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.

Bots are everywhere. From simple algorithms and aggregator bots to complex “artificially” intelligent machine-learning systems, they have become inescapable. Some are in chat programs.

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

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.

You have full access to this article via your institution. An artificial intelligence (AI) system based on Google DeepMind’s AlphaZero AI created algorithms that, when translated into the standard programming language C++, can sort data up to three times as fast as human-generated versions.

A human player has comprehensively defeated a top-ranked AI system at the board game Go, in a surprise reversal of the 2016 computer victory that was seen as a milestone in the rise of artificial intelligence.

A human player has comprehensively defeated a top-ranked AI system at the board game Go, in a surprise reversal of the 2016 computer victory that was seen as a milestone in the rise of artificial intelligence.

A cylinder sits in a room. It is impassive, smooth, simple and small. It stands 14.8cm high, with a single blue-green circular light that traces around its upper rim. It is silently attending. A woman walks into the room, carrying a sleeping child in her arms, and she addresses the cylinder.

As elite distance swimmer Ben Lecomte approached the edge of the Great Pacific Garbage Patch, he started finding more and more of something unexpected — a lot of life.

As elite distance swimmer Ben Lecomte approached the edge of the Great Pacific Garbage Patch, he started finding more and more of something unexpected — a lot of life.

Coury and Try go over what it's like to get started with the MiSTer FPGA project in 2022 - the parts you need, the processes required to set it up, what you need to do to get great audio and video, and what kinds of fun things you can do with the many console, computer, handheld, and arcade cores! You might just see that it isn't nearly as hard as you thought it was!

► Resources

► MiSTer Development & Documentation :: https://github.com/MiSTer-devel :: https://mister-devel.github.io/MkDocs_MiSTer/

► MiSTer Social Resources :: https://misterfpga.org/ :: https://discord.gg/misterfpga

► MiSTer YouTube Resources :: https://www.youtube.com/MiSTerFPGA :: https://www.youtube.com/MiSTerWalrusFPGA :: https://www.youtube.com/VideoGameEsoterica

:: https://www.youtube.com/LusRetroSource

► Chapters 00:00 - Opening 1:55 - Part 1: MiSTer Overview 6:45 - Part 2: Core Focus: Atari Consoles, ColecoVision and other Pre-NES Consoles 12:06 - Part 3: Building your MiSTer 19:26 - Part 4: Core Focus: NES and Super NES 27:38 - Part 5: Setting up the SD Card 33:34 - Part 6: Core Focus: PC-Engine/Turbografx-16 & Neo Geo 44:18 - Part 7: MiSTer OS, Input Options and other Odds 'n Ends 53:51 - Part 8: Universal MiSTer Settings, Editing the .ini File 01:05:16 - Part 9: Core Focus: Sega Master System, Game Gear, Genesis/Mega Drive and Sega CD 01:20:16 - Part 10: MiSTer Audio and Video Settings 01:37:07 - Part 11: Core Preview: MiSTer PlayStation 1 01:43:32 - Part 12: Core Focus: 486 PC, Commodore 64, Amiga, ZX Spectrum, MSX, Sharp X68000 02:10:07 - Part 13: Core Focus: Game Boy / Color, Game Boy Advance, WonderSwan, Atari Lynx 02:25:25 - Part 14: Core Focus: Capcom CPS-1 & CPS-2, Sega System-16 and more Classic Arcade Games 02:37:02 - Ending

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My Life in Gaming makes documentaries, deep dives into retro console hardware, and more.

IN THE FIRST MONTHS OF QUARANTINE, my apartment became my personal ecosystem. The idiosyncrasies of daily life in isolation—the peculiar sleep hours, the midnight meals on the fire escape, the evening Scrabble ritual—felt entirely specific.

------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

In a new paper, published in Trends in Ecology and Evolution, the team sets out how these insights can be used to forecast the future of ecosystem services such as climate change mitigation, food provisioning and clean water.

We’ve seen our fair share of bizarre VR experiments over the years, but this one might just take the cake.

Horror movies played a huge role in my life and horror classics such as "The Shining," "The Exorcist," and "The Thing." are and likely always will be some of my favorite films of all time. But the horror genre has changed drastically. The plots are formulaic, remakes and reboots are the norm and the scares are dried up.

I'll always be a fan of horror movies, but if you are looking for some severe scares this Halloween, consider checking out a non-horror. A BBC produced Docu-drama from 1984 called, "Threads."

The most realistic and gruesome depiction of nuclear war and the price to be paid afterward are on full display in "Threads." (1984) And there are no shortages of terrifying scares.

With "Threads," (1984) if you know, you know. If you don't know and are on the hunt for scares and a shock to your system, look no further than "Threads" (1984)

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You based the technology on parasitic hookworms. Where did that idea come from? We’ve been trying to deliver drugs through the gastrointestinal tract, and that is a formidable challenge because the gastrointestinal tract has a mucosa – a mucus layer.

Animal immune systems depend on white blood cells called macrophages that devour and engulf invaders.

The term terraforming refers to the transformation of the ecosystems of other planets or satellites to enable them to support Earth-like life.

It sounds like a sci-fi movie, or the weirdest series of Big Brother ever. Eight volunteers wearing snazzy red jumpsuits seal themselves into a hi-tech glasshouse that’s meant to perfectly replicate Earth’s ecosystems.