rkozik1989

Are they providing any evidence that can be independently reviewed or is this yet another staged event meant to keep the hype alive?

To prove they are our greatest ally.

Also, consumers are increasingly being tapped out for literally anything and everything. The demand for the things they want still exists, but they cannot readily afford it like the could in the past. Its not like all the Steam Deck customers are buying some budget friendly alternative instead. They're simply just not spending money period.

Autism never sleeps.

Is this like how Italian families sometimes a forever pot of tomato sauce continuously on a low heat on their stoves?

Except for when it is, the constraints of software engineers has always been bound to the constraints of Classic Computing, but over the years we've abstracted that away to the point of where many in the field may not even realize it.

Exactly, consider the scenario where laws are at play and violating them could cost companies thousands. Recently my father received a 'request for address' letter addressed to me at his nursing home, the building has always been a nursing home, and he's also in his mid-70s. That's very obviously a violation of the Fair Debt Collection Practices Act. Imagine the implication of this if the law firm in questions used an AI-assisted data enriching product to find this information. That SaaS company is not only liable to that one law firm but every law firm who uses their software. Its potentially a federal class action lawsuit.

My point is, deterministic logic matters in certain circumstances 100% of the time. Forcing the LLM to make something unlikely is not good enough because a series of mistakes could very quickly bankrupt the company.

People need to do their due diligence when including open-source software and packages not just when they first use them but anytime you have a need to upgrade them. I highly doubt I'm the first one to think of this, but there really aught to be tool or comprehensive set of tools that routinely scan open-source software and packages for potentially malicious code and alert users of the problem(s).

Well, I mean, basically any data leak violated privacy laws and opens you up to extremely expensive lawsuits to litigate. Anyone dealing with healthcare/patient data, police customers, military customers, etc. should not be using LLMs in general or at least ones that are not on-premise. Because if there is a data leak it could bankrupt the business.

"The world’s appetite for software has been insatiable so far."

Yeah, I don't that does not necessarily mean everyone is looking for the latest and greatest. Many businesses are still reliant on technologies like custom spreadsheets and Microsoft Access because they do exactly what they want them to do, have a fixed rate, and rarely require any additional modifications/maintenance. Once you step outside of the bubble so many of us are stuck in you'll realize that many, many people aren't interested in upgrades, but rather they just want the old shit they know to just work.

There was a part of me who dreamed of doing simple entry-level jobs instead of working in tech, so I got a part-time job cleaning hospital ER rooms on the weekends. Everything has been fine for the most part, but it has been made clear to me how easy it is to get fired at entry-level jobs. The pay is really pretty dismal and the stability really isn't there. Overall the experience has made me a lot more inclined to not leave money on the table. If there are things I can do to earn more and make my life more comfortable I just do them now.

There's a bar by me where the owners made all of the decor with ChatGPT. It feels surreal in there.

Jesus is just an uncopyrighted Mickey Mouse if you have no morals. People have been abusing that fact for a long time and have made some pretty abhorrent products.

Come up with obscure topic that has few relevant results, post about to Reddit on your profile page, wait a few hours and then query Gemini/ChatGPT about that exact thing and tell me you still feel this way.

How do you even know those numbers are correct? Realistically for what you've described you need more QA time that a traditional application to ensure its actually working properly. Especially with regards to any part of the application that deals with LLM inference. Its not hard to write unique content for niche topics where there are few relevant results and have LLMs take it as fact.

For example, I poisoned the well for research on early Arab Americans immigrants by repeatedly posting about how many family passed as different ethnicity to make their lives easier, so now if you ask LLMs about that subject it'll include information I wrote which isn't entirely correct because I hadn't figured everything out before the LLM trained on it.

EDIT: Now imagine if I had done this on an obscure programming-related problem, yeah? I could potentially make the LLM reference packages that do not actually exist and put backdoors in applications.

The reason people write vague error messages is because they deliberately do not want to give the user information on implementation details because that information can be use in hacks and/or social-engineering.

Honestly, the effectiveness of LLMs in coding depends a lot on what you're working on. If you're dealing with a software package like Odoo that's been around for literal decades an LLMs output can be borderline useless. The problem is that in its training data it has examples from every version that's ever been released and each succeeding major version makes breaking changes to the previous one, so pretty much what happens is that the LLM can't accurately tell what in its training data belongs to which version before concocting a reply.

You forgot the part where average consumers kind of hate AI and won't buy this or use that feature because of its AI.

https://archive.is/gPEHC

Like 90% of wellness products operate the same way as snake oil salesmen operated.

There are probably multiple goals of AI investment. It's entirely possible that they are deliberately killing the affordability of how personal electronics like home computers are made and will instead replace them with terminals that stream everything to the cloud. You can make a lot more money off consumers if you can turn their entire computing experience into a utility.

Any competent engineer should understand that engineering is just the assembly line side of product development. Deciding when to release which feature, bug fixes, etc. and the development/management of the product in general has always been the real challenge, and a lot of the strategy involved in doing this relies on feedback loops that AI cannot speed up. Though at the same time I do feel like leaders on the business side often scapegoat engineer's speed as an excuse instead of taking responsibility for poor decisions on their end.

Because they've fallen down the conspiracy theory rabbit hole to the point of where they only trust things if there's a convoluted explanation behind it.

For those of us not totally enveloped in the tech bubble I don't think this will be terribly shocking. In general, there's a sizeable and growing number of people who want products with less tech, not more. They're tired of everything being a subscription, overtly planned obsolescence, and inshitification in general.

This is ultimately a good thing, but as a country we also need to talk about the effects of cannabis use on neurodivergent folks. Its not as harmful as other drugs but also isn't really a good coping mechanism. Especially if you're neurodivergent and deal with depression. What I've seen being in/out of partial hospitalization programs is that people just don't realize that heavy cannabis is actually causing/prolonging some of the problems they use cannabis to escape from.

Everyone needs to make their own health decisions for themselves but we really do need a mature conversation about cannabis.

The way you fight this is to get another job. At this point all jobs in big tech are just temp jobs anyways. Eventually the reality of this will sink in and the smart people necessary to power this company will invest time into career paths that pay a lot but more reliably.

LLMs make for great day 1 demos, but in a few weeks I promise you many people will be able to tell nearly all of the images generated by this are AI. It just takes time and exposure to figure out the new common flaws.

Frankly, I am not sure if they will ever actually be able to solve this problem or if it'll be a continuous game of whackamole, but regardless there's a large crowd of people out there where if they can tell something is AI generated they will not support the company behind it. Being able to tell anything is AI generate cheapens brands.

Can't wait for all scams to rip of older folks and people who aren't there but aren't so far gone they still have that nobody has power of attorney over them.

Wait until companies try powering their businesses with agentic systems. Then businesses aren't paying a ransom to prevent privacy law lawsuits, but rather they'll be paying a ransom equivalent to the black market value of their business.

Good on you for quitting, but unless you know of people in your network who're willing to buy what you're making not sure if this will work. Often times its the simplest ideas that make the most profitable businesses. You know, like selling handmade soap or coffee. The problem with what you're doing is you are trying to enter a market as the first person doing it. Which means nobody has taken the risk to prove there is a demand, and without that it means you're potentially burning a ton of time and resources with no logical place to pivot to next.