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dingliqing53

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Launch HN: CodeComplete (YC W23) – Copilot for Enterprise

138 points·by dingliqing53·3 anni fa·68 comments

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dingliqing53
·3 anni fa·discuss
CodeComplete AI | Bay Area / remote | GitHub Copilot for Enterprises

- We're looking for founding MLEs & one full stack engineer to join our team. Read about our HN launch here: https://news.ycombinator.com/item?id=35152851

- Salary range $160K-260K + equity + benefits (depending on experience and interviews)

- If you're excited about 10x-ing developer productivity, getting your hands dirty with foundational LLMs, and want to have a direct impact on the product (we're an early venture-backed startup), please reach out to [email protected] with your resume and include HN in your title!
dingliqing53
·3 anni fa·discuss
Definitely want to offer this in the future but not currently our ICP. Like rileyphone mentioned, the cost of hosting a model is substantial. Could you please elaborate on why the small IT teams can't send code to OpenAI? We'd love to think more about this!
dingliqing53
·3 anni fa·discuss
Yea, there are tons of public data to train on. Copilot's under fire right now: https://githubcopilotlitigation.com/, but we make sure we only train on permissively licenses because some companies are sensitive to the IP issues here.
dingliqing53
·3 anni fa·discuss
Thank you!! You've hit the nail on the head and our thoughts exactly. One anecdote is we offer video demos and one potential customer just said, "I don't need to see it. I know what Copilot does." We do offer pilots for customers after fine-tuning on their codebase!
dingliqing53
·3 anni fa·discuss
Another thing is that since Microsoft/Github are working with OpenAI's closed source Codex model, we think it's unlikely they'll offer something on-prem anytime soon since they would have to reveal the model weights, and thus risk a leak (ex. Meta's LLaMA model weights got leaked within a week)
dingliqing53
·3 anni fa·discuss
Yes! Thanks for elaborating for us! :)
dingliqing53
·3 anni fa·discuss
Yes! We definitely have that on our product roadmap, though we think of it more in terms of improving model performance vs. deterring clients from switching to a different tool. Since we're working with large enterprise codebases and deploying models to behind their firewalls, there's (hopefully) a nontrivial switching cost. Thanks for pointing it out!