Links Milenu.at & David Röthler

Patreon: https://www.patreon.com/daveshap (Discord via Patreon) Substack: https://daveshap.substack.com/ (Free Mailing List) LinkedIn: https://www.linkedin.com/in/dave-shap-automator/ GitHub: https://github.com/daveshap IMF AGI Preparation https://www.imf.org/en/Publications/fandd/issues/2023/12/Scenario-Planning-for-an-AGI-future-Anton-korinek Anton Korinek Fellow, Brookings Institute Professor, UVA Former, Johns Hopkins, IMF Frontier of Automation - Task complexity of machines increases over time Unbounded Distribution - Human task complexity can go up indefinitely, meaning that some people will always be ahead of AGI and ASI Bounded Distribution - Humans have a maximum task complexity (Theory of General Relativity) Outlines 3 Scenarios 1. Business as Usual - All current trends continue without the frontier of automation continuing 2. 20 Year Baseline - AGI's frontier of automation subsumes most/all human abilities within about 20 years 3. 5 Year Aggressive - AGI's frontier of automation subsumes most/all human abilities within 5 years (more likely) Wages vs Output 1. Business as Usual - Wages and output continue to grow more or less correlated for the foreseeable future 2. 20 Year Baseline - Productivity (output) accelerates, but wages peak by about 10 years and then collapse to zero or near zero 3. 5 Year Aggressive - Same, but the parabolic curve is steeper (more likely IMHO) Persistent Jobs - Nostalgiac Jobs - Human preference for humans (such as politicians and religious positions) - Experience Jobs - Tour guides, sex workers, performing artists - Care Jobs - Child care, massage therapy, nurses

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Studierende und Lehrende der Hochschule München (HM) und der HAWK Hildesheim erhalten lizenzierten Zugang zu ChatGPT.

Prof. Christian Spannagel über Künstliche Intelligenz und deren Auswirkung auf das Lernen und die Lehre. Generative KI wie ChatGPT oder Google Bard stellen d...

Labs.Google is Google’s home for the latest AI tools, technology and discourse.

KI oder "Künstliche Intelligenz" begegnet uns schon seit einiger Zeit in vielen Lebenslagen: etwa beim Navi, bei der Datensuche im Netz oder beim Formulieren der Ansprache für das nächste Familienfest. Auch im Journalismus wird längst auf diese neuen Möglichkeiten zurückgegriffen - und vor den Risiken gewarnt. Das war das Thema des ostbelgischen Medientages, zu dem […]

Künstlich generierte Videos können die Reputation von Politiker*innen gefährden. Wie einfach das geht, zeigt eine Forscherin aus Innsbruck.

David Röthler ist Berater, Erwachsenenbildner und Dozent an den Universitäten Salzburg und Klagenfurt. Er ist Gründer der Community of Practice #denkbar zur Vernetzung und zum Austausch für KI-Interessierte (milenu.at/denkbar. Weblog: david.roethler.at).

A candidate in a competitive Pennsylvania congressional race is using “Ashley,” an AI campaign volunteer, stretching the bounds of how technology shapes retail politics.

Die EU will künstliche Intelligenz per Gesetz regulieren. Nach mehrtägigen Verhandlungen einigten sich EU-Staaten und das Europäische Parlament auf den "AI Act".

Aus bereits veröffentlichten Beiträgen erzeugt ChatGPT Texte. Anschließend prüfen und redigieren die Newsletter-Autoren, was die KI generiert hat. Der Vorteil: Eine enorme Zeitersparnis.

Björn Ommer hat das berühmte KI-Bildprogramm Stable Diffusion erfunden, jetzt fordert der Informatiker mehr KIs für die Hosentasche.

Audiobox is Meta's new foundation research model for audio generation. It can generate voices and sound effects using a combination of voice inputs and natural language text prompts.

