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Notes -
As others have already implied, this study seems to be a vehicle for attracting media attention, rather than a serious attempt at evaluating the impact of LLMs on productivity. "Rapid revenue acceleration"? So we're already excluding anything that is merely cost-saving by replacing employees?
The actual paper is not freely available, so I don't actually know how rigorous their research was. At the very least, it is described as being enterprise only - historically the slowest and least agile when it comes to adopting new technologies. There are basic bitch wrappers that already have billion dollar+ valuations! And if it is focused solely on revenue generation as the benchmark, you will be cutting out a huge swath of projects that involve LLMs.
One might also wonder at timing. While LLMs will seem old news to rats and SSC readers due to familiarity with GPT-2, ChatGPT has only been around since November of 2022: not even 3 years old. And that was GPT3.5, GPT4 only came out in March of '23. Any other technology would be incredible if it drove rapid revenue acceleration in ~15 enterprise deployments after such a tiny amount of time. That's not to mention the yuge problem of AI studies becoming out of date simply because the whole thing moves way too quickly for academia. When was this study completed? Autumn of last year, if we're being generous?
Again, without reading the primary source it would be harsh to jump to conclusions, but based on the article linked this just screams "proactive title finding to get attention" rather than something important to learn about business adoption.
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