I used to work in investment banking in the city of London and later in Canary Wharf. I loved working in the city as it was a beautiful old place, people were very social and having 2-3 hour boozy lunches with someone who you might do business with one day wasn't a rarity (mind you, I moved out before covid, I understand things have changed quite a bit).
Then I switched jobs and ended up in Canary Wharf. For those who don't know it, Canary Wharf is a newly built finance district in the London Docklands. If you've been to Singapore, Dubai, La Defense in Paris or Songdo in Korea, you know the kind of place. Everything is clean, new, modern. Everything has 90 degree angles. Everything has cameras, security guards and cleaning stuff. What it doesn't have is any resemblance of a real city, any organicity or soul.
I hated it. Every morning I saw the streams of suite dressed worker drones pouring from the tube directly into their office towers (Canary Wharf has a huge underground shopping mall/railway station that allows you to go from the subway directly into your office without ever seeing the sun).
I was unhappy. So I did similar things to the OP. I got up earlier and walked there. (I lived in Mile End). It was a nice walk along the canal for a while and then a not so nice walk through smog and traffic, but I didn't mind. I took my lunch outside on the remaining docks. And finally, I got up so early that I arrived an hour before work began.
I spent this hour in a Cafe. Alone. Having breakfast. I loved this hour. I sat there, as the only one not rushing in, getting their "strong capo", beeping their card against the reader and rushing out. I observed the grey and black dressed stream of people. I day dreamed.
It helped - for a while. It was a band aid before I left London all together and moved to Berlin. But most of all, it is a uniquely calm and joyful experience. It decelerates you. The boheme in Paris or Prague has long figured this out. Sit in a cafe. Enjoy a coffee or a glass of wine. Look at people. Daydream. Reflect, be enough - there's a lot to it.
Singapore to a tea. Spooky that I had a similar path, Sydney -> HK -> New York -> Singapore. Crescendo-ing up to New York, then off a cliff into a full blow school-like world (but great trains).
It was a privatization in name only. The German state held 100% of its shares since the beginning. As such, it might have no longer been subject to the state specific demands of hiring etc. - but instead found itself in an uneasy tension as the only supplier of services to an entity that was something between a customer and a shareholder.
Which brings up an interesting question: How do you structure something with a large piece of infrastructure like a rail network in a way that could benefit from the market forces of competition and innovation?
> Which brings up an interesting question: How do you structure something with a large piece of infrastructure like a rail network in a way that could benefit from the market forces of competition and innovation?
A rail network is near to a natural monopoly. You can build overlapping rail networks, but it's complex and interconnecting instead of overlapping would usually offer better transportation outcomes and there's a lot less gauge diversity so interconnection is more likely than overlap.
All that to say, you can't really get market forces on the rails. Rails compete with other modes of transit, but roads and oceans and rivers and air aren't driven by market forces either.
Transit by rail does compete in the market for transit across modes. You can have multiple transportation companies running on the same rails, and have some market forces, but capacity constraints make it difficult to have significant competition.
> capacity constraints make it difficult to have significant competition
Thirty years ago, you would be correct. In the modern day, you could tie switch signalling to real-time auctions and let private rail's command centers decide how much to bid and thus whether or not they win the slot for putting their cars onto the shared rails. The public rail owner likely needs to set rules allowing passenger rail to pay a premium to secure slots in advance (say, a week) so that a timetable can be guaranteed to passengers during peak rush hour, but off-peak slots can and should be auctioned to naturally handle the difference between off-peak passenger rail and not-time-sensitive, more-cost-averse freight rail.
You can’t. Every attempt at privatizing rail is a failure with worse performance, higher prices, and an inevitable level of special treatment by the state due to the monopolistic utility-like nature of rail infrastructure. Not everything needs to or should be privatized.
Not, that "insight" again. Yes it was privatized and yes it is still completely owned by the state. "Privatization" is a term of art (in German) that refers to the corporate structure not the ownership. There are also public corporations in Germany, that are fully owned by random people: e.V. = registered association.
I believe modern economists are studying how ownership should be assigned. The thinking is that contracts and rules handle the majority of situations but emergencies and edge cases require an owner who has authority and whose interests align with the thing they control. And you want a mechanism to reassign ownership when the previous owner is incompetent.
