Nate Gaylinn

I've got a quick question for the friendly microbiologists of Mastodon.

It's my understanding that it's common for some environmental change to wipe out 90+% of a bacterial colony, only to have the survivors quickly multiply back to their original numbers, this time with a mutation that grants resistance to whatever the threat was.

Is there a name for this phenomenon (not "gene fixation," but the die back and recovery)? Are there canonical papers about it?

EDIT: I think "population bottleneck" is the best way to describe what I mean, though I got a few other very good suggestions for related terms.

Thanks everyone! You guys are the best. ❤️

#microbiology #bacteria

It's obnoxious how every website wants you to install their app or whatever.

Like, the whole point of the web is that you can access any information and software without installing it on your computer. The modern browser is a sandbox and a virtual machine, a portal that grants you access to any site without granting them access to you (in theory).

But everyone wants access to your machine. They want to stay resident, to monitor and monetize you, even if it's a security vulnerability and a drain on your personal resources. The web's greatest feature is an obstacle to them, and they're getting very good at bypassing it.

I thought this was a particularly good analysis of the problem of using LLMs for science. It explores the purpose of science, the perverse incentives that drive people to use LLMs, and the impact this has on skill building and training future scientists.

My lab group has been struggling with this topic lately, without much consensus. This blog post captures a lot of our thinking, and very clearly made some good points that we appreciated. It mostly just describes the mess we're in without offering much useful advice, but just laying out the problems do nicely is helpful. That said, I do worry the author may be underestimating the impact these tools might have on experienced researchers.

https://ergosphere.blog/posts/the-machines-are-fine/
#academicchatter #llm

The most important "productivity hack" I have learned is to recognize when my brain is out of juice for the day. It has a very distinct feeling to it. Once that happens, no work of quality or substance will get done, no matter how long I bang my head against it. So, I might as well go home and rest.

I can't express just how much my well-being improved after I fully embraced this. And I get more done, of higher quality.

Man, marsupials are so weird. I just found out they don't have a corpus callosum connecting the two halves of their brain, and I was like: of course. Why not. Very marsupial. Two opossums, one body.

Never change, marsupials.

These days, so much of our lives and work and relationships are mediated by screens. I think this is a big part of why folks think AI is approaching human capacity.

It's important to remember: we choose to interact through this narrow, impoverished interface. It is not normal or healthy for human beings, just convenient for our mechanized society. It limits us, captures only a small sliver of our humanity, and makes building relationships hard.

Deep learning can do amazing things with text and images, but those are vastly easier than the messiness and complexity of real life. We talk about AGI, but these systems can only compete with us when we hobble and contort ourselves to play the machine's game.

AI systems don't even attempt to play our game, to live a human life. They simply could not. Nor do their makers want them to. An LLM with feelings, aspirations, free will, and meaningful relationships would be a disaster! They want a multipurpose digital slave, not anything like a human being.

#ai

I hate how LLMs are often used, but as a model of cognition I think they're fascinating. Take this paper, for example.

Here they look at reasoning over long sequences of data that can't fit into working memory. The latest LLMs can solve problems like this, using hybrid memory models that consolidate "short-term" memories in an LRU cache into "long-term" memories in the form of persistent weights (which is good to know about generally).

However, this paper shows that this is still a very hard problem. In particular, it's hard to organize the consolidated information in a way that's useful for doing future work, and that a "sleep-like" process of iterative offline processing can help significantly.

It remains to be seen how important this will be and how "sleep-like" it really is. Still, I love how this work draws inspiration from nature and could potentially help us learn about animal minds and cognition generally. Much better than many LLM studies.

#science #ai #llm

Neural networks have been one of the most transformative technologies of the past decade. They were originally inspired by human brains, and their promise is to help us understand human intelligence (or replace it, depending on who you ask). With all the excitement and drama around AI these days, you might be forgiven for thinking we're nearly there! In reality, though, we've only understood a tiny fraction of what the brain is doing. I'd like to convince you that what's happening in your skull is vastly more, and that there's plenty of opportunity in the field of AI that's far afield of where most of today's research is focused.

https://thinkingwithnate.wordpress.com/2026/04/01/brain-like-computing/

#science #ai #blog #neuroscience

I just had to buy on over-the-counter home medical test kit, and the only option they had was a digital one.

That means they increased the cost of the kit to put in disposable electronics (destined to become e-waste) so they can force me to install an app (who knows what tracking they're doing?) and endure ads for telehealth and prescription drugs just to get the results.

WTF?! This is disgusting, and should 100% be illegal.

My research is about how life evolved the mechanisms for evolution as we see today, and how the particular form they take shapes the direction and speed of evolution. Interestingly, that's led me to the origin of life literature! It turns out, biologists are mostly concerned with evolution as it is today, which makes it hard to talk about how the process of evolution itself evolved.

So, I'm exploring papers like this one that talk explicitly about the emergence of genetics and how that might change the robustness and evolvability of very early organisms. There's a lot to like here!

They cut through the debate of whether metabolism or genetics came first with a reframe: perhaps this about processing and evolution of biological information, in analog or digital forms? From this perspective, we can talk about the pros and cons of each vs. both together, and perhaps this can help us put a finer point on what makes life special?

#science #evolution #biology
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Ugh, LinkedIn is the worst!

I try to disable all the notifications that aren't directly relevant to me, but they keep inventing new kinds of notifications that I have to opt out of! So annoying.

Trying to do that this morning, I see they have "simplified and regrouped" their notification settings, which is hilarious, because they're showing me a list of 14 top-level notification categories, each with its own tree of sub-categories beneath it. There must be a few dozen different categories of notification, each with multiple options within.

I think I found the one I needed to turn off? I have no idea. This is actively hostile UX.

#linkedin #ux #ui

I like watching Last Week Tonight, although it is often upsetting. The most recent episode on Prediction Markets hit me a lot harder than I expected.

I dunno. Clearly there are worse things going on in the world. But the sort of hyper-capitalist nihilism these apps represent is profoundly depressing to me. It's even worse to see this being promoted by the Trump administration and adopted by young people.

"The world is burning, might as well make a quick buck off of others' misfortune" is just such a bleak and toxic ideology. Where is our empathy? Where are our aspirations for anything besides wealth and status? It makes me so sad that people think like this.

I enjoy puzzles, but there are many kinds, of course.

I think I'm drawn to science and engineering because I like "why is this not working?" puzzles. Those are some of the most frustrating puzzles I know! Also the most rewarding.

I wonder how much of a factor this sort of thing is in what sort of jobs and lifestyles people choose for themselves?

Welch Labs puts out some killer AI explainer videos! I really enjoyed this one about using LLMs for robotics. It explores the VLA architecture, which cleverly integrates latent spaces between natural language, computer vision, and motion planning tasks.

This is an elegant algorithm, and I feel like the video makes it very intuitive for me why it works so well. I'm also just glad to see more well explained examples of transformer architectures being used in interesting ways and going beyond the domain of natural text where they were originally designed. I'm still developing an intuition for what it is they do, so having such examples is quite helpful.