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Episode 12 - Leaked Google Strategy Memo, Open Source, AI Value Chains

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Manage episode 407381684 series 3560533
Content provided by Jeff Hwang and Seymour Duncker. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jeff Hwang and Seymour Duncker 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.

Jeff and Seymour briefly discuss Google I/O which happened last week including the release of PaLM 2. Most of the episode is spent on the strategic and ecosystem implications of an internal Google strategy memo and the impact of open source. They also discuss AI Supply Chains in the context of a series of MIT blog posts from April. Finally, they draw analogies from earlier eras of tech history including the rise of the PC industry and IBM/Oracle's relationship with Linux in the late 20th century. Links:

  • Jordan Burgess pushes back on Google strategy memo
  • Andrej Karpathy's perspective
  • Andrej's overall view of current LLM landscape which is similar to Jeff and Seymour's four part framework of understanding gen AI: (1) pre-trained foundation model; (2) fine-tuning; (3) whole product / end user UX; and (4) distribution
  • Examples of fine-tuning methods: (1) RHLF; (2) LoRA; (3) LLaMA Adaptor
  • Explanation of quantization to make foundation models lighter weight

Send questions/comments to stepfunctionpod@gmail.com and find us on the web at www.stepfunction.org

  continue reading

19 episodes

Artwork
iconShare
 
Manage episode 407381684 series 3560533
Content provided by Jeff Hwang and Seymour Duncker. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jeff Hwang and Seymour Duncker 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.

Jeff and Seymour briefly discuss Google I/O which happened last week including the release of PaLM 2. Most of the episode is spent on the strategic and ecosystem implications of an internal Google strategy memo and the impact of open source. They also discuss AI Supply Chains in the context of a series of MIT blog posts from April. Finally, they draw analogies from earlier eras of tech history including the rise of the PC industry and IBM/Oracle's relationship with Linux in the late 20th century. Links:

  • Jordan Burgess pushes back on Google strategy memo
  • Andrej Karpathy's perspective
  • Andrej's overall view of current LLM landscape which is similar to Jeff and Seymour's four part framework of understanding gen AI: (1) pre-trained foundation model; (2) fine-tuning; (3) whole product / end user UX; and (4) distribution
  • Examples of fine-tuning methods: (1) RHLF; (2) LoRA; (3) LLaMA Adaptor
  • Explanation of quantization to make foundation models lighter weight

Send questions/comments to stepfunctionpod@gmail.com and find us on the web at www.stepfunction.org

  continue reading

19 episodes

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