Lab grown T-Rex Leather made into purse to be sent to auction. Carefully announced April 2nd.Via Reddit

Aphantasia - an interesting variant in human experience (New Yorker archive link) Nick knew that whenever Zeman talked about aphantasia he was at pains to emphasize that it was not a disorder, or even a bad thing... Some people he interviewed were unbothered—there was definitely a range of responses—but others saw it as a curse.Many could remember very little about their lives, and even with the events they did remember they could not muster the feeling of what they'd been like. They knew that some things had made them happy and others had made them sad, but that knowledge was factual—it didn't evoke any emotions in the present.

When I read the very 1st paragraph of this article, I had a series of mini revelations about how my mind works, and perhaps the minds of others. I'd appreciate it if you read it first (just the 1st paragraph), and then came back here to explore with me why I think it was interesting... Thanks for coming back!

So, my question is slightly loaded, because I have what is called 'aphantasia', and reading this paragraph made me wonder whether the way non-aphants think (around 96% of the population) was fairly represented by this writer.

When you pictured the scene, how specific was it? Did the follow-up descriptions the writer gives fairly mirror your own experience?

Because when I read it, I didn't get a visual 'picture' in my head, (there is nothing visual in my head, because I am an aphant) but I did imagine the scene conceptually. The thing is, for me the scene I imagined was absolutely abstracted. It was the idea of a person washing hands at a sink. There was little to no specificity. There was no bathroom or kitchen, circular or square sink in my inner imagination. There was no specific person, man or woman, black or white, no specific way their hands moved, no specific relationship between the redness of the liquid, and what it might be (i.e. blood or paint). I just imagined an abstracted set of related ideas: person, washing hands, sink, red. That was it.

So when the writer goes on to then assume everyone pictured something really specific, that made me wonder: is the abstractness of aphantasic thinking universal? Do aphants always imagine in a kind of realm of Platonic ideals? Do none aphants always picture specific things? How much of the writer's assumption here is fair, given that we ALL sit on the spectrum of mental visual imagination? What are the social implications of these different ways of thinking?

What happened in your mind when you read this paragraph? I am intrigued to know, and where you usually sit on the spectrum of visual imagination.

After unbearable levels of speculation and leaks, Japanese gaming giant Nintendo finally announced the Switch 2 today, surprising nobody. Most of the leaked features were verified by the trailer, but in traditional Nintendo fashion the mysterious 'C' button was rendered blank. What could this little anonymous square be for?

Welcome to the first of what we hope will be many posts about teaching writing in the age of AI! The Important Work is a space for writing instructors at all levels—high school, college, and beyond—to share reflections about teaching writing in the era of generative AI.

Documenting our lives for Snapchat and Instagram can decrease the likelihood of retaining those moments as a significant memory. This story appears in VICE Magazine's Truth and Lies Issue. Click HERE to subscribe.

Neuroscience research into people with aphantasia, who don’t experience mental imagery, is revealing how imagination works and demonstrating the sweeping variety in our subjective experiences. Introduction Two years ago, Sarah Shomstein realized she didn’t have a mind’s eye.

Doomsaying can become a self-fulfilling prophecy. Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

The term Luddite is usually used as an insult. It suggests someone who is backward-looking, averse to progress, afraid of new technology, and frankly, not that bright. But Brian Merchant claims that that is not who the Luddites were at all.

The video site isn’t just a platform. It’s infrastructure. Produced by ElevenLabs and NOA, News Over Audio, using AI narration.

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?

“Men have to toughen up,” Jordan B. Peterson writes in 12 Rules For Life: An Antidote to Chaos, “Men demand it, and women want it.” So, the first rule is, “Stand up straight with your shoulders back” and don’t forget to “clean your room.

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.

Of all the buzzy 21st-century tech phrases, “machine learning” threatens to be the most important. Programming computers is slow, but we’re nearing the point where humans give the bots parameters and let them teach themselves.

It has long been claimed that pornography drives technology. This claim is over-stated, no doubt, but what’s clear is that pornography very quickly and cleverly takes advantage of new communication technologies.

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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Produced by Rob Sutton and Bobby Fingers.

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Big thanks to L. Sierakowski for the use of his beautiful music. https://furniture-music.bandcamp.com

Thanks to Esref Akinci, Ossman Yetkin and Dr. Nihat Cicek at Holiday Estetic https://holidayestetic.com/

Amazon march footage courtesy of Shabbir Lakha/Rank and FIle Combine https://www.instagram.com/shabbirlakha/ CHECK HIM OUT!!!! AMAZING PERSON!!!

Director of Photography - Shane Serrano - https://www.shaneserrano.com/

Additional Camera work by Rob Sutton https://www.instagram.com/rob.sutton/ Clem McInerney (Water Cinematography) https://clemmcinerney.com/ Shane Joyce https://www.instagram.com/shanej0yce/ Alex Genn-Bash https://www.instagram.com/shuttermug/ Berke Beyazpınar https://www.instagram.com/berkebeyazpinar/ Emma McNamara https://www.instagram.com/rc86maker/ Jason Flood (whats your social Jason?)

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Sound Recordist - Eoin Gleeson https://www.instagram.com/eoingleeson/

Visual Effects by Ray Sullivan https://www.instagram.com/directedbyray/

Additional editing by Rob Sutton and Nathan Campion https://www.instagram.com/nathanthecampionoftheworld/

Makeup by Sadhbh Nic Uidhir https://www.instagram.com/sadhbhniqueer/ Clodagh McInerney

Costumes by Gerdi McGlynn Pamela McGlynn Grace Burke Sarah Allen

Jet Ski Operator - James Monaghan

The Pirates were played by Jean McGlynn Michael O'Donoghue Mike Finnernanan Martin Cooke Nhlanhla Banda Cein Daly Shane Davis Luke McEvoy Isaac Bryant Cian Egan Matt Kelly Darren O'Carroll Tobi Omoteso Conor McNelis Robert Walsh

Special thanks to Shirani Bolle, Díní McGlynn, Romee Mcglynn, Antoinette Bolle, Wayne Cuddy, Dominic Yard http://www.thisisyard.com/ Ali Day, Rebecca Ní Churnáin, Mick Dolan and all the gang at Dolans, Rebecca Pearson, Bec Hill, Matt Parker, Dr. Billy Fingers, Gary MacMahon, Brian O'Brien, Mike Hogan, Bono Kavanagh, Emma Tierney, Steve Lock and the gang at Soho theatre, Conor O'Brien, Laura Davoren, Paul Ryan from Film In Limerick, Keelan Christie, Mary Gallagher Cooke, Brendan Kennedy from Panda.ie. Thanks to John and all the lads in Mungret Civic Ameneties, Elle Coughlan, Alan Ward and the guys in the National 50m Pool in UL.

If I've forgotten anyone, please let me know, I can add your name in here very easily.

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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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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.