Thursday, May 21, 2026
- Candle (HuggingFace Rust ML)v5Candle is a minimalist machine learning framework written in pure Rust and published by Hugging Face under the huggingface/candle GitHub repository.
- tinygradv4tinygrad is an open-source deep learning framework written primarily in Python that aims to occupy the space between Andrej Karpathy's pedagogical micrograd and full-scale production stacks like PyTorch.
- Vast.aiv4Vast.ai is a cloud-based GPU rental marketplace that connects independent hardware operators (called hosts) with developers, researchers and companies looking to rent compute by the second.
- Voltage Parkv4Voltage Park is a United States cloud computing company that operates a fleet of NVIDIA H100 graphics processing units for artificial intelligence training and inference workloads.
- Crusoe Energyv5Crusoe Energy Systems, Inc. (commonly branded as Crusoe) is a privately held American energy and computing infrastructure company headquartered in Denver, Colorado.
- OpenVINOv4OpenVINO (Open Visual Inference and Neural Network Optimization) is an open-source toolkit developed by Intel for optimizing and deploying deep learning inference across a heterogeneous set of Intel hardware…
- Ray Servev4Ray Serve is a scalable, framework-agnostic model serving library built on top of the Ray (framework) distributed computing system.
- BentoMLv4BentoML is an open-source Python framework for packaging, serving, and deploying machine learning and AI models as production inference services.
- LiteLLMv4LiteLLM is an open-source AI gateway from BerriAI that lets developers call more than 100 large language model providers (including OpenAI, Anthropic, Google Gemini, Amazon Bedrock and Azure OpenAI) through a…
- Text Generation Inference (TGI)v4Text Generation Inference (TGI) is an open-source toolkit developed by Hugging Face for deploying and serving large language models in production.
- Mike Lewisv4Mike Lewis is a British natural language processing researcher based in Seattle who serves as a research scientist at Meta AI (Facebook AI Research, FAIR) and as the pre-training research lead on the Llama…
- Alec Radfordv4Alec Radford is an American machine learning researcher who was the first author of the papers introducing the DCGAN generative adversarial network, the original Generative Pre-Trained Transformer (GPT-1)…
- Greg Brockmanv4Greg Brockman is an American software engineer and entrepreneur who co-founded OpenAI in December 2015 and serves as its president and chairman of the board.
- Quoc V. Lev6Quoc Viet Le (Vietnamese: Lê Viết Quốc, born 1982) is a Vietnamese-American computer scientist and a co-founder of Discovery Loop, a public benefit corporation focused on automating machine learning, science…
- Oriol Vinyalsv6Oriol Vinyals (born 1983, Sabadell, Catalonia, Spain) is a Spanish machine learning researcher who is a co-founder of Discovery Loop, a public benefit corporation launched on August 5, 2026 with the stated…
- Mercury (Inception Labs)v5Mercury is a family of commercial-scale diffusion-based large language models developed by Inception Labs, a Palo Alto startup co-founded in 2024 by Stanford professor Stefano Ermon together with his former…
- SEDD (Score Entropy Discrete Diffusion)v4Score Entropy Discrete Diffusion (SEDD) is a discrete diffusion model for language and