Started playing with @bot this week, first problem I'm using it to solve is automatically picking my lunches from Factor every week because any time I forget they send me stuff I don't like. Becoming really easy to see how the way we use the web is going to totally change.
you need to somehow internalize it and it has to be relatively effortless and automatic. It has to become automatic at some level and then you can move through life fairly smoothly in a socially very complex way.
And I'm not claiming this as a published study, but so I think there's a there's a direct autonomic training component as well in terms of the strength and the automaticity, the ease with which you can regulate emotions that they can become kind of automatically regulated.
making intelligence cheap does not automatically make “agency” cheap. people are constrained by time, money, confidence, health, education, institutions, family, geography; a model does not magic any of that away. there’s a perfectly believable future where these tools mostly compound the advantage of people who already have the skill, taste, money and the spare time to use them well.
Um, and while this generally improves the reliability of the model, uh, people eventually get tired and it's hard to get really, really high reliability with a person that's manually tuning this. And so what would be even better is if the AI system itself can iterate on the scenario in which you want it to have higher reliability where it on its own automatically seeks out places where it needs more data, where it needs more supervision.
Facts and Fallacies of Software Engineering by Robert L. Glass. In essence, this is a book about an industry that refuses to learn. That was true 25 years ago when this book was published, and it's probably twice as true today. (Just think about all the AI adoption metrics being rolled out — back to productivity mistaken for lines of code produced, only more elaborate. And expensive). What I like about this book is that Glass doesn't present anything new. Quite the opposite, actually. Rather, it's about research lessons that we all should know, but tend to forget. Ever had to do an estimate, or plan according to a requirements spec? Or maybe you thought that enough eyeballs make all bugs shallow? Then this book is for you. A great work by a fantastic author.
Coding isn't yet another application domain -- it's the meta-skill required for AI to automatically develop its own training material, via symbolic world models. That's how the RSI loop actually kicks off.
common failure mode is picking the tech that gives you the fastest early ramp, riding that steep curve, feeling like you're winning, projecting that, you know, steep slope into the future and feeling like the sky is the limit, and then hitting the plateau, and discovering that the technology path that you picked actually flattens out way before the performance that is required by your product.
And it's really about being empirical. So forget all of the things that you learned about past models. Forget everything that you've learned about computer science theory in class. Look at the model, try to do a task, see where it struggles, and then based on that adjust. So it's just like very much become it's not a theoretical science, it's become an empirical science.
And as a result of identifying that person in a lineup, that person then replaces what they actually saw. So our memory can be contaminated just like any form of evidence could be contaminated.
Using these BenQ light bars allows me to better illuminate my desk at night without having to keep my overhead lights on. What I really like about this light bar is that it can be configured to automatically turn off when I leave the desk.
And I believe the best product CEOs are in the minutia of the details. you know, all the stories about Steve Jobs. I was so impressed when I heard that he insisted on picking out the carpeting in the conference rooms, you know, and and I tried to have that same mentality of micromanaging the really small pixel level details that matter.
But being good or even excellent at that does not automatically make you good at understanding user needs and making informed judgement calls about what features will meet those needs and how they should be designed.
Now the thing is you can of course write examples in your documentation and Rust makes all examples into tests. This means that if you change the underlying code now your test fails. And so this means that you can't even you can't forget to update your examples in your documentation.
I mean, you could argue that we we're already past peak truth on the on the on the internet, right? And now there's there's just more and more garbage every every day. It gets harder and harder to suss out the stuff that you do want to include in the training set in order to actually make something more intelligent.
as leaders we get so focused on value statement mission statements we forget the mission statement is not the mission. The map is not the territory. Mission is an emergent property of the living superorganism of the thing we're birthing.
Uh but whenever we do a systematic study, um any given problem, an AI tool has a success rate of maybe 1 or 2%. Uh it's just that it's just that they can apply at scale and and you just pick the winners, it looks great.
Marketing grows only as fast as you can improve marketing. We all know that's quite hard actually. It's linear. It's hard to find new channels that aren't trivial. Like, it's hard. Of course, we're going to do it, but like it it's hard. Whereas, cancellations grow automatically as you grow, right? So, cancellations always overtake marketing for this reason.
