Tanjreeve

Welcome to the problem of hiring and managing employees generally.

So basically you can't find fault with the numbers but you find the tone annoying?

I took that as exactly his point. Learning the syntax of Python or C++ or whatever isn't particularly hard. If reading the manual or being the one guy in the company who knew how the yamls worked was your "moat" then your career was built on sand. The challenge has always been leveraging that use of the tool into actually doing something useful with it.

This will do as much to solve your problem as talking to Google on why a search result was bad. Even if they agreed they won't change their coffee machine while you're there and they won't rehire more skilled staff etc etc.

Yes. At least, the manufacturing of compute is. And a lot of the chain has been bitten hard by increasing capacity prematurely in the past so they're reticent to increase bandwidth at vast cost.

There's an actual working product now, albeit one which is currently loss leading. In software world at least there is definitely enough value for it to be used even if it's just better search engine. I'm not sure why it would disappear if the financial music stops as opposed to being commoditised.

It's on the people pushing AI as the panacea that has changed things to show workings. Not someone saying "I've not seen evidence of it". Otherwise it's "vibes" as you put it.

That's still actuating using existing infrastructure that already existed. I agree with the summarise + decide part maybe being quicker sometimes but the bottleneck remains collection and collation and actioning infrastructure

AI doesn't increase the amount of data captured or the processing throughput is the difference with your cameras metaphor. As said at best it can summarise things better sometimes.

It's a compiler backend for programming languages not a runtime JIT compiler. Especially inside a DBMS a lot of the assumptions it was built with don't hold. Some people in DBMS world (mostly at TUM with Umbra/CedarDB) have written their own and others tried multi pass approaches where you have an interpreter first then a more optimised LLVM pass later.

This is the same mistake as made in Iraq and Syria by media policy pundits. Dictatorial regimes collapse pretty quickly without a significant base of support enough to stop a revolution happening. They might not have a majority of people supporting but it isn't a democracy. Dictatorial regimes will always have one or more of military, business, or sub-groups of citizens in their pockets as clients.

Whenever we say "the regime is hated by it's people it will collapse" it should be asked "then why didn't it collapse already?". In Iran metropolitan areas are where you see opposition. That's also where people have cameras and media orgs tend to be. We get a warped depiction of opposition in Iran even without our own media's baggage. Meanwhile the power base of Iran is everywhere but metropolitan cities. And there's a lot of clients who benefit from the regime. I think this might be worse than the sectarian violence that came out of the Hussein regimes collapse because the Sunni sect his base was built around was still a minority. This time it's the majority and the people being fought against are the Americans, the Israelis and the Arabs so their backs are against the wall this is a total war already from their side.

AI doesn't add anything to the ability to do mass surveillance. That genie was already out of the bottle from clouds and big data systems. At best AI might take on some of the gruntwork for drawing conclusions from profiles but it's doing it's usual thing of being a powerful interface built on top of other systems.

Ads and brainless corporate propaganda and culture wars will do that.

It means you can't crank up the knob on "burger king recommendations" for instance.

For a brief blip in time the last few years it was possible to jump from a code camp to a decent paying job and vaguely disappear for a while like Milton from office space. The current period from a bad economy is more of a reversion to the mean.

The amount of "apps" I've had dumped on my team that are everything from un-releasable to deployed on some random shit-cloud we haven't approved (vercel comes up a lot). If you needed hand holding to release things or had to throw software over the fence to others to "productionise" etc then you probably don't know what you're talking about.

Customers do see poor performance, long outages and slow releases of new features though. "Customers don't see the code" isn't a new insight.

What are you implying 5 years of experience as a Product technical delivery architect influencer and some basic web development skills don't transfer to writing critical software?

There are a few people with a powerful platform in terms of money and influence for whom it would be much simpler if the majority of people were not capable of pointing out BS or seeing how they're getting screwed. Purely coincidentally I'm sure the loudest media voices constantly declare various versions of how we should throw in the towel on educating the majority of people while also funding initiatives to enshittify public education and it would be better for most people to go into the trades and not worry their little heads about how the wider world works.

