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169 afleveringen, van nieuw naar oud
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(Voiceover) OpenAI's o3: The grand finale of AI in 2024
20 december 2024 · 18 min
Original post: Lees meer
https://www.interconnects.ai/p/openais-o3-the-2024-finale-of-ai
Chapters
00:00 Introduction
02:51 o3 overview
05:57 Solving the Abstraction and Reasoning Corpus (ARC)
10:41 o3’s architecture, cost, and training (hint: still no tree search)
16:36 2024: RL returns
Figures
Fig 1, Frontier Math results
Fig 2, Coding results
Fig 3, ARC AGI results
Fig 4, ARC AGI result details
Fig 5, ARC AGI example 1
Fig 6, ARC AGI example in text
Fig 7, ARC AGI example “easy”
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
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(Voiceover) The AI agent spectrum
18 december 2024 · 11 min
Original post: https://www.interconnects.ai/p/the-ai-agent-spectrum Lees meer
Chapters
00:00 Introduction
03:24 Agent cartography
08:02 Questions for the near future
Figures
Fig 1. multiple feedbacks diagram
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
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(Voiceover) OpenAI's Reinforcement Finetuning and RL for the masses
11 december 2024 · 13 min
Original post: Lees meer
https://www.interconnects.ai/p/openais-reinforcement-finetuning
Chapters
00:00 Introduction
04:19 The impact of reinforcement finetuning’s existence
07:29 Hypotheses on reinforcement finetuning’s implementation
Figures
Fig. 1, Yann’s Cake
Fig. 2, Grader config
Fig. 3, RLVR learning curves
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
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Interviewing Finbarr Timbers on the "We are So Back" Era of Reinforcement Learning
5 december 2024 · 1 uur 9 min
Finbarr Timbers is an AI researcher who writes Artificial Fintelligence — one of the technical AI blog’s I’ve been recommending for a long time — and has a variety of experiences at top AI labs including DeepMind and Midjourney. The goal of this interview was to do a few things: Lees meer
* Revisit what reinforcement learning (RL) actually is, its origins, and its motivations.
* Contextualize the major breakthroughs of deep RL in the last decade, from DQN for Atari to AlphaZero to ChatGPT. How could we have seen the resurgence coming? (see the timeline below for the major events we cover)
* Modern uses for RL, o1, RLHF, and the future of finetuning all ML models.
* Address some of the critiques like “RL doesn’t work yet.”
It was a fun one. Listen on Apple Podcasts, Spotify, YouTube, and where ever you get your podcasts. For other Interconnects interviews, go here.
Timeline of RL and what was happening at the time
In the last decade of deep RL, there have been a few phases.
* Era 1: Deep RL fundamentals — when modern algorithms we designed and proven.
* Era 2: Major projects — AlphaZero, OpenAI 5, and all the projects that put RL on the map.
* Era 3: Slowdown — when DeepMind and OpenAI no longer had the major RL projects and cultural relevance declined.
* Era 4: RLHF & widening success — RL’s new life post ChatGPT.
Covering these is the following events. This is incomplete, but enough to inspire a conversation.
Early era: TD Gammon, REINFORCE, Etc
2013: Deep Q Learning (Atari)
2014: Google acquires DeepMind
2016: AlphaGo defeats Lee Sedol
2017: PPO paper, AlphaZero (no human data)
2018: OpenAI Five, GPT 2
2019: AlphaStar, robotic sim2real with RL early papers (see blog post)
2020: MuZero
2021: Decision Transformer
2022: ChatGPT, sim2real continues.
2023: Scaling laws for RL (blog post), doubt of RL
2024: o1, post-training, RL’s bloom
Interconnects is a reader-supported publication. Consider becoming a subscriber.
Chapters
* [00:00:00] Introduction
…
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(Voiceover) OpenAI's o1 using "search" was a PSYOP
4 december 2024 · 12 min
Original post: https://www.interconnects.ai/p/openais-o1-using-search-was-a-psyop Lees meer
Figures
Figure 0: OpenAI’s seminal test-time compute plot
Figure 1: Setup for bucketed evals
Figure 2: Evals with correctness labels
Figure 3: Grouped evals
Figure 4: Hypothetical inference scaling law
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
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(Voiceover) OLMo 2 and building effective teams for training language models
26 november 2024 · 10 min
Full post: Lees meer
https://www.interconnects.ai/p/olmo-2-and-building-language-model-training
OLMo 2 demo: https://playground.allenai.org/
OLMo 2 artifacts: https://huggingface.co/collections/allenai/olmo-2-674117b93ab84e98afc72edc
Chapters
00:00 Building AI Teams
06:35 OLMo 2
Figures
Fig 1, pretrain plot: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmo2/pretrain.webp
Fig 2, pretrain table: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmo2/pretrain-table.webp
Fig 3, post-train table: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmo2/postrain-table.webp
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
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(Voiceover) Tülu 3: The next era in open post-training
21 november 2024 · 8 min
Original post: https://www.interconnects.ai/p/tulu-3 Lees meer
Chapters
00:00 History
05:44 Technical details sneak peak
Figures
Fig 1, results: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/results.webp
Fig 2, overview: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/overview.webp
Fig 3, preferences: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/preferences.webp
Fig 4, RLVR: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/rlvr.webp
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
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(Voiceover) Scaling realities
14 november 2024 · 4 min
Original post: https://www.interconnects.ai/p/scaling-realities Lees meer
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
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(Voiceover) Saving the National AI Research Resource & my AI policy outlook
13 november 2024 · 11 min
Original post: https://www.interconnects.ai/p/saving-the-nairr Lees meer
Chapters
05:26: Do we need an AI research resource or an LM research resource?
