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Daily log archive for May 2025. Go to the current daily log, or browse the archive index.

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2025-05-07

Alternate Coffee Varieties

The resilient coffee discovery that could save our morning brew #coffee #stenophylla

While one solution is to shift production geographically as the climate changes, people like Davis, head of coffee research at Kew, and longtime collaborator Jeremy Haggar of the University of Greenwich, think a more sustainable answer is to diversify into climate-resilient choices among the 131 coffee species identified so far.

The two most exciting new species on the block, Davis told me, are excelsa and stenophylla. Excelsa has a deeper root system, allowing access to water in drought conditions, and is also resistant to heat, pests and disease. The first coffee from a Ugandan excelsa project that he has been involved in will come to the UK market this year (he reports the smooth taste to be comparable to a speciality arabica).

Stenophylla is at a more experimental stage. In 2018, Davis and Haggar managed to track down the plant in Sierra Leone with the help of Daniel Sarmu, a coffee specialist in the country. Together with the coffee company Sucafina, the NGO Welthungerhilfe and the co-operation of local communities, the trio have planted wild varieties in trial plots across Sierra Leone with a view to reviving it as a coffee crop (its prospects withered in the mid-20th century as local farmers turned to robusta). The first harvest is expected this year.

Podcast Bros and Brain Rot

Podcast Bros and Brain Rot - Nathan Cofnas’s Newsletter #brainrot #podcasts #social-media

People who don’t trust “experts” now look to podcasters and other alt-media figures—many of whom (including Rogan and Brand) are comedians—to decide what to believe about everything from WWII to vaccines to Ukraine to tariffs. The result has been a proliferation of ignorance with disastrous consequences for our culture and public policy.

Uneducated podcast bros have not found a magic shortcut to knowledge. Even on Covid, they have not outperformed actual experts. However, it’s true that many so-called experts are fake and/or corrupt. Blind obedience to credentialed authority (associated with the left) or trust in a “marketplace of ideas” that rewards brain-rotting infotainment (associated with the right) are both failed strategies.

Matt Levine on Memecoins

OpenAI Will Get A Bit More Normal - Bloomberg #memecoin #crypto

The point of a memecoin is that for 15 minutes everyone in crypto coordinates to (1) pay attention to some person and (2) turn that attention into money by buying a token. And then they move on. I don’t know why this is a fun game for anyone to play, but apparently it is. In this game, somebody is going to make money by buying the token at the beginning of the 15 minutes, and somebody else is going to lose money by buying it at the end of the 15 minutes. There is not a different thing that can happen; the memecoin is not going to build enduring value and steady cash flows. It is going to go up while people are briefly paying attention, and then it is going to go down when they stop. Perhaps you can get people to pay attention more than once, but that is just repeating the same process; it’s not building enduring value.

Oh now obviously if people buy the coin before its public announcement, they will do even better than the people who buy it right after the public announcement. And one can guess that those people are insiders who are connected with the promoters of the memecoin. But of course those are the people who will make money! It’s their meme! You are paying money to buy a token representing “I paid attention to Melania Trump today.” Who should get that money, if not Melania Trump or whoever set up the coin for her?

The enshittification of tech jobs

Pluralistic: The enshittification of tech jobs (27 Apr 2025) – Pluralistic: Daily links from Cory Doctorow #tech #jobs #enshittification

Cory Doctorow is a really gifted writer. Love the concept of Vocational Awe in the paragraph

Tech workers are a weird choice for "princes of labor," but for decades they've enjoyed unparalleled labor power, expressed in high wages, lavish stock grants, and whimsical campuses with free laundry and dry-cleaning, gourmet cafeterias, and kombucha on tap:

https://www.youtube.com/watch?v=nhUtdgVZ7MY

All of this, despite the fact that tech union density is so low it can barely be charted. Tech workers' power didn't come from solidarity, it came from scarcity. When you're getting five new recruiter emails every day, you don't need a shop steward to tell your boss to go fuck themselves at the morning scrum. You can do it yourself, secure in the knowledge that there's a company across the road who'll give you a better job by lunchtime.

Tech bosses sucked up to their workers because tech workers are insanely productive. Even with sky-high salaries, every hour a tech worker puts in on the job translates into massive profits. Which created a conundrum for tech bosses: if tech workers produce incalculable value for the company every time they touch their keyboards, and if there aren't enough tech workers to go around, how do you get whichever tech workers you can hire to put in as many hours as possible?

The answer is a tactic that Fobazi Ettarh called "vocational awe":

https://www.inthelibrarywiththeleadpipe.org/2018/vocational-awe/

"Vocational awe" describes the feeling that your work matters so much that you should accept all manner of tradeoffs and calamities to get the job done. Ettarh uses the term to describe the pathology of librarians, teachers, nurses and other underpaid, easily exploited workers in "caring professions." Tech workers are weird candidates for vocational awe, given how well-paid they are, but never let it be said that tech bosses don't know how to innovate – they successfully transposed an exploitation tactic from the most precarious professionals to the least precarious.

As farcical as all the engineer-pampering tech bosses got up to for the first couple decades of this century was, it certainly paid off. Tech workers stayed at the office for every hour that god sent, skipping their parents' funerals and their kids' graduations to ship on time. Snark all you like about empty platitudes like "organize the world's information and make it useful" or "bring the world closer together," but you can't argue with results: workers who could – and did – bargain for anything from their bosses…except a 40-hour work-week.

