A lego-like kit that depicts the Chernobyl reactor facility before and after it melted down in 1986.

Information about the various models of RasPi.

Phineas Gage became the center of a landmark neuroscience case when an explosion forced a red-hot tamping iron through this railroad foreman’s brain and skull. He survived, but reportedly suffered a personality change. This was the first evidence suggesting that the frontal lobe of the brain was linked to one’s personality. A more complete story is hosted at the website of the Warren Anatomical Museum at Harvard Medical School, which happens to be the current home of the original skull.

This work is a derivative of the CT scan made of the Phineas Gage Skull as discussed in The Tale of Phineas Gage, digitally remastered (Ratiu, P et. al., 2004), and is being shared with the kind permission of the Warren Anatomical Museum at Harvard Medical School’s Countway Library.

This model is also being shared at Thingiverse: http://www.thingiverse.com/thing:1417528

This framework provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks. Text is embedded in vector space such that similar text are closer and can efficiently be found using cosine similarity. We provide an increasing number of state-of-the-art pretrained models for more than 100 languages, fine-tuned for various use-cases. Further, this framework allows an easy fine-tuning of custom embeddings models, to achieve maximal performance on your specific task. CUDA enabled.

Seems to lend itself to research coding. The real winner here is that you can generate embeddings and vectors for arbitrary text, which would make it ideal for writing a utility that could do only this without a lot of heavy lifting.

Comes with pre-trained models for over 100 languages. Has documentation and examples for building your own models.

MEALPY is the largest python library in the world for most of the cutting-edge meta-heuristic algorithms (nature-inspired algorithms, black-box optimization, global search optimizers, iterative learning algorithms, continuous optimization, derivative free optimization, gradient free optimization, zeroth order optimization, stochastic search optimization, random search optimization). These algorithms belong to population-based algorithms (PMA), which are the most popular algorithms in the field of approximate optimization.

This repository is intended as a minimal, hackable and readable example to load LLaMA (arXiv) models and run inference by using only CPU. Thus requires no videocard, but 64 (better 128 Gb) of RAM and modern processor is required. Make sure you have enough swap space (128Gb should be ok :).

OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots for various applications. The kit includes an instruction-tuned 20 billion parameter language model, a 6 billion parameter moderation model, and an extensible retrieval system for including up-to-date responses from custom repositories. It was trained on the OIG-43M training dataset, which was a collaboration between Together, LAION, and Ontocord.ai. Much more than a model release, this is the beginning of an open source project. We are releasing a set of tools and processes for ongoing improvement with community contributions.

Includes pre-trained network weights.

A curated list of modern Generative Artificial Intelligence projects and services.

For something in between a pytorch and a karpathy/micrograd. This may not be the best deep learning framework, but it is a deep learning framework. Due to its extreme simplicity (<= 1000 lines of code), it aims to be the easiest framework to add new accelerators to, with support for both inference and training. Support basic ops and you get SOTA vision and language models.

Threat models and tools for staying safe, private and informed while Online, used by the average person.

EleutherAI is a grassroots AI research group aimed at democratizing and open sourcing AI research. Multiple projects and usable training corpora. F/OSS model called GPT-Neo.

Several spinoff projects to investigate.

Awesome list about all kinds of interesting topics: Laws, Principles, Mental Models, Cognitive Biases, and more.

spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. spaCy comes with pre-trained statistical models and word vectors, and currently supports tokenization for 45+ languages. It features the fastest syntactic parser in the world, convolutional neural network models for tagging, parsing and named entity recognition and easy deep learning integration. It's commercial open-source software, released under the MIT license.

Following the Terms of Service change at Thingiverse, archive.org downloaded the whole bloody thing and put it online. The tarball's 81 gigabytes in size, so I hope you've got some disk space...

CADquery aims to be to 3D modeling what jQuery is to Javascript, i.e., making the construction of parametric models simpler. Provides an open, plain text model format that can be loaded and viewed with a web brower as well as sliced and run through a 3D printer. You can either model or program shapes in text, or possibly both.

Requires FreeCAD.

A site that offers many different algorithms, functions, and models as microservices that you can send data to via REST API and then receive results from. A Huginn agent has been created as a ruby gem already. An official Python module that presents the API natively exists, also. Attempts to be as language agnostic as possible.