08:59: Policy roundups
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
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Interviewing Tim Dettmers on open-source AI: Agents, scaling, quantization and what's next
7 november 2024 · 1 uur 16 min
Tim Dettmers does not need an introduction for most people building open-source AI. If you are part of that minority, you’re in for a treat. Tim is the lead developer behind most of the open-source tools for quantization: QLoRA, bitsandbytes, 4 and 8 bit inference, and plenty more. He recently finished his Ph.D. at the University of Washington, is now a researcher at the Allen Institute for AI, and is starting as a professor at Carnegie Mellon University in fall of 2025. Lees meer
Tim is a joy to talk to. He thinks independently on all the AI issues of today, bringing new perspectives that challenge the status quo. At the same time, he’s sincere and very helpful to work with, working hard to uplift those around him and the academic community. There’s a reason he’s so loved in the open-source AI community.
Find more about Tim on his Twitter or Google Scholar. He also has a great blog where he talks about things like which GPUs to buy and which grad school to choose.
Listen on Apple Podcasts, Spotify, YouTube, and where ever you get your podcasts. For other Interconnects interviews, go here.
Show Notes
Here's a markdown list of companies, people, projects, research papers, and other key named entities mentioned in the transcript:
* QLoRA
* Bits and Bytes
* Llama 3
* Apple Intelligence
* SWE Bench
* RewardBench
* Claude (AI assistant by Anthropic)
* Transformers (Hugging Face library)
* Gemma (Google's open weight language model)
* Notebook LM
* LangChain
* LangGraph
* Weights & Biases
* Blackwell (NVIDIA GPU architecture)
* Perplexity
* Branch Train Merge (research paper)
* "ResNets do iterative refinement on features" (research paper)
* CIFAR-10 and CIFAR-100 (computer vision datasets)
* Lottery Ticket Hypothesis (research paper)
* OpenAI O1
* TRL (Transformer Reinforcement Learning) by Hugging Face
* Tim's work on quantization (this is just one example)
Timestamps
* [00:00:00] Introduction and background on Tim Dettmers
* [00:01:53] Future of op…
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Interviewing Andrew Carr of Cartwheel on the State of Generative AI
31 oktober 2024 · 54 min
Andrew Carr is co-founder and chief scientist at Cartwheel, where he is building text-to-motion AI models and products for gaming, film, and other creative endeavors. We discuss how to keep generative AI fun and expansive — niche powerful use-cases, AI poetry, AI devices like Meta RayBans, generalization to new domains like robotics, and building successful AI research cultures. Lees meer
Andrew is one of my well read friends on the directions AI is going, so it is great to bring him in for an official conversation. He spent time at OpenAI working on Codex, Gretel AI, and is an editor for the TLDR AI Newsletter.
Listen on Apple Podcasts, Spotify, YouTube, and where ever you get your podcasts. For other Interconnects interviews, go here.
Show Notes
Named entities and papers mentioned in the podcast transcript:
* Codex and GitHub Copilot
* Gretel AI
* TLDR AI Newsletter
* Claude Computer Use
* Blender 3D simulator
* Common Sense Machines
* HuggingFace Simulate, Unity, Godot
* Runway ML
* Mark Chen, OpenAI Frontiers Team Lead
* Meta’s Lingua, Spirit LM, torchtitan and torchchat
* Self-Rewarding Language Models paper
* Meta Movie Gen paper
Timestamps
* [00:00] Introduction to Andrew and Cartwheel
* [07:00] Differences between Cartwheel and robotic foundation models
* [13:33] Claude computer use
* [18:45] Supervision and creativity in AI-generated content
* [23:26] Adept AI and challenges in building AI agents
* [30:56] Successful AI research culture at OpenAI and elsewhere
* [38:00] Keeping up with AI research
* [44:36] Meta Ray-Ban smart glasses and AI assistants
* [51:17] Meta's strategy with Llama and open source AI
Transcript & Full Show Notes: https://www.interconnects.ai/p/interviewing-andrew-carr
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
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(Voiceover) Why I build open language models
30 oktober 2024 · 10 min
Full post: Lees meer
https://www.interconnects.ai/p/why-i-build-open-language-models
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
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(Voiceover) Claude's agentic future and the current state of the frontier models
23 oktober 2024 · 11 min
How Claude's computer use works. Where OpenAI, Anthropic, and Google all have a lead on eachother. Lees meer
Original post: https://www.interconnects.ai/p/claudes-agency
Chapters
00:00 Claude's agentic future and the current state of the frontier models
04:43 The state of the frontier models
04:49 1. Anthropic has the best model we are accustomed to using
05:27 Google has the best small & cheap model for building automation and basic AI engineering
08:07 OpenAI has the best model for reasoning, but we don’t know how to use it
09:12 All of the laboratories have much larger models they’re figuring out how to release (and use)
10:42 Who wins?