Meanwhile those people's own children are getting educated at schools with no technology allowed and are not going into trades. So it seems it's both possible to educate people given enough effort and a lot of people are capable of tertiary+ education given the right intellectual capital.

Personally I think we should allow billionaires to exist but there's plenty of nuances and implications to the political choice of allowing individuals to accumulate more money than countries to the point they get to put their thumb on the scales of politics and make markets less free but we aren't trained to reflexively dismiss discussion of that as absurd.

This might be the most annoying habit of corporarte AI that it might be one of the few industries that goes around demanding everyone else provides clear use cases and proof of efficacy for it.

1. If the benchmarks are just testing the ability to get the answers from history then something is clearly wrong with the benchmark.

2. If that's even a possibility then that's going to lower confidence in the ability to deal with the vast majority of problems where you don't already have the answer written down.

3. That's not the customers problem to solve on behalf of the vendor.

Why does this matter if these models are a super intelligence with reasoning etc and don't need the answers sucked off the internet?

This reads like you're ridiculing people for being proved right?

The first two statements would upset a lot of people but I think you'd find theyre arguably true. Most software products are various flavours of configuration. Unless you're genuinely leveraging some novel algorithm/hardware etc it's very hard to argue it's R&D if it's just branding on a collected bag of software various OSS/commercial companies developed. Claiming all software is R&D because you leverage OSS and put a known algorithm on top of some components would be like a supermarket claiming to be a research company because they have a different mix of products + customer experience to their rivals.

I think the third statement is a bit personal so will leave that alone.

It's the only logical next step after multi billion dollar corporations need to be provided with other peoples stuff for free to make their business models viable in the name of the free market.

The only actual hard data cited in this article is the opposite conclusion to the headline.

Still, language-learning app Duolingo and fintech app Klarna have recently walked back aggressive stances on replacing humans with AI.

Some studies have also shown AI isn’t panning out as much as hoped, so far. An IBM survey found that 3 in 4 AI initiatives fail to deliver their promised ROI. And a National Bureau of Economic Research study of workers in AI-exposed industries found that the technology had next to no impact on earnings or hours worked.

The data in favour of the articles conclusion is "some linkedin influencer said so" and

But Indeed’s findings show that “for about two-thirds of all jobs, 50% or more of those skills are things that today’s generative AI can do reasonably well, or very well.”

And if you read THAT article that's linking it's some MBAs speculating again at a conference. Which isn't inherently a bad thing not everything in the world can or should be quantified in a clear statistical conclusion. But appropriating the language and implying it and then the source is "some ceo dudebro said so" should be treated with at least some dubiousness at this point when a lot more of job market trends can be explained far less nebulously by a generalised slowdown in hiring and economic shocks. If I'm being less generous I can say this is yet another example of the linkedin media complex trying to rewrite reality again.

Probably never. The complexity is borne by Amazon. Even before any of the development begins if you want a RAID setup with some sort of decent availability you've already multiplied your server costs by the number of replicas you'd need. It's a Sisyphean task that also has little value for most people.

Much like twitter it's conceptually simple but it's a hard problem to solve at any scale beyond a toy.

Probably same reason as anything you work on might have undocumented stuff. Combo of lack of time and/or not wanting to imply support for unstable/experimental features. If you're only screwing over the team on the next desk or whatever it's a lot easier to change things.

If you're scared of SQL/have a massive operations team to throw infrastructure problems over the fence then that would be a positive to push all complexity into the application code as you aren't the one paying that cost.

Reputation matters. If someone comes to market with a shoddy product or missing features/slideware then it's a self created problem that people don't check the product release logs every week for the next few years waiting for them rectifying it. And even once there is an announcement people are perfectly entitled to have scepticism that it isn't a smoke and mirrors feature and not spend hours doing their own due diligence. Again self created problem.