It's time to talk about the Ludding times. That's how they talked about it, those who were there, when readying themselves for an insurrection a few years later.

This video explores the journey of AI language models, from their modest beginnings through the development of OpenAI's GPT models. Our journey takes us through the key moments in generative neural network research involved in next word prediction. We delve into the early experiments with tiny language models in the 1980s, highlighting significant contributions by researchers like Jordan, who introduced Recurrent Neural Networks, and Elman, whose work on learning word boundaries revolutionized our understanding of language processing. It leaves us with a question: what is thought? Is simulated thought, thought? Featuring Noam Chomsky Douglas Hofstadter Michael I. Jordan Jeffrey Elman Geoffrey Hinton Ilya Sutskever Andrej Karpathy Yann LeCun and more. (Sam altman)

My script, references & visualizations here: https://docs.google.com/document/d/1s7FNPoKPW9y3EhvzNgexJaEG2pP4Fx_rmI4askoKZPA

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This is the last video in the series "The Pattern Machine" you can watch it all here: https://www.youtube.com/playlist?list=PLbg3ZX2pWlgKV8K6bFJr5dhM7oOClExUJ

00:00 - Introduction 00:32 - hofstader's thoughts on chatGPT 01:00 - recap of supervised learning 01:55 - first paper on sequential learning 02:55 - first use of state units (RNN) 04:33 - first observation of word boundary detection 05:30 - first observation of word clustering 07:16 - first "large" language model Hinton/Sutskever 10:10 - sentiment neuron (Ilya | OpenAI) 12:30 - transformer explaination 15:50 - GPT-1 17:00 - GPT-2 17:55 - GPT-3 18:20 - In-context learning 19:40 - ChatGPT 21:10 - tool use 23:25 - philosophical question: what is thought?

This is a 1 hour general-audience introduction to Large Language Models: the core technical component behind systems like ChatGPT, Claude, and Bard. What they are, where they are headed, comparisons and analogies to present-day operating systems, and some of the security-related challenges of this new computing paradigm. As of November 2023 (this field moves fast!).

Context: This video is based on the slides of a talk I gave recently at the AI Security Summit. The talk was not recorded but a lot of people came to me after and told me they liked it. Seeing as I had already put in one long weekend of work to make the slides, I decided to just tune them a bit, record this round 2 of the talk and upload it here on YouTube. Pardon the random background, that's my hotel room during the thanksgiving break.

• Slides as PDF: https://drive.google.com/file/d/1pxx_ZI7O-Nwl7ZLNk5hI3WzAsTLwvNU7/view?usp=share_link (42MB)
• Slides. as Keynote: https://drive.google.com/file/d/1FPUpFMiCkMRKPFjhi9MAhby68MHVqe8u/view?usp=share_link (140MB)

Few things I wish I said (I'll add items here as they come up): - The dreams and hallucinations do not get fixed with finetuning. Finetuning just "directs" the dreams into "helpful assistant dreams". Always be careful with what LLMs tell you, especially if they are telling you something from memory alone. That said, similar to a human, if the LLM used browsing or retrieval and the answer made its way into the "working memory" of its context window, you can trust the LLM a bit more to process that information into the final answer. But TLDR right now, do not trust what LLMs say or do. For example, in the tools section, I'd always recommend double-checking the math/code the LLM did. - How does the LLM use a tool like the browser? It emits special words, e.g. |BROWSER|. When the code "above" that is inferencing the LLM detects these words it captures the output that follows, sends it off to a tool, comes back with the result and continues the generation. How does the LLM know to emit these special words? Finetuning datasets teach it how and when to browse, by example. And/or the instructions for tool use can also be automatically placed in the context window (in the “system message”). - You might also enjoy my 2015 blog post "Unreasonable Effectiveness of Recurrent Neural Networks". The way we obtain base models today is pretty much identical on a high level, except the RNN is swapped for a Transformer. http://karpathy.github.io/2015/05/21/rnn-effectiveness/ - What is in the run.c file? A bit more full-featured 1000-line version hre: https://github.com/karpathy/llama2.c/blob/master/run.c

Chapters: Part 1: LLMs 00:00:00 Intro: Large Language Model (LLM) talk 00:00:20 LLM Inference 00:04:17 LLM Training 00:08:58 LLM dreams 00:11:22 How do they work? 00:14:14 Finetuning into an Assistant 00:17:52 Summary so far 00:21:05 Appendix: Comparisons, Labeling docs, RLHF, Synthetic data, Leaderboard Part 2: Future of LLMs 00:25:43 LLM Scaling Laws 00:27:43 Tool Use (Browser, Calculator, Interpreter, DALL-E) 00:33:32 Multimodality (Vision, Audio) 00:35:00 Thinking, System 1/2 00:38:02 Self-improvement, LLM AlphaGo 00:40:45 LLM Customization, GPTs store 00:42:15 LLM OS Part 3: LLM Security 00:45:43 LLM Security Intro 00:46:14 Jailbreaks 00:51:30 Prompt Injection 00:56:23 Data poisoning 00:58:37 LLM Security conclusions End 00:59:23 Outro

Stephen is delighted to welcome one of his favorite directors, the Master of Horror himself, John Carpenter. Watch as they discuss his 1982 classic film, “The Thing,” and stick around for a peek into Carpenter’s directing process for his latest project, “Suburban Screams.”

