Bjorkbat

I was actually about to make a comment on that. They got that number from some dumb "experiment" they did where told two groups of developers to implement an HTTP server in Javascript. The group with Copilot got the job done 55% faster (https://github.blog/2022-09-07-research-quantifying-github-c...)

So yeah, they did an experiment with <100 developers asking them to create implement something that only took the control group 3 hours to finish from scratch, and from this we got the "55% more productive" statistic.

Something I keep thinking about is how we’re seeing the end of what I call the “tech zeitgeist”.

Started upon realizing that we‘ve likely seen the end of the social network era. No new social networking startups have popped-off in a while, and the recent ones are arguably more about connecting you to entertainers than friends.

Besides that, a lot of the tech ideas from 2012-2020 have kind of fizzled out. 3D printing will likely never enter the mainstream. VR/AR has failed to launch. In broad strokes, everything has either reached maturity or faded away.

AI is the one exception it seems, and when you realize that you start to realize that all the hype and money being poured into AI may be more out of desperation than anything else. It’s AI or nothing it seems.

And then, you have Apple at what is arguably its most vulnerable, while many other tech giants go through some kind of enshittification phase.

Can’t wait for the end personally.

I'd like to see if this still works if I took a picture of myself wearing a MAGA hat

I love this podcast so much I make something of an event out of it when each episode comes out.

When the video format Egyptian one comes out, I’ll probably try my hand at some Egyptian Koshari and Mesopotamian Mersu.

Put a UVC emitting light in your mouth for 5 minutes a day (please don’t)

Yeah, but does it matter? Most of their revenue comes from enterprise clients and it seems more likely that someone is going to create a killer app for AI by leveraging APIs and publishing their work on traditional distribution channels rather than creating something that only works on a relatively niche platform.

Like, hypothetically, if Anthropic took the lead in this effort, I don't think it would derail OpenAI's plans in the slightest.

Reminds me of an early rumor back when Sam Altman was fired (and briefly re-hired) that the old board allegedly was very much against the GPT store.

I kind of get why now. It arguably doesn't really aid in the non-profit's mission to pursue AGI, or share the benefits of AI with humanity, or any of that stuff. Doesn't even seem to be much of a worthwhile endeavor from a purely money-making perspective either.

I mean, since we're sharing Forbes links https://www.forbes.com/sites/kenrickcai/2023/06/04/stable-di...

The CEO of Stability seems to be rather controversial person at the helm of a rather controversial company. I'm honestly surprised more people haven't left the company by now, unless they had some absurd incentives to stick around.

He also left DeepMind because of allegations of bullying employees (https://en.wikipedia.org/wiki/Mustafa_Suleyman). Between that, what you just brought up, and the strange PR blitz he went on to promote his book, I kind of predicted Inflection would run into major trouble well before OpenAI and Anthropic

Huh, this whole time I thought they were just a way to launder money from selling meth

Reminds me of this paper where some researchers had AIs role play as employees at a startup and tasked them with building various forms of software. It was pretty interesting. Managed to build Pong.

Thing is though, they neglected to compare this against a control, and the examples they tested this on were examples that GPT had no problem building. No idea if this actually improved performance in LLMs.

I think comments like these are worthwhile because, frankly, I can’t trust AI researchers to run good experiments or evaluate their models properly for a variety of reasons. I mean, most scientific papers in general are hard to replicate and have flaws concerning sample size and what have you (Related, I still remember my disillusion in finding out that the average Hacker News commenter was an idiot incapable of critical thinking when the LK-99 hype reached a fever pitch). In any other context we would be deeply suspicious of the results if they were sponsored by a corporate party, yet in the context of AI we don’t seem to care that most AI researchers work for Microsoft.

Something not often discussed when it comes to work in the trades is that it can really beat up your body after some years. Not uncommon to hear stories of guys getting hooked on painkillers.

> Disclosing that the content was generated by AI

Hmm, hadn't thought of that angle before. So, like, if one uses a copilot to generate code, does it now have to be watermarked somehow?

You don't necessarily need AI to create a door that opens during a fire alert. You could simply make it so that the door is no longer badge controlled if a fire alert goes off.

