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Build Your Second Brain One Piece At A Time episode artwork

Jul 28, 2024 48 min

Build Your Second Brain One Piece At A Time

from AI Engineering Podcast Hosted by Tobias Macey

Summary Generative AI promises to accelerate the productivity of human collaborators. Currently the primary way of working with these tools is through a conversational prompt, which is often cumbersome and unwieldy. In order to simplify the integration of AI capabilities into developer workflows Tsavo Knott helped create Pieces, a powerful collection of tools that complements the tools that developers already use. In this episode he explains the data collection and preparation process, the collection of model types and sizes that work together to power the experience, and how to incorporate it into your workflow to act as a second brain. Announcements Hello and welcome to the AI Engineering Podcast, your guide to the fast-moving world of building scalable and maintainable AI systems Your host is Tobias Macey and today I'm interviewing Tsavo Knott about Pieces, a personal AI toolkit to improve the efficiency of developers Interview Introduction How did you get involved in machine learning? Can you describe what Pieces is and the story behind it? The past few months have seen an endless series of personalized AI tools launched. What are the features and focus of Pieces that might encourage someone to use it over the alternatives? model selections architecture of Pieces application local vs. hybrid vs. online models model update/delivery process data preparation/serving for models in context of Pieces app application of AI to developer workflows types of workflows that people are building with pieces What are the most interesting, innovative, or unexpected ways that you have seen Pieces used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Pieces? When is Pieces the wrong choice? What do you have planned for the future of Pieces? Contact Info LinkedIn Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers. Links Pieces NPU == Neural Processing Unit Tensor Chip LoRA == Low Rank Adaptation Generative Adversarial Networks Mistral Emacs Vim NeoVim Dart Flutter Typescript Lua Retrieval Augmented Generation ONNX LSTM == Long Short-Term Memory LLama 2 GitHub Copilot Tabnine Podcast Episode The intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0

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Build Your Second Brain One Piece At A Time

0:00 48:27

Chapters

  1. 0:05 Introduction and Guest Introduction
  2. 0:50 Early Days in Machine Learning
  3. 2:09 Overview of the Pieces Project
  4. 6:27 Differentiating Pieces from Other AI Tools
  5. 12:13 Model Integration and Contextualization
  6. 17:57 Design and Development of Pieces
  7. 21:25 Model Deployment and Updates
  8. 24:02 Workflow Integration and Use Cases
  9. 32:20 User Control and Monetization
  10. 36:06 Unexpected Uses and Lessons Learned
  11. 40:40 When Pieces is the Wrong Choice
  12. 42:36 Future Plans and Exciting Projects
  13. 44:56 Challenges in AI and ML Adoption
  14. 47:38 Closing Remarks

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This episode was published on July 28, 2024.

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