Large language models like those offered by OpenAI and Google famously require vast troves of training data to work. The latest versions of these models have already scoured much of the existing internet which has led some to fear there may not be enough new data left to train future iterations.

It’s no easy task, but developing your tone of voice can build trust, reduce conflict, and set the stage for more learning in your classroom, research shows. Using your voice to manage a classroom is one of the most powerful tools at your disposal.

Do you like Star Wars lore? Exactly how much do you like Star Wars lore? I ask because A Very Brief Analysis: The Phantom Menace is 12 hours long and is chock full of Star Wars lore. "This is not a defence of Episode 1, nor is it an attack. The idea is a detailed, fair, and informed analysis. We'll go over the entire movie, giving credit and blame as needed."

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?

For as long as I can remember, I’ve desired romantic relationships with boys, and then as I got older, men. Also for as long as I can remember, I’ve had sexual fantasies exclusively about girls, and then as I got older, women.

For a manifesto to succeed, it must speak to our hearts like a poem while infecting the mind with images and ideas that are dazzlingly new.

What Are You Watching? is a weekly space for The A.V Club’s staff and readers to share their thoughts, observations, and opinions on film and TV.  It’s common for viewers first coming to the work of the late Polish director Andrzej Żuławski to find it both wildly undisciplined and inspired.

And a chatbot is not a human. And a linguist named Emily M. Bender is very worried what will happen when we forget this. This article was featured in One Great Story, New York’s reading recommendation newsletter. Sign up here to get it nightly. Nobody likes an I-told-you-so.

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

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About this video essay: We've all felt it: the movies have changed. But how so exactly, and why? And what can be done about it? In this extensive critique, I try to capture the decline of modern cinema in one unifying theory.

00:00 The Marvelization of Cinema 01:52 What is Storytelling Entropy? 06:26 Hollow Franchises 11:15 Meta-References to Nowhere 17:40 Corporate Passion 25:23 Breaking the Cycle 33:08 Meaningful Engagement

Further Reading: Like Stories of Old – The Complete Reading List: https://kit.co/likestoriesofold/reading-list 10 Books that changed my life: https://kit.co/likestoriesofold/10-books-that-changed-my-life 10 More books that inspired my thinking: https://kit.co/likestoriesofold/10-more-books-that-inspired-my-thinking

My Camera Gear: https://kit.co/likestoriesofold/my-travel-camera-gear

Media included: 12 Angry Men; 2001 A Space Odyssey; A Good Day to Die Hard; A Hidden Life; Aftersun; Ahsoka; Alien; Alien vs. Predator; Aliens; Ant-Man and the Wasp Quantumania; Asteroid City; Avengers Age of Ultron; Avengers Endgame; Avengers Infinity War; Babylon; Barbie; Batman Begins; Batman v Superman; Blade Runner 2049; Captain America Civil War; Captain America The First Avenger; Captain America The Winter Soldier; Citadel; Deadpool; Decision to Leave; Die Hard; Doctor Strange in the Multiverse of Madness; Dune; Dungeons and Dragons; Eternals; Foundation; Fast X; Free Guy; Game of Thrones; Ghostbusters Afterlife; Ghosted; Gladiator; Godzilla; Godzilla vs Kong; Goodfellas; Inception; Indiana Jones and the Dial of Destiny; Invasion of the Body Snatchers; Iron Man 3; Iron Man; John Wick Chapter 3 & 4; Jurassic Park; Jurassic World; Jurassic World Dominion; Lawrence of Arabia; Loki; Mission Impossible 1, 2, Fallout, Rogue Nation & Dead Reckoning; Moon Knight, Obi-Wan Kenobi; Ocean's Eleven; Once Upon a Time in Hollywood; Past Lives; Predator 1 & 2; Red Notice; Secret Invasion; Seven Samurai; Shang-Chi; She-Hulk; Spiderman 1 & 2; Spider-Man No Way Home; Star Wars A New Hope, The Empire Strikes Back, Return of the Jedi, The Phantom Menace, The Revenge of the Sith, The Force Awakens, The Last Jedi & the Rise of Skywalker; Synecdoche New York; Terminator 1, 2 & Dark Fate; The Dark Knight, The Amazing Spider-Man 2; The Avengers; The Fabelmans; The Falcon and the Winter Soldier; The Flash; The Godfather 1 & 2; The Gray Man; The Hobbit Trilogy; The Lord of the Rings Trilogy; The Rings of Power; The Matrix 1 & 4; The Mummy; The Prestige; The Thing; The Witcher; Thor Love and Thunder; Thor Ragnarok; Thor The Dark World; Top Gun; Top Gun Maverick; Transformers Rise of the Beasts; Uncharted