In the case of a national train system, you may want to create a national entity to develop, coordinate, and make the physical trains and support technologies. You would create regional or metro entities to control the train network for their local area including the train stations. They coordinate with each other via negotiated contracts. Any edge cases or emergency falls under the purview of the owning entity. For example, the national entity controls the switch from diesel locomotives to the newest engine. The local authority is responsible for repairing the lines after a natural disaster.
If an entity is egregiously incompetent or failing, the national regulatory authority, with support of the majority of all the different train entities, takes control and reforms it.
I'm wondering if this overlooks areas where we experience much higher levels of deviation today. Take music, for example. When I grew up, I was basically limited to whatever was playing on the radio or MTV—there was only so much airtime for a small set of popular songs. The mainstream was much more mainstream. Today, I can listen to obscure Swedish power metal bands with fewer than 5,000 monthly listeners on Spotify without any difficulty.
The same goes for fashion. I have a picture of my mom and her friends where everyone looks like a miniature version of Madonna. Today, fashion seems far more individualistic.
Streaming has given us a vast spectrum of media to consume, and we now form tiny niche communities rather than all watching Jurassic Park together. There are still exceptions like Game of Thrones, The Avengers, or Squid Game, but they are less common.
One of my friends is into obscure K-pop culture that has virtually zero representation in our domestic media. Another is deeply interested in the military history of ancient Greece—good luck finding material on that when there were only two TV channels.
Maybe deviance hasn't disappeared—maybe it's just shifted elsewhere…?
I'd also argue the culture of "digital degeneracy" has permeated the internet and is no longer locked away in, say, the bastion of mid/late 2000s 4chan. What used to be violent NSFL liveleaks content is now easily accesible by anyone with a phone. Softcore content is completely widespread on "clean" apps like IG and Tiktok.
If we measure deviance only by the metrics that existed before social media, we will of course find what is expected.
Consuming niche stuff isn't really deviance in any meaningful sense.
There's no risk-taking there, no producing something new for the world, and very little personal actualization beyond getting to consume a thing you like.
Maybe we're looking at this wrong. Maybe 'new' stuff just isn’t that interesting to people any more. I mean the amount of 'new' things out there are huge and we are constantly exposed to them lots of them. Then when you couple that with the massive amount of advertising that is everywhere on every surface and site, people start to brain adblock and focus on patterns they recognize.
we're actually working on a practical implementation of aspects of what Fei-Fei describes - although with a more narrow focus on optimizing operations in the physical space (mining, energy, defense etc) https://hivekit.io/about/our-vision/
Looks amazing- and the point they're making in the article is correct. Switching back and forth from VS to PG Admin creates friction that this seems to solve in a much nicer way
Maybe we need to widen our search for life. Earth is a planet with about 15 degree average temperature and abundant water and oxygen. So that's what live here consumes and where it thrives. But life is all about adaptation. So, father than looking for planets with similar temperatures and resources, shouldn't we be looking for other possible foundations for life? Maybe there's a thriving civilization out there, living happily at 300 degrees, breathing neon and eating sulfur?
I don't think its about devaluing the currency to pay back debt at all. I believe it's about a fundamental vision of an autark USA, decoupled from any international obligations, whether its NATO, WHO or WTO and focused purely on producing and selling domestically whilst having a "beautiful ocean on each side".
I believe that's an unrealistic vision, not least since America's debt means it cannot afford significant shrinkage of its global market or a loss of its status as reserve currency, but I believe autarkie is the goal none the less.
I believe there are two kinds of skill: standalone and foundational.
Over the centuries we’ve lost and gained a lot of standalone skills. Most people throughout history would scoff at my poor horse-riding, sword fighting or my inability to navigate by the stars.
My logic, reasoning and oratory abilities on the other hand, as well as my understanding of fundamental mechanics and engineering principles would probably hold up quite well (language barrier notwithstanding) back in ancient Greece or in 18th century France.
I believe AI is fine to use for standalone skills in programming. Writing isolated bits of logic, e.g. a getRandomHexColor() function in JavaScript or a query in an SQL dialect you’re not deeply familiar with is a great help and timesaver.
On the other hand, handing over the fundamental architecture of your project to an AI will erode your foundational problem solving and software design abilities.
Fortunately, AI is quite good at the former, but still far from being able to do the latter. So, to me at least, AI based code editors are helpful without the risk of long term skill degradation.
This is a great comment and says what I've been thinking but hadn't put into words yet.
