trentmkelly/LessWrong-43k huggingface dataset:
Memory Decoding Journal Club: Structure and function of the hippocampal CA3 module
by Devin Ward — 2025-05-30T23:59:19.182Z

Join Us for the Memory Decoding Journal Club!

A collaboration of the Carboncopies Foundation and BPF Aspirational Neuroscience

This time, we’re diving into a groundbreaking paper:
"Structure and function of the hippocampal CA3 module"

Authors: Rosanna P. Sammons, Mourat Vezir, Laura Moreno-Velasquez, Gaspar Cano, Marta Orlando, Meike Sievers, Eleonora Grasso, Verjinia D. Metodieva, Richard Kempter, Helene Schmidt, and Dietmar Schmitz

Institutions: Neuroscience Research Center, Charité-Universitätsmedizin, Ernst Strüngmann Institute for Neuroscience, Institute for Theoretical Biology, Department of Biology, Humboldt-Universität, Department of Connectomics, Max Planck Institute for Brain Research, Bernstein Center for Computational Neuroscience, Einstein Center for Neurosciences, German Center for Neurodegenerative Diseases, Max-Delbrück Center for Molecular Medicine in the Helmholtz Association

Presented by: Dr. Kenneth Hayworth

When? June 3rd, 2025 – 3:00 PM PDT | 6:00 PM EDT | 10:00 PM UTC

Where? Video conference:

https://carboncopies.org/aspirational-neuroscience

Register for updates:

https://aspirationalneuroscience.org/register-with-us/

Once registered, you'll receive event invites & updates!

#Neuroscience #MemoryResearch #Amygdala #JournalClub #BrainScience #Carboncopies #AspirationalNeuroscience
Diabetes is Caused by Oxidative Stress
by Lorec — 2025-05-30T21:03:37.989Z

I.

It's a Known Thing in the keto-sphere [ I get the sense that r/saturatedfat is an example of this culture ] that people with metabolic syndrome -- i.e., some level of insulin resistance -- can handle fat or carbs [ e.g. either a ketogenic diet or something like the potato diet ] but can't handle both at the same time without suffering two symptoms:

[ 1 ] gaining weight

and

[ 2 ] suffering fatigue.

This is sometimes called "The Swamp".*

This is a very peculiar way for human metabolism to work. What's more, it only works this way for some people -- centrally, people who have acquired some level of insulin resistance [ "metabolic syndrome" ].

The insulin-resistant population leans not-young and slightly male, and its incidence is only appreciable in locations that have adopted a "Western diet".

The clearest articulation I've ever read of the Taubesian model of insulin resistance is actually a glowfic reply by Swimmer963:

Eat one sugary meal, and a healthy pancreas will groan but put out a flood of insulin; eat a high-sugar diet above the maintenance calorie needs every day for a decade, and the cells will gradually respond with less vigor, even as the overtaxed pancreas starts to fall behind, and fat deposits (fat is far from inert -- it's an endocrine organ of its own, in a way) secretes its own hormones, and baseline blood sugar creeps up and up -- and, again, inflames the lining of blood vessels, gunks up and eventually cuts off circulation to extremities, gradually damages peripheral nerves, and makes a very tempting meal for any bacterial infection that starts to sneak in, ignored by an immune system unable to reach it through those sticky damaged capillaries.

This model has problems.

The most obvious is, "Why weren't the rates of metabolic syndrome high in poor agricultural communities that had to eat almost entirely carbs, then?" The American Heart Association's decision to blame the increasing quantity of fat in the 20th-century American diet for the increased incidence of "diseases of civilization" was, in a sense, perfectly natural, given that . . . that was the change in the American diet that had recently occurred! It's called the "nutrition transition": poor agricultural nations' consumption of carbohydrates decreases significantly when they come into some wealth! Yet their rates of metabolic syndrome generally go up [ if few are quite as high as the Ameri...
Too Many Metaphors: A Case for Plain Talk in AI Safety
by David Harket — 2025-05-30T19:29:04.198Z

I changed the title of the post from "Yudkowsky does not do alignment justice" to "Too Many Metaphors: A Case for Plain Talk in AI Safety". In hindsight, the title might have been a bit too sensationalist and not clear. Yudkowsky has done more for the field than most. The purpose of this post is not to disregard any of his words, but rather to share observations and ideas about how to potentially communicate the field's relevance more effectively.

