Investment giant Goldman Sachs published a research paper
Goldman Sachs researchers also say that
It's not a research paper; it's a report. They're not researchers; they're analysts at a bank. This may seem like a nit-pick, but journalists need to (re-)learn to carefully distinguish between the thing that scientists do and corporate R&D, even though we sometimes use the word "research" for both. The AI hype in particular has been absolutely terrible for this. Companies have learned that putting out AI "research" that's just them poking at their own product but dressed up in a science-lookin' paper leads to an avalanche of free press from lazy credulous morons gorging themselves on the hype. I've written about this problem a lot. For example, in this post, which is about how Google wrote a so-called paper about how their LLM does compared to doctors, only for the press to uncritically repeat (and embellish on) the results all over the internet. Had anyone in the press actually fucking bothered to read the paper critically, they would've noticed that it's actually junk science.
saying the quiet part out loud... big tech won't like that.
I've found like, 4 tasks that are really helped with by AI, and I don't have the faintest idea how you could monetize any of them beyond "Subscribe to chatgpt"
At my previous job their was a role where you just called insurance companies and asked them incredibly basic questions about what they planned to do for a patient with diagnosis X and plan Y. This information should be searchable in a document with a single correct answer, but insurance companies are too scummy for that to be reliable.
In 2021 we started using a robot that sounded like a human to call instead. It could handle the ~80%+ of calls that don't use any critical thinking. At a guess, that's maybe 5-10% of our division's workforce that wasn't needed anymore.
With the amount of jobs like this that are 100% bullshit, I'm sure there are plenty of other cases where businesses can save money by buying an automated bullshit generator, instead of hiring a breathing bullshit generator.
The problem is that 20% failure rate has no validation and you are 100% liable for the failures of an AI you're using as a customer support agent, which can end up costing you a ton and killing your reputation. The unfixable problem is that an AI solution takes a ton of effort to validate, way more than just double checking a human answer.
With streaming services they're proving it's not viable to run a resource hog of a service with a measly monthly subscription.
With social media they're proving it's not viable to run a resource hog of a service for free, even with advertisement.
So naturally the best plan to monetize AI is to run a resource hog of a service with a measly monthly subscription and a free version without advertisements. /s
Sometimes that bear shits in my yard. And then the little asshole trashes my garden. I might buy a tag and shoot the son of a bitch this fall if he keeps it up.........
Recently there was one in British Columbia that locked itself in a hot car, freaked out and tore up the interior completely, and then had to be rescued by the cops.
The stuff they're calling ai now is just predictive text algorithms. I really can't wait to stop hearing about this because it is all artificial with no intelligence.
LLMs have been shown to have emergent math capabilities (that are the opposite of what is trained) so you’re simplifying way too much. Yes a lot is just “predictive text” but there’s a ton of “this was not the training and we don’t know how it knows this” as well.
LLMs are predictive-associative token algorithms with a degree of randomness and some self-reflection. A key aspect is that anything can be a token, they can self-feed their own output, creating the basis for a thought cycle, as well as output control input for other algorithms. It remains to be seen whether the core of "(human) intelligence" is much more than that, and by how much.
Stable Diffusion is a random image generator that refines its output based on perceptual traits associated with a prompt. It's like a "lite" version of human dreaming, only with a super-human training set. Kind of an "uncanny valley" version of dreaming.
It just so happens that both algorithms have been showcased at about the same time, and it's the first time we can build a "set and forget" AI system that can both make decisions about its own next steps, and emulate human creativity... which has driven the hype into overdrive.
I don't think we'll stop hearing about it, but I do think there is much more to be done, and it's pretty much impossible to feed any of the algorithms with human experience data, without registering at least one human learning cycle, as in over many years from inside a humanoid robot.
American Psycho (Sam Altman) and his chorus have been hyping AI and the rest of the world's reaction has ranged from "these guys seem smart and chatgpt is impressive so what do I know?" to "isn't this guy a bitcoin bro?"
Funny you should mention that McKinsey published a paper a few months back concluding that GenAI will take over most of the jobs in America because it was good at doing what McKinsey Associates do. Missed by the authors is that the job of a McKinsey associate is to confidently spout nonsense all day long and that's actually exactly what chatgpt is programmed to do.
chatgpt: "Artificial Intelligence (AI) represents a transformative investment opportunity, characterized by robust growth potential and broad applicability across industries. The AI market, projected to exceed $190 billion by 2025, offers substantial upside in sectors such as healthcare, finance, automotive, and e-commerce. As businesses increasingly adopt AI to enhance efficiency and innovation, associated firms are poised for significant returns. Key investment areas include machine learning, natural language processing, robotics, and AI-driven analytics. Despite risks like regulatory challenges and ethical concerns, the strategic deployment of capital in AI technologies holds promise for long-term value creation. Diversification within this space is advisable to mitigate volatility."
I mean, ask pretty much anyone familiar with the workings of AI who doesn't have a vested interest, and they'll say the same thing. Goldman is right.
I'd also say that it does have applications, but it's going to take a moment for all the bullshit artists to move on to the next thing so the grown-ups can work. It's a bit like graphene research circa-2011, although it's way more proven than graphene ever was.
They might also say that the moment it does work reliably we should be scared, although it's fair to say there's many experts who take the obvious stance.
There are studies that suggest that the information investment firms publish is not based on what they believe to be true, but on what they want others, including their competitors, believe to be true. And in many cases for serving their investment strategy, it benefits them to publish the opposite of what they believe to be true.
Oh no, you mean the big "smart" money investors that manage to crash the economy every decade or so and ruin every business they touch are gonna leave generative AI alone? Oh nooo. How will the science progress without Goldman Sachs's guiding hand?
Oh, so now we're supposed to pay attention? Internet pundits came to the same realisation from the beginning, but we don't have the same kind of purchasing power.
Yep, as wildly expensive and unreliable as AI is, so are staff.
Watch as loads of people get laid off, they realise the AI can't do their jobs after all, but you know who can give it a go? Some guy in a third world country on $3 an hour.