And I realized it was the first one on the list and I thought, huh, I wonder if people are just picking the first one. So then then we randomized the list so everyone saw a different order of the list and now all the items were picked equally
You don't call uninformed. You call knowing as much as there is to know and then you start picking the brains of people who might know more and have not said.
I've worked a lot of companies right but I'm wrong all the time and I think consumer behavior can be very fickle and especially when you work at a company you become a power user naturally. So sometimes you you may forget like what the actual user experience is for a brand new user.
So yes, the tools are great. We can use cursor. It helps us. It autocompletes. It writes a bunch of things. But the acceleration of learning I think is another maybe underutilized tool in all of our arsenals
I'm pretty sure people thought Microsoft had an advantage on the internet and Google and um Meta had an advantage on mobile and everyone thought IBM was going to win PCs. Like once IBM made a PC, that was it. It's all over now. And we kind of forget that like there were PCs before and then IBM made one and that kind of became the standard but then IBM lost it.
If you look at the S&P 500 now and you look at the amount of value from companies created in that, one could argue that actually almost all of the exuberance and hype was totally warranted and it in fact did change commerce in fundamental ways.
Rapid AI progress does not automatically mean rapid medical progress. If the point of AI progress is human flourishing, we must make other complementary investments too.
So picking the right question is the hardest part of science and making the right hypothesis. And that's what today's systems definitely they can't do. So I often say it's harder to come up with a conjecture, a really good conjecture than it is to solve it.
Consistent with the Kantian hypothesis, reasoning models automatically gain greater autonomy, self-consistency and long-horizon planning ability for free.
And so the great mistake of the past years was to forget how fundamental inflation was to the rise of the last political order and to profoundly underestimate how much inflation would change the current political order.
A number of studies, conducting full life-cycle analyses, have found that vertical farms currently have a higher carbon footprint than conventional outdoor farming.
I forget (again!) how I chanced across it, but it fills a very real need for a lot of the students in my inequality class, and I intend to make it recommended/optional reading in the future. (I'll have to see if the library can buy a digital copy.)
I would argue having a business leader run these institutions and then having a board that has, itself, diverse viewpoints, and by the way, permanently structured to have diverse viewpoints is a much better way to run a university than picking an academic that the faculty supports.
This, as was noted on Twitter, is a recipe for bad studies: it encourages the cherry-picking of results that went your way and the hiding of those that didn’t.
If you’ve got a small genome, the chances of you picking up the right bit of DNA from the environment is much higher than if you’ve got a genome of 20,000 genes. To do that, you’ve effectively got to be picking up DNA all the time, all day long and nothing else, and you’re still going to get the wrong DNA. You’ve got to pick up large chunks, and in the end, you’ve got to line them up, you’re forced into sex, to coin a phrase.
So, experts are highly aware of mistakes. But people who are journeymen, many of them stay as journeymen because they they want to move on and forget about their mistakes.
Governments have not been bailed out by their central banks. As I discussed earlier, central bank intervention does not reduce the overall liabilities of the consolidated government, just their composition. And it does not automatically lead to more inflation: It increases the size of the balance sheet of the central bank, but it does not increase the size of the non-interest-paying money stock.
For handling email, I use GMail with lots of filters to automatically file and label message (I get about 1400 email messages per day, so I have to be quite efficient to deal with it all in a reasonable amount of time).
When I get home all of my documents automatically upload to Flickr on private mode, so that I can choose which ones to reveal or delete with a minimum of work. I use an EyeFi Connect 4G SD card for this.
In the real world, picking up a new language takes a few weeks of effort and after 6 to 12 months nobody will ever notice you haven’t been doing that one for your entire career.
The Macbook is contextually reconfigured with Marco Polo. For example, when I plug in an Ethernet cable, Marco Polo automatically disables Airport; upon removal, Airport is turned back on.
In other words, when you go through life thinking “if I can make it through this, things will be better later,” you eventually forget what “better” means.
A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com.
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.