Interconnects

Exploring the complexities of defining an open-source LLM, new naming schemes, bio-risks, transparency, safety, licenses, and copyright in AI models. Debunking myths, discussing regulatory implications, and the impact of Elon Musk's lawsuit against OpenAI on the tech ecosystem.

Louis Castricato, a researcher at EleutherAI and founder of Synth Labs, dives deep into the fascinating world of RLHF. He explores the complexities of preference learning and the shift from PPO to DPO in reinforcement learning. The conversation highlights the challenges of biases in AI, especially regarding representation in training data. Castricato also shares insights on Gemini's impact on data safety, the evolution of model evaluation techniques, and the importance of collaborative efforts in advancing AI research.

Tips on assessing and curating AI content, focusing on model credibility, depth vs. breadth, reproducibility, and community dynamics. Emphasizes the importance of research papers, networking, and building relationships in the AI field.

Google rejoins the open model party and gets some backlash for a frequent problem for generative AI.This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/gemma-google-ships-it00:00 Google ships it: Gemma open LLMs and Gemini backlash03:12 Getting to know Gemma07:11 Alignment details08:55 Aside: What is REINFORCE? Some history of RL11:08 Implementation details and RLHF12:18 Terms of use: RAIL Licenses history repeated14:05 Is Google back on top? Gemini's woesFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/gemma/img_008.webpFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/gemma/img_014.pngFigure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/gemma/img_035.pngFigure 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/gemma/img_051.pngFigure 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/gemma/img_055.png This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe

10 Sora and Gemini 1.5 follow-ups: code-base in context, deepfakes, pixel-peeping, inference costs, and moreThis is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/sora-gemini-follow-up00:00 10 Sora and Gemini 1.5 follow-ups: code-base in context, deepfakes, pixel-peeping, inference costs, and more00:46 1. Deepfake detection of Sora01:59 2. Playing with long-context, problem settings, and prompting03:39 3. Gemini paper snooping: contamination and citation games05:42 4. Training data and token estimates of YouTube07:42 5. Unlocking model-based RL and downstream research08:52 6. Midjourney style matching, V-JEPA, replicating Sora in the open10:09 7. Architectures and academic links10:57 8. Pixel peeping from the arts11:58 9. Inference costs13:24 10. Pressure on Llama and Mistral14:03 11. Sound effects, physics, and the complete pictureFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_003.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_007.mp4Figure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_009.mp4Figure 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_011.mp4Figure 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_037.mp4Figure 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_044.pngFigure 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_047.pngFigure 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-2/img_049.mp4 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe

Emergency blog! Three things you need to know from the ML world that arrived yesterday.This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/sora-gemini-and-mistral-next0:00 OpenAI's Sora for video, Gemini 1.5, and a secret Mistral model0:53 Sora: OpenAI's text-to-video model4:59 Gemini 1.5: Google's effectively infinite context length8:01 Mistral-next: Another funny release methodFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-gemini-mistral/img_015.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-gemini-mistral/img_023.pngFigure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-gemini-mistral/img_026.pngFigure 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/sora-gemini-mistral/img_036.png This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe

In an era dominated by direct preference optimization and LLMasajudge, why do we still need a model to output only a scalar reward?This is AI generated audio with Python and 11Labs. Music generated by Meta's MusicGen.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: In an era dominated by direct preference optimization and LLM-as-a-judge, why do we still need a model to output only a scalar reward?Podcast figures:Figure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_004.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reward-models/img_009.png0:00 Why reward models are still key to understanding alignment This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe

This podcast discusses the challenges faced by ScaleAI, a startup providing data services for reinforcement learning from human feedback (RLHF). It explores ScaleAI's revenue growth, partnership with major labs, and defense arm. The podcast also explores the concept of scaling alignment as a service through AI feedback alignment and potential business opportunities in RLHF.

A small model at the beginning of big changes.This is AI generated audio with Python and 11LabsSource code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/olmo0:00 Open Language Models (OLMos) and the LLM landscape6:24 Thought experiments7:51 The LLM landscape heading into 2024Figure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmo/img_010.png This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe

Note: some of the audio in the second half is a little wonky, but the general voice was upgraded so hopefully it's a little less "poppy" until then!I'm trying to fix little pronunciation problems on a weekly basis. Thanks to my early fans! It'll keep improving. E.g. some of the months were wonky.When what seems like pure LLM black magic is actually supported by the literature.This is AI generated audio with Python and 11LabsSource code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/model-merging00:00 Model merging lessons in The Waifu Research Department02:21 How and why does model merging work?07:13 Aside: merging vs. ensembles vs. mixture of experts08:21 Why are people doing this?11:22 Tools & Links11:51 Brief (visual) literature review12:07 Full model merging and recent methods15:55 Weight averaging during pretraining17:18 LoRA merging17:53 More backgroundFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_005.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_016.pngFigure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_042.pngFigure 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_051.pngFigure 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_055.pngFigure 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_058.pngFigure 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_060.pngFigure 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_062.pngFigure 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_065.pngFigure 10: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_075.pngFigure 11: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_077.pngFigure 12: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-merging/img_084.png This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.interconnects.ai/subscribe