Join Mark Russinovich & Scott Hanselman to explore the landscape of generative AI security, focusing on large language models. They cover the three primary risks in LLMs: Hallucination, indirect prompt injection and jailbreaks (or direct prompt injection). We'll explore each of these three key risks in depth, examining their origins, potential impacts, and strategies for mitigation and how to work towards harnessing the immense potential of LLMs while responsibly managing their inherent risks.

Demystifying attention, the key mechanism inside transformers and LLMs. Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support Special thanks to these supporters: https://www.3blue1brown.com/lessons/attention#thanks An equally valuable form of support is to simply share the videos. Demystifying self-attention, multiple heads, and cross-attention. Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support The first pass for the translated subtitles here is machine-generated, and therefore notably imperfect. To contribute edits or fixes, visit https://translate.3blue1brown.com/ And yes, at 22:00 (and elsewhere), "breaks" is a typo. ------------------ Here are a few other relevant resources Build a GPT from scratch, by Andrej Karpathy https://youtu.be/kCc8FmEb1nY If you want a conceptual understanding of language models from the ground up, @vcubingx just started a short series of videos on the topic: https://youtu.be/1il-s4mgNdI?si=XaVxj6bsdy3VkgEX If you're interested in the herculean task of interpreting what these large networks might actually be doing, the Transformer Circuits posts by Anthropic are great. In particular, it was only after reading one of these that I started thinking of the combination of the value and output matrices as being a combined low-rank map from the embedding space to itself, which, at least in my mind, made things much clearer than other sources. https://transformer-circuits.pub/2021/framework/index.html Site with exercises related to ML programming and GPTs https://www.gptandchill.ai/codingproblems History of language models by Brit Cruise,  @ArtOfTheProblem  https://youtu.be/OFS90-FX6pg An early paper on how directions in embedding spaces have meaning: https://arxiv.org/pdf/1301.3781.pdf ------------------ Timestamps: 0:00 - Recap on embeddings 1:39 - Motivating examples 4:29 - The attention pattern 11:08 - Masking 12:42 - Context size 13:10 - Values 15:44 - Counting parameters 18:21 - Cross-attention 19:19 - Multiple heads 22:16 - The output matrix 23:19 - Going deeper 24:54 - Ending ------------------ These animations are largely made using a custom Python library, manim. See the FAQ comments here: https://3b1b.co/faq#manim https://github.com/3b1b/manim https://github.com/ManimCommunity/manim/ All code for specific videos is visible here: https://github.com/3b1b/videos/ The music is by Vincent Rubinetti. https://www.vincentrubinetti.com https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. If you're reading the bottom of a video description, I'm guessing you're more interested than the average viewer in lessons here. It would mean a lot to me if you chose to stay up to date on new ones, either by subscribing here on YouTube or otherwise following on whichever platform below you check most regularly. Mailing list: https://3blue1brown.substack.com Twitter: https://twitter.com/3blue1brown Instagram: https://www.instagram.com/3blue1brown Reddit: https://www.reddit.com/r/3blue1brown Facebook: https://www.facebook.com/3blue1brown Patreon: https://patreon.com/3blue1brown Website: https://www.3blue1brown.com

Andrew Ross Sorkin speaks with Microsoft AI CEO Mustafa Suleyman at the Aspen Ideas Festival.

ChatGPT - na logisch, oder?: Eine Keynote von Katharina Zweig auf dem University:Future Festival 2024.In Ihrem Vortrag diskutiert Professorin Zweig die Frage...

Attached: 1 video Asking AI to make a hit country song. #netzfund Es ist famos :)

Attached: 1 video

There are 100 billion individual neurons in the human brain. Working together, they allow us to make sense of, and move through, the world around us. Scientists have built replicas of the human brain with computers, but no one has ever successfully made a brain out of humans. On this episode, I’ll travel back to my hometown of Stilwell, Kansas, and turn it into a working brain!Available with YouTube Premium - https://www.youtube.com/premium/originals. To see if Premium is available in your country, click here: https://goo.gl/A3HtfP