But for tech bosses, this vocational awe wheeze had a fatal flaw: if you convince your workforce that they are monk-warriors engaged in the holy labor of bringing forth a new, better technological age, they aren't going to be very happy when you order them to enshittify the products they ruined their lives to ship. "I fight for the user" has been lurking in the hindbrains of so many tech workers since the Tron years, somehow nestling comfortably alongside of the idea that "I don't need a union, I'm a temporarily embarrassed founder."

About the narrative of AI vs reality of AI

Bindley spoke to David Markley, an Amazon veteran turned executive coach, who attributed the worsening conditions (for example, managers being given 30 direct reports) to the "narrative" of AI. Not, you'll note, the actual reality of AI, but rather, the story that AI lets you "collapse the organization," slash headcount and salaries, and pauperize the (former) princes of labor.

The point of AI isn't to make workers more productive, it's to make them weaker when they bargain with their bosses. Another of Bindley's sources went through eight rounds of interviews with a company, received an offer, countered with a request for 12% more than the offer, and had the job withdrawn, because "the company didn’t want to move ahead anymore based on the way the compensation conversation had gone."

Arvind Narayanan on Avoiding Risks with Generative AI

https://x.com/random_walker/status/1919359709062033850 #ai #risks

When we use generative AI for work, there are two ever-present risks: hallucinations/confabulations and deskilling. For each of my AI use cases, I try to make sure I know how I'm avoiding those risks. Specifically:

  • AI is helpful despite being error-prone if it is faster to verify the output than it is to do the work yourself. For example, if you're using it to find a product that matches a given set of specifications, verification may be a lot faster than search.

  • There are many uses where errors don't matter, like using it to enhance creativity by suggesting or critiquing ideas.

  • At a meta level, if you use AI without a plan and simply turn to AI tools when you feel like it, then you're unlikely to be able to think through risks and mitigations. It is better to identify concrete ways to integrate AI into your workflows, with known benefits and risks, that you can employ repeatedly.

  • Turning to deskilling, in some cases the worries are overblown. We should distinguish between essential skills and incidental skills for each job. Incidental skills are those that it's okay to delegate to automation as long as people understand the underlying principles. For example, back in the day when programming languages and compilers were developed, there were worries about people losing the ability to directly write machine code, but that proved unfounded.

  • On the other hand, if a junior developer relies too much on vibe coding and hence can't program at all by themselves, in any language, and doesn't understand the principles of programming, that definitely feels like a problem.

  • Deskilling is usually discussed in the context of junior workers but I think it's a problem at any career stage. Even setting aside AI, there are many senior people who stop learning and have an ossified set of skills.

  • Deskilling is a much more insidious problem than errors, because it happens gradually over years, so you may never notice.

  • I think the way to address it is structural, and not even AI-specific. If you're always scrambling to meet a deadline, there will be too much temptation to take shortcuts (including, but not limited to, overuse of AI), and your skills will atrophy.

  • My own strategy is to set aside about one day a week, sometimes more, for activities that are more about learning and growth than about productivity. This comes at a huge short-term cost but I think it is necessary in the long run.

  • Depending on the job and task, there are other potential risks from AI. Having a plan to address errors and deskilling is necessary, but not sufficient, to ensure a beneficial approach to AI.

The Solution Problem

A great series of essays which in a long-winded but very thoughtful and insightful way tries to explain why the mental health landscape is pretty bad nowadays.

In Part I, I reviewed three answers to the question: “Why are diagnoses of mental illness on the rise?” These answers were: because of progress, because of evolutionary mismatch, and because of the solution problem. I threw my weight behind the final two and promised to bust the first like a piñata.

Next, I divided problems into three types—unknown, tolerable, and regular—as part of my argument that in order to judge a solution, we need to ask what kind of problem it solves, whether it improves experience, and what it costs. The milder the problem, and the less its solution enhances quality of life, the harder it becomes to justify the solution’s costs.

The fifth cost of solutions, which I am most interested in, is the tendency of solutions to create problems. A.k.a. the solution problem. We already saw an example above. When my neighbor has a heated steering wheel, my hands feel colder. Indeed, the very existence of a solution “escalates” the problem from unknown or tolerable to regular—because all of a sudden, something can be done. The opposite is true, too. If you want to make something more tolerable, ensure that everyone has to deal with it. That nothing can be done.

In part 3:

By the way, I am sure that my many criticisms of the mental health field have given some readers the impression that I dislike my job. Nothing could be further from the truth. In fact, the only person who loves their job more than I do is my friend, who is also a therapist but sees more clients.

The simplest way I can put it is this: I love my job because it lets me build meaningful relationships with my clients. In fact, I often find myself wishing the rest of my life matched the intimacy of a good therapy session. And when my clients improve, it's typically because of the relationship. (Turns out—newsflash!—a deep social bond is pretty healing for a deeply social species.) But the rest? The DSM diagnoses, the medications, the ever-multiplying therapeutic orientations, the canon of mental health theorists from Freud and Jung to Beck and Satir, the saturation of mental health thinking into every corner of life—most of that is nonsense, and I can’t be asked to support it.

