jessehu

Awesome launch! Just curious, what does the "run everything locally, send results to a server" approach mean and why do you love it?

What’s wrong with Faiss? https://github.com/facebookresearch/faiss

What is the inline metadata trick?

Would you mind posting it?

Nice hustle! How did you decide to start in CS research? Do you attend a math & sciences HS, or have family members in academics? Or perhaps just from reading the internet?

I’m rather confused why doing this as a consumer product in Assistant makes more sense than an enterprise product. There is so much room for improvement in call centers, and would be a huge market opportunity.

This is hardly even a time saver. What would be helpful is if this is also able to stay on hold for you — probably an easy task.

After your startup and Google experience, you were hired as an SWE1? Also, curious if the experience of the startup or subsequent integration was perhaps more valuable than the opportunity cost.

Google is so strong with ML today, and not stopping, I don't know what will allow smaller competitors to stay differentiated. I just had a call with a G recruiter, and pretty much 100% of the roles they have in all their European offices are ML-related roles, on most products. And they hire without ML experience, which I think is a sign of how much they are investing in ML.

Weird. I'm having the opposite experience, where I'm not having luck finding an ML team, even with research experience. What teams/products are hiring for ML-related roles without experience?