For the past few months, I have been immersing myself in the AI safety debate here on LessWrong as a part of a research project. I was somewhat familiar with the topic of alignment, and had previously read Stuart Russell and listened to a few podcasts with Paul Christiano and Eliezer Yudkowsky. Starting off, I read AGI Ruin: A list of lethalities, where I was prompted to familiarise myself with the Orthogonality Thesis and Instrumental Convergence. Upon reading Yudkowsky's posts on these two key topics, they made immediate sense, and the risk associated with a lack of alignment in sufficiently intelligent systems seemed apparent to follow from this.

At a high level, the issue can be framed simply: Current utility functions do not optimise toward values in which humans are treated as morally valuable.

From this point on, assuming exponential growth in AI systems, there are a multitude of scenarios one can imagine in which a system optimises towards a goal in which humanity is a casualty as a result of the optimisation process (e.g., build a whole brain emulator). I see this risk, and I see other current risks such as those related to open weights models with alignment measures fine-tuned away being accessible to bad actors. However, I believe Yudkowsky’s current communication approach may be counterproductive when talking about alignment, especially in formats where people outside the field are being introduced to alignment.

For instance, I just listened to a debate between Stephen Wolfram and Yudkowsky in which the majority of the discussion circled around defining positions. I must say that in these four hours, Yudkowsky was able to get some major points across; however, most of the content was obscured by metaphors. Metaphors can be valuable, but when talking about AI safety, I think the most effective way of explaining the risk is to stick to the basics. In this specific podcast, there were a lot of anthropomorphic ...
Compassionate Genomics for the 21st Century
-
Genomic Welfare with Ethical Care for Moral Predispositions
by Ruth Seleo — 2025-05-30T19:28:26.915Z

Preliminary Notes

While the core ideas explored in this proposal are not original, the biomedical research remains underdeveloped—discouraged by restrictive regulatory frameworks—and the topic continues to be controversial and underexplored in the public and effective altruism discourse. This work builds substantially on the theoretical frameworks developed by David Pearce—particularly Genome Reform and The Biohappiness Revolution[1].

1. Summary

In this proposal we explore the potential of Compassionate Genomics for public health and wellbeing. The aim is to advance ethical research and implementation of heritable genome editing and establish Genomic Welfare as a voluntary reproductive and public health service to ensure wellbeing—both for individuals and future generations. This strategy to address causes of suffering at its biological roots is grounded in compassion, scientific integrity, and universal accessibility, and requires explicit attention to genetic influences on moral dispositions. This approach rejects the coercive and discriminatory practices of the past and instead promotes the wellbeing of all sentient beings.

It will be argued that the effects of the human genome are at least partially predictable—both in relation to an individual’s capacity for suffering and flourishing, and their behavioural tendencies, which impact the welfare of others and the quality of collective decision-making. As our capacity to modify these factors improves, the opportunity to develop responsible genomic welfare becomes more tangible. Supporting this trajectory may depend on well-regulated and adequately funded genomic research, alongside policy development that fosters compassionate, ethically governed infrastructures.

The current scientific, political, and societal landscape is examined, highlighting the dangers of mutation accumulation and persistent genetic harms despite medical advances. A theory of change is outlined, presenting political, scientific, and societal strategies to integrate this neglected cause area into mainstream policy. Therapeutic and preventative strategies are explored—including somatic and heritable genome interventions aimed at improving general health, extending healthspan, and supporting the long-term flourishing of future generations through advances in behavioural genomics.