2025-05-06

Ava on Friendships

always on your side - by Ava - bookbear express #friendship #love

Some beautiful thoughts on friendship by Ava. Really needed this today.

At the party the topic came up: can men and women be friends? P said that she didn’t think they could, that male/female friendships could never be as unboundaried as her friendship was with me. Which is probably true: we went to Japan for a week and shared the same hotel room, which is not something I can imagine doing with any male friend. But everyone else in the conversation pointed out that the presence of boundaries didn’t mean a friendship wasn’t real.

Some of my best friends are guys, and at this point I’ve known them for about 10 years. I have matching tattoos with a couple, C and B. At this point they feel like family, as in: I couldn’t imagine us breaking up for any reason. We drift, and we go through different seasons, but the relationship has proven so extremely durable. In friendships you don’t often explicitly talk about values, but we have the same values. The same orientation towards work and love. And also a thousand subtler things. We understand each other’s dreams, big and small, and we can really talk. I think that’s what it comes down to: I can really talk to my friends, and I can talk to them through everything.

Friendship brings out the best in me, and sometimes I fear that romantic relationships bring out the worst. As a friend, I’m steady, warm, receptive. As a partner, I’m only sometimes that. At my most difficult, I fear that I couldn’t possibly be lovable. But that’s too simplistic of a narrative, so let me try again.

Here we go: over the years I’ve sometimes called my friends, crying, anxious, and let them be my anchor to reality. The unconditional acceptance they model to me is how I would like to show up in every moment of my life, in each important relationship. In reality, there are plenty of times I don’t show up like that, when I crack under stress, when I am not patient and kind. It’s easier to be generous to your friends, because you have some level of remove from them—they are usually not pressed up against you in your worst moments, privy to your most destructive tendencies. But friends are still our first and sometimes best model of someone who chooses to be always on your side.

We don’t have many good theories about friendship, or a lot of scripts. It’s so different from dating, which is so scripted it can feel stifling, where so much of the possibility space is prescribed or proscribed. The guy should pay on the date. The girl shouldn’t make the first move. You should respond to a text in this amount of time. Since I started matchmaking, a ton of people have told me: I prefer to get to know someone as a friend first. Dating apps feel so unnatural and stilted. I think this is because everything feels more organic when there’s not a script. When I’m not playing a role, when I can be just who I am and you love me anyway, everything feels more real.

At a holiday party last year, a guy told me that he believed friendship should be easy. He was close to his family, and he had a partner he loved very much. Those were the relationships in his life that he had the capacity to be challenged by. He wanted his friendships to be light, loose, simple.

For many people, friendship’s appeal lies in its relative lack of complications. No taxes or laundry, no sex, no fighting. People are allowed to walk away and no one gets mad. You get to choose how much you opt in. When contrasted with romantic relationships, which at their worst can resemble a merry-go-round in Hell, they seem all upside.

2025-05-05

AI and the Humanities

Will the Humanities Survive Artificial Intelligence? | The New Yorker #ai #humanities

But factory-style scholarly productivity was never the essence of the humanities. The real project was always us: the work of understanding, and not the accumulation of facts. Not “knowledge,” in the sense of yet another sandwich of true statements about the world. That stuff is great—and where science and engineering are concerned it’s pretty much the whole point. But no amount of peer-reviewed scholarship, no data set, can resolve the central questions that confront every human being: How to live? What to do? How to face death?

The answers to those questions aren’t out there in the world, waiting to be discovered. They aren’t resolved by “knowledge production.” They are the work of being, not knowing—and knowing alone is utterly unequal to the task.

For the past seventy years or so, the university humanities have largely lost sight of this core truth. Seduced by the rising prestige of the sciences—on campus and in the culture—humanists reshaped their work to mimic scientific inquiry. We have produced abundant knowledge about texts and artifacts, but in doing so mostly abandoned the deeper questions of being which give such work its meaning.

Now everything must change. That kind of knowledge production has, in effect, been automated. As a result, the “scientistic” humanities—the production of fact-based knowledge about humanistic things—are rapidly being absorbed by the very sciences that created the A.I. systems now doing the work. We’ll go to them for the “answers.”

But to be human is not to have answers. It is to have questions—and to live with them. The machines can’t do that for us. Not now, not ever.

The 80-hour myth

The 80-Hour Myth (Why We're Addicted To Being Busy) - Dan Koe #productivity #hustle #culture

The usual productivity spiel but I thought this section was interesting

Work Like A Lion, Not A Cow

There are two approaches to work.

First, is like a cow who grazes the fields:

  • Consistent long hours every day
  • Steady and predictable output
  • Trading time for money in a linear fashion
  • Showing up regularly regardless of energy
  • Often leads to burnout and diminishing returns

Second, is like a lion, which we share a similar psychological wiring in that we are hunters (at least when it comes to work).

Our brain craves the novelty and dopamine that comes along with discovering resources (like ideas) that aid in our survival:

  • Intense bursts of focused, high-energy work
  • Long periods of rest and recovery between hunts
  • Work according to energy and creativity cycles
  • Prioritize impact over number of hours logged
  • Aim for leverage where results aren’t tied to time

A lion, by today’s perception, is a massive procrastinator, and people discourage that. They make you feel guilty for taking your time. They tell you that you lack discipline and you should take things more seriously.

