ai

KI sei für die Menschheit so revolutionär wie die Nutzbarmachung der Elektrizität – das war das Versprechen. Doch daraus wird nichts, weil das Hauptproblem dieser Technologie ungelöst bleibt.

@ronaldtootall@tech.lgbt @hannu_ikonen@zeroes.ca LLM are not reliable enough to "check facts" this isn't what they are even designed to do well. What they are designed to do is generate plausible seeming streams of text similar to existing sets of text. That is all. There is no logic behind that, no verification. It's pure chance. Do not use them to check facts, please.

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.

Follow us on Twitter @Hackread - Facebook @ /Hackread

OpenAI’s founder is asking Washington to spend hundreds of billions of dollars on new power plants. Society needs to see the benefit, too.

Long-time Slashdot reader Geoffrey.landis writes: Despite its impressive output, a recent study from MIT suggests generative AI doesn't have a coherent understanding of the world. While the best-performing large language models have surprising capabilities that make it seem like the models are impli…

As OpenAI and Meta introduce LLM-driven searchbots, I'd like to once again remind people that neither LLMs nor chatbots are good technology for information access. A thread, with links: Chirag Shah and I wrote about this in two academic papers: 2022: https://dl.acm.org/doi/10.1145/3498366.3505816 2024: https://dl.acm.org/doi/10.1145/3649468 We also have an op-ed from Dec 2022: https://iai.tv/articles/all-knowing-machines-are-a-fantasy-auid-2334

As the debate on public interest AI is still a young and emerging one, we see this special issue as a way to help establish this field and its community by bringing together interdisciplinary positions and approaches.

Es gibt viel Unsicherheit über Datenschutz und Datensicherheit rund um KI-Textgeneratoren wie ChatGPT oder Gemini. Was darf man ihnen anvertrauen? Was soll

Nein! Doch! Oooh! #KI ist teuer und bringt keinen ROI, sagt Gartner??? Gartner sounds alarm on AI cost, data challenges | CX Dive https://www.customerexperiencedive.com/news/gartner-symposium-keynote-AI/731122/

🚑Crazy case yesterday in the ER: fulminant Glianorex infection with REALLY high Neurostabilin levels. Figured I'd ask ChatGPT for help and it honestly would… | 35 comments on LinkedIn

Vortrag von Beat Döbeli Honegger vom 01.02.2024

OpenAI and Microsoft are funding projects to bring more AI tools into the newsroom.

Nach Ansicht von Salesforce-CEO Mark Benioff ist Microsofts KI ein großer Reinfall.

Wobei KI besonders gut helfen kann, ist Muster aus Daten, Texten oder in Bildern oder Videos zu erkennen. Was wiederholt sich, was ergänzt sich, wo ist ein „Bruch“ in einer Folge… Heute 3 Experimente dazu: Experiment 1 – KI Profilbewertung – Was ich nicht weiß Nadja Schwind hat vor ein paar Tagen folgendes Experiment geteilt: […]

Hatdware rack power

Google’s first nuclear energy deal is a step toward helping the world decarbonize through investments in advanced clean energy technologies.

Important new study from Apple

The massive computer clusters powering artificial intelligence consume vast quantities to answer the world’s queries, but how is Big Tech redressing the balance?

In the largest venture-capital-backed investment round of all time, OpenAI has successfully raised $6.6 billion from its most gullible brilliant and handsome friends. This gives OpenAI an imaginary…

Widersprüche im Umgang mit Künstlicher Intelligenz in der Schule

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning - tirthajyoti/Papers-Literature-ML-DL-RL-AI

"Let me get this straight," he said. "You're hosting a 'future of AI' event in a city that has failed humanity so miserably?"

Silicon Valley is helping to accelerate the climate crisis in at least 3 major ways

Eryk Salvaggio says we must dispense with myths if we are to think more clearly about what AI actually is and does.

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

Did you know you can play Doom on a diffusion model now? It’s true, Google just announced it! Just don’t read the paper too closely. In their paper “Diffusion models are real-time game engines,” Go…