Sure, it's possible someone might exploit this by creating a fake fire alert to open the door, but they could also trick the AI you suggested by using a fake panicked expression, maybe get some friends in on the prank.

Kind of a segue into why I think AI hype and crypto hype are uncannily similar. You could argue that blockchains have a lot of potential uses, it's just that we already have some kind of legacy technology that works fine and is usually much cheaper. In much the same way, I'd say 90% of people are using LLMs as search engines, albeit search engines that are more expensive and return strange results.

Anyway, point being, 99% of the applications one could imagine getting sniped by this law probably can probably be implemented using alternative, non-AI technologies.

Reminds me of the no-code / low-code hype around 2020, tons of startups advertising app-builders that used little, if any, AI. Just blocks that you dragged-and-dropped. While many of them were successful, it seems like overall they didn't really make much of a dent in industry, which I found very curious.

Like, by now you'd think it would be inevitable that we wouldn't be writing software in a text-editor or IDE. Everything else we do on a computer is more graphical rather than textual, with the exception of software development. Why is that?

Part of the reason why I'm kind of bearish on AI is because it seems like we could have replaced written code with GUI diagrams as far back as the 80s, or at the very least in the early 2000s, and it seems like something that should have obviously caught on given that would probably be much easier for the average person. Again though, curiously, we're still using text editors. Perhaps despite the popularization of AI no-code builders we'll still see that the old model of hiring someone good at writing code in a text-editor remains largely unchanged.

Makes me wonder if there's just something about the process that we overlook, and if this same something could frustrate attempts at automating the process of writing code using AIs as much as it frustrated our attempts at capturing code using graphical symbols.

Also, something else to consider, I kind of consider the automation of writing code not all that different from the automation of architectural and engineering drawings. No doubt some engineers were distraught when computers took the fun out of drawing, and professional draftsmen were devastated, but otherwise engineering is still viable enough as a career for parents to pressure their kids into studying it.

Perhaps a more realistic prediction of the future is that we start to identify a little more as designers, concerned more with the design of software and how it functions, rather than engineering concerns like making code performant and efficient.

I felt that software engineering as a career had a short shelf-life around 2020, but I wasn't too worried about it, as I figured I'd probably just transition to design as a career, I kind of think graphic design is cooler anyway. I began to have doubts about this plan once DALL-E caused an existential panic among illustrators, but otherwise I think it still has legs.

Those who adapt will probably do so by essentially becoming UI/UX designers who happen to also know how to code well, and probably know some other more general design skills just to round things out a little more.

Something I kind of tell myself is that if AI effectively becomes a drop-in replacement for software engineers (or is at least 95% as good as the median one) it's going to suck because I lost my job and we've killed one of the few good careers that exist out there, but on the other hand, look at the big picture. I'm not even sure the "software" industry will exist.

I mean, think about it. Rationally speaking, if people can hire AI engineers at a fraction of the cost of minimum wage employee, then the price pressure on software will be "significant" to put it mildly. The more complex a piece of software is, the more incentive there is for open-source developers to collaborate and pool their resources to make a cheaper alternative using AI agents. This logic could even extend to the AI agents themselves.

I know my prediction is deeply flawed, but basically, if we create an AI that's a drop-in replacement for (most) software engineers, we're probably going to have a massive deflationary crash not just from the software sector, but in the economy in general considering that many white-collar workers have also probably been automated, with the consequences that follow.

I might lose my job, but I'm going to take so much more down with me. My loss is their catastrophe. Sounds terrifying, maybe terrifying enough for our political representatives to address the elephant in the room, that an AI just took out their tax base, the people who still have a job probably make so little that their tax contributions are cancelled out by government benefits (not just welfare mind you, but the simple fact that they drive on free roads), and taxing corporations won't fix this when corporate revenue is probably going to also decrease.

Otherwise though, we're notoriously bad at predicting the future and estimating the general difficulty of something as ambitious as trying to replace certain careers with AI or robots. Any argument you could make for why software engineers (or white-collar work in general) will be different this time was probably made earlier by someone in reference to something like self-driving cars or physical labor, or possibly in reference to a prior attempt at automating white-collar work using a more primitive form of AI.

