding-deprived and distracted, execs struggle to counter coordinated efforts to restrict their reckless actions. Journalists turn on tech darlings. Optimism makes way for mass outrage, for all the wasted money and reckless harms. You may not think a crash is likely. But if it happens, we can turn the tide. Preparing for a crash is our best bet.[1] But our community is poorly positioned to respond. Core people positioned themselves inside institutions – to advise on how to maybe make AI 'safe', under the assumption that models rapidly become generally useful. After a crash, this no longer works, for at [...] --- First published: April 1st, 2025 Source: https://www.lesswrong.com/posts/aMYFHnCkY4nKDEqfK/we-re-not-prepared-for-an-ai-market-crash --- Narrated by TYPE III AUDIO .…
Epistemic status: Reasonably confident in the basic mechanism. Have you noticed that you keep encountering the same ideas over and over? You read another post, and someone helpfully points out it's just old Paul's idea again. Or Eliezer's idea. Not much progress here, move along. Or perhaps you've been on the other side: excitedly telling a friend about some fascinating new insight, only to hear back, "Ah, that's just another version of X." And something feels not quite right about that response, but you can't quite put your finger on it. I want to propose that while ideas are sometimes genuinely that repetitive, there's often a sneakier mechanism at play. I call it Conceptual Rounding Errors – when our mind's necessary compression goes a bit too far . Too much compression A Conceptual Rounding Error occurs when we encounter a new mental model or idea that's partially—but not fully—overlapping [...] --- Outline: (01:00) Too much compression (01:24) No, This Isnt The Old Demons Story Again (02:52) The Compression Trade-off (03:37) More of this (04:15) What Can We Do? (05:28) When It Matters --- First published: March 26th, 2025 Source: https://www.lesswrong.com/posts/FGHKwEGKCfDzcxZuj/conceptual-rounding-errors --- Narrated by TYPE III AUDIO .…

1 “Tracing the Thoughts of a Large Language Model” by Adam Jermyn 22:18
22:18
Play Later
Play Later
Lists
Like
Liked22:18
[This is our blog post on the papers, which can be found at https://transformer-circuits.pub/2025/attribution-graphs/biology.html and https://transformer-circuits.pub/2025/attribution-graphs/methods.html.] Language models like Claude aren't programmed directly by humans—instead, they‘re trained on large amounts of data. During that training process, they learn their own strategies to solve problems. These strategies are encoded in the billions of computations a model performs for every word it writes. They arrive inscrutable to us, the model's developers. This means that we don’t understand how models do most of the things they do. Knowing how models like Claude think would allow us to have a better understanding of their abilities, as well as help us ensure that they’re doing what we intend them to. For example: Claude can speak dozens of languages. What language, if any, is it using "in its head"? Claude writes text one word at a time. Is it only focusing on predicting the [...] --- Outline: (06:02) How is Claude multilingual? (07:43) Does Claude plan its rhymes? (09:58) Mental Math (12:04) Are Claude's explanations always faithful? (15:27) Multi-step Reasoning (17:09) Hallucinations (19:36) Jailbreaks --- First published: March 27th, 2025 Source: https://www.lesswrong.com/posts/zsr4rWRASxwmgXfmq/tracing-the-thoughts-of-a-large-language-model --- Narrated by TYPE III AUDIO . --- Images from the article:…

1 “Recent AI model progress feels mostly like bullshit” by lc 14:29
14:29
Play Later
Play Later
Lists
Like
Liked14:29
About nine months ago, I and three friends decided that AI had gotten good enough to monitor large codebases autonomously for security problems. We started a company around this, trying to leverage the latest AI models to create a tool that could replace at least a good chunk of the value of human pentesters. We have been working on this project since since June 2024. Within the first three months of our company's existence, Claude 3.5 sonnet was released. Just by switching the portions of our service that ran on gpt-4o, our nascent internal benchmark results immediately started to get saturated. I remember being surprised at the time that our tooling not only seemed to make fewer basic mistakes, but also seemed to qualitatively improve in its written vulnerability descriptions and severity estimates. It was as if the models were better at inferring the intent and values behind our [...] --- Outline: (04:44) Are the AI labs just cheating? (07:22) Are the benchmarks not tracking usefulness? (10:28) Are the models smart, but bottlenecked on alignment? --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/4mvphwx5pdsZLMmpY/recent-ai-model-progress-feels-mostly-like-bullshit --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…
(Audio version here (read by the author), or search for "Joe Carlsmith Audio" on your podcast app. This is the fourth essay in a series that I’m calling “How do we solve the alignment problem?”. I’m hoping that the individual essays can be read fairly well on their own, but see this introduction for a summary of the essays that have been released thus far, and for a bit more about the series as a whole.) 1. Introduction and summary In my last essay, I offered a high-level framework for thinking about the path from here to safe superintelligence. This framework emphasized the role of three key “security factors” – namely: Safety progress: our ability to develop new levels of AI capability safely, Risk evaluation: our ability to track and forecast the level of risk that a given sort of AI capability development involves, and Capability restraint [...] --- Outline: (00:27) 1. Introduction and summary (03:50) 2. What is AI for AI safety? (11:50) 2.1 A tale of two feedback loops (13:58) 2.2 Contrast with need human-labor-driven radical alignment progress views (16:05) 2.3 Contrast with a few other ideas in the literature (18:32) 3. Why is AI for AI safety so important? (21:56) 4. The AI for AI safety sweet spot (26:09) 4.1 The AI for AI safety spicy zone (28:07) 4.2 Can we benefit from a sweet spot? (29:56) 5. Objections to AI for AI safety (30:14) 5.1 Three core objections to AI for AI safety (32:00) 5.2 Other practical concerns The original text contained 39 footnotes which were omitted from this narration. --- First published: March 14th, 2025 Source: https://www.lesswrong.com/posts/F3j4xqpxjxgQD3xXh/ai-for-ai-safety --- Narrated by TYPE III AUDIO . --- Images from the article:…