Figures
Fig 1, Sonnet New Benchmarks: https://substackcdn.com/image/fetch/w_1456,c_limit,f_webp,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5d2e63ff-ac9f-4f8e-9749-9ef2b9b25b6c_1290x1290.png
Fig 2, Sonnet Old Benchmarks: https://substackcdn.com/image/fetch/f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4bccbd4d-f1c8-4a38-a474-69a3df8a4448_2048x1763.png
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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
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Interviewing Arvind Narayanan on making sense of AI hype
17 oktober 2024 · 54 min
Arvind Narayanan is a leading voice disambiguating what AI does and does not do. His work, with Sayash Kapoor at AI Snake Oil, is one of the few beacons of reasons in a AI media ecosystem with quite a few bad Apples. Arvind is a professor of computer science at Princeton University and the director of the Center for Information Technology Policy. You can learn more about Arvind and his work on his website, X, or Google Scholar. Lees meer
This episode is all in on figuring out what current LLMs do and don’t do. We cover AGI, agents, scaling laws, autonomous scientists, and past failings of AI (i.e. those that came before generative AI took off). We also briefly touch on how all of this informs AI policy, and what academics can do to decide on what to work on to generate better outcomes for technology.
Transcript and full show notes: https://www.interconnects.ai/p/interviewing-arvind-narayanan
Chapters
* [00:00:00] Introduction
* [00:01:54] Balancing being an AI critic while recognizing AI's potential
* [00:04:57] Challenges in AI policy discussions
* [00:08:47] Open source foundation models and their risks
* [00:15:35] Personal use cases for generative AI
* [00:22:19] CORE-Bench and evaluating AI scientists
* [00:25:35] Agents and artificial general intelligence (AGI)
* [00:33:12] Scaling laws and AI progress
* [00:37:41] Applications of AI outside of tech
* [00:39:10] Career lessons in technology and AI research
* [00:41:33] Privacy concerns and AI
* [00:47:06] Legal threats and responsible research communication
* [00:50:01] Balancing scientific research and public distribution
Get Interconnects (https://www.interconnects.ai/podcast)...
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This is a public episode. If you'd like to discuss this with other subscribers or ge…
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(Voiceover) Building on evaluation quicksand
16 oktober 2024 · 17 min
Read the full post here: https://www.interconnects.ai/p/building-on-evaluation-quicksand Lees meer
Chapters
00:00 Building on evaluation quicksand
01:26 The causes of closed evaluation silos
06:35 The challenge facing open evaluation tools
10:47 Frontiers in evaluation
11:32 New types of synthetic data contamination
13:57 Building harder evaluations
Figures
Fig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/manual/openai-predictions.webp
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
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Interviewing Andrew Trask on how language models should store (and access) information
10 oktober 2024 · 1 uur
Andrew Trask is one of the bright spots in engaging with AI policy for me in the last year. He is a passionate idealist, trying to create a future for AI that enables privacy, academic research, and government involvement in a rapidly transforming ecosystem. Trask is a leader of the OpenMined organization facilitating researcher access to non-public data and AIs, a senior research scientist at Google DeepMind, a PhD student at the University of Oxford, an author and educator on Deep Learning. Lees meer
You can find more about Trask on Twitter or Google Scholar. You may want to watch his recent talk at Cohere on the future of AI (and why data breakthroughs dominate), his lecture at MIT on privacy preserving ML, or his book on deep learning that has a substantial GitHub component. Here’s a slide I liked from his recent Cohere talk:
The organization he helps run, OpenMined, has a few principles that say a lot about his ambitions and approaches to modern AI:
We believe we can inspire all data owners to open their data for research by building open-source privacy software that empowers them to receive more benefits (co-authorships, citations, grants, etc.) while mitigating risks related to privacy, security, and IP.
We cover privacy of LLMs, retrieval LLMs, secure enclaves, o1, Apple's new models, and many more topics.
More on Andrew: https://x.com/iamtrask
Transcript and more information: https://www.interconnects.ai/p/interviewing-andrew-trask
Interconnects (https://www.interconnects.ai/)...