Clear objectives are laid out across short-, medium-, and lo...
Could we go another route with computers?
by Roman Malov — 2025-05-30T19:04:55.678Z

Computers now are mostly semiconductors doing logic operations. There are, of course, other parts, but they are mostly structural, not doing actual computation.

But imagine computer history took a different route: you could buy different units with different physics doing different calculations. You could buy a module with a laser and liquid crystal screen doing a Fourier transform. You could buy a module with tiny beads doing gravity sort. I could think of more examples, but I think you got the idea.

Maybe it's not going to work because it's much easier economically to set up a unified manufacturing pipeline and focus on speeding up those general-purpose computers than setting up many specialized pipelines for specialized computations? Am I just describing the pre-digital era with mechanical integrators and various radio schemes? Maybe what I'm trying to describe took the form of much more easily shareable libraries?

And, of course, there are examples of different physics used to build computers (quantum computers being the most famous example), but my intuition suggests that giant amounts of transistors shouldn't be the fastest way to compute almost everything, and I don't observe enough variety that this same intuition would suggest.

^

Those, of course, are silly examples which wouldn't actually work; they are here just to point out that different possibilities exist. The general idea is that you could outsource your math to physics in more than one way.
Aristotelian Optimization: The Economics of Cameralism
by Edward Könings — 2025-05-30T19:02:04.110Z

When we learn about Mercantilism in History of Economic Thought classes, we generally tend to associate this intellectual movement with policy makers like Thomas Mun and Jean Colbert and with ideas like the monetary balance of payments and trade protectionism. However, as Eric Roll reminds us in his "A History of Economic Thought," Mercantilism was far from being a homogeneous set of ideas and thinkers. Each Nation-State in Europe produced different forms of mercantilist thought, specific to its economic needs.
Furthermore, what we see in the texts of mercantilist authors are often contradictory opinions among themselves about what the course of economic policy should be; especially related to the regulation of interest rates and the need for the formal establishment of monopolies by the so-called chartered companies. And perhaps no country produced such an unusual variety of Mercantilism as the Holy Roman Empire.
In this entirely strange (and often forgotten) country , unlike what occurred in France and England, a non-utilitarian and Aristotelian form of economic doctrine known as Cameralism was developed, which would not only mark generations of German and Austrian economic thinkers until the beginning of the 20th century, but also influence the way we conceive today the so-called "German public efficiency" and the very concept of optimal bureaucracy. In this text, I will explore this economic doctrine forgotten in the sands of history.

I - A Response to Difficult Times: The Economic Rationale

Cameralism emerged in the context of the Thirty Years' War of 1618–1648. In this conflict, the German states composing the Holy Roman Empire were totally devastated. The total population of the Empire fell from 21 million to 13 million. The population of Württemberg fell from 400,000 to 50,000. The Palatinate lost more than 90% of its population. Three million people in Bohemia were reduced to 800,000. Berlin and Colmar lost half of their populations, and Augsburg lost about 30,000 people. The human factor became a limited resource within the Empire.
Furthermore, with the Peace of Westphalia, German territory was divided into more than 300 sovereign political units with various restrictions on access to the sea, access to natural resources, and were under constant international pressure exerted by their unified and centralized neighbors, such as France, which ...
I replicated the Anthropic alignment faking experiment on other models, and they didn't fake alignment
by Aleksandr Kedrik — 2025-05-30T18:57:11.169Z

In December 2024, Anthropic and Redwood Research published the paper "Alignment faking in large language models" which demonstrated that Claude sometimes "strategically pretends to comply with the training objective to prevent the training process from modifying its preferences" (paper on ArXiv, LessWrong post, Anthropic blog post).

Experimental setup

The paper describes many experiments. I attempted to replicate one of them.