Documentation for LocalAI

Discover the best ChatGPT GPTs at GPTStore.AI

The realm of artificial intelligence (AI) continues to rapidly evolve, with large language models like ChatGPT demonstrating eerily…

M3 Max is a Machine Learning BEAST. So I took it for a spin with some LLM's running locally. Temperature/fan on your Mac: https://www.tunabellysoftware.com/tgpro/index.php?fpr=alex (affiliate link) Run Windows on a Mac: https://prf.hn/click/camref:1100libNI (affiliate) Use COUPON: ZISKIND20 🛒 Gear Links 🛒 * 🍏💥 New MacBook Air M1 Deal: https://amzn.to/3S59ID8 * 💻🔄 Renewed MacBook Air M1 Deal: https://amzn.to/45K1Gmk * 🎧⚡ Great 40Gbps T4 enclosure: https://amzn.to/3JNwBGW * 🛠️🚀 My nvme ssd: https://amzn.to/3YLEySo * 📦🎮 My gear: https://www.amazon.com/shop/alexziskind 🎥 Related Videos 🎥 * 🌗 RAM torture test on Mac - https://youtu.be/l3zIwPgan7M * 🛠️ Set up Conda on Mac - https://youtu.be/2Acht_5_HTo * 👨‍💻 15" MacBook Air | developer's dream - https://youtu.be/A1IOZUCTOkM * 🤖 INSANE Machine Learning on Neural Engine - https://youtu.be/Y2FOUg_jo7k * 💻 M2 MacBook Air and temps - https://youtu.be/R7F-TxEukdY * 💰 This is what spending more on a MacBook Pro gets you - https://youtu.be/iLHrYuQjKPU * 🛠️ Developer productivity Playlist - https://www.youtube.com/playlist?list=PLPwbI_iIX3aQCRdFGM7j4TY_7STfv2aXX Timestamps 00:00 Intro 00:40 Build from scratch - manual 09:44 Bonus script - automated 11:21 LM Studio - one handed Repo https://github.com/ggerganov/llama.cpp/ Commands //assuming you already have a conda environment set up, and dev tools installed (see videos above for instructions) *Part 1 - manual* brew install git-lfs git lfs install git clone https://github.com/ggerganov/llama.cpp cd llama.cpp pip install -r requirements.txt make git clone https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B openhermes-7b-v2.5 mv openhermes-7b-v2.5 models/ python3 convert.py ./models/openhermes-7b-v2.5 --outfile ./models/openhermes-7b-v2.5/ggml-model-f16.gguf --outtype f16 ./quantize ./models/openhermes-7b-v2.5/ggml-model-f16.gguf ./models/openhermes-7b-v2.5/ggml-model-q8_0.gguf q8_0 ./quantize ./models/openhermes-7b-v2.5/ggml-model-f16.gguf ./models/openhermes-7b-v2.5/ggml-model-q4_k.gguf q4_k ./batched-bench ./models/openhermes-7b-v2.5/ggml-model-f16.gguf 4096 0 99 0 2048 128,512 1,2,3,4 ./server -m models/openhermes-7b-v2.5/ggml-model-q4_k.gguf --port 8888 --host 0.0.0.0 --ctx-size 10240 --parallel 4 -ngl 99 -n 512 *Part 2 - auto* bash -c "$(curl -s https://ggml.ai/server-llm.sh)" 💻 MacBooks in this video M3 Max (16/40) 16" MacBook Pro 64GB/2TB #m3max #macbook #macbookpro — — — — — — — — — 📱LET'S CONNECT ON SOCIAL MEDIA ALEX ON TWITTER: https://twitter.com/digitalix

Deploy Open Source Models on watsonx → https://ibm.biz/BdSaSj Large Language Models (LLMs) can be proprietary to a given company, or open source and free for anyone to access and modify. While proprietary LLMs are often larger, the benefits of transparency, fine-tuning, and community contributions make open source an attractive alternative. Both proprietary and open source LLMs share risks, including inaccuracies, bias, and security concerns. In this video, Master Inventor Martin Keen covers the tradeoffs so you can make an informed decision of which option is best for you.

Mit Civic Coding bündeln wir unsere Kräfte, um eine lebendiges Netzwerk für gemeinwohlorientierte KI anzustoßen.

Open-Source- und Graswurzelbewegungen im Innovationsfeld KI: Sei live dabei beim 3. Civic Coding-Schlaglicht am 06.12.2023 um 16 Uhr!

Study Fetch transforms your powerpoints, class notes, and study guides into flashcards, quizzes, and tests with an AI tutor right by your side.

We’re releasing a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias.

Bringing AI to your desktop 🖥️. Fully encrypted, stored locally, runs on your device.

Read AI launches its Large Meeting Models (LMMs) to expand the context window from a single meeting to thousands of meetings.