There are also hard mathematical limits stalling AI growth. Frontier models haven’t improved in like a year despite being fed money by basically the entire global economy. Diminishing returns on steroids basically. They’re already at the limit of what they can make, and going further gives a much smaller improvement in the model, and now I hear there might not be enough human written material on the internet to train them.
It also looks like hallucinations are inherent to LLMs and you can’t get rid of them. It’s a side effect of the model. What commercial applications are there then, if you can’t guarantee the output? It’s worse than a human for most things since it doesn’t know truth from lie and will confidently say both as if they’re fact. It also looks like prompt injection isn’t something you can fully guard against either.
What’s the value proposition when you can’t trust the output and the model might give a massive refund or discount to a customer and the courts rule the AI speaks on behalf of your company?
I feel like calling „hallucinations“ a side effect isn’t really describing the issue properly. They’re not a side effect, nor are they hallucinations. It implied that there’s somehow something that distinguishes „correct“ output from „incorrect“. There isn’t, it’s all just output. The output resembling actual factual reality is statistical chance.
It’s worse than a human for most things since it doesn’t know truth from lie and will confidently say both as if they’re fact
It works for most executives and sales folks.
Baseless confidence is the recipe for business success, which is why they love these AI chatbots.
Bigger problem for the business leaders is how sycophantic they want to be to the user. If an insurance company used it for claims, it might actually approve a claim, and that would be unforgivable for them.
There are also hard mathematical limits stalling AI growth. Frontier models haven’t improved in like a year despite being fed money by basically the entire global economy. Diminishing returns on steroids basically. They’re already at the limit of what they can make, and going further gives a much smaller improvement in the model, and now I hear there might not be enough human written material on the internet to train them.
It also looks like hallucinations are inherent to LLMs and you can’t get rid of them. It’s a side effect of the model. What commercial applications are there then, if you can’t guarantee the output? It’s worse than a human for most things since it doesn’t know truth from lie and will confidently say both as if they’re fact. It also looks like prompt injection isn’t something you can fully guard against either.
What’s the value proposition when you can’t trust the output and the model might give a massive refund or discount to a customer and the courts rule the AI speaks on behalf of your company?
I feel like calling „hallucinations“ a side effect isn’t really describing the issue properly. They’re not a side effect, nor are they hallucinations. It implied that there’s somehow something that distinguishes „correct“ output from „incorrect“. There isn’t, it’s all just output. The output resembling actual factual reality is statistical chance.
It works for most executives and sales folks.
Baseless confidence is the recipe for business success, which is why they love these AI chatbots.
Bigger problem for the business leaders is how sycophantic they want to be to the user. If an insurance company used it for claims, it might actually approve a claim, and that would be unforgivable for them.
Diminishing returns on steroids? No, clearly we just need to pump EVEN MORE MONEY AND DATA into this
If we just vaporize the future of everyone under 60 we can make our auto correct engine 3% less likely to lie out of its ass 🤡