Colbert #SuburbanScreams #JohnCarpenter

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Watch The Late Show with Stephen Colbert weeknights at 11:35 PM ET/10:35 PM CT. Only on CBS.

Stephen Colbert brings his signature satire and comedy to THE LATE SHOW with STEPHEN COLBERT, the #1 show in late night, where he talks with an eclectic mix of guests about what is new and relevant in the worlds of politics, entertainment, business, music, technology and more. Featuring bandleader Louis Cato and “THE LATE SHOW band,” the Peabody Award-winning and Emmy Award-nominated show is broadcast from the historic Ed Sullivan Theater. Stephen Colbert took over as host, executive producer and writer of THE LATE SHOW on Sept. 8, 2015.

When we talk about artificial intelligence, we rely on metaphor, as we always do when dealing with something new and unfamiliar. Metaphors are, by their nature, imperfect, but we still need to choose them carefully, because bad ones can lead us astray.

The incessant hype over AI tools like ChatGPT is inspiring lots of bad opinions from people who have no idea what they’re talking about.

The incessant hype over AI tools like ChatGPT is inspiring lots of bad opinions from people who have no idea what they’re talking about.

People kept talking about a "vibe shift," but what had shifted was that all people seemed to talk about were vibes... the vibe was ambient grift, with an undercurrent of paranoia.

Recorded Monday June 20th, 2022

After fifteen years art directing photography books and magazines such as Elle and Tatler, Dr Grant Scott began to work solely as a photographer for commercial and editorial clients in 2000. His images combine his experience working with some of the greatest photographers of the last century with his graphic and journalistic talents to create engaging photographic narratives from every commission.

Grant is the founder/curator of United Nations of Photography, a Senior Lecturer and Subject Coordinator for Photography at Oxford Brookes University, Oxford, a working photographer, documentary filmmaker, BBC Radio contributor and the author of Professional Photography: The New Global Landscape Explained (Routledge 2014), The Essential Student Guide to Professional Photography (Routledge 2015) and New Ways of Seeing: The Democratic Language of Photography (Routledge 2019).

In the talk Grant addresses the constantly shifting sands of engagement with the photographic medium. Noting that we read books and acquire a respect for how difficult it is to write and are taught how to read the written word and appreciate its transformative power Grant will makes the case for the importance of visual literacy. He will explain how digital photography has democratised the medium, with ensuing debates between those with analogue experience and the digital natives and focus on the importance of ‘the personal’ in defining subject matter. The talk and following questions and answers are an exploration on what makes a successful visual narrative.

The Japanese newspaper The Mainichi first reported on the marital troubles back in January, with the New York Times providing further details this week.

The FADER Interview is a brand new podcast series in which the world’s most exciting musicians talk with the staff of The FADER about their latest projects.

The Japanese newspaper The Mainichi first reported on the marital troubles back in January, with the New York Times providing further details this week.

The FADER Interview is a brand new podcast series in which the world’s most exciting musicians talk with the staff of The FADER about their latest projects.

This article is part of our coverage of the latest in AI research. Artificial intelligence research lab OpenAI made headlines again, this time with DALL-E 2, a machine learning model that can generate stunning images from text descriptions.

Share this so it isn't my last episode. Join our Discord! https://discord.gg/SrDAqQzQ

✳ PATREON: https://www.patreon.com/user?u=711561 ✳ Twitter: http://twitter.com/_lucasrizzotto ✳ Facebook: http://facebook.com/lucasrizzotto ✳ Instagram: http://instagram.com/_lucasrizzotto ✳ Website: http://lucasrizzotto.com]

Thanks for the wild ride, friends. This one was a joy (and hell) to make. Make sure you follow me closely on social media - got some big announcements to make this week!

I really appreciate you all, specially those of you who dig deep into the description to find hidden bits like this :)

This channel never really blew up the way I thought it would but it brought me close with some of the most passionate people I've ever seen and I'll always be eternally grateful.

Love ya,

Swooty McBooty

Special thanks to: Austin Beaulier (for helping me get the epic smooth shots in the memories sequence) Cix Liv (for all his expert insight as Dimitri) Max Noir (for dealing with all the bs of making this video for almost a year lmao) Stephen Hodgson (for helping out hugely with GPT-3 code)

Chapters!

