Comment by kwindla | Hacker News Reader

Comment by kwindla | Hacker News Reader

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"Generative" AI/ML is moving so fast in so many directions that keeping up is a challenge even if you're trying really hard to stay current!

I'm part of a team building developer tools for real-time AI use cases (voice and video). I feel like I have three overlapping perspectives and goals re this new stuff:

1. To figure out what we should build I need to have a good understanding of what's possible and useful right now.

2. I talk to our customers a lot. Helping them understand what's possible and useful today (and what that might look like six months or a year from now) is part of my job.

3. I think this is a step-function change in what computers are good at, and that's really exciting and intellectually interesting.

My AI information diet right now is a few podcasts, twitter, and email newsletters. A few links:

  - Latent space podcast and newsletter: https://www.latent.space/podcast
  - Ben's Bites newsletter: https://news.bensbites.com/
  - Ethan Mollick newsletter: https://www.oneusefulthing.org/
  - Zvi Mowshowitz newsletter: https://thezvi.substack.com/
  - Rohan Paul twitter: https://x.com/rohanpaul_ai

(got pinged here from f5bot) thanks so much kwindla :)

always looking for ideas on how to serve this audience better. feel like there could be more I should be doing.

Hey Swyx, I'm a dev who did your (excellent!) email LLM course, so maybe I can give some info. I'm in the Latent Space Discord and have been trying to figure out what's next after the course. The challenge I've found is that most online discussions about LLMs are either very basic or assume a fair amount of context (true for the Latent Space discussion/podcast, as well as Karpathy's videos).

I've been trying to find the best next step and what seems fruitful from my vantage point are:

1. Cohere's LLM University - Seems to go more in depth into terms like embeddings that are still pretty unclear to me. 2. promptingguide.ai - For similar reasons, that it covers terms and concepts I see a lot but don't know much about. 3. Reading survey-level papers.

I'm including this info just in case it's useful to you, as I've really appreciated all the content you've put together.

One specific thing you or someone else could do that is simple yet high value is to create a list of "the first 20 LLM papers you should read". I've looked for this to build out more base knowledge, but have yet to find it. Suspect it would be helpful to others as well.

I have a VoIP software (https://www.mizu-voip.com/Software/SIPSDK/JavaSIPSDK.aspx) and I am trying to market it as the interface between AI and real time audio/video. It already has real-time in/out streaming capabilities, i just want to add some more helper methods to make it more obvious for AI input/output. Can you help me with a little feedback? I am trying to think with the mind of an AI developer and I am interested on your thoughts on how to implement the real-time interactivity for your software/service? Is our JVoIP library close to your requirements or are you going to use something completly different to interact with the endusers and/or backend services? (To what kind of software/service are you thinking more exactly to cover this part?)

What company do you work for? I am working in the field and curious what the product is

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