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Music: Dexter Britain - Hoursglass Jo Blankenburg - Dirt Dexter Britain - Your Own World Alaskan Tapes - Swimming and Dancing and Floating in Circles Dexter Britain - Headspace Cultus - Between Mountains Dexter Britain - Air Dexter Britain - Raising

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E se Super Mario Bros. Wonder fosse um jogo NES de 1988?

Esse foi um projeto muito audacioso, pois além do 3D e do 2D, tive que fazer toda a pixel art do suposto jogo de NES!

Muitos dos gráficos que aparecem no gameplay eu consegui graças ao site https://www.spriters-resource.com

Também fiz a narração (peço desculpas).

No comercial é possível ver um "Wario" de capa correndo do Toad carregando um cogumelo. Esse "Wario" é uma homenagem ao Alexsandro Magalhães dos canais @cedjogos e @AlexsandroMagalhaes

Eu espero que você tenha gostado!

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When King George III of England began to show signs of acute mania toward the end of his reign, rumors about the royal madness multiplied quickly in the public mind. One legend had it that George tried to shake hands with a tree, believing it to be the King of Prussia.

The bartender pouring free drinks glances around with nothing to do as the raucous room full of startup founders and software developers gravitates toward its preferred drug: networking.

The system was as predictable as it was brutal. It was at Haileybury, caught between the indignities of space and the pressures of time, that Christopher Nolan realised he was going to die. Everyone knew the pecking order at Haileybury and Imperial Service College.

Ok this is kind of incredible: Brick Technology built a solar-powered Lego clock that will keep time for a billion years.

Remember when “epic bacon” was the height of comedy? Thirteen years ago, a man was sitting at the Denver airport. Bored, he turned his attention to his favorite website: “I see a lot of people on laptops around using the free wifi,” he wrote on the popular subreddit r/AskReddit.

From dragging steamboats over mountains, to holding Klaus Kinski at gunpoint, Herzog’s career has been guided by a quest for ‘ecstatic truth’, explored in a new exhibition at Amsterdam’s EYE Filmmuseum These interviews act as funny asides, embracing intense outsider figures the way Herzog al

Trine Freiesleben and Jean-Claude discussing the fingerprints and where to take OSL samples. Credit: Kristina Thomsen, CC-BY 4.0 (creativecommons.org/licenses/by/4.

Workers hired via crowdsource services like Amazon Mechanical Turk are using large language models to complete their tasks – which could have negative knock-on effects on AI models in the future. Data is critical to AI.

Guardian: 'The annual CGC (Crap Games Competition) has been bringing Spectrum fans together for more than 25 years' ... "What makes the CGC entertaining is the self-deprecating, sardonic British humour," explains 43-year-old Paul Collins from Reading, who first entered the CGC in 2000 with Pear-Shaped ("a simple maze game where you try to collect as many pears as possible") and Crap Football, featuring a digitised Des Lynam. "There are ideas that can't possibly work, eg Sim City: The Text Adventure or Blind Flight Simulator. Or names that are just funny, like Whack a Nun II and European Sandwich Hunt."