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We Mention
* Claude 3.5 launch and “pre release testing with UK AISI” (and the US AI Safety Institute)
* OpenMined and PySyft
* CSET (Center for Security and Emerging Technology)
* NAIRR
* The “open data wall”
* Apple’s Secure Enclaves, Nvi…
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How scaling changes model behavior
9 oktober 2024 · 12 min
How scaling changes model behavior Lees meer
Some trends are reasonable to extrapolate, some are not. Even for the trends we are succeeding at extrapolating, it is not clear how that signal translates into different AI behaviors.
Read it here: https://www.interconnects.ai/p/how-scaling-changes-model-behavior
[00:00] How scaling changes model behavior
[05:03] Metaphors for what scaling may solve
[08:45] Short-term scaling is already de-risked
Fig. 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/manual/openai-predictions.webp
Fig. 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/manual/scaling-laws.webp
Fig. 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/manual/situational-awareness.webp
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
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[Article Voiceover] AI Safety's Crux: Culture vs. Capitalism
2 oktober 2024 · 10 min
SB1047's veto, OpenAI's turnover, and a constant treadmill pushing AI startups to be all too similar to big technology name brands.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/ai-safety-culture-vs-capitalism Lees meer00:00 AI Safety's Crux: Culture v Capitalism
06:03 SB1047 as a regulatory litmus test for AI safety
08:36 Capitalism at the helmThis 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
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Interviewing Riley Goodside on the science of prompting
30 september 2024 · 1 uur 9 min
Riley Goodside is a staff prompting engineer at Scale AI. Previously working in data science, he is often seen as the default for the new role of a “prompt engineer.” He regularly posts incisive prompts that illicit notable behavior from the most popular AI models. Lees meer
I really resonated with this saying from Anthropic’s recent podcast on prompt engineering — “now we write essays and treat them as code.” In order to be good at prompting, you need to understand that natural language operates as our code used to.
This episode is a masterclass on why you should care about prompting and how it impacts results. Of course, there’s a bunch of great discussion on recent models that reflect the need for different and or better prompting. Enjoy it!
Listen on Apple Podcasts, Spotify, and where ever you get your podcasts. For other Interconnects interviews, go here.
We mention:
* Prompting to push the frontier of AI models,
* Post-training and prompting interaction,
* Prompting base models,
* o1, Reflection 70B, reasoning,
* Scale’s leaderboard, evaluation tricks, evaluation needs,
* PlanSearch paper
* Julius AI
* “The hottest programming language is english”
* “Think silently” instructions
* Scale Leaderboard and Humanity’s Last Exam
* ChatML formatting
Chapters
* [00:00:09] Introduction
* [00:02:40] Riley's path to LLMs
* [00:07:54] Impact of ChatGPT on prompt engineering
* [00:12:03] OpenAI's o1
* [00:18:21] Autoregressive inference and prompting sensitivities
* [00:24:48] Reflection 70B model and its implications
* [00:28:00] Impact of prompting on evaluation
* [00:32:43] Prompting vs. Google search
* [00:46:55] Prompting and RLHF/post-training
* [00:56:57] Prompting of AI agents
* [01:01:20] Importance of hands-on experience with language models
* [01:05:00] Importance and challenges of AI model evaluation
Transcript
Built with smol-podcaster.
Nathan L. [00:01:08]: Hey, Riley, welcome to the show.
Riley G. Hey, Nathan, great to be here.
Nathan…
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[Article Voiceover] Llama 3.2 Vision and Molmo: Foundations for the multimodal open-source ecosystem
27 september 2024 · 14 min
Sorry this one was late! Thanks for bearing with me, and keep sending feedback my way. Still a year or two away from when I have time to record these, but I would love to. Lees meer
Open-source tools, examples, limits, and the state of training multimodal models.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/molmo-and-llama-3-vision00:00 Llama 3.2 Vision and Molmo: Foundations for the multimodal open-source ecosystem
02:47 Llama vision: Multimodality for the masses of developers
03:27 Molmo: a (mostly) open-source equivalent to Llama vision
08:45 How adding vision changes capabilities and reasoning
11:47 Multimodal language models: Earlier on the exponentialFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_013.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_015.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_021.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_023.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_027.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_030.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_037.png
Fig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_046.png
Fig 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_048.png
Fig 10: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-and-molmo/img_050.png
Fig 11: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/… -
[Article Voiceover] Reverse engineering OpenAI's o1
17 september 2024 · 19 min
What productionizing test-time compute shows us about the future of AI. Exploration has landed in language model training.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/reverse-engineering-openai-o1 Lees meer00:00 Reverse engineering OpenAI's o1
01:52 From Q-star to Strawberry to o1
05:13 Training o1 with reinforcement learning
09:24 What is o1 doing when given a prompt?
11:49 Questions to consider to understand o1's structure
11:56 1. How does an RL-trained language model act?
12:38 2. Is it an online / test-time search?
14:20 3. Is it one model at inference?
