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My employer PoC'd, collaborated with and eventually bought Codeium's solution. I couldn't care less about (any, so also neither about) the LLM hype. Especially

by kmarc 2y ago

My employer PoC'd, collaborated with and eventually bought Codeium's solution. I couldn't care less about (any, so also neither about) the LLM hype. Especially didn't bother going to a new web site (ChatGPT), or installing new IDEs etc. I checked Codeium's mycompany-customized landing page: a one-liner vim plug-in installation and copy pasting an auth token. I started typing in the very same editor, very same environment, very same everything, and the thing just works, most of the time guesses well what I would want to write, so then I just press tab to accept and voila. I wasn't expecting such a seamless experience. I still haven't integrated its "chat" functionality into my workflow (maybe I won't at all). I'm not hyped about it, it just feels like a companion to already working (and correct) code completion. I read a lot about other people's usages (I'm a devXP engineer), and I feel like that for whatever reason there is more love / hype / faith on their chosen AI companion than how much they actually could improve if took a humble way of understanding code, reading (and writing) docs, reasoning about the engineering solution. As everything, now AI is losing hype, but somehow (in my bubble) seems like engineers are still high on it. But I also see that this will distill further the set of people who I look up to and want to collaborate with, because e of that mentioned humbleness, as opposed to just accepting text predicted solutions mindlessly.

antupis 2y ago
> As everything, now AI is losing hype, but somehow (in my bubble) seems like engineers are still high on it. But I also see that this will distill further the set of people who I look up to and want to collaborate with, because e of that mentioned humbleness, as opposed to just accepting text predicted solutions mindlessly. It is dotcom bust again. Mainstream is losing interest but at the same time I see our internal chatbots / ai agents doing hockey stick growth and I am using several hours code pilot daily.
0x008 2y ago
I think we need to be very careful making blanket statements about the usefulness of certain LLMs. In my experience for every task another LLM is excelling and where one was good it might fail for the other task. They can do great things, but it’s not guaranteed and a lot of manual intervention and back and forth is still needed. We are not at the point where using AI in the company ist just a blanket win for everyone involved. Companies are investing a lot but the return is hard to measure and not always guaranteed. This is the problem with early technologies, they work sometimes but not guaranteed and we build our expectations on extrapolating their usefulness. We should not judge this technology by the current success rate, but rather by how much impact it will have once we get the success rate to higher and higher levels. Still, what we can say is that for certain occupations it already helps them reduce their work by 15% (software engineers) and probably even more for some (writers, product owners, office warriors and alike). This is a great achievement in of itself, think how much this will make up in a company as large as MS or Google.

by kmarc 2y ago

antupis 2y ago

> As everything, now AI is losing hype, but somehow (in my bubble) seems like engineers are still high on it. But I also see that this will distill further the set of people who I look up to and want to collaborate with, because e of that mentioned humbleness, as opposed to just accepting text predicted solutions mindlessly. It is dotcom bust again. Mainstream is losing interest but at the same time I see our internal chatbots / ai agents doing hockey stick growth and I am using several hours code pilot daily.

0x008 2y ago

I think we need to be very careful making blanket statements about the usefulness of certain LLMs. In my experience for every task another LLM is excelling and where one was good it might fail for the other task. They can do great things, but it’s not guaranteed and a lot of manual intervention and back and forth is still needed. We are not at the point where using AI in the company ist just a blanket win for everyone involved. Companies are investing a lot but the return is hard to measure and not always guaranteed. This is the problem with early technologies, they work sometimes but not guaranteed and we build our expectations on extrapolating their usefulness. We should not judge this technology by the current success rate, but rather by how much impact it will have once we get the success rate to higher and higher levels. Still, what we can say is that for certain occupations it already helps them reduce their work by 15% (software engineers) and probably even more for some (writers, product owners, office warriors and alike). This is a great achievement in of itself, think how much this will make up in a company as large as MS or Google.