On The Bike Shed, hosts Joël Quenneville and Stephanie Minn discuss development experiences and challenges at thoughtbot with Ruby, Rails, JavaScript, and whatever else is drawing their attention, admiration, or ire this week.
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Episode 253: AI with Katerina Skroumpelou
MP3•Episode home
Manage episode 378196015 series 2440978
Content provided by John Papa, Dan Wahlin, Ward Bell, and Craig Shoemaker. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by John Papa, Dan Wahlin, Ward Bell, and Craig Shoemaker or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Host(s):
- John Papa @John_Papa
- Ward Bell @WardBell
- Dan Wahlin @DanWahlin
- Craig Shoemaker @craigshoemaker
Guest:
- Katerina Skroumpelou @psybercity
Recording date: Sep 14, 2023
Brought to you by
Visit nx.dev to get the preeminent open-source toolkit for monorepo development, today.
Resources:
- Soul Train the Musical
- ChatGPT
- Nx Docs
- Link to Nx AI Assistant (Disclaimer: I did NOT build the UI (I am useless in UI stuff).)
- NxConf event
- Grounding LLMs
- Hallucination (artificial intelligence)
- AI & Vectors
- PostgreSQL
- What is RAG?
- Supabase
- Based on/inspired by: (we'll have our own blog post explaining our AI docs once they're out)
- Mastering temperature and Top P in Open AI
- SkyNet
- Text Blaze
- "The numeric representation of knowledge and logic—Two artificial intelligence applications in medical education" W. D. Hagamen 1986
- Ward's citation: "Medical applications of data-driven APL programs" 1975 (Note that the abstract had to explain what "data-driven" means even to a highly technical audience. That's where we were in those days.)
Timejumps
- 00:28 Welcome
- 03:54 Introducing Katerina
- 04:45 How did you get into AI?
- 05:45 Why AI assistant is important for documentation?
- 09:46 Sponsor: Ag Grid
- 10:51 How do you feel it's been going?
- 16:32 What approach did you end up using to train AI?
- 18:36 What are embeddings?
- 20:32 Sponsor: Narwhal
- 21:06 Acknowledging our AI knowledge
- 24:25 How AI answers a question
- 28:31 How did you decide how often to call the API?
- 32:41 What is Rag?
- 36:49 Final thoughts
Podcast editing on this episode done by Chris Enns of Lemon Productions.
293 episodes
MP3•Episode home
Manage episode 378196015 series 2440978
Content provided by John Papa, Dan Wahlin, Ward Bell, and Craig Shoemaker. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by John Papa, Dan Wahlin, Ward Bell, and Craig Shoemaker or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Host(s):
- John Papa @John_Papa
- Ward Bell @WardBell
- Dan Wahlin @DanWahlin
- Craig Shoemaker @craigshoemaker
Guest:
- Katerina Skroumpelou @psybercity
Recording date: Sep 14, 2023
Brought to you by
Visit nx.dev to get the preeminent open-source toolkit for monorepo development, today.
Resources:
- Soul Train the Musical
- ChatGPT
- Nx Docs
- Link to Nx AI Assistant (Disclaimer: I did NOT build the UI (I am useless in UI stuff).)
- NxConf event
- Grounding LLMs
- Hallucination (artificial intelligence)
- AI & Vectors
- PostgreSQL
- What is RAG?
- Supabase
- Based on/inspired by: (we'll have our own blog post explaining our AI docs once they're out)
- Mastering temperature and Top P in Open AI
- SkyNet
- Text Blaze
- "The numeric representation of knowledge and logic—Two artificial intelligence applications in medical education" W. D. Hagamen 1986
- Ward's citation: "Medical applications of data-driven APL programs" 1975 (Note that the abstract had to explain what "data-driven" means even to a highly technical audience. That's where we were in those days.)
Timejumps
- 00:28 Welcome
- 03:54 Introducing Katerina
- 04:45 How did you get into AI?
- 05:45 Why AI assistant is important for documentation?
- 09:46 Sponsor: Ag Grid
- 10:51 How do you feel it's been going?
- 16:32 What approach did you end up using to train AI?
- 18:36 What are embeddings?
- 20:32 Sponsor: Narwhal
- 21:06 Acknowledging our AI knowledge
- 24:25 How AI answers a question
- 28:31 How did you decide how often to call the API?
- 32:41 What is Rag?
- 36:49 Final thoughts
Podcast editing on this episode done by Chris Enns of Lemon Productions.
293 episodes
All episodes
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