15:29 Open-source o1, the future of o1, and the future of AIFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_014.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_016.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_018.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_020.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_024.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_026.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_034.png
Fig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/o1/img_048.pngThis 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
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Futures of the data foundry business model
11 september 2024 · 12 min
Scale AI's future versus further scaling of language model performance. How Nvidia may take all the margins from the data market, too.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/ai-data-foundry Lees meer00:00 Futures of the data foundry business model
02:57 What it is like to work with data vendors
06:06 Data foundries: Risks
08:18 Data foundries: Growth vectors
09:50 Realistic expectationsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/data-foundry/img_008.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/data-foundry/img_012.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/data-foundry/img_023.pngThis 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
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A post-training approach to AI regulation with Model Specs
10 september 2024 · 6 min
And why the concept of mandating "model spec's" could be a good start.
(Oops, forgot to upload this yesterday!)
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/a-post-training-approach-to-ai-regulation Lees meer0:00 A post-training approach to AI regulation with Model Specs
1:45 Expanded roles of Model Specifications
3:40 Near future of Model SpecificationsThis 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
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OpenAI's Strawberry, LM self-talk, inference scaling laws, and spending more on inference
5 september 2024 · 11 min
Whether or not scaling works, we should spend more on inference.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/openai-strawberry-and-inference-scaling-laws Lees meer00:00 OpenAI's Strawberry, LM self-talk, inference scaling laws, and spending more on inference
01:51 OpenAI's Strawberry
04:16 Self-talk in language models
07:45 Inference scaling lawsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/strawberry/img_006.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/strawberry/img_021.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/strawberry/img_023.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/strawberry/img_037.pngThis 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
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OLMoE and the hidden simplicity in training better foundation models
4 september 2024 · 11 min
Ai2 released OLMoE, which is probably our "best" model yet relative to its peers, but not much has changed in the process.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/olmoe-and-building-better-llms Lees meer00:00 OLMoE and the hidden simplicity in training better foundation models
02:04 Frontier model team compute allocations
04:19 De-risking training complexity
06:40 On organizational complexity
09:05 Compounding improvements -- the key to building better language modelsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_005.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_007.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_009.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_011.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_028.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_030.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/olmoe/img_032.pngThis 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
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On the current definitions of open-source AI and the state of the data commons
28 augustus 2024 · 8 min
The Open Source Initiative is working towards a definition.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/defining-open-source-ai Lees meer0:00 On the current definitions of open-source AI and the state of the data commons
3:17 Reasons to not mandate fully released data
4:24 Sufficient but not exhaustive data docs
5:22 Frustration with the data commons
7:04 We need more examples to define the definitionFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/defining-open-source/img_005.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
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Nous Hermes 3 and exploiting underspecified evaluations
16 augustus 2024 · 9 min
The latest model from one of the most popular fine-tuning labs makes us question how a model should be identified as a "frontier model."
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/nous-hermes-3 Lees meer0:00 Nous Hermes 3 and exploiting underspecified evaluations
5:29 Parsing training lessons from Hermes 3Fig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_005.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_010.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_012.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_020.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_027.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_030.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_032.png
Fig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/nous-hermes-3/img_036.pngThis 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
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Interviewing Ross Taylor on LLM reasoning, Llama fine-tuning, Galactica, agents
8 augustus 2024 · 1 uur 2 min
I had the pleasure of Talking with Ross Taylor, who has a great spectrum of unique experiences in the language modeling space — evaluation experience, Galactica lead author, Llama post training, etc. This is a really great conversation on the frontier of language model (LM) reasoning, LM deployments and demos, LM’s for science, RLHF, and other topics. I’ve been trying to get Ross to come on for a bit. He’s one of those people in the LM space that doesn’t speak too much, but when you do, you listen. Lees meer
Ross Taylor was previously an LLM lead at Meta AI, heading up the reasoning team. Previously he led the early work on LLM agents, and was the research lead on the Galactica project. Before that, he was a co-founder of Papers with Code, which was acquired by Meta in 2019. Before that, he has worked as a quant in sports betting and finance, and before that a policy advisor for the UK Government. He is currently working on a new startup.
Listen on Apple Podcasts, Spotify, and where ever you get your podcasts. For other Interconnects interviews, go here.