If you’re bad at texting people back, or you tend to put your work (or homework) off until the last second, it’s not a character flaw, it’s how many people are wired.

If that sounds like you, what you need to understand is that intensity is better than duration, rest is the most productive form of work, and results matter more than hours.

But there are a few moving pieces here.

First, is leveraging your unique strengths that give you an asymmetric advantage.

Second, is choosing to pursue work that allows you to put lifestyle first.

That way, you can work according to your energy cycles and make a conscious choice as to what you should be working on. Some creatives worked late into the night while others preferred the morning.

If someone tells you what to work on, you can’t really change that, and your first priority must be to leave that work.

The Seven-Year Rule

The Seven-Year Rule - MacSparky

Years ago, I encountered a fascinating concept in a book by the Dalai Lama: every seven years, human beings transform into entirely new versions of themselves. This idea stems from the biological principle that our bodies replace virtually all their cells over a seven-year cycle. The person you are today doesn’t share a single cell with the version of you from seven years ago. (This is, of course, a generalization as some cells regenerate much faster and others a little slower.)

There’s something profoundly liberating about this constant state of transformation. We often become fixated on our past: mistakes we’ve made, opportunities we’ve missed, harms inflicted upon us (and by us), or wounds we’ve suffered. But what if we truly internalized that the person who experienced those things no longer exists in a physical sense?

I recently spoke with a friend who was still dwelling on something that happened thirty years ago. “Why do you care?” I asked him. “That was four versions of you ago. That person doesn’t exist anymore. Move on.”

This perspective applies equally to our future selves. The version of you that will exist seven years from now hasn’t formed yet. So why not focus your energy and attention on the present moment?

As you read these words, you are uniquely yourself, different from who you were a moment ago and who you’ll become in the next. By embracing this present version of yourself, you release yourself from the bonds of history while simultaneously doing the greatest possible favor to your future self.

We exist in a perpetual state of transformation: cellular, psychological, and spiritual. When we recognize and honor this constant evolution, we free ourselves to live more fully in the eternal now. Adopt the Seven-Year Rule. You’ll be doing yourself a favor.

Minimalift program by Matt D'Avella

I cut my training by 70% (and got better results) - YouTube #fitness #workout #lifting

ChatGPT Summary: ChatGPT - Minimalist Strength Training Overview

There is too much workout/lifting content out there. But this one caught my eye because of its minimalist approach. Some materials available for sale include options to do workouts at home using just barbells and bodyweight exercises.

This is mainly to motivate myself to resume my workouts.

Recipes from a Tech Bro

Recipes #recipes #food

I stumbled upon these recipes accidentally when I visited the site to check out another technical blog post. I found the recipes to be simple and to the point.

Experts and Elites Play Fundamentally Different Games

Experts and Elites Play Fundamentally Different Games #status #hierarchy #experts #elites #power

Experts are people who know things. They’re judged by other experts—people who speak the same language, use the same methods, and know the same details. You can spot experts by their credentials, their technical precision, or just the way they argue. They care about being right. They’re evaluated on whether their work holds up—whether it can be tested, measured, replicated, or defended under scrutiny. They debate each other, go deep into the weeds, and let the details decide who’s correct.

Elites are different. They’re not judged on technical knowledge but on being impressive across a broader range: wealth, looks, taste, social fluency, connections, charisma, and cultural feel. Elite institutions tend to screen for such qualities, which is why educational pedigree is also often important. This is why you can major in anything at Harvard and still get an elite job. No need for narrow expertise in, say, engineering or mathematics.

There is some interesting exploration of the idea of the expert-elite spectrum.

2025-05-04

Field Guide to AI Assisted Communication

You Sent the Message. But Did You Write It? #ai #communication #slang

Last week, I got a message from someone I’ve known for ten years. It was articulate, thoughtful…and definitely not written by him.

It’s one example of what has increasingly unsettled me about the way people interact - myself included - as we all participate in this vast, unprecedented, AI-enhanced communication experiment.

That’s when it dawned on me: we don’t have a vocabulary for this.

We’re surrounded by AI-shaped communication—but we’re still talking about it like everything is normal.

So I started writing down the weirdness. And it turned into a glossary.

Here are ten terms offered to help name, diagnose, and spark reflection on the strange new ways we communicate in the age of AI:

The terms listed are:

  1. Chatjacking
  2. Prasting
  3. Prompt ponging
  4. AI’m a Writer Now (aka Sudden Scribe Syndrome)
  5. Promptosis
  6. Subpromptual
  7. GPTMI
  8. Chatcident
  9. GPTune
  10. Syntherity

Why are big companies so slow

Why are big tech companies so slow? | sean goedecke

Big tech companies spend a lot of time and money building things that a single, motivated engineer could build in a weekend. This fact puzzles a lot of people who don’t work in big tech. Often those people share theories about why this is true:

  1. Big tech engineers are incompetent and unproductive, and big tech routinely wastes billions of dollars in salary on bad hires
  2. Big tech companies use processes, like Agile, that are so inherently inefficient as to slow down work by 100x for no good reason
  3. Big tech engineers are lazy and are stealing time from their employers
  4. Big tech companies are dominated by coordination problems that sap much of the value of each extra engineer
  5. Big tech operates at web scale, so comparing weekend features to big tech features is like comparing a diecast toy car to a Ferrari

Why are big tech companies slow? Because they’ve packed in as many features as possible in order to make more money, and the interaction of existing features adds an unimaginable amount of cognitive load. Some hackers are revolted by this, because they love simple tools that do one thing well. That’s a fair reaction. But don’t let your revulsion fool you into thinking that big tech companies are full of stupid people.

