Interconnects

109 Episoder

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

   Publisert: 29.5.2024
2. Name, image, and AI's likeness

   Publisert: 22.5.2024
3. OpenAI chases Her

   Publisert: 16.5.2024
4. OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions

   Publisert: 13.5.2024
5. RLHF: A thin line between useful and lobotomized

   Publisert: 1.5.2024
6. Phi 3 and Arctic: Outlier LMs are hints

   Publisert: 30.4.2024
7. AGI is what you want it to be

   Publisert: 24.4.2024
8. Llama 3: Scaling open LLMs to AGI

   Publisert: 21.4.2024
9. Stop "reinventing" everything to "solve" alignment

   Publisert: 17.4.2024
10. The end of the "best open LLM"

    Publisert: 15.4.2024
11. Why we disagree on what open-source AI should be

    Publisert: 3.4.2024
12. DBRX: The new best open LLM and Databricks' ML strategy

    Publisert: 29.3.2024
13. Evaluations: Trust, performance, and price (bonus, announcing RewardBench)

    Publisert: 21.3.2024
14. Model commoditization and product moats

    Publisert: 13.3.2024
15. The koan of an open-source LLM

    Publisert: 6.3.2024
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

    Publisert: 4.3.2024
17. How to cultivate a high-signal AI feed

    Publisert: 28.2.2024
18. Google ships it: Gemma open LLMs and Gemini backlash

    Publisert: 22.2.2024
19. 10 Sora and Gemini 1.5 follow-ups: code-base in context, deepfakes, pixel-peeping, inference costs, and more

    Publisert: 20.2.2024
20. Releases! OpenAI’s Sora for video, Gemini 1.5's infinite context, and a secret Mistral model

    Publisert: 16.2.2024