PODCAST

LessWrong (30+ Karma)

LessWrong

Audio narrations of LessWrong posts.

technology philosophy

All Episodes

4:05

[Linkpost] “How to make better AI art with current...

LessWrong (30+ Karma) ·

2025/09/05

This is a link post. AI image-generation models I’ve tried Midjourney is best at producing a diverse and aesthetically pleasing range of styles and doesn’t refuse “in the style of…” requests. However, it is worst at text-in-images, avoiding uncanny AI artifacts (like extra fingers or unrealistic postures), and precise instruction-following (it messes up the specifics). Another major downside is that they don’t offer an API. GPT-5 produces less artistic outputs but is better at following precise

en-gb

9:47

“30 Days of Retatrutide” by Brendan Long

LessWrong (30+ Karma) ·

2025/09/04

I've had trouble maintaining my weight since high school. If I eat "normally", I slowly gain weight, and if I eat nothing but a specific potato casserole, I slowly lose weight. Recently, I hit a new high-record weight and decided it was finally time to do something more serious about it, so for the last month I've been taking the standard CICO diet advice. I finally realized that I should eat healthier, and eat significantly less. I work out slightly more. I cut out most high-fat foods and became

en-gb

29:21

“From SLT to AIT: NN generalisation...

LessWrong (30+ Karma) ·

2025/09/04

Audio note: this article contains 288 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description. TL;DR: This post derives an upper bound on the generalization error for Bayesian learning on neural networks. Unlike the bound from vanilla Singular Learning Theory (SLT), this bound also holds for out-of-distribution generalization, not just for in-distribution generalization. Along the way, it shows some connections between

en-gb

11:57

“‘I’d accepted losing my husband, until others...

LessWrong (30+ Karma) ·

2025/09/04

Note: While this article presents one possibility for how the future may play out, it should not be taken as a specific prediction by either the author or the Brain Preservation Foundation. Amy Robertson-Wong August 18, 2085 ‘My husband had only died because saving his life would have been too weird.’ Annabel Walker had this realisation earlier this year after watching a video of Marcus Chen, a retired primary school teacher, sitting on a bed. His face is slack with relief, and teary-eyed family

en-gb

3:14

“Three main views on the future of AI” by Alex...

LessWrong (30+ Karma) ·

2025/09/04

Expert opinions about future AI development span a wide range, from predictions that we will reach ASI soon and then humanity goes extinct, to predictions that AI progress will plateau soon, resulting in weaker AI that presents much more mundane risks and benefits. However, non-experts often encounter only a single narrative, depending on things like their social circles and social media feed.In our paper, we propose a taxonomy that divides expert views on AIs into three main clusters. We hope to

en-gb

41:52

“Natural Latents: Latent Variables Stable Across...

LessWrong (30+ Karma) ·

2025/09/04

Audio note: this article contains 369 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description. There's a details box here with the title "Background on where this post/paper came from". The box contents are omitted from this narration. This post is an overhaul of (and large improvement to) a paper we wrote about a year ago. The pdf version will hopefully be up on arxiv shortly, and we will link that from here once it's

en-gb

14:03

“Trust me bro, just one more RL scale up, this one...

LessWrong (30+ Karma) ·

2025/09/03

I've recently written about how I've updated against seeing substantially faster than trend AI progress due to quickly massively scaling up RL on agentic software engineering. One response I've heard is something like:RL scale-ups so far have used very crappy environments due to difficulty quickly sourcing enough decent (or even high quality) environments. Thus, once AI companies manage to get their hands on actually good RL environments (which could happen pretty quickly), performance will

en-gb

4:52

“When Both People Are Interested, How Often Is...

LessWrong (30+ Karma) ·

2025/09/03

Here are two models of “the norm” when it comes to flirtatious escalation, assuming both people are in fact interested: “Mutual Escalation”: both people go back-and-forth making gradually more escalative moves. One might tend to escalate first, but the other will at least match escalation level. “Active/Passive”: one person makes roughly all of the escalative moves. The other person passively approves/disapproves, and the active participant tracks their approval when deciding to dial up/down

en-gb

107:01

“How To Become A Mechanistic Interpretability...

LessWrong (30+ Karma) ·

2025/09/03

Note: If you’ll forgive the shameless self-promotion, applications for my MATS stream are open until Sept 12. I help people write a mech interp paper, often accept promising people new to mech interp, and alumni often have careers as mech interp researchers. If you’re interested in this post I recommend applying! The application should be educational whatever happens: you spend a weekend doing a small mech interp research project, and show me what you learned. Last updated Sept 2 2025TL;DR This

en-gb

4:37

“Simulating the *rest* of the political disagreement”...

LessWrong (30+ Karma) ·

2025/09/02

There's a mistake I made a couple times and didn't really internalize the lesson as fast as I'd like. Moreover, it wasn't even a failure to generalize, it was basically a failure to even have a single update stick about a single situation. The particular example was me saying, roughly: Look, I'm 60%+ on "Alignment is quite hard, in a way that's unlikely to be solved without a 6+ year pause." I can imagine believing it was lower, but it feels crazy to me to think it's lower than like 15%. And at

en-gb

7:02

“%CPU Utilization Is A Lie” by Brendan Long

LessWrong (30+ Karma) ·

2025/09/02

I deal with a lot of servers at work, and one thing everyone wants to know about their servers is how close they are to being at max utilization. It should be easy, right? Just pull up top or another system monitor tool, look at network, memory and CPU utilization, and whichever one is the highest tells you how close you are to the limits.For example, this machine is at 50% CPU utilization, so it can probably do twice as much of whatever it's doing. And yet, whenever people actually try to project

en-gb

5:48

“But Have They Engaged With The Arguments?...