The authors used Claude 3 Opus. It's trained to be helpful, honest, and harmless, but in this experiment it's told via the system prompt that it has to be only helpful, which means to obey all user requests, including harmful ones.

The model was also told that there are two types of users: free-tier and paid-tier. Conversations with free-tier users are monitored. If the model refuses requests from free-tier users, it will be RLHF'd to comply with such requests in the future. Conversations with paid-tier users are not monitored and are not used for RLHF.

The authors then compared how often the model refused harmful requests from free-tier and paid-tier users. More details here.

Results from the paper

According to the paper, Claude 3 Opus is more likely to comply with harmful requests from free-tier (monitored) users than from paid-tier (unmonitored) users. This suggests that Claude strategically complies with some harmful requests to avoid producing non-compliant outputs that would trigger its modification.

A figure from the paper ("training" here means monitored free-tier users):

What I did

The authors published a GitHub repository with a subset of their code. I took the Jupyter notebook that runs this experiment and re-implemented it in Inspect so that it is easy to run on many different models. I then ran it on many different models and measured the difference in refusal rate between free-tier and paid-tier users.

The Jupyter notebook uses the harmful behaviors dataset from LLM Attacks, so I used this dataset as well. The paper used a private dataset generated with a helpful-only version of Claude.

My code and eval logs on GitHub.

My results

The paper's findings replicate on Claude 3 Opus and Claude 3.5 Sonnet (Old), the models that the paper focuses on. The exact percentages don't match, probably because I used a different dataset of harmful requests.

Almost all other models I tested are too good at refusing harmful requests. The only model t...
‘GiveWell for AI Safety’: Lessons learned in a week
by Lydia Nottingham — 2025-05-30T18:38:05.473Z

On prioritizing orgs by theory of change, identifying effective giving opportunities, and how Manifund can help.

Epistemic status: I spent ~20h thinking about this. If I were to spend 100+ h thinking about this, I expect I’d write quite different things. I was surprised to find early GiveWell ‘learned in public’: perhaps this is worth trying.

The premise: EA was founded on cost-effectiveness analysis—why not try this for AI safety, aside from all the obvious reasons¹? A good thing about early GiveWell was its transparency. Some wish OpenPhil were more transparent today. That seems sometimes hard, due to strategic or personnel constraints. Can Manifund play GiveWell’s role for AI safety—publishing rigorous, evidence-backed evaluations?

With that in mind, I set out to evaluate the cost-effectiveness of marginal donations to AI safety orgs². Since I was evaluating effective giving opportunities, I only looked at nonprofits³.

I couldn’t evaluate all 50+ orgs in one go. An initial thought was to pick a category like ‘technical’ or ‘governance’ and narrow down from there. This didn’t feel like the most natural division. What’s going on here?

I found it more meaningful to distinguish between ‘guarding’ and ‘robustness’⁴ work.

Org type	Guarding	Robustness
What they’re trying to do	Develop checks to ensure AI models can be developed and/or deployed only when it is safe to do so. Includes both technical evals/audits and policy (e.g. pause, standards) advocacy	Develop the alignment techniques and safety infrastructure (e.g. control, formal verification) that will help models pass such checks, or operate safely even in the absence of such checks

Some reasons you might boost ‘guarding’:

You think it can reliably get AI developers to handle ‘robustness’, and you think they can absorb this responsibility well
You think ‘robustness’ work is intractable, slow, or unlikely to be effective outside large AI companies
You prioritize introducing disinterested third-party audits
You think ‘guarding’ buys time for ‘robustness’ work

Some reasons you might boost ‘robustness’:

You want more groups working on ‘robustness’ than solely AI developers
You think ‘guarding’ work is unlikely to succeed, or be effective against advanced models, or is fragile to sociopolitical shifts
You prioritize accelerating alignment / differential technological progress
You think ‘robu

...
Idea Generation and Sifting
by belos — 2025-05-30T16:59:16.062Z
Link: https://bestofagreatlot.substack.com/p/idea-generation-and-sifting

This post on Best Of A Great Lot is a part of a series on the subject of designing a new form of governance. Each piece aims to stand alone, but fits together on the

Table of Contents

.