YouTube
Chapters
* [00:00:00] Introduction of Ross Taylor and his background
* [00:02:12] Papers with Code
* [00:09:58] Galactica, goals, controversy, legacy
* [00:18:12] Technical details of the Galactica model
* [00:23:18] Potential for language models to make scientific discoveries
* [00:25:21] Defining and improving reasoning in language models
* [00:32:38] Process-based reward models and their potential applications
* [00:35:00] Generating synthetic data for SFT
* [00:40:23] Evaluating the effectiveness of language models as judges for human preference data
* [00:42:43] Considerations for creating base models that are easy to fine-tune
* [00:46:45] Balancing SFT and RLHF
* [00:54:13] Characteristics of successful post-training teams
* [00:58:26] Future directions for language model development
We mention
* Galactica
* Papers with Code
* Rob Stojnic (co-founder of Papers with Code)
* DPO, PPO
* Arm…
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A recipe for frontier model post-training
7 augustus 2024 · 10 min
Apple, Meta, and Nvidia all agree -- synthetic data, iterative training, human preference labels, and lots of filtering.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/frontier-model-post-training Lees meer00:00 Llama 3.1 post-training and the new normal for RLHF
01:18 A new standard pipeline
01:45 Human preference data
02:59 Scaling RLHF
05:03 Synthetic data
06:10 The new normal
06:51 Data quality is king
07:18 Apple confirms the new normalFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/frontier-rlhf/img_018.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/frontier-rlhf/img_020.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/frontier-rlhf/img_031.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/frontier-rlhf/img_033.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/frontier-rlhf/img_035.pngThis 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
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Interviewing Sebastian Raschka on the state of open LLMs, Llama 3.1, and AI education
1 augustus 2024 · 1 uur 4 min
This week, I had the pleasure of chatting with Sebastian Raschka. Sebastian is doing a ton of work on the open language model ecosystem and AI research broadly. He’s been writing the great Ahead of AI newsletter (that has the biggest audience overlap with Interconnects, at 26%, so a lot of you know him) and multiple educational books, all on top of being a full time machine learning engineer at Lightning.ai, where he maintains LitGPT, which he described as being like Karpathy’s NanoGPT, with slightly more abstractions. Lees meer
This conversation mostly surrounds keeping up with AI research, the state of the open LLM ecosystem post Llama 3.1, and many narrow topics in between. I learned that Sebastian used to be an Arxiv moderator, which gives some simple color on how Arxiv and sifting through thousands of papers works. We cover a lot of ground here, so I hope you enjoy it.
Listen on Apple Podcasts, Spotify, and where ever you get your podcasts. For other interviews, go here.
YouTube
Chapters
* [00:00:00] Introduction & Sebastian’s background
* [00:04:28] The state of deep learning and language models in 2018
* [00:08:02] Sebastian's work at Lightning AI and LitGPT
* [00:12:23] Distillation and its potential in language model training
* [00:14:14] Implementing language models and common pitfalls
* [00:18:45] Modern architectures: Mixture of experts models, early v. late fusion multimodal
* [00:24:23] Sebastian's book on building language models from scratch
* [00:27:13] Comparing ChatGPT, Claude, and Google's Gemini for various tasks
* [00:38:21] Vibing and checking new language models during implementation
* [00:40:42] Selecting papers to read and moderating Arxiv
* [00:45:36] Motivation for working on AI education
* [00:52:46] Llama 3 fine-tuning
* [00:57:26] The potential impact of AI on jobs in writing and education
* [01:00:57] The future directions of AI
Transcript
Built with smol-podcaster and with love of Latent Space.
Nathan Lambert [00:00:00]: …
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GPT-4o-mini changed ChatBotArena
31 juli 2024 · 8 min
And how to understand Llama three point one's results.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/gpt-4o-mini-changed-chatbotarena Lees meer0:00 GPT-4o-mini changed ChatBotArena
3:23 Llama 3 in the arena
5:13 Partial solutions and next stepsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_013.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_015.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_019.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_021.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_025.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_039.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/new-chatbotarena/img_043.pngThis 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
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Llama 3.1 405b, Meta's AI strategy, and the new open frontier model ecosystem
24 juli 2024 · 15 min
Defining the future of the AI economy and regulation. Is Meta's AI play equivalent to the Unix stack for open-source software?
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/llama-405b-open-frontier-model Lees meer00:00 Llama 3.1 405b, Meta's AI strategy, and the new open frontier model ecosystem
01:37 Meta's open frontier model
03:51 Zuckerberg's vision for open-source AI (vs. reality)
08:35 Does the Llama 3.1 license support open-source AI?
12:55 Different futures for regulating frontier modelsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-405/img_008.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-405/img_010.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-405/img_015.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-405/img_018.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama-405/img_050.pngThis 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
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SB 1047, AI regulation, and unlikely allies for open models
17 juli 2024 · 14 min
SB 1047, AI regulation, and unlikely allies for open models
The rallying of the open-source community against CA SB 1047 can represent a turning point for AI regulation.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/sb-1047-and-open-weights Lees meer00:00 Introduction
01:53 SB 1047 and targeting regulation
07:57 Unlikely allies of "open"
12:05 What would I regulate today?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
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Switched to Claude 3.5
3 juli 2024 · 7 min
I Switched to Claude 3.5
Speculations on the role of RLHF and why I love the model for people who pay attention.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/switched-to-claude-from-chatgpt Lees meer00:00 I Switched to Claude 3.5
03:57 Product priorities
05:15 RLHF's peak?Fig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/claude/img_016.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/claude/img_018.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/claude/img_020.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/claude/img_022.pngThis 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
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Interviewing Dean Ball on AI policy: CA SB 1047, upcoming AI disaster response, Llama 3 405B, Chinese open-source AI, and scaling laws
27 juni 2024 · 56 min
I’m really excited to resume the Interconnects Interviews with Dean W. Ball from the Hyperdimensional Substack (you should subscribe). We cover the whole stack of recent happenings in AI policy, focusing of course on California’s bill SB 1047. We cover many, many more great topics here including: Lees meer
* What will happen in the case of a minor AI disaster,
* If Meta will release the 405B model, and why,
* The status of Chinese open-source AI,
* Training on model outputs,
* Anthropic’s recent strategy,
* What scaling laws actually mean,
* Creating content and shifting the needle of the AI discourse.