Too many people think what I do is "write code". That is incorrect. What I do is listen, read, watch and think. If code needs writing then it already basically writes itself because at that point I've already done the thinking. The typing part is an inconvenience that I'd happily give up if I could get my thoughts into the computer directly somehow.
AI tools make the easy stuff easier. They don't help much with hard stuff. The most useful thing I've found them for is getting an initial orientation in a completely unfamiliar area. But after that, when I need hard details, it's books, manuals, blogs etc just like before. I find juniors are already lacking in their ability to find and assimilate knowledge and I feel like having AI isn't going to help here.
Abstracting away the software paraphernalia makes this more clear in my view: our job is to understand and specify abstract symbolic systems. Making them work with the current computer architectures is incidental.
This is why I don't see LLM assisted coding as revolutionary. At best I think it's a marginal improvement on indexing, search and code completion as they have existed for at least a decade now.
NLP is a poor medium for specifying abstract symbolic systems. And LLMs work by finding patterns in latent space, I think. But the latent space doesn't represent reality, it represents language as recorded in the training data. It's easy to underestimate just how much training data were used for the current state-of-the-art foundational models. And it's easy to overestimate the ability these tools have to weave language and by induction attribute reasoning abilities to them.
The intuition I have about these LLM-driven tools is that we're adding degrees of freedom to the levers we use. When you're near an attractor congruent with your goals it feels like magic. But I think this is over fitting: the things we do now are closely mirrored by the data we used to train these models. But as we move forward in terms of tooling, domains, technology, culture etc, the data available will become increasingly obsolete, relevant data increasingly scarce.
Besides there's the problem of unknown unknowns: lots of people using these tools are assuming that the attractors they see pulling on their outcome is adequate because they can only see some arbitrary surface of it. And since they don't know what geometries lie beneath, they end up creating and exposing systems with several unknown issues that might have implications in security, legality, morality, etc. And since there's a time delay between their feeling of accomplishment and the surfacing of issues, and they will be likely to use the same approach, we might be heading for one hell of a bullwhip effect across dimension we can't anticipate at all.
>The typing part is an inconvenience that I'd happily give up if I could get my thoughts into the computer directly somehow
I understand what you mean, but for some reason I cannot imagine my younger self getting into his first programming practice, going "ugh, why do I have to type this? Why can't I just think and let the computer do it for me". I don't think I would've reached where I am if I saw the act of practice as a tedium that I wish to get it removed.
You probably see it like that because you're not that kid anymore, and for today's "you" code is just a means to provide and nothing more.
I'd classify this as theoretical skills vs tool skills.
Even your engineering principles are probably superior to ancient Greeks, since you can simulate bridges before laying the first stone. "It worked the last time" is still a viable strategy, but the models we have today means we can often say "it will work the first time we try."
My point being that theory (and thus what is considered foundational) has progressed as well.
> horse-riding, sword fighting or my inability to navigate by the stars.
Some better more suitable examples would be warranted here, none of these were as widespread or common as you'd assume. Little to no metaphorical scoffing would happen for those. Now, sewing and darning, and subsistence, while mundane, are uncommon for many of us.
For some strange reason, I’m better at sewing than both my wife and mother-in-law. I learned it in public school when both genders learned both woodworking and sewing, and maintained an interest so that I could wear “grunge” in the 1990s. The teachers I had remembered that those classes were gendered while they worked.
“still far from being able to do the latter”
These models have been in wide use for under three years. AI IDEs barely a year. Gemini 2.5 Pro is shockingly good at architecture if you make it into a conversation rather than expecting a one-shot exercise. I share your native skepticism, but the pace of improvement has taken me aback and made me reluctant to stake much on what LLMs can’t do. Give it 6 months.
I'd say because psychologically (and also based on CS Theory) creating something and verifying draw from similar but also unrelated skills.
It's like NP. Solving an NP problem is very hard. Verifying that the solution is correct is very easy.
You might not know the statements required, but once the AI reminds you of which statements are available, you can check the logic using these statements makes sense.
Yes, there is a pitfall of being lazy and forgetting to verify the output. That's where a lot of vibe coding problems come from in my opinion.
The biggest problem with LLMs is that they are very good at presenting something that looks like a correct solution without having the required knowledge to confirm if it is indeed correct.
So my concern is more "do you know how to verify" rather than "did you forget to verify".
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