00:00 - Teaser 00:38 - Introduction 02:35 - Jeff Bezos' Tale 04:22 - The Brain Transplant 05:07 - GIANT METAL DEATH MACHINES 06:00 - Okay Let Me Explain GPT-3 For Real Now lol 07:10 - Writing Fake Memories 09:30 - PLOT TWIST! An Old Friend 11:20 - Ad-Break 12:24 - The Conversation Begins 13:36 - Microwave Gets Personal 14:45 - Microwave Politics 15:43 - Oh God He Likes Hitler 16:18 - Dramatic Question Montage 19:34 - Unintended Consequences 20:19 - Microwave PTSD Montage 21:12 - The Murder Attempt 23:04 - Lucas Moves Far Away... 23:33 - ... To Uganda LOL 24:22 - Haunted By Nightmares 24:53 - Talking to an Expert 26:34 - Is Magnetron Fake? 27:06 - The Final Conversation 30:12 - Goodbye, Magnetron 31:34 - Is it over? 32:15 - Outro / Sad Announcements 34:20 - Goodbyes & Reminiscing

------Curiosity Stream Sign Up Link----- https://curiositystream.com/fdsignifier

After a few months of “success” on the platform, I sat to contemplate my journey from unknown content creator scraping for views to hot new video essayist and legit “left tuber”. This contemplation led to numerous questions and ponderings, and as I dived into those questions I started to get frustrated the answers that I arrived at. I got tired of people asking me “where have you been this whole time” when I knew I had been just quietly treading water, wondering why my videos weren’t being seen, and wondering why I barely saw any creators in the mold of what I wanted to do.

To explore these emotions, I talked to a variety of creators and experts on the nature of YouTube as a media platform the algorithmic systems that govern it, and the greater culture around it. I delved into my own concerns and observations about the landscape of YouTube, especially “left tube”.

This video is my thesis on what challenges I and other black creators face.

00:00 Intro 02:12 How Did I Get Here? 08:22 The Untold History of Breadtube/Lefttube 33:17 No Favors From the Algorithm 1:09:10 Problems in the Community

Creators Featured Voice Memos for the Void - https://www.youtube.com/c/voicememosforthevoid Jordan Harrod- https://www.youtube.com/c/JordanHarrod/videos The Storyteller- https://www.youtube.com/c/TheStorytellerAJ CJ the X- https://www.youtube.com/c/CJTheX Noah Samsen- https://www.youtube.com/c/NoahSamsen khadija Mbowe- https://www.youtube.com/c/KhadijaMbowe T1J- https://www.youtube.com/c/the1janitor Legal Eagle- https://www.youtube.com/c/LegalEagle Hank Green- https://www.youtube.com/c/SciShow

Channels Mentioned Yara Zayd- https://www.youtube.com/c/Yharazayd Kolpeshtheyardstick- https://www.youtube.com/channel/UC2Vj51Kp7qPC102MsA98Fww Victory- https://www.youtube.com/channel/UC8JTStI16odEK-N3JJcMmpw

DJ Trackmatic- https://www.instagram.com/trackmatic_idris/?hl=en https://youtube.com/channel/UCqeWnr-XOv2x8jr2fW72mnA

Resources-

Pewdie Pipeline by Noncompete https://www.youtube.com/watch?v=pnmRYRRDbuw&t=1029s

The Alt Right Playbook series by Innuendo Studios https://www.youtube.com/watch?v=4xGawJIseNY&list=PLJA_jUddXvY7v0VkYRbANnTnzkA_HMFtQ

Not So Awesome (channel awesome fall out documentary) https://www.youtube.com/watch?v=FvedKSaHCBQ

Implicit Bias Primer- https://www.simplypsychology.org/implicit-bias.html

Implicit Bias Association Harvard Study- https://implicit.harvard.edu/implicit/takeatest.html

From floating ‘3D street art’ to a talking Henri Rousseau painting, Meta’s vision of the future is drained of all imagination When I was a kid, I had a book about the future.

Many years ago, when I was a junior professor at Yale, I cold-called a colleague in the anthropology department for assistance with a project I was working on. I didn’t know anything about the guy; I just selected him because he was young, and therefore, I figured, more likely to agree to talk.

Sometime last week, an editor who semi-ghosted me on an article I wrote several months ago texted me saying she wanted to talk. I didn’t want to talk to her because my mild annoyance had faded to almost nothing and the idea of hearing an apology felt wearying.

I phoned Mick Jackson in LA to discuss THREADS. We also talked about A Guide To Armageddon, and The Day After, plus liquorice and all manner of nuclear horror.