Watch the video on YouTube below or listen on podcast players here.
Interconnects is a reader-supported publication. Consider becoming a subscriber.
Chapters
* 00:00 Intro and Welcome Dean Ball
* 02:44 The Origins of California Bill SB1047
* 08:56 The Evolution of Bill SB1047
* 13:00 How SB1047 Affects Fine-Tuning
* 20:00 The Future of Bill SB1047
* 21:58 The Impact of AI Disasters
* 29:02 Meta and its 400 billion Parameter Model
* 32:25 Open Source AI and the Chinese Market
* 37:37 The Future of Open Source AI
* 43:35 Synthetic Data, Licenses, and Future AI Development
* 45:18 Anthropic's Approach to AI Safety
* 50:46 Scaling Laws
* 53:01 The Role of Audience in Influencing AI Policy
Links
* Dean’s series on SB-1047: one, two, and three.
* Other AI policy Substacks: Jural Networks and Intersecting AI
* Senator Scott Wiener. CA SB 1047 itself.
* Another post on CA SB 1047 from Answer AI.
* Situational Awareness by Leopold Aschenbrenner.
* Lina Kahn on her P(doom) and warnings in support of open-source.
* Ben Thompson’s Framework for Moderation in technology.
Transcript
Nathan Lambert (00:00:01): Hello, and welcome back to InterConnect's interview series. It's been a few months. I'm really excited for this one. We're here with Dean Ball, who is a research fellow at the Mercatus Center. He works on AI policy right now, and he's the author of the …
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RLHF Roundup: Trying to get good at PPO, charting RLHF's impact, RewardBench retrospective, and a reward model competition
26 juni 2024 · 12 min
Things to be aware of if you work on language model fine-tuning.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/rlhf-roundup-2024 Lees meer00:00 RLHF Roundup: Trying to get good at PPO, charting RLHF's impact, RewardBench retrospective, and a reward model competition
04:32 How big is the impact of RLHF relative to pretraining?
05:54 RewardBench retrospective after 100 models and 90% peak accuracy
09:19 LMSYS's reward modeling competitionFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf-roundup/img_009.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf-roundup/img_012.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf-roundup/img_017.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf-roundup/img_026.pngThis 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
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Frontiers in synthetic data
22 juni 2024 · 11 min
Synthetic data is known to be a super powerful tool for every level of the language modeling stack. It's documented as being used for expanding vanilla pretraining data and creating large swaths of fine-tuning data. Many, many more rumors surround its use, Anthropic's pretraining-scale constitutional AI, Mistral AI's first models being pretrained on OpenAI outputs, Q-star's hopes as OpenAI's remaining moat, and much more. The diversity of use cases for synthetic data makes planning around the role of synthetic data in solving specific goals.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/frontiers-in-synthetic-data Lees meer00:00 Frontiers in synthetic data
01:14 1. Direct distillation is still king
02:54 2. Are Gemini Flash and Claude Haiku distilled?
04:03 3. Filtering prevents collapse
06:30 4. Synthetic data strategy taxes
07:32 5. Pros and cons of training on multi-output-source synthetic datasets
08:54 6. Structured synthetic data
09:42 7. Weak-to-strong generalization is maybe real
10:27 8. Creating synthetic prompts is overlooked againThis 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
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Text-to-video AI is already abundant
18 juni 2024 · 8 min
Signs point to a general-use Sora-like model coming very soon, maybe even with open-weights.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/text-to-video-ai-is-already-abundant Lees meer0:00 Text-to-video AI is already abundant
5:08 What's next for the text-to-video market?
6:49 Are text-to-video models good for the world?Fig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_005.mp4
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_009.mp4
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_011.mp4
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_013.mp4
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_015.mp4
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/text-to-video/img_017.mp4This 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
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AI for the rest of us
12 juni 2024 · 13 min
Apple Intelligence makes a lot of sense when you get out of the AI bubble.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/apple-intelligence Lees meer00:00 AI for the rest of us
02:46 Apple's technical approach
03:32 Core models: What did Apple build?
05:35 Alignment strategies: Some new things!
10:00 Orchestrating adapters and on-device magic
11:58 Light for other narratives around AIFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/apple-intelligence/img_005.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/apple-intelligence/img_015.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/apple-intelligence/img_039.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/apple-intelligence/img_041.pngThis 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
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A realistic path to robotic foundation models
5 juni 2024 · 8 min
A realistic path to robotic foundation models
Not "agents" and not "AGI." Some thoughts and excitement after revisiting the industry thanks to Physical Intelligence founders Sergey Levine and Chelsea Finn.