Capturing value at the margin is really difficult to do well. That’s why big tech pays big tech salaries for it!

2025-05-03

Jujutsu Version Control

zerowidth positive lookahead | What I've learned from jj

I have taken baby steps with jujutsu so far. This seems like a good article

I recently started using the Jujutsu version control system, and it’s changed how I think about working with code. As someone who’s been using git for nearly two decades, it’s refreshing to gain new perspectives on my daily work and get a sense of what might be possible in the future.

Working with git has been great, especially in contrast to what came before. But despite years of development, it still has sharp edges and presents a steep learning curve. Jujutsu doesn’t fix that, exactly, but it sands off some rough edges and makes some different decisions that result in a much safer and far more flexible workflow.

Psychedelics and Indigenous Communities

The ancient psychedelics myth: ‘People tell tourists the stories they think are interesting for them’ | Drugs | The Guardian #psychedelics #history

This article upends notions I had held about psychedelics that were informed by the usual sources mentioned in the article (like Pollan). It's good to read a good critique informed by sources.

Based on this and other evidence, Brabec de Mori argues that ayahuasca diffused through the Peruvian Amazon in the past 300 years. It is likely older among Tukanoan peoples further north, who, he suspects, transmitted the practice to populations missionised early in the lowlands. Yet in the regions most frequented by tourists, it seems to be a relative novelty. Brabec de Mori isn’t the first to make the argument – the anthropologist Peter Gow proposed something similar in 1994 – but he, more than anyone else, has found the anthropological data to support it.

Brabec de Mori’s findings represent one of many cracks in the stories we tell about the history of psychedelics. As these substances become the mainstream, so do narratives about their role in human societies, narratives that often bind them to shamanism. Just look at the media coverage. In 2020, a journalist for the Washington Post wrote that consciousness-altering substances “have been used by Indigenous cultures for physical and psychological healing for thousands of years”. Michael Pollan endorsed a similar narrative throughout his bestselling 2018 book, How to Change Your Mind, writing that “elements of shamanism might have a role to play in psychedelic therapy – as indeed it has probably done for several thousand years”.

These quotes all subscribe to what I call the global archaic psychedelic shamanism (Gaps) hypothesis. It consists of three claims. First, that psychedelics have long been widespread. Second, that use of psychedelics goes back to the ancient past. Third, that psychedelics have long been used by shamans for therapeutic healing.

Like so many of the stories we tell about human history, the Gaps hypothesis is rooted in glimmers of truth. Yet much of what passes as psychedelic history has been distorted by a seductive mixture of flimsy archaeological evidence, outdated anthropological approaches and economically expedient ideology. “It’s a romantic image that Indigenous people have been using everything they do for thousands of years,” Brabec de Mori said. “If we change the picture, it’s kind of unromantic, and it seems that people like romanticism.”

For Erika Dyck, who has studied the history of attitudes about psychedelics, stories about traditional psychedelic use are rooted in financial and ideological goals. “A lot of the enthusiasm for investing in psychedelic drugs,” she said, stems from an expectation that they will bring “a paradigm shift in the way we think about mental disorders.” Our stories reflect that goal. We portray shamans around the world as psychotherapists and psychopharmacologists. We imagine how we want to use psychedelics and then project those imaginings on to cultures we know little about.

2025-05-02

10 books that are dating red flags

10 books that are dating red flags | Dazed #dating #books

I first thought the title was a bit unserious, but the actual article turned out to be very insightful and funny.

On A Clockwork Orange

It’s a thought-provoking read and probably one of my favourite books, but if the person you’re dating thinks Alex is some kind of aspirational antihero, it’s safe to say you should probably run a mile.

On American Psycho

So if a man you’re dating loves American Psycho, just try to make sure this is due to its trenchant critique of consumer-capitalism, and not because he thinks Patrick Bateman is a based alpha giga-chad.

TIL, there is such a thing as "dude-bro" books:

I’ve always been perplexed by the idea that there are large numbers of obnoxious literary bros out there, bragging about having read Infinite Jest and terrorising the people around them with Jack Kerouac quotes. I have met a handful of men like that in my life, but they don’t exist as a meaningful constituency – most men simply don’t read fiction, if they read at all. If I met someone who loved Pynchon, DeLillo, Bolaño or any other author from the “dude bro” canon, I’d be more inclined to think of them as interesting than as pretentious.

On All About Love by Bell Hooks

I actually don’t think All About Love is inherently a red flag book. But it can be alarming to many when certain people (men) have this book in their possession. When I think about All About Love, I think of that picture a guy took of himself on a beach reading it, and everyone commented that he was only on page one and was already taking pictures of himself 😭. All About Love has become associated with a kind of performance for men. It often sits on the corner of their desks collecting dust, but it’s there so that any potential romantic partner they bring home will be impressed by their supposed desire to engage with hooks’ work and better themselves. Beyond that, I know people have a lot of problems with All About Love, especially because hooks writes that love and abuse cannot coexist. When I first read the book at 17, that particular line triggered one of the worst mental breakdowns I’ve had to date. Now that I’m 25, I understand that what people write in books isn’t always fact and that they can be wrong.

