Thesis:
LLM's are unpopular, they successfully replaced the "multi-trillion" dollar market of StackOverflow dot com, and they want you to carry the bag with your 401k.
My background:
I'm a 35 year old software engineer, former Microsoft Azure, and was laid off due to AI. I have 17+ years of dev experience, the most recent of which has been spent working on Datacenter technology (Azure).
The Technology and the facts:
LLMs and generative AI as a whole are almost exclusively responsible for the recent. At its core, LLMs are an algorithm that works as such: when given a user input, the LLM calculates the mathematical approximation of what the user asked for. It really is that simple, there is no thinking, it just looks at what you are asking for, scours its training and the internet for the best match, adds some randomness, and then spits out an answer.
Let's look at Anthropic's Fable model for example. If I were to give a simple prompt like "Build me a full dating application inspired by Tinder", you'll see it quickly deliver a seemingly impressive "functioning" dating website in a matter of 30 minutes. While on the surface this seems impressive, it's a lot less so when you consider that building a dating website is essentially the tutorial island of web development; there are just sooo many resources online on how to build a Tinder clone, it's not a secret.
To really see how terribly inadequate LLM's are at replacing software engineers, all you have to do is add in a small twist, ask it to do something that lacks broad documentation. Once a LLM is trusted to make any decisions on its own, or tasked with coming up with something "original", it crumbles. By its nature this is an impossible task; the LLMs ability to create something is directly proportional to the amount of data it has on that specific topic.
This explains why LLMs are very powerful in shallow contexts such as "help me design this component" or "help me refactor this chunk of code", but terrible at broad unspecific tasks like "improve this codebase" or "develop this new web application idea". Once you put the LLM in a context is has little training for, it's strategy of plagiarizing other people's code quickly falls apart. This applies to other generative AI domains such as image, video, and music generation.
The OpenAI Whistleblower Suchir Balaji:The counter argument:
"But the market is fake, they will pump the stocks anyways"
To who? The main issue with this premise is that people who have been investing trillions into these data centers and these slop models have no got any return on their investment yet. The problem, unlike previous Tech Startup success stories, there is no product and there is no demand. It's all predicated on the promise that it will eventually replace us all, it's a transparent lie.
"The government will step in and ensure AI can't fail"
Maybe, but that can't really happen until a bubble bursts. You can't stimulate a stock market that is sitting at all time highs, especially with 40 trillion in debt.
External pressures:
US losing complete control of the Strait, a PDF file and gambling economy, no houses for young people, insane gas prices, 40 trillion in debt, you take your pick.
What do you do:
I'm not telling you. Fuck it, YOLO.