109 Episodio

  1. We aren't running out of training data, we are running out of open training data

    Pubblicato: 29/05/2024
  2. Name, image, and AI's likeness

    Pubblicato: 22/05/2024
  3. OpenAI chases Her

    Pubblicato: 16/05/2024
  4. OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions

    Pubblicato: 13/05/2024
  5. RLHF: A thin line between useful and lobotomized

    Pubblicato: 01/05/2024
  6. Phi 3 and Arctic: Outlier LMs are hints

    Pubblicato: 30/04/2024
  7. AGI is what you want it to be

    Pubblicato: 24/04/2024
  8. Llama 3: Scaling open LLMs to AGI

    Pubblicato: 21/04/2024
  9. Stop "reinventing" everything to "solve" alignment

    Pubblicato: 17/04/2024
  10. The end of the "best open LLM"

    Pubblicato: 15/04/2024
  11. Why we disagree on what open-source AI should be

    Pubblicato: 03/04/2024
  12. DBRX: The new best open LLM and Databricks' ML strategy

    Pubblicato: 29/03/2024
  13. Evaluations: Trust, performance, and price (bonus, announcing RewardBench)

    Pubblicato: 21/03/2024
  14. Model commoditization and product moats

    Pubblicato: 13/03/2024
  15. The koan of an open-source LLM

    Pubblicato: 06/03/2024
  16. Interviewing Louis Castricato of Synth Labs and Eleuther AI on RLHF, Gemini Drama, DPO, founding Carper AI, preference data, reward models, and everything in between

    Pubblicato: 04/03/2024
  17. How to cultivate a high-signal AI feed

    Pubblicato: 28/02/2024
  18. Google ships it: Gemma open LLMs and Gemini backlash

    Pubblicato: 22/02/2024
  19. 10 Sora and Gemini 1.5 follow-ups: code-base in context, deepfakes, pixel-peeping, inference costs, and more

    Pubblicato: 20/02/2024
  20. Releases! OpenAI’s Sora for video, Gemini 1.5's infinite context, and a secret Mistral model

    Pubblicato: 16/02/2024

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Audio essays about the latest developments in AI and interviews with leading scientists in the field. Breaking the hype, understanding what's under the hood, and telling stories. www.interconnects.ai

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