On Crime and Punishment

If you’re seeing someone who is reading a book by Fyodor Dostoevsky, good news! They have a brain cell. The bad news, however, is that that brain cell is deficient in serotonin; this person likely takes themselves quite seriously, has a morose outlook on life, and struggles with chronic depression (at least, if they didn’t when they started it, they will have developed it by the time they’ve finished it).

What Goes Around Comes Around... And Around...

What Goes Around Comes Around... And Around... | ACM SIGMOD Record #databases #sql #relational

The PDF can also be found here: whatgoesaround-sigmodrec2024.pdf

This is a great survey of all the interesting things that have happened in databases w.r.t to data modeling and query languages, which concludes that ultimately every converges to Relational Modeling and SQL.

In this paper, we analyze the last 20 years of data model and query language activity in databases. We structure our commentary into the following areas:

  1. MapReduce Systems
  2. Key-value Stores
  3. Document Databases
  4. Column Family / Wide-Column
  5. Text Search Engines
  6. Array Databases
  7. Vector Databases
  8. Graph Databases

We contend that most systems that deviated from SQL or the RM have not dominated the DBMS landscape and often only serve niche markets. Many systems that started out rejecting the RM with much fanfare (think NoSQL) now expose a SQL-like interface for RM databases. Such systems are now on a path to convergence with RDBMSs. Meanwhile, SQL incorporated the best query language ideas to expand its support for modern applications and remain relevant.

Although there has not been much change in RM fundamentals, there were dramatic changes in RM system implementations. The second part of this paper discusses advancements in DBMS architectures that address modern applications and hardware: 9. Columnar Systems 10. Cloud Databases 11. Data Lakes / Lakehouses 12. NewSQL Systems 13. Hardware Accelerators 14. Blockchain Databases

Some of these are profound changes to DBMS implementations, while others are merely trends based on faulty premises.

Karpathy vibe-coding a production grade web-app

Vibe coding MenuGen | karpathy #llm #coding #software #programming #vibe-coding

TLDR. Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services, docs, API keys, configurations, dev/prod deployments, team and security features, rate limits, pricing tiers... Meanwhile the LLMs have slightly outdated knowledge of everything, they make subtle but critical design mistakes when you watch them closely, and sometimes they hallucinate or gaslight you about solutions. But the most interesting part to me was that I didn't even spend all that much work in the code editor itself. I spent most of it in the browser, moving between tabs and settings and configuring and gluing a monster. All of this work and state is not even accessible or manipulatable by an LLM - how are we supposed to be automating society by 2027 like this?

2025-05-01

Adolescence TV show

The problem with Adolescence | Dazed #tv #misogyny #gender #manosphere

Finally ended up watching this show. Now catching with all the internet think pieces on it!

It’s true that those of us on social media – that’s 98 per cent of us Gen Zers – are entirely at the mercy of algorithms. Major platforms like TikTok remain maddeningly opaque about exactly how their algorithms work, but it’s not difficult to spot patterns in what they choose to recommend. Speaking to the BBC in 2024, Andrew Kaung, a former analyst at TikTok, algorithms are designed to fuel engagement by showing you content which you’re inclined to spend longer watching. Often, this sort of thumb-stopping content is extremist in nature; independent research and reporting has consistently found that social media algorithms amplify misogynistic and inflammatory content.

But while it is impossible for parents to ensure their children are forever shielded from the likes of Andrew Tate, there’s no reason why this problem can’t be tackled at the root. If parents and teachers are powerless to adequately monitor the kind of content children are consuming online, why can’t social media companies do something? Why can’t misogynistic content be removed from platforms before it has a chance to poison impressionable young minds? It’s a question worth asking, but one Adolescence fails to pose. Instead the show meekly throws its hands up in defeat. “You can’t keep an eye on them all the time, love. We just can’t,” Eddie says.

Typing Practise

Studio: How To Type Fast #typing #practice

Found in this video: Learning to Type FAST in 5 Days - 150+ wpm Guide from MKBHD Team - YouTube

Typing Practice 2

If you’re from the video welcome! The following is the exact instructions I gave our team to follow for 1 work week which is why you’ll see instructions to record scores for each day. Enjoy!

For the next 5 work days dedicate 20 minutes a day to doing these practice exercises.

  • 10 minutes before lunch, 10 minutes after lunch.
  • You can break these 10 minutes up, but please make sure you’re doing at least 20 minutes a day.
  • During all of these tests you should be trying your hardest to never look at your keyboard. Try to focus on not looking during regular work day typing as well.
  • Focus on accuracy over speed at all times, even when you’re taking tests at the end of each day.
  • Use the same keyboard for all of this practice.

NOTES:

  • Try to do all of these activities at least once unless they seem too hard.
  • I’d suggest starting with an easy activity first and then moving onto the harder ones.
  • At the end of each day, go to Monkeytype and take 5x 15 second tests. Record your best score each day.

First

Keybr - This test needs to be finished before starting any other activities.