Best course of action, individually, is probably to skate to where the puck is heading and make an earnest effort at improving your productivity with software copilots, but otherwise I think the least likely outcome is that automating the software engineering profession is as easy as the e/acc crowd on Twitter would have you believe.

I mean, this might just be existential cope, but my first thought when looking at the Upwork demo posted on Twitter (https://x.com/cognition_labs/status/1767548768734294113?s=20) was that it seemed a little bit suspicious.

Namely, the client was asking for an unusually specific (for Upwork) ask. It was an almost perfect example of a job to be given to an AI agent for testing purposes.

For the longest time I thought the person behind the account was just some random guy who was probably very into crypto and decided to dabble in AI because of the parallels between e/acc and the whole "to the moon" messaging you find in crypto communities.

Never would have guessed the guy was an actual physicist

Honestly, as interesting as the the chip sounds, I'm admittedly kind of biased against the company's probability of success simply because the founder is basically the #1 e/acc meme account/shitposter on Twitter.

Like, it's hard to take someone seriously when they spend tons of time shitposting on Twitter, it's even harder when it's revealed that they're behind one of the most popular shitposting accounts within a niche, almost cult-like community.

I'm not sure how much of a risk this is to LLMs in particular, but I feel like we're already seeing the impact on image AI models.

Even though they're getting better at generating hands that make sense and other fine details, you can generally tell that an image is AI generated because it has a certain "style". Can't help but wonder if this is partly due to generated images contaminating the training data and causing subsequent AI image generators to stylistically converge over time.

Ironically Claude 3 appears to have certain "quirks" arguably caused by the fact that its training data contains synthetic data. In one instance (https://twitter.com/DimitrisPapail/status/176477229891207585...), it kept referring to itself as ChatGPT.

Granted, one could argue that this only happened because the API version of Claude doesn't appear to use a system prompt. If that's the case, then the LLM lacks any identity otherwise defined by the initial system prompt, and thus, kind of makes one up.

Nonetheless, point remains, it's kind of interesting to see that in the years since the launch of ChatGPT we're already seeing a tangible impact on publicly available training data. LLMs "know" what ChatGPT is, and may even claim to be it.

I mean, I definitely disagree with the statement that GPT-4 is an AGI, but OpenAI themselves define an AGI in their charter as an AI that is better than the median human at most economically valuable work.

Even when taking that into consideration I don't consider GPT-4 to be an AGI, but you can see how someone might make attempt to make a convincing argument.

Personally though, I think this definition of AGI sets the bar too high. Let's say, hypothetically, GPT-5 comes out, and it exceeds everyone's expectations. It's practically flawless as a lawyer. It can diagnose medical issues and provide medical advice far better than any doctor can. It's coding skills are on par with that of the mythical 10x engineer. And, obviously, it can perform clerical and customer support tasks better than anyone else.

As intelligent as it sounds, you could make the argument that according to OpenAI's charter it isn't actually an AGI until it takes an embodied form, since most US jobs are actually physical in nature. According to The Bureau of Labor Statistics, roughly 45% of jobs required medium strength back when the survey was taken in 2017 (https://www.bls.gov/opub/ted/2018/physically-strenuous-jobs-...)

Hypothetically speaking, you could argue that we might wind up making superintelligence before we get to AGI simply because we haven't developed an intelligence capable of being inserted into a robot body and working in a warehouse with little in the way of human supervision. That's only if you take OpenAI's charter literally.

Worth noting that Sam Altman himself hasn't actually used the same definition of AGI though. He just argues that an AGI is one that's simply smarter than most humans. In which case, the plaintiffs could simply point to GPT-4's score on the LSAT and various other tests and benchmarks, and the defendants would have to awkwardly explain to a judge that, contrary to the hype, GPT-4 doesn't really "think" at all. It's just performing next-token prediction based on its training data. Also, look at all the ridiculous ways in which it hallucinates.

Personally, I think it would be hilarious if it came down to that. Who knows, maybe Elon is actually playing some kind of 5D chess and is burning all this money just to troll OpenAI into admitting in a courtroom that GPT-4 actually isn't smart at all.

A little anecdotal evidence, I've been car free for over 3 years now, and do everything by e-bike unless it's after dark, in which case I just get an Uber. About a year-and-a-half into being car-free I made the switch from a normal bike to an e-bike, and not long after began to make far, far longer trips as a result. Pretty much opened up the whole city to be.

