Can't win against irrational exuberance and fraud that isn't prosecuted in the capital markets ("voting machine vs weighing machine"). Just have to wait for failure of the enterprise, equity wipeout, and recapitalization under better human management (if you're optimizing for a company that actually manufacturers and sells a product vs a shell to pump a stock and enrich the board members who enable him with a lack of corporate governance). The factories and Supercharger network will remain intact under a reorganization.
Musk can move money around SpaceX/Tesla/XAI/whatever the next story to investors is to prop up valuations and share prices, but can he win against China's clean tech export machine? Long term, I think not (China is a third of global manufacturing capacity as of this comment, and the world is their TAM). So he'll do the tech bro thing, giving talks, going to demo days, spending his wealth on pet projects, etc, while innovators innovate and point the firehose of these products at the world. Are you going to talk people out of his religion? Unlikely. The faithful will remain so, because that's how the human brain sometimes operates.
Ember Energy: China Cleantech Exports Data Explorer - https://ember-energy.org/data/china-cleantech-exports-data-e... (updated monthly) ("In 2024, China produced around 80% of the world’s solar PV modules and battery cells, and 70% of electric vehicles.")
(as of this comment, ~50% of light vehicle sales in China are NEVs [battery electric of plug in hybrid] while exporting ~6M units/year, more than total annual US light vehicle sales)
It’s never settled as the data is never perfectly accurate or exhaustive. We just have to do with the caveats and understand that perfection does not exist, even if you have more data than you can handle. That’s what error bars, uncertainty analysis, and confidence intervals are for.
Top athletes they have stats to measure. I guess for these researchers I guess there are papers? How do you know who did what with multiple authors? How do you figure out who is Jordan vs Steve Kerr?
This over reliance on llms is crazy. People are going to forget how to code. Sometimes the llm makes up shit or uses the wrong version of the API. Sometimes it's easier to look up the documentation and write some code.
All you need is a magnetized needle and a steady hand.
Years ago I interviewed at Rackspace. They did a data structures and algorithms type interview. One of the main questions they had was about designing a data structure for a distributed hash table, using C or equivalent, to be used as a cache and specifically addressing cache invalidation. After outlining the basic approach I stopped and said that I have used a system like that in several projects at my current and former jobs and I would use something like Redis, memcache, or even Postgres in one instance, and do a push to cache on write system rather than a cache server pulling values from the source of truth if it suspected it had stale data. They did not like that answer. I asked why and they said it’s because I’m not designing a data structure from scratch. I asked them if the job I am applying for involved creating cache servers from scratch and they said “of course not. We use Redis.” (It might have been memcache, I honestly don’t remember which datadore they liked). Needless to say, this wasn’t a fit for either of us. While I am perfectly capable of creating toy versions of these kinds of services, I still stand by using existing battle tested software over rolling your own.
If you worry about forgetting how to code, then code. You already don’t know how to code 99% of the system you are using to post this comment (Verilog, CPU microcode, GPU equivalents, probably MMU programming, CPU-specific assembly, and so on). You can get ahead of the competition by learning some of that tech. Or not. But technically all you need is a magnetized needle and a steady hand.
Heh, I remember an interview once and they wanted me to figure out if a word contained double letters (i.e. there's 2 L's in letters).
I was like well I'd probably just make a Set in Java and insert letters until it has a duplicate.
They didn't like that. So I was like well I guess I can make a double for-loop and check that way and they liked that ... It is weird how people like you to re-invent the wheel as opposed to just import one.
Not that I'm a fan of this kind of interview, but these answers illustrate different kinds of skill/intelligence.
One is domain knowledge which is less important in the age Google search and StackOverflow (and even less so in the age of LLMs but I guess interview techniques haven't caught up yet).
The second is the ability to understand a nested for loop, and if a coder can't do that by the point they reach an interview, it can probably never be taught.
It could be argued that being able to think up using a set in this instance is also an important skill, and I agree. But nested for loops are foundational skills, if the interviewee has problems there it's a good thing to know about early.
It could also be argued that they should just say directly "solve this using loops" if that's what they want, and well, yeah.
A Bloom filter would be a way more fun solution. But I think the quiet part of this is that people conducting interviews just like to feel clever in knowing some puzzle and its answer. Make them feel good about their puzzle and they like you that much more as a candidate.
My favorite way to interview people is to ask them about their work and personal projects and about what parts of those were tricky, why, and how they solved those challenges. This gets candidates to talk much more openly about what experience they have and we can discuss real world practical problems down to having them show pseudo code (or showing off their GitHub repos of specific projects) that can very efficiently tell you how they think. It’s the equivalent of “tell me about bridges you have designed” vs “here are popsicle sticks, design a toy bridge” approach.
Just lmao, their interviews were delusional, you aren’t alone in your experience. Especially considering what they actually mostly did was janitor MySQL databases and Drupal.
The company itself also turned into a circle of hell so probably for the best.
It was weird because their remote interview was very good and done well. It was a pair coding exercise but one that wasn’t terrible at all. And they flew me out to SF and paid for 3 days of time there which honestly was very nice. But the in person interview was a mess. Different teams I suppose.
Jokes aside, while I'm almost sure that the ability to code can be lost and regained just like training a muscle what I'm more worried is the rug pull and squeeze that is bound to happen sometime in the next 5 to 10 years unless LLMs go the way of Free Software GNU style. If the latter happens then LLMs for coding will be like calculators and such more or less and personally I don't know how more harmful that would be compared to the boost in productivity.
