There’s this popular trope in fiction about a character being mind controlled without losing awareness of what’s happening. Think Jessica Jones, The Manchurian Candidate or Bioshock. The villain uses some magical technology to take control of your brain - but only the part of your brain that’s responsible for motor control. You remain conscious and experience everything with full clarity.

If it’s a children’s story, the villain makes you do embarrassing things like walk through the street naked, or maybe punch yourself in the face. But if it’s an adult story, the villain can do much worse. They can make you betray your values, break your commitments and hurt your loved ones. There are some things you’d rather die than do. But the villain won’t let you stop....

Over the past six months there's been a huge amount of discussion in the Davis Square Facebook group about a proposal to build a 25-story building in Davis Square: retail on the ground floor, 500 units of housing above, 100 of the units affordable. I wrote about this a few weeks ago, weighing the housing benefits against the impact to current businesses (while the Burren, Dragon Pizza, etc have invitations to return at their current rent, this would still be super disruptive to them if they even did return).

The impact to local businesses is not the only issue people raise, however, and I wanted to get a better overall understanding of how people view it. I went over the thousands of comments on the posts (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16) over the last six months, and categorized the objections I saw. Overall I...

Scott Alexander famously warned us to Beware Trivial Inconveniences.

When you make a thing easy to do, people often do vastly more of it.

When you put up barriers, even highly solvable ones, people often do vastly less.

Let us take this seriously, and carefully choose what inconveniences to put where.

Let us also take seriously that when AI or other things reduce frictions, or change the relative severity of frictions, various things might break or require adjustment.

This applies to all system design, and especially to legal and regulatory questions.

Table of Contents

1. Levels of Friction (and Legality).
2. Important Friction Principles.
3. Principle #1: By Default Friction is Bad.
4. Principle #3: Friction Can Be Load Bearing.
5. Insufficient Friction On Antisocial Behaviors Eventually Snowballs.
6. Principle #4: The Best Frictions Are Non-Destructive.
7. Principle #8: The Abundance Agenda and Deregulation as Category 1-ification.
8. Principle

OpenAI reports that o3-mini with high reasoning and a Python tool receives a 32% on FrontierMath. However, Epoch's official evaluation^[1] received only 11%. 

There are a few reasons to trust Epoch's score over OpenAIs:

• Epoch built the benchmark and has better incentives.
• OpenAI reported a 28% score on the hardest of the three problem tiers - suspiciously close to their overall score.
• Epoch has published quite a bit of information about its testing infrastructure and data, whereas OpenAI has published close to none.

Edited in Addendum:
Epoch has this to say in their FAQ:

The difference between our results and OpenAI’s might be due to OpenAI evaluating with a more powerful internal scaffold, using more test-time compute, or because those results were run on a different subset of FrontierMath (the 180 problems in frontiermath-2024-11-26 vs the 290 problems in frontiermath-2025-02-28-private).

1. ^{^}

   Which had Python access.

In an interview, Erica Komisar discusses parenting extensively. I appreciate anyone who thinks deeply about parenting, so I mostly value Erica's contributions. However, I believe she is mistaken on many points.

One claim she makes follows a broader pattern that I find troubling. To paraphrase:

"Fathers can take on the primary caregiver role, but they would be fighting biology. It goes against what all mammals do."

I see this kind of reasoning frequently-arguments that begin with "From an evolutionary standpoint..." or "For mammals..." But this argument is nonsense. Not only is it incorrect, but I suspect that most people, when pressed, would find it indefensible. It often functions as a stand-in for more rigorous reasoning.

Disclaimer: Erica makes more nuanced claims to support her perspective. Here, I am only critiquing one

By Roland Pihlakas, Sruthi Kuriakose, Shruti Datta Gupta

Summary and Key Takeaways

Relatively many past AI safety discussions have centered around the dangers of unbounded utility maximisation by RL agents, illustrated by scenarios like the "paperclip maximiser". Unbounded maximisation is problematic for many reasons. We wanted to verify whether these RL runaway optimisation problems are still relevant with LLMs as well. 

Turns out, strangely, this is indeed clearly the case. The problem is not that the LLMs just lose context. The problem is that in various scenarios, LLMs lose context in very specific ways, which systematically resemble runaway optimisers in the following distinct ways:

• Ignoring homeostatic targets and “defaulting” to unbounded maximisation instead.
• It is equally concerning that the “default” meant also reverting back to single-objective optimisation.

Our findings suggest that long-running scenarios are important. Systematic failures emerge after periods...

"CS-ReFT finetunes LLMs at the subspace level, enabling the much smaller Llama-2-7B to surpass GPT-3.5's performance using only 0.0098% of model parameters."
https://x.com/IntologyAI/status/1901697581488738322

The Moravec paradox is an observation that high-level reasoning is relatively simple for computers, while sensorimotor skills that humans find effortless are computationally challenging. This is why AI is superhuman at chess but we have no self driving cars. Evolutionarily recent developments such as critical thinking is easier for computers than older ones, because these recent developments are less efficient in humans, and they are computationally simpler anyway (much more straightforward to pick one good decision among many rather than to move a limb through space). 

This is what fast takeoff looks like. The paper is very math heavy, and the solution is very intelligent. It is...