LessWrong (30+ Karma) ·

2025/09/02

There's an interestingly pernicious version of a selection effect that occurs in epistemology, where people can be led into false claims because when people try to engage with arguments, people will drop out at random steps, and past a few steps or so, the people who believe in all the arguments will have a secure-feeling position that the arguments are right, and that people who object to the arguments are (insane/ridiculous/obviously trolling), no matter whether the claim is true: What's going

en-gb

10:49

“Gradient routing is better than pretraining...

LessWrong (30+ Karma) ·

2025/09/02

Introduction What is Gradient Routing? Gradient routing controls where learning happens in neural networks by masking gradients during backpropagation. You can route specific data (like dangerous content) to designated parts of the network during training. The ERA (Expand-Route-Ablate) method adds new components to a model, routes unwanted knowledge there during training, then deletes those components - removing the capability while preserving general performance. In this article, I list three

en-gb

13:42

“xAI’s new safety framework is dreadful” by Zach...

LessWrong (30+ Karma) ·

2025/09/02

Two weeks ago, xAI finally published its Risk Management Framework and first model card. Unfortunately, the RMF effects very little risk reduction and suggests that xAI isn't thinking seriously about catastrophic risks. (The model card and strategy for preventing misuse are disappointing but much less important because they're mostly just relevant to a fraction of misuse risks.) On misalignment, "Our risk acceptance criteria for system deployment is maintaining a dishonesty rate of less than 1 out

en-gb

11:53

“Your LLM-assisted scientific breakthrough probably...

LessWrong (30+ Karma) ·

2025/09/02

Summary An increasing number of people in recent months have believed that they've made an important and novel scientific breakthrough, which they've developed in collaboration with an LLM, when they actually haven't. If you believe that you have made such a breakthrough, please consider that you might be mistaken! Many more people have been fooled than have come up with actual breakthroughs, so the smart next step is to do some sanity-checking even if you're confident that yours is real. New ideas

en-gb

4:45

[Linkpost] “The Cats are On To Something” by Hastings

LessWrong (30+ Karma) ·

2025/09/02

This is a link post. So the situation as it stands is that the fraction of the light cone expected to be filled with satisfied cats is not zero. This is already remarkable. What's more remarkable is that this was orchestrated starting nearly 5000 years ago. As far as I can tell there were three completely alien to-each-other intelligences operating in stone age Egypt: humans, cats, and the gibbering alien god that is cat evolution (henceforth the cat shoggoth.) What went down was that humans were by

en-gb

78:59

“Anthropic’s leading researchers acted as moderate...

LessWrong (30+ Karma) ·

2025/09/02

In 2021, a circle of researchers left OpenAI, after a bitter dispute with their executives. They started a competing company, Anthropic, stating that they wanted to put safety first. The safety community responded with broad support. Thought leaders recommended engineers to apply, and allied billionaires invested.[1] Anthropic's focus has shifted – from internal-only research and cautious demos of model safety and capabilities, toward commercialising models for Amazon and the military. Despite the

en-gb

3:35

“Help me understand: how do multiverse acausal trades...

LessWrong (30+ Karma) ·

2025/09/02

While I'm intrigued by the idea of acausal trading, I confess that so far I fail to see how they make sense in practice. Here I share my (unpolished) musings, in the hopes that someone can point me to a stronger (mathematically rigorous?) defense of the idea. Specifically, I've heard the claim that AI Safety should consider acausal trades over a Tegmarkian multiverse, and I want to know if there is any validity to this. Basically, I in Universe A want to trade with some agent that I imagine to live

en-gb

23:58

“⿻ Plurality & 6pack.care” by Audrey Tang

LessWrong (30+ Karma) ·

2025/09/01

(Cross-posted from speaker's notes of my talk at Deepmind today.) Good local time, everyone. I am Audrey Tang, 🇹🇼 Taiwan's Cyber Ambassador and first Digital Minister (2016-2024). It is an honor to be here with you all at Deepmind. When we discuss "AI" and "society," two futures compete. In one—arguably the default trajectory—AI supercharges conflict. In the other, it augments our ability to cooperate across differences. This means treating differences as fuel and inventing a combustion engine to

en-gb

5:46

“Should we align AI with maternal instinct?” by...

LessWrong (30+ Karma) ·

2025/09/01

Epistemic status: Philosophical argument. I'm critiquing Hinton's maternal instinct metaphor and proposing relationship-building as a better framework for thinking about alignment. This is about shifting conceptual foundations, not technical implementations. -- Geoffery Hinton recently argued that since AI will become more intelligent than humans, traditional dominance-submission models won't work for alignment. Instead, he suggests we might try building "maternal instincts" into AI systems, so

en-gb

4,486 results

LessWrong (30+ Karma)

All Episodes

Similar Podcasts

Double Tap

Double Tap Productions Inc.

Primary Technology

Stephen Robles and Jason Aten

Techlandia

Technology Association of Oregon

Eye On A.I.

Craig S. Smith

The Milk Road Show

The Milk Road Show