Which is significant, as I live in Albuquerque. It's one of the least densely populated cities in the US. Everything's all spread out, and the difference in elevation from the highest to the lowest parts of the city is over 1,500ft

If you had given me their explanation of events before I had any knowledge of the output from ChatGPT, then I would infer that the output would be random gibberish, or perhaps something more akin to creating an accidental shift cipher of sorts. Instead, while ChatGPT's outputs still made no sense, they still followed a certain "order".

In one amusing Twitter example, some guy asked it a math problem and ChatGPT replied with "It's the mix, it's the match, it's the meter, it's the method." and repeated sentences of this structure for who knows how long.

I guess what I'm getting at is that it's kind of an underwhelming, unsatisfying explanation of events given how truly bizarre some of the outputs are. Like, you'd assume it would be something more other than "Oops, picked the wrong numbers, gonna repeat this sentence 100x but with slightly different word choices each time".

It's more that they don't care if, say, an automated support chatbot doesn't work in Firefox. In which case they tell you to just use Chrome rather than submit a ticket telling one of their web devs to fix something.

Something I take issue with concerning AI, which is also incidentally why I remain skeptical of it, is that it feels like it doesn’t increase agency in any meaningful way, and sometimes decreases it.

With image generation, you can generate seemingly infinite images with nothing but a prompt, but you’ll never get what you really want. You’ll get an approximation at best. You have all this agency, but also no real agency that matters.

But of course if you’re a visual professional of some kind then I imagine it’s even worse, a net decrease in agency. Not only can you never quite get what you want, but having to go in and edit things is tedious and dull. Even if you’re saving time this way, the lack of enthusiasm and flow makes it feel like the job takes much longer than before.

Likewise, with programming, at the end of the day it feels as if I’d be more productive and just wrote down my thoughts as code rather than delegate to a copilot or ChatGPT and waste time making sure this actually works or solving for the occasional bug that came from a chunk of mystery code.

At the end of the day, you aren’t creating the image or the video, the AI is and you make adjustments where you can but otherwise accept the results. Extrapolating this to software, I don’t imagine a future of where people are empowered to write their own software, but simply a future where people ask for software from an AI, it gives it to them, and they do an awkward back and forth to try and get the details right until they inevitably accept what’s been given to them.

It’s depressing, but also so goofy that it’s hard to imagine this being the final outcome.

As bad as Google Search is I‘m cautious about the prospects of this making a dent in their search monopoly.

Remember when ChatGPT was integrated into Bing? Turns out that did nothing for search market share.

I have the paywall as well, but in the opening sentence they mention they confirmed it with a spokesperson at the company. Sounds pretty legit.

>Large companies in any industry are generally not trendsetters but laggards because they have so much invested in the systems they already have in place. Moving all of Google or Microsoft remote is a daunting task. Starting a new company fully remote and then growing to Google or Microsoft's scale is much more practical and I think something we'll see over the next 10 to 15 years.

Yeah, but Google and Microsoft both already have offices in India. They have logistics and infrastructure that have been in place not just for years, but for 2 decades. Nonetheless, latest figures I could pull for Microsoft's total headcount in India was 18,000. Impressive, until you consider that they employ 238,000 employees.

I'm not saying it's curious that they haven't gone fully remote by now. What I'm saying is that it's curious that their talent pool isn't more evenly distributed across the globe despite the fact that they've had a 20 year head start.

Sure, large companies aren't trendsetters, but by this point outsourcing is pretty conservative. Just within tech alone it was something that was talked about in the very early 2000s.

Regarding the two points you bring up, agree in that it makes hiring globally distributed talent easier. It's no longer inconvenient to make special accommodations for an employee in LatAm when you're making the same accommodations as everyone else.

Nonetheless, you still have companies that were fully-distributed and fully-remote well before it became trendy. They made the same special accommodations for everyone. The technology available at the time was already good enough to allow them to hire talent from anywhere across the globe. Even so in many cases it's the exception rather than the rule that their employees live in a low CoL country rather than a high one. Most of the employees tend to work either in the US or Europe. Take any prominent company that's been remote since the early 2010s, look at their about page, you generally see this trend.