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?

Top highlightThe New Self-HelpThe Only Way to Resist the Attention EconomyQuitting Facebook isn’t the answerWe live in an age where there are many systemic abuses that should be refused. I propose that one great place to start is the abuse of our attention.

When I was nine or ten years old, my grandmother gave me a book full of so many random, interesting facts and tidbits of science and history I sometimes think it’s the secret source of all my adult obsessions.

Aside from the physical heft of data centers seen from highways and the fiber optic cables crawling into homes and offices, the digital world mostly exists in our imagination. That imagination is shaped by the people selling services that rely on that infrastructure.

To my own shame, I have become a jaded reader in recent years. By this I mean that my enthusiasm and curiosity, my drive to experience new worlds, have all been damaged by a persistent disjunct between reality and the speculative fiction I most enjoy.

I don't think Nvidia CEO Jensen Huang is a bad guy, or that he has nefarious plans for Nvidia, but the most consequential villains in history are rarely evil. They just go down a terribly wrong path, and end up leaving totally forseeable, but ultimately inevitable ruin in their wake.

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.

They see facial recognition, smart diapers, and surveillance devices as inevitable evolutions. They’re not. Imagine you’re taking an online business class — the kind where you watch video lectures and then answer questions at the end.

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

consider joining my channel as a YouTube member: https://www.youtube.com/channel/UCotwjyJnb-4KW7bmsOoLfkg/join

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.

But even after I overcame my instinct for detachment, I remained wary of the movement’s language, which was a language of binaries: women and men.

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

Start exploring the riches of cinema with an extended free trial at https://mubi.com/likestoriesofold

Help me make more videos! Support this channel: https://www.patreon.com/LikeStoriesofOld Leave a One-Time Donation: https://www.paypal.me/TomvanderLinden

Facebook: https://www.facebook.com/LikeStoriesofOld Instagram: https://www.instagram.com/tom.vd.linden Twitter: https://twitter.com/Tom_LSOO

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

Business inquiries: lsoo@standard.tv
Say hi: likestoriesofold@gmail.com

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

Take your films to the next level with music from Musicbed. Sign up for a free account to listen for yourself: https://fm.pxf.io/c/3532571/1347628/16252

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

Subscribe To "The Late Show" Channel: http://bit.ly/ColbertYouTube

Watch full episodes of "The Late Show": http://bit.ly/1Puei40 Listen to "The Late Show Pod Show" podcast: https://link.chtbl.com/Awagtx95?sid=yt Like "The Late Show" on Facebook: http://on.fb.me/1df139Y Follow "The Late Show" on X: http://bit.ly/1dMzZzG Follow "The Late Show" on Instagram: http://bit.ly/29wfREj

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.

Scientists are planning to solve one of the world’s greatest archaeological mysteries.

A video about neural networks, function approximation, machine learning, and mathematical building blocks. Dennis Nedry did nothing wrong. This is a submission for #SoME3

My Links Patreon: https://www.patreon.com/emergentgarden Discord: https://discord.gg/ZsrAAByEnr

Links and Content: On Mathematical Maturity, Thomas Garrity: https://www.youtube.com/watch?v=zHU1xH6Ogs4 Earth Rotation Loop: https://www.youtube.com/watch?v=aiQdLP2mBJE Modeling Shell Surfaces: https://www.geogebra.org/m/xtv7zpn5 Fourier Features Paper: https://arxiv.org/abs/2006.10739 Code for mandelbrot/image approximations: https://github.com/MaxRobinsonTheGreat/mandelbrotnn Code for line/surface approximations: https://github.com/MaxRobinsonTheGreat/ManimApproximations

Music: https://youtube.com/@acolyte-compositions

Timestamps (0:00) Functions Describe the World (3:15) Neural Architecture (5:35) Higher Dimensions (11:55) Taylor Series (15:20) Fourier Series (21:25) The Real World (24:32) An Open Challenge

Responding to the 1 millionth time that people have said "the left has failed men" and somehow... kinda agreeing with Shoe on Head

2:00 Y'all are overreacting to that table 7:40 The Manosphere isn't new it's just more visible 11:08 Algorithms make this an uphill battle 15:14 The online left does have a weak analysis of masculinity 17:57 Stop whining about mean feminist and do the work 19:40 The real problems facing men

Classic debunks of various manosphere topics MuneCat debunks the manosphere - https://www.youtube.com/watch?v=BgO25FTwfRI&pp=ygUHbXVuZWNhdA%3D%3D My Black Manosphere video - https://www.youtube.com/watch?v=upt_ks61_70&t=1466s&pp=ygUQYmxhY2sgbWFub3NwaGVyZQ%3D%3D Sissyphus trying to make sense of the manosphere - https://www.youtube.com/watch?v=lSq3bcyrJY0&pp=ygUOdGhlIG1hbm9zcGhlcmU%3D Frank Laundry explaining Fresh and Fit - https://www.youtube.com/watch?v=WBsCmYCShqI&pp=ygUbZnJhbmsgbGF1bmRyeSBmcmVzaCBhbmQgZml0 Zatzman on the Manosphere as a content farm - https://www.youtube.com/watch?v=pvZITKjaffw&pp=ygUOdGhlIG1hbm9zcGhlcmU%3D

Other male content creators to check out

@Salari @FinntasticMrFox @ForeignManinaForeignLand @NoahSamsen @Sisyphus55 @TheZatzman @COLORMIND.mp4 @victorythecreator @lilbilliam @ThinkpieceTribe @JawnLouis

Monitoring the future study 2022 - https://monitoringthefuture.org/wp-content/uploads/2022/12/mtf2022.pdf Political ideology data from 2021 - https://monitoringthefuture.org/wp-content/uploads/2023/08/PoliticalBeliefTrends12thGraders1976-2021.xlsx CDC Deaths of despair study - https://www.cdc.gov/surveillance/blogs-stories/deaths-of-dispair.html Meta study mentioned - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566538/

Peter Bauman (Monk Antony) develops a framework for appreciating and analyzing generative art through an investigation of the movement’s locus of artistic intent.

Late one recent night, I enlisted GPT-4 to fix my life. I began by soliciting broad-strokes summaries of my journalistic interests and an expedited five-step protocol for breaking in raw-denim jeans (if you know, you know).