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PODCAST

Interconnects

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

technology

All Episodes

7:59

(Voiceover) Tülu 3: The next era in open post-training

Interconnects ·

2024/11/21

Original post: https://www.interconnects.ai/p/tulu-3Chapters00:00 History05:44 Technical details sneak peakFiguresFig 1, results: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/results.webpFig 2, overview: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/overview.webpFig 3, preferences: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/tulu3-img/preferences.webpFig 4, RLVR:

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4:21

(Voiceover) Scaling realities

Interconnects ·

2024/11/14

Original post: https://www.interconnects.ai/p/scaling-realities Get full access to Interconnects at www.interconnects.ai/subscribe

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11:22

(Voiceover) Saving the National AI Research Resource...

Interconnects ·

2024/11/13

Original post: https://www.interconnects.ai/p/saving-the-nairrChapters05:26: Do we need an AI research resource or an LM research resource?08:59: Policy roundups Get full access to Interconnects at www.interconnects.ai/subscribe

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75:45

Interviewing Tim Dettmers on open-source AI: Agents,...

Interconnects ·

2024/11/07

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.Tim is a joy to talk to. He

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54:10

Interviewing Andrew Carr of Cartwheel on the State of...

Interconnects ·

2024/10/31

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.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

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10:19

(Voiceover) Why I build open language models

Interconnects ·

2024/10/30

Full post:https://www.interconnects.ai/p/why-i-build-open-language-models Get full access to Interconnects at www.interconnects.ai/subscribe

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11:23

(Voiceover) Claude's agentic future and the current...

Interconnects ·

2024/10/23

How Claude's computer use works. Where OpenAI, Anthropic, and Google all have a lead on eachother.Original post: https://www.interconnects.ai/p/claudes-agencyChapters00:00 Claude's agentic future and the current state of the frontier models04:43 The state of the frontier models04:49 1. Anthropic has the best model we are accustomed to using05:27 Google has the best small & cheap model for building automation and basic AI engineering08:07 OpenAI has the best model for reasoning, but we don’t know how

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54:21

Interviewing Arvind Narayanan on making sense of AI hype

Interconnects ·

2024/10/17

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.This episode is all in on figuring out what current LLMs do and don’t do

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16:36

(Voiceover) Building on evaluation quicksand

Interconnects ·

2024/10/16

Read the full post here: https://www.interconnects.ai/p/building-on-evaluation-quicksandChapters00:00 Building on evaluation quicksand01:26 The causes of closed evaluation silos06:35 The challenge facing open evaluation tools10:47 Frontiers in evaluation11:32 New types of synthetic data contamination13:57 Building harder evaluationsFiguresFig 1: https://huggingface.co/datasets/natolambert/interconnects-figures/resolve/main/manual/openai-predictions.webp Get full access to Interconnects at

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60:12

Interviewing Andrew Trask on how language models...

Interconnects ·

2024/10/10

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.You can

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11:47

How scaling changes model behavior

Interconnects ·

2024/10/09

How scaling changes model behaviorSome 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-riskedFig. 1:

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10:30

AI Safety's Crux: Culture vs. Capitalism

Interconnects ·

2024/10/02

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-toolsOriginal post: https://www.interconnects.ai/p/ai-safety-culture-vs-capitalism00:00 AI Safety's Crux: Culture v Capitalism06:03 SB1047 as a regulatory litmus test for AI safety08:36 Capitalism at the helm

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68:39

Interviewing Riley Goodside on the science of prompting

Interconnects ·

2024/09/30

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.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

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68:39

Interviewing Riley Goodside on the science of prompting

Interconnects ·

2024/09/30

More information: https://www.interconnects.ai/p/riley-goodside-on-science-of-promptingRiley 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.I really resonated with this saying from Anthropic’s recent podcast on prompt engineering — “now we write essays and treat them as code.” In

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14:04

Llama 3.2 Vision and Molmo: Foundations for the...

Interconnects ·

2024/09/27

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.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-toolsOriginal post: https://www.interconnects.ai/p/molmo-and-llama-3-vision00:00 Llama 3.2 Vision and Molmo: Foundations for the

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18:52

Reverse engineering OpenAI's o1

Interconnects ·

2024/09/17

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-toolsOriginal post: https://www.interconnects.ai/p/reverse-engineering-openai-o100:00 Reverse engineering OpenAI's o101:52 From Q-star to Strawberry to o105:13 Training o1 with reinforcement learning09:24 What is o1 doing when given a prompt?11:49 Questions to

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11:32

Futures of the data foundry business model

Interconnects ·

2024/09/11

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-toolsOriginal post: https://www.interconnects.ai/p/ai-data-foundry00:00 Futures of the data foundry business model02:57 What it is like to work with data vendors06:06 Data foundries: Risks08:18 Data foundries: Growth vectors09:50 Realistic

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5:39

A post-training approach to AI regulation with Model...

Interconnects ·

2024/09/10

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-toolsOriginal post: https://www.interconnects.ai/p/a-post-training-approach-to-ai-regulation0:00 A post-training approach to AI regulation with Model Specs1:45 Expanded roles of Model Specifications3:40 Near future of Model Specifications

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10:40

OpenAI's Strawberry, LM self-talk, inference scaling...

Interconnects ·

2024/09/05

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-toolsOriginal post: https://www.interconnects.ai/p/openai-strawberry-and-inference-scaling-laws00:00 OpenAI's Strawberry, LM self-talk, inference scaling laws, and spending more on inference01:51 OpenAI's Strawberry04:16 Self-talk in language models07:45 Inference scaling lawsFig 1:

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10:31

OLMoE and the hidden simplicity in training better...

Interconnects ·

2024/09/04

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-toolsOriginal post: https://www.interconnects.ai/p/olmoe-and-building-better-llms00:00 OLMoE and the hidden simplicity in training better foundation models02:04 Frontier model team compute allocations04:19 De-risking training complexity06:40 On organizational

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