That said if the former becomes reality (and I hope not!) then we're in for some huge existential crises when people realize they can barely materialize the labour part of their jobs after doing the thinky part and the meetings part.
I don't think the rug pull and squeeze are possible. Because I've had the same worry. But using an existing LLM to train or fine tune a new one seems to be standard practice, and to work quite well. So any LLM with an API will end up training all the others - even open source LLMs - and all will benefit. And every day that passes, Moore makes it less and less costly for amateurs to commit the compute necessary for fine tuning, and eventually training from scratch.
In time, even video and embodied training may be possible for amateurs, though that's difficult to contemplate today.
This rhymes with the discussion we had when higher level languages became popularized. And many of us did forget how to write assembly! What might the world have looked like otherwise?
Your average professional python programmer knows a lot less about how computers work than the assembly machine level programmers of yesteryear. Software today is both worse and better. Slack uses 2gb of RAM, but is there anyone who wants to go back?
Things will probably continue in that general direction. And just like today, a small number of people who really know what they're doing keep everything humming so people can build on top of it. By importing 13 python libraries they don't completely understand, or having an AI build 75% of their CRUD app.
I think it's more like every engineer will either become like a lead or a principal or have problems. I'm a principal. I have for years had multiple teams building things that I prototyped designed or worked with them on the specs for. There's a level of touch and letting go that you have to employ to not over burden them or you getting bogged down in details that don't matter and missing those that do.
One of the skills I've developed is spinning (back) up on problems quickly while holding the overall in my head. I find with AI I'm just doing that even more often and I now have 5 direct reports (AI) added to the 6 teams of 8 I work with through managers and roadmaps.
I think there is one big difference that will differentiate between principal/lead devs and euqally experienced senior devs working with AI.. AIs are not people. Lead/principal developers are good at delegating work to, and managing, people. People and AIs have very little in common and I don't think the skills will really translate that well. I think the people who will really shine with AI are those at the principal level of skill but who are better with computers than people. They will be able to learn the AI system interaction skills without first having to unlearn all the people interaction skills and I'm not sure if the "leadership skills" that are prized in principal devs can even be unlearned they seem to be more a natural affinity than a skill.
Pretty much me with some IDEs and their code inspections and refactoring capabilities and run profile configurations (especially in your average enterprise Java codebase). Oh well.
The future is going to be great for us that have been resisting going all in. Unfortunately I feel a lot of work will be detangling the mess these llms make in larger repos.
The devils is in the details, as they say. And software engineering used to be exorcism, now they want it to be summoning. Now I'm just hopping for the majority to realize that hell is not a great environment for business.
> software engineering used to be exorcism, now they want it to be summoning. Now I'm just hopping for the majority to realize that hell is not a great environment for business
I mean, it’s just like having an army of interns that works for (near) free. It’s a huge positive for productivity, and I don’t think we will forget how. I’m more concerned with how we make new senior/staff engineers from now on, since the old “do grunt work for a couple years, then do simple well defined work for a few years” is 100% not a career path that exists even now.
This is my question as well. I am already wondering how prepared college grads will be. Getting help with programming assignments meant going to the dungeon and collaborating with fellow students while the TA made their rounds and overall just figuring it out. Today, an LLM knocks out the programming assignments in once shot, probably. And industry seems hellbent on hiring seniors mostly so where are the juniors to become seniors going to come from?
I think the talent pipeline has contracted and/or will and overcorrect. But maybe the industry’s carrying capacity of devs has shrunk.
The ironic part is that for about 10 years from 2012-2022 I used to tell people that I was very bullish on programming as a career, since I couldn't imagine any possible future where we needed less software to be written in year N+1 than we did in year N. I just didn't think of any world where we could have more software written with fewer engineers. Surprise!
This is a problem for new generations that should be mindful of but then again how many people can whip some assembly? Certainly not the majority of developers and it is certainly not required for most programming tasks. We might end up in the same situation - most of the plumbing will be done by high-level coding with the help of AI agents.
Programmable calcs were banned when I went to school since everyone was cheating with them. People even had programs to simulate the clearing of memory.
Most of our professors did allow them. As they explained their reasoning, the information you could store in your calculator memory at that time was roughly equivalent to what you could write on a single piece of paper. So they would usually allow either a cheat sheet or a programmable calculator, and designed the tests accordingly.
I personally think he and Tesla can weather this current decline in sales and make it to a world where most people have an electric car. At that point, most MAGA types around the world might just choose a Tesla over cheaper better alternatives for the status, same way many American men buy pavement princess pickup trucks over cheaper, higher utility alternatives.
IF the Maga types would be buying electric cars it'd probably be a Dodge with horns or something alike. Sleek/futuristic was never their thing to begin with.
I'm 90% sure China will be ready, able, and willing to sell a reasonably priced alternative to Americans by the time of the next US presidential election.
And the remaining 10% includes not just that they can't industrial-espionage their way to copying both product and launch vehicle, but also all the combined odds of "WW3" and "the US no longer exists" and the other less dramatic things that may stand in the way.
The most vehement Trump supporters are not the type of demographic that will make enough purchases of Teslas and Starlink to make any difference overall to the company...
He wanted to be CEO and they said no. He went a different American company that said they would let him be CEO, but he realized he didn't want to be the CEO there.