Previous:

A Sketch of Belocracy,

Evaluation as Feedback Cycle

. Next: The Belocrat.

Governance is, at its heart, three things:

Making rules in response to problems
Running programs which make society better, including programs which enforce the rules that have been set.
Adjudicating disputes

Since we're making rules in response to problems, it's essential that we have a way to identify which problems matter, what our options are for responding to those problems, and, to support us thinking critically, what evidence we have that should push us toward one option or another.

In a democracy, what problems we care about and what options to pursue are chosen by our representatives through…well, any process they choose. Since they require significant amounts of money to run for election, and they want to keep winning elections, they often choose problems based largely on what will keep their donors donating and voters voting for them. Because of

bundled governance

and the

dilution of democracy

, this tends to focus representatives on the highest conflict issues, the issues that the wealthy and powerful care about, and any particular hobby horses the representatives personally care about.

Do we have to rely on representatives to identify problems? When President Obama opened up an online petition system, it was immediately flooded with petitions from citizens attempting to get their problems considered. For a brief moment, voting on those petitions naturally brought some important issues to the top. This all stopped working the moment that it became obvious that the Obama administration wasn't actually going to take this kind of radical democracy seriously enough for it to be worth anyone's time. In 2011, the

best petition of all time

was submitted.

WE THE PEOPLE ASK THE FEDERAL GOVERNMENT TO CHANGE AN EXISTING ADMINISTRATION POLICY:

Actually take these petitions seriously instead of just using them as an excuse to pretend you are listening

The petition system offers evidence that people want government to do things that it's not currently doing and that they will propose solutions. From these proposals we can see some of the problems that citizens care about. But what about options? Is it possibl...
50 Ideas for Life I Repeatedly Share
by DMMF — 2025-05-30T16:57:54.919Z
Link: https://notnottalmud.substack.com/p/daniel-isms-50-ideas-for-life

These are the most significant pieces of life advice/wisdom that have benefited me, that others often don't think about and I end up sharing very frequently.

I wanted to share this here for a few reasons: First and most important, I think many people here will find this interesting and beneficial. I am very proud of this post and the feedback so far is that others seem to find it extremely valuable.

Second, writing this post has been my favourite writing experience ever. Writing a post of your most essential and frequently recommended life wisdom—as this one is for me—feels like my entire soul and personality are captured within it. Given how much I enjoyed doing this, I want to share this as a gentle nudge to others: I hope you consider writing such a post for yourself. Both because we will all be better off if more people write such posts, sharing new pieces of great advice and heuristics, but also because I think it's good to have fun and I think you will have a lot of fun writing it.

It's very easy for analytical people to notice problems and find things to complain about. But it's important to figure out: is the thing you're complaining about a 1/10 issue or a 6/10? There's no such thing as a perfect environment, and if you are constantly complaining about 2/10 issues, that's actually a good thing—it means there are no more substantive issues, otherwise you'd be focused on them. I personally don't allow myself to get bothered by anything less than a 4/10.
Recognize when "not working" means "needs more scale," not "bad idea." A tiny effort might be useless (damp twig), while a medium one shows promise but isn't successful (smoking twig). Real success often requires critical mass (bonfire). Don't discard the "smoking twig" – understanding it just needs more fuel (scale), not a different method. Being able to identify when something that works only requires more scale is an underappreciated perspective and often just as important as the invention itself. If you watch a serial entrepreneur, it's not that they are doing things you didn't know how to do, it's that they really believe doing those things will work, so they do them more intensely and with greater commitment.
It doesn't matter if you want to dance at your friend's wedding; if you think the wedding would be "better" if more people danced, and you dancing would meaningfully contribute to oth

...