AI/ML

In this video, I look at the release of the new Gemma 3 models, which come in four different flavors: a 1B, a 4B, a 12B, and the new Big 27B parameter model. Demo: https://huggingface.co/spaces/huggingface-projects/gemma-3-12b-it Blog: https://blog.google/technology/developers/gemma-3/?linkId=sam_witteveen Model Weights: https://huggingface.co/collections/google/gemma-3-release-67c6c6f89c4f76621268bb6d For more tutorials on using LLMs and building agents, check out my Patreon Patreon: https://www.patreon.com/SamWitteveen Twitter: https://x.com/Sam_Witteveen 🕵️ Interested in building LLM Agents? Fill out the form below Building LLM Agents Form: https://drp.li/dIMes 👨‍💻Github: https://github.com/samwit/llm-tutorials ⏱️Time Stamps:

This isn't really a "timeline", as such – I don't know the timings – but this is my current, fairly optimistic take on where we're heading. …

How to back up, downgrade, and restore Ollama on macOS without losing models or data

This article provides an in-depth exploration of the DeepSeek-R1 model architecture. Let’s trace DeepSeek-R1 model from input to the output…

In this video, I look at the latest release from Mistral AI, which is their Mistral OCR model. I look at how it works and how it compares to other models, as well as how you can get started using it with code. Colab: https://dripl.ink/Sr4Uk Blog: https://mistral.ai/news/mistral-ocr For more tutorials on using LLMs and building agents, check out my Patreon Patreon: https://www.patreon.com/SamWitteveen Twitter: https://x.com/Sam_Witteveen 🕵️ Interested in building LLM Agents? Fill out the form below Building LLM Agents Form: https://drp.li/dIMes 👨‍💻Github: https://github.com/samwit/llm-tutorials ⏱️Time Stamps: 00:00 Intro 00:17 Other models 00:35 Mistral OCR Blog 05:45 Mistral OCR Demo 13:47 Mistral OCR Batch inference

I'm sure OpenAI's implementation of "deep research" is great, but I can't afford that. Ai2’s ScholarQA tool is FREE and open source!! Allen AI’s Scholar QA: https://scholarqa.allen.ai/ Please Like and Subscribe to support the channel! @LearnMetaAnalysis Access state of the art LLMs all in one place with ChatLLM – My 3 month review of ChatLLM: https://youtu.be/_Z3nLKvTbGc Tutorials and how-to guides: Connect a LLM to your Zotero (or any other local folder): https://youtu.be/b2BSZfOtD_w Conventional meta-analysis: https://www.youtube.com/playlist?list=PLXa5cTEormkEbYpBIgikgE0y9QR7QIgzs Three-level meta-analysis: https://www.youtube.com/playlist?list=PLXa5cTEormkHwRmu_TJXa7fSb6-WBXXoJ Three-level meta-analysis with correlated and hierarchical effects and robust variance estimation: https://www.youtube.com/playlist?list=PLXa5cTEormkEGenfcnp9X5dQUhmm7f9Jp Want free point and click (no coding required) meta-analysis software? Check out Simple Meta-Analysis: https://learnmeta-analysis.com/pages/simple-meta-analysis-software Tired of manually extracting data for systematic review and meta-analysis? Check out AI-Assisted Data Extraction, a free package for R! https://youtu.be/HuWXbe7hgFc Free ebook on meta-analysis in R (no download required): https://noah-schroeder.github.io/reviewbook/ Visit our website at https://learnmeta-analysis.com/ 0:00 OpenAI’s Deep Research 0:36 ScholarQA 1:26 First Test 11:49 Second Test 21:15 Debrief

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Local LLM inference speed tests on various devices - itsmostafa/inference-speed-tests

I currently own a MacBook M1 Pro (32GB RAM, 16-core GPU) and now a maxed-out MacBook M4 Max (128GB RAM, 40-core GPU) and ran some inference speed...

Deep Research is the title of a new mode in several GenAI apps, including Google’s Gemini, OpenAI’s ChatGPT, and most recently, Perplexity. In this article, I will be focusing on the currently most hyped of these: OpenAI’s Deep Research. Although they weren’t first to release a product with this title (that was Google), they have […]

Implements harmful/harmless refusal removal using pure HF Transformers - Sumandora/remove-refusals-with-transformers

Granite Snack Cookbook -- easily consumable recipes (python notebooks) that showcase the capabilities of the Granite models - ibm-granite-community/granite-snack-cookbook

Discover how DeepSeek's DeepSeek-R1 and Anthropic's Claude 3.5 Sonnet (new) stack up in performance, features, and applications. Read our detailed comparison to find out which AI model best suits your needs.

R1+Sonnet has set a new SOTA on the aider polyglot benchmark. At 14X less cost compared to o1.

aider is AI pair programming in your terminal. Contribute to Aider-AI/aider development by creating an account on GitHub.

I’m a big fan of Claude Sonnet. I’m ashamed to admit, it’s mostly vibes based. It’s friendlier and writes code in a way that I like. The…

Quantitative benchmarks of LLM code editing skill.

Results from Wolfram's ongoing tracking of LLM performance. The benchmark is based on a Wolfram Language code generation task.

Kagi Search Help

In this video, I look at olmOCR, the OpenOCR system from Allen AI. Colab: https://dripl.ink/HpaK4 Blog: https://olmocr.allenai.org/blog macOS ver: https://jonathansoma.com/words/olmocr-on-macos-with-lm-studio.html For more tutorials on using LLMs and building agents, check out my Patreon Patreon: https://www.patreon.com/SamWitteveen Twitter: https://x.com/Sam_Witteveen 🕵️ Interested in building LLM Agents? Fill out the form below Building LLM Agents Form: https://drp.li/dIMes 👨‍💻Github: https://github.com/samwit/llm-tutorials ⏱️Time Stamps: 00:00 Intro 00:31 Allen AI Blog 01:20 olmOCR Blog 02:08 olmOCR Hugging Face 04:52 olmOCR GitHub 05:41 Demo 05:59 Running olmOCR on macOS with LM Studio

Learn how to have your own locally hostedl OpenAI Deep Research-like service in Msty

LLM 0.23 is out today, and the signature feature is support for schemas—a new way of providing structured output from a model that matches a specification provided by the user. …

For some time, I’ve argued that a common conception of AI is misguided. This is the idea that AI systems like large language and vision models are individual intelligent agents, analogous to human agents. Instead, I’ve argued that these models are “cultural technologies” like writing, print, pictures, libraries, internet search engines, and Wikipedia.

Hello and welcome to my new blog post. Today I am going to discuss a future threat which is invisible. With greater power comes greater…

Converts ASCII Prompts to Unicode Generating “Invisible” Prompts - Unighost_Prompt_Injection.py

Learn about invisible prompt injection, which is a silent threat to secure AI.

Payloads All The Things, a list of useful payloads and bypasses for Web Application Security