Interconnects Audio

Data licensing deals, scaling, human inputs, and repeating trends in open vs. closed.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/the-data-wall0:00 We aren't running out of training data, we are running out of open training data2:51 Synthetic data: 1 trillion new tokens per day4:18 Data licensing deals: High costs per token6:33 Better tokens: Search and new frontiers

Celebrity's power will only grow in the era of infinite content.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/name-image-and-ai-likeness0:00 Name, image, and AI's likeness1:11 OpenAI's second terrible, horrible, no good, very bad week4:36 The expansion of name and likeness7:46 Culture and AI development

ChatGPT leaves the textbox, and Google is building the same, and more, as practical tools.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/openai-and-her00:00 OpenAI chases Her02:10 Talking to ChatGPT03:53 GPT-4o: Toward omnimodal models08:25 Google's mirror with Gemini10:11 OpenAI's AI Safety: Have your cake and eat it tooFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/her/img_018.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/her/img_023.jpg

Now we will have some grounding for when weird ChatGPT behaviors are intended or side-effects -- shrinking the Overton window of RLHF bugs.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/openai-rlhf-model-spec00:00 OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions02:56 Reviewing the Model Spec08:26 Where RLHF can fail OpenAI12:23 From Model Spec's to personalizationFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_027.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_029.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_033.pngFig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_034.pngFig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_041.webpFig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_046.webp

Many, many signs of life for preference fine-tuning beyond spoofing chat evaluation tools.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/how-rlhf-works-200:00 How RLHF works, part 2: A thin line between useful and lobotomized04:27 The chattiness paradox08:09 The mechanism for making models chattier10:42 Next steps for RLHF researchFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_012.webpFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_018.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_025.png

Models that seem totally out of scope from recent open LLMs give us a sneak peek of where the industry will be in 6 to 18 months.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/phi-3-and-arctic-llms0:00 Phi 3 and Arctic: Outlier LMs are hints1:01 Arctic & open mixture of expert trends6:10 Phi 3, synthetic data, and small modelsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_004.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_008.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_018.png

Certain definitions of AGI are backing people into a pseudo-religious corner.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/agi-is-what-you-want-it-to-be00:00 AGI is what you want it to be04:01 RL still rules the AGI discourse05:43 Modern AGI tests07:37 Agency and shifting goalpostsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/agi/img_018.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/agi/img_020.png

Meta shows that scaling won't be a limit for open LLM players in the near future.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/llama-3-and-scaling-open-llms00:00 Llama 3; scaling open LLMs to AGI01:44 Pretraining, data, and basic evals06:06 Alignment and human evaluations10:08 Chatting with Meta AI and Llama 3 70B Instruct11:55 Same Llama license (mostly)12:52 The healthy open LLM ecosystemFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_011.jpegFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_013.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_015.pngFig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_020.pngFig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_036.pngFig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_040.pngFig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_046.jpegFig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_061.pngFig 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_063.webpFig 10: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_066.pngFig 11: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_068.jpeg

Integrating some non computing science into reinforcement learning from human feedback can give us the models we want.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/reinventing-llm-alignment0:00 Stop "reinventing" everything to "solve" AI alignment2:19 Social Choice for AI Alignment: Dealing with Diverse Human Feedback7:03 OLMo 1.7 7B: A truly open model with actually good benchmarksFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_013.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_015.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_018.pngFig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_024.pngFig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_027.png

Modeling the compute versus performance tradeoff of many open LLMs.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/compute-efficient-open-llms0:00 The end of the "best open LLM"3:05 Compute efficient open LLMsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_004.jpegFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_009.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_014.pngFig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_016.pngFig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_018.pngFig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_020.pngFig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_022.pngFig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_024.pngFig 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_028.png

Last minute title change from: The tech industry can't agree on what open-source AI means. That's the process.How to read what multiple people mean by the word openness and see through the PR speak.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolsOriginal post: https://www.interconnects.ai/p/flavors-of-open-source-ai0:00 The tech industry can't agree on what open-source AI means. That's the process.2:45 1. Effective Accelerationists, Techno-Optimists, capitalists, etc.3:39 2. Scientists, promoting understanding and transparency5:16 3. Inclusion, public interest, and fighting concentration of power6:19 4. Freedom advocates7:25 Dissecting "openness"Fig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/openness/img_004.png