This is AI generated audio with Python and 11Labs.
Source code: https://github.com/natolambert/interconnects-tools
Original post: https://www.interconnects.ai/p/robotic-foundation-models Lees meer0:00 A realistic path to robotic foundation models
2:51 Key factors for the future of robotics
6:19 Everything is a token: The transformerification of roboticsThis 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
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We aren't running out of training data, we are running out of open training data
29 mei 2024 · 8 min
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-tools
Original post: https://www.interconnects.ai/p/the-data-wall Lees meer0:00 We aren't running out of training data, we are running out of open training data
2:51 Synthetic data: 1 trillion new tokens per day
4:18 Data licensing deals: High costs per token
6:33 Better tokens: Search and new frontiersThis 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
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Name, image, and AI's likeness
22 mei 2024 · 9 min
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-tools
Original post: https://www.interconnects.ai/p/name-image-and-ai-likeness Lees meer0:00 Name, image, and AI's likeness
1:11 OpenAI's second terrible, horrible, no good, very bad week
4:36 The expansion of name and likeness
7:46 Culture and AI developmentThis 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
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OpenAI chases Her
16 mei 2024 · 12 min
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-tools
Original post: https://www.interconnects.ai/p/openai-and-her Lees meer00:00 OpenAI chases Her
02:10 Talking to ChatGPT
03:53 GPT-4o: Toward omnimodal models
08:25 Google's mirror with Gemini
10:11 OpenAI's AI Safety: Have your cake and eat it tooFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/her/img_018.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/her/img_023.jpgThis 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
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OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions
13 mei 2024 · 14 min
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-tools
Original post: https://www.interconnects.ai/p/openai-rlhf-model-spec Lees meer00:00 OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions
02:56 Reviewing the Model Spec
08:26 Where RLHF can fail OpenAI
12:23 From Model Spec's to personalizationFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_027.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_029.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_033.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_034.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_041.webp
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/model-spec/img_046.webpThis 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
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RLHF: A thin line between useful and lobotomized
1 mei 2024 · 13 min
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-tools
Original post: https://www.interconnects.ai/p/how-rlhf-works-2 Lees meer00:00 How RLHF works, part 2: A thin line between useful and lobotomized
04:27 The chattiness paradox
08:09 The mechanism for making models chattier
10:42 Next steps for RLHF researchFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_012.webp
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_018.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/rlhf/img_025.pngThis 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
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Phi 3 and Arctic: Outlier LMs are hints
30 april 2024 · 10 min
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-tools
Original post: https://www.interconnects.ai/p/phi-3-and-arctic-llms Lees meer0:00 Phi 3 and Arctic: Outlier LMs are hints
1:01 Arctic & open mixture of expert trends
6:10 Phi 3, synthetic data, and small modelsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_004.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_008.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/phi3/img_018.pngThis 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
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AGI is what you want it to be
24 april 2024 · 11 min
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-tools
Original post: https://www.interconnects.ai/p/agi-is-what-you-want-it-to-be Lees meer00:00 AGI is what you want it to be
04:01 RL still rules the AGI discourse
05:43 Modern AGI tests
07:37 Agency and shifting goalpostsFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/agi/img_018.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/agi/img_020.pngThis 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
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Llama 3: Scaling open LLMs to AGI
21 april 2024 · 15 min
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-tools
Original post: https://www.interconnects.ai/p/llama-3-and-scaling-open-llms Lees meer00:00 Llama 3; scaling open LLMs to AGI
01:44 Pretraining, data, and basic evals
06:06 Alignment and human evaluations
10:08 Chatting with Meta AI and Llama 3 70B Instruct
11:55 Same Llama license (mostly)
12:52 The healthy open LLM ecosystemFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_011.jpeg
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_013.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_015.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_020.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_036.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_040.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_046.jpeg
Fig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_061.png
Fig 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_063.webp
Fig 10: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_066.png
Fig 11: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/llama3/img_068.jpegThis 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
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Stop "reinventing" everything to "solve" alignment
17 april 2024 · 8 min
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-tools
Original post: https://www.interconnects.ai/p/reinventing-llm-alignment Lees meer0:00 Stop "reinventing" everything to "solve" AI alignment
2:19 Social Choice for AI Alignment: Dealing with Diverse Human Feedback
7:03 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.png
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_015.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_018.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_024.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/reinvention/img_027.pngThis 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
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The end of the "best open LLM"
15 april 2024 · 7 min
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-tools
Original post: https://www.interconnects.ai/p/compute-efficient-open-llms Lees meer0:00 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.jpeg
Fig 2: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_009.png
Fig 3: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_014.png
Fig 4: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_016.png
Fig 5: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_018.png
Fig 6: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_020.png
Fig 7: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_022.png
Fig 8: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_024.png
Fig 9: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/scaling/img_028.pngThis 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