1 “Policy for LLM Writing on LessWrong” by jimrandomh 4:17
4:17
Play Later
Play Later
Lists
Like
Liked4:17
LessWrong has been receiving an increasing number of posts and contents that look like they might be LLM-written or partially-LLM-written, so we're adopting a policy. This could be changed based on feedback. Humans Using AI as Writing or Research Assistants Prompting a language model to write an essay and copy-pasting the result will not typically meet LessWrong's standards. Please do not submit unedited or lightly-edited LLM content. You can use AI as a writing or research assistant when writing content for LessWrong, but you must have added significant value beyond what the AI produced, the result must meet a high quality standard, and you must vouch for everything in the result. A rough guideline is that if you are using AI for writing assistance, you should spend a minimum of 1 minute per 50 words (enough to read the content several times and perform significant edits), you should not [...] --- Outline: (00:22) Humans Using AI as Writing or Research Assistants (01:13) You Can Put AI Writing in Collapsible Sections (02:13) Quoting AI Output In Order to Talk About AI (02:47) Posts by AI Agents --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/KXujJjnmP85u8eM6B/policy-for-llm-writing-on-lesswrong --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

1 “Will Jesus Christ return in an election year?” by Eric Neyman 7:48
7:48
Play Later
Play Later
Lists
Like
Liked7:48
Thanks to Jesse Richardson for discussion. Polymarket asks: will Jesus Christ return in 2025? In the three days since the market opened, traders have wagered over $100,000 on this question. The market traded as high as 5%, and is now stably trading at 3%. Right now, if you wanted to, you could place a bet that Jesus Christ will not return this year, and earn over $13,000 if you're right. There are two mysteries here: an easy one, and a harder one. The easy mystery is: if people are willing to bet $13,000 on "Yes", why isn't anyone taking them up? The answer is that, if you wanted to do that, you'd have to put down over $1 million of your own money, locking it up inside Polymarket through the end of the year. At the end of that year, you'd get 1% returns on your investment. [...] --- First published: March 24th, 2025 Source: https://www.lesswrong.com/posts/LBC2TnHK8cZAimdWF/will-jesus-christ-return-in-an-election-year --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.…

1 “Good Research Takes are Not Sufficient for Good Strategic Takes” by Neel Nanda 6:58
6:58
Play Later
Play Later
Lists
Like
Liked6:58
TL;DR Having a good research track record is some evidence of good big-picture takes, but it's weak evidence. Strategic thinking is hard, and requires different skills. But people often conflate these skills, leading to excessive deference to researchers in the field, without evidence that that person is good at strategic thinking specifically. Introduction I often find myself giving talks or Q&As about mechanistic interpretability research. But inevitably, I'll get questions about the big picture: "What's the theory of change for interpretability?", "Is this really going to help with alignment?", "Does any of this matter if we can’t ensure all labs take alignment seriously?". And I think people take my answers to these way too seriously. These are great questions, and I'm happy to try answering them. But I've noticed a bit of a pathology: people seem to assume that because I'm (hopefully!) good at the research, I'm automatically well-qualified [...] --- Outline: (00:32) Introduction (02:45) Factors of Good Strategic Takes (05:41) Conclusion --- First published: March 22nd, 2025 Source: https://www.lesswrong.com/posts/P5zWiPF5cPJZSkiAK/good-research-takes-are-not-sufficient-for-good-strategic --- Narrated by TYPE III AUDIO .…
When my son was three, we enrolled him in a study of a vision condition that runs in my family. They wanted us to put an eyepatch on him for part of each day, with a little sensor object that went under the patch and detected body heat to record when we were doing it. They paid for his first pair of glasses and all the eye doctor visits to check up on how he was coming along, plus every time we brought him in we got fifty bucks in Amazon gift credit. I reiterate, he was three. (To begin with. His fourth birthday occurred while the study was still ongoing.) So he managed to lose or destroy more than half a dozen pairs of glasses and we had to start buying them in batches to minimize glasses-less time while waiting for each new Zenni delivery. (The [...] --- First published: March 20th, 2025 Source: https://www.lesswrong.com/posts/yRJ5hdsm5FQcZosCh/intention-to-treat --- Narrated by TYPE III AUDIO .…
Welcome to Player FM!
Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.