Databricks' new model is surpassing the performance of Mixtral and Llama 2 while still being in a size category that's reasonably accessible.This is AI generated audio with Python and 11Labs.Source code: https://github.com/natolambert/interconnects-toolshttps://www.interconnects.ai/p/databricks-dbrx-open-llm00:00 DBRX: The new best open model and Databricks' ML strategy03:36 The DBRX narrative07:33 Databricks' open LLM (and AI) strategy09:42 Playing with DBRX Instruct14:54 Digging for detailsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_007.pngFig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_012.pngFig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_023.pngFig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_045.pngFig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_047.pngFig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_059.pngFig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_066.jpegFig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/dbrx/img_068.png

Evaluation is not only getting harder with modern LLMs, it's getting harder because it means something different.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/evaluations-trust-performance-and-price00:00 Evaluations: Trust, performance, and price (bonus, announcing RewardBench)03:14 The rising price of evaluation05:40 Announcing RewardBench: The First reward model evaluation tool08:37 Updates to RLHF evaluation toolsYouTube code intro: https://youtu.be/CAaHAfCqrBAFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/evals/img_026.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/evals/img_030.pngFigure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/evals/img_034.pngFigure 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/evals/img_040.png

Where moats are tested now that so many people have trained GPT4 class models. Claude 3, Gemini 1.5, Inflection 2.5, and Mistral Large are here to party.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/gpt4-commoditization-and-moats00:00 Building LLM moats despite the commoditization of GPT404:38 The Open's opportunities08:02 It's amazing people still think LLMs aren't going to be useful09:50 Things that are comingFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/moats/img_004.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/moats/img_028.pngFigure 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/moats/img_032.png

A proposal for a new definition of an "open source" LLM and why no definition will ever just work.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/an-open-source-llm00:00 The koan of an open-source LLM03:22 A new naming scheme for open LLMs07:09 Pivot points and politics08:16 Claude 3, arms race, commoditization, and national security10:01 Doomers debunking bio risks of LLMs themselves11:21 Mistral's perceived reversal and the EU13:22 Messy points: Transparency, safety, and copyright13:32 The muddling of transparency15:22 The muddling of "safety"16:30 The muddling of licenses and copyright20:12 Vibes points and next stepsFigure 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/open-source/img_046.pngFigure 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/open-source/img_064.png

Louis recently has been founding a new startup focused on synthetic data for alignment, Synth Labs, and is a researcher at Eleuether AI. This interview should speak for itself, and it’ll need re-listens, even for myself. The list of topics we cover touches on pretty much every major and minor issue facing model fine-tuning. Please reach out or comment if there’s a paper we mention that I didn’t link before. Happy to dig it up for you. This post is very technical. If you’re having a hard time with it, I suggest you listen to my RLHF 201 post on Latent Space first.Full transcript available here: https://www.interconnects.ai/p/rlhf-interview-1-louis00:00:00: Introduction00:01:24: Gemini News and RLHF’s Part in it00:09:05: Long Context, In-Context, and Multimodal RLHF00:21:20: What are people missing about RLHF these days?00:30:30: OpenAI's Influence and the Need for Alternatives00:39:20: Synth Labs and the Future of Alignment00:55:00: Evaluation Talk p2: Open-ended Evaluation and Data Diversity00:59:20: Algorithm Roundup: PPO, DPO, KTO, IPO01:18:38: CarperAI, Early Days of RLHF, Reflecting on ChatGPT

Basic tips on how to assess inbound ML content and cultivate your news feed.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/making-a-ml-feed00:00 How I assess all these AI releases01:22 1. Model access and demos are king of credibility02:31 2. Focus your feed on depth or breadth03:09 3. Examples of using the model normally show its usable, shockingly04:10 4. Leaderboards as the single leading claim is often anti-signal05:00 5. Basic deep learning conceptual checks will often save you06:13 6. If it's not even remotely reproducible or verifiable, it's not science07:10 7. Don't over-index on Twitter08:32 8. Data sharing, licenses, communication clarity, and small things add up08:58 9. Research papers, technical reports, blog posts, and Tweets all serve different purposes09:49 10. Socialize your information and build relationships

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

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

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