  • Read all the instructions before you start.
  • Create an account to keep track of progress.
  • Unlock all letters as green before moving on
  • If it takes you the full 5 days to complete this that’s fine

After Keybr is completed and all letters are green, here’s a list of different ways to practice during your time slots. I’ve grouped them in different tiers of difficulty.

Easy:

  1. Go to Monkeytype and choose the “words” category on top.

  2. You’ll have 50 words to type with no time limit

  3. Focus on finishing each test with no errors

  4. Before you start another test, select “Practice Words”, select “Words” for missed words and “On” for slow words and click “Start” and take the new focused test.

  5. Open “Zen” mode in Monkeytype

  6. Here you wont have words, but you just type what comes to mind.

  7. Type in here what you need to accomplish for the day or just some things on your mind.

  8. We practice a lot of typing while reading words on a screen, but in the real world you’ll be typing something in your head.

  9. Press “Shift - Enter” to finish Zen mode.

  10. Go to Monkeytype and select “Custom” then “Change”

  11. In the custom box put your full name.

  12. Our names are something we type all the time

  13. Set it to 30 seconds and practice typing your name.

  14. Continue Practice Mode in Keybr

Medium:

  1. Go to Monkeytype and select “Quote”

  2. This will add capitalization and punctuation to your tests

  3. Play TypeRacer

  4. Racing game where you race against other people with similar typing speeds

  5. This also includes punctuation

  6. Play Z Type

  7. Asteroids based typing game.

  8. No punctuation or capitalization

  9. Go to Monkeytype and select times over 1-2 minutes

  10. Allow yourself to type for longer amounts of time vs a short test.

  11. Focus on accuracy

Hard:

  1. Go to Monkeytype and select either “time” or “words”

  2. Go to Settings and “Funbox”

  3. Select “Read Ahead Easy”

  4. This will remove the next word as you type forcing you to read ahead while typing.

  5. If this is too easy, move to “Read Ahead” or “Read Ahead Hard”

  6. Go to TypeLit.io

  7. This website lets you choose a book and type the chapters.

  8. Lots of punctuation and general formatting you must follow

  9. Type a page at a time

  10. Go to Monkeytype, in funbox settings click “Wikipedia”

  11. This will give you prompts that are based on Wikipedia articles

  12. Lots of punctuation again, but in the familiar Monkeytype layout

  • Try to do all of these activities at least once unless they seem too hard.
  • I’d suggest starting with an easy activity first and then moving onto the harder ones.
  • At the end of each day, go to Monkeytype and take 5 15 second tests. Record your scores if you want to keep track!

Case for Living Online

Tyler Cowen: The Case for Living Online - by Tyler Cowen #online #culture

Why do I spend so much of my time with email, group chats, and also writing for larger audiences such as Free Press readers? I ask myself that earnestly, and I have arrived at a pretty good answer. I believe that by spending time online I will meet and befriend a collection of individuals around the world, who are pretty much exactly the people I want to be in touch with. And then I will be in touch with them regularly.

I call them “the perfect people for me.”

I recognize that many of these communications are online, and thus they are “thinner” than many more local, face-to-face relationships. Yet I do end up meeting most of these people, and with great pleasure. That, in turn, enhances the quality of the online communications. And frankly, if forced to choose, I would rather have thinner relationships with “the perfect people for me” than regular bear hugs and beer guzzlings with “people who are in the 87th percentile for me.”

The internet, in other words, has invented a new means of human connection, characterized by “the perfect people for me.” For me, it’s people who are into analytical thinking and tech and AI and music and economics, and much more. For others? It can be Survivor obsessives or vegans or knitters or Survivor obsessives who are vegan and love to knit. The point is that there is a niche for all 8 billion of us. And now we know where to find each other.

And it turns out we value that very, very highly. So highly that we are willing to obsess over our little devices known as smartphones.

The renaissance of personal software

The 70% problem: Hard truths about AI-assisted coding #ai #programming

I believe we're going to see a renaissance of personal software development. As the market gets flooded with AI-generated MVPs, the products that will stand out are those built by developers who:

  • Take pride in their craft

  • Care about the little details

  • Focus on the full user experience

  • Build for the edge cases

  • Create truly self-serve experiences

The irony? AI tools might actually enable this renaissance. By handling the routine coding tasks, they free up developers to focus on what matters most - creating software that truly serves and delights users.

How to live like an Epicurean — 9 key habits

How to live like an Epicurean — 9 key habits #epicurean #philosophy

If you’re looking for a way to live a more fulfilling or simpler life, living like an Epicurean might be the answer. Epicureanism is a philosophy that emphasises the importance of pursuing pleasure and avoiding pain to live a fulfilling life. However, this idea of pleasure was not limited to physical pleasure alone but also included intellectual pleasures such as knowledge and wisdom. It teaches that the greatest good is pleasure and the absence of pain.

  1. Focus on Inner Happiness: Seek joy from within rather than external possessions.
  2. Practice Self-Control: Master your emotions to achieve tranquility.
  3. Prioritize Meaningful Relationships: Cultivate genuine friendships for support and happiness.
  4. Embrace the Present Moment: Live fully in the now and enjoy simple pleasures.
  5. Seek Healthy Pleasures: Find joy in virtuous living rather than excess.
  6. Cultivate a Mindfulness Practice: Engage in meditation or reflection for greater self-awareness.
  7. Accept What You Cannot Control: Let go of the need to control everything around you.
  8. Challenge Adversity: View challenges as opportunities for growth and resilience.
  9. Live Moderately: Avoid excess and focus on balanced choices that promote well-being.

Avoiding Skill Atrophy in the Age of AI

Avoiding Skill Atrophy in the Age of AI - by Addy Osmani #ai #software #programming

Here are the key points from the section "Using AI as a collaborator, not a crutch":

These practices aim to leverage AI's advantages while preserving essential coding skills and critical thinking abilities.

"AI-first" is the new Return To Office

"AI-first" is the new Return To Office - Anil Dash

Big tech CEOs and VCs really love performing for each other. We know they hang out in group chats like high schoolers, preening and sending each other texts, each trying to make sure they're all wearing the latest fashions, whether it's a gold chain or a MAGA hat or just repeating a phrase that they heard from another founder. A key way of showing that they're part of this cohort is to make sure they're having a tantrum and acting out against their workers fairly regularly.

The return to office fad was a big part of this effort, often largely motivated by reacting to the show of worker power in the racial justice activism efforts of 2020. Similarly, being AI-first shows that a company is participating in the AI trend in the "right" way, by imposing it on workers, rather than trusting workers to judge what tools are useful for them to do their jobs.

There's an orthodoxy in tech tycoon circles that's increasingly referred to, ironically, as "tech optimism". I say "ironically", because there's nothing optimistic about it. The culture is one of deep insecurity, reacting defensively, or even lashing out aggressively, when faced with any critical conversation about new technology. That tendency is paired with a desperate and facile cheerleading of startups, ignoring the often equally interesting technologies stories that come from academia, or from mature industries, or from noncommercial and open source communities that don't get tons of media coverage, but quietly push forward innovating without the fame and fortune. By contrast, those of us who actually are optimistic about technology (usually because we either create it, or are in communities with those who do) are just happily moving forward, not worrying when people point out the bugs that we all ought to be fixing together.

Reimagining Democracy

Reimagining Democracy - Schneier on Security #democracy #politics

Bruce Schneier writes with a lot of clarity. The whole article is worth reading.

Indeed, the very idea of representative government was a hack to get around technological limitations. Voting is easier now. Does it still make sense for all of us living in the same place to organize every few years and choose one of us to go to a single big room far away and make laws in our name? Representative districts are organized around geography because that was the only way that made sense two hundred-plus years ago. But we do not need to do it that way anymore. We could organize representation by age: one representative for the thirty-year-olds, another for the forty-year-olds, and so on. We could organize representation randomly: by birthday, perhaps. We can organize in any way we want. American citizens currently elect people to federal posts for terms ranging from two to six years. Would ten years be better for some posts? Would ten days be better for others? There are lots of possibilities. Maybe we can make more use of direct democracy by way of plebiscites. Certainly we do not want all of us, individually, to vote on every amendment to every bill, but what is the optimal balance between votes made in our name and ballot initiatives that we all vote on?

Manas Saloi on his favorite thinkers

This tweet by Manas Saloi intrigued me a little bit so I went on a bit of a rabbit hole to locate all the resources he is referencing:

Welcome to the Era of Experience

“Welcome to the Era of Experience” by David Silver and Richard Sutton

In key domains such as mathematics, coding, and science, the knowledge extracted from human data is rapidly approaching a limit. The majority of high-quality data sources - those that can actually improve a strong agent’s performance - have either already been, or soon will be consumed. The pace of progress driven solely by supervised learning from human data is demonstrably slowing, signaling the need for a new approach. Furthermore, valuable new insights, such as new theorems, technologies or scientific breakthroughs, lie beyond the current boundaries of human understanding and cannot be captured by existing human data.

To progress significantly further, a new source of data is required. This data must be generated in a way that continually improves as the agent becomes stronger; any static procedure for synthetically generating data will quickly become outstripped. This can be achieved by allowing agents to learn continually from their own experience, i.e., data that is generated by the agent interacting with its environment. AI is at the cusp of a new period in which experience will become the dominant medium of improvement and ultimately dwarf the scale of human data used in today’s systems.

An experiential agent can continue to learn throughout a lifetime. In the era of human data, language-based AI has largely focused on short interaction episodes: e.g., a user asks a question and (perhaps after a few thinking steps or tool-use actions) the agent responds. Typically, little or no information carries over from one episode to the next, precluding any adaptation over time. Furthermore, the agent aims exclusively for outcomes within the current episode, such as directly answering a user's question. In contrast, humans (and other animals) exist in an ongoing stream of actions and observations that continues for many years. Information is carried across the entire stream, and their behaviour adapts from past experiences to self-correct and improve. Furthermore, goals may be specified in terms of actions and observations that stretch far into the future of the stream. For example, humans may select actions to achieve long-term goals like improving their health, learning a language, or achieving a scientific breakthrough.

The era of human data offered an appealing solution. Massive corpuses of human data contain examples of natural language for a huge diversity of tasks. Agents trained on this data achieved a wide range of competencies compared to the more narrow successes of the era of simulation. Consequently, the methodology of experiential RL was largely discarded in favour of more general-purpose agents, resulting in a widespread transition to human-centric AI. However, something was lost in this transition: an agent's ability to self-discover its own knowledge.