all this started in 2023? alas no time marches on, llm have been a thing for decades and the main boom happened more in 2021. progress is not fast, no, these are companies throwing as much compute at their problems as they can. deepseek’s caused a 2t drop by being marginal progress in a field (llms specifically) out of ideas.
regardless of where you want to define the starting point of the boom, it’s been clear for months up to years depending on who you ask that they are plateuing. and harshly. stop listening to hypesters and people with a financial interest in llm being magic.
It’s gambling. The potential payoff is still huge for whoever gets there first. Short term anyway. They won’t be laughing so hard when they fire everyone and learn there’s nobody left to buy anything.
The tech is already good enough that any call center employees should be looking for other work. That one is just waiting on the company-specific implementations. In twenty years, calling a major company’s customer service and having any escalation path that involves a human will be as rare as finding a human elevator operator today.
the tech is barely good enough that it is vaguely maybe feasibly cheaper to waste someone’s time using a robot rather than a human- oh wait we do that already with other tech.
“in 20 years imagine how good it’ll be!” alas, no, it scales logarithmically at best and all discussion is poisoned by “what it might be!” in the future, rather than what it is.
It’s not necessary to improve the quality to make this happen, only to train it to work with that company’s products and issues, and integrate it into whatever other systems that may be needed. Just need enough call logs for training data, and that’s already something that’s collected.
except current robot systems and people are likely cheaper, especially when you consider companies are liable for what llm say. which leaves, essentially, scams and other slop, as the last remaining use cases. multi trillion dollar business without a use case.
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Well both of those things have been true months if not years, so if those are the conditions for a pop then they are met.
How are both conditions meer when all this just started 2(?) years ago? And progress is still going very fast.
all this started in 2023? alas no time marches on, llm have been a thing for decades and the main boom happened more in 2021. progress is not fast, no, these are companies throwing as much compute at their problems as they can. deepseek’s caused a 2t drop by being marginal progress in a field (llms specifically) out of ideas.
The huge AI LLM boom/bubble started after chatGPT came out.
But of fucking course it existed before.
regardless of where you want to define the starting point of the boom, it’s been clear for months up to years depending on who you ask that they are plateuing. and harshly. stop listening to hypesters and people with a financial interest in llm being magic.
It’s gambling. The potential payoff is still huge for whoever gets there first. Short term anyway. They won’t be laughing so hard when they fire everyone and learn there’s nobody left to buy anything.
gets where first?
Get to the point of replacing a category of employee with automation.
Oh! Hahahaha. No.
the vc techfeudalist wet dreams of llm replacing humans are dead, they just want to milk the illusion as long as they can.
The tech is already good enough that any call center employees should be looking for other work. That one is just waiting on the company-specific implementations. In twenty years, calling a major company’s customer service and having any escalation path that involves a human will be as rare as finding a human elevator operator today.
the tech is barely good enough that it is vaguely maybe feasibly cheaper to waste someone’s time using a robot rather than a human- oh wait we do that already with other tech.
“in 20 years imagine how good it’ll be!” alas, no, it scales logarithmically at best and all discussion is poisoned by “what it might be!” in the future, rather than what it is.
It’s not necessary to improve the quality to make this happen, only to train it to work with that company’s products and issues, and integrate it into whatever other systems that may be needed. Just need enough call logs for training data, and that’s already something that’s collected.
except current robot systems and people are likely cheaper, especially when you consider companies are liable for what llm say. which leaves, essentially, scams and other slop, as the last remaining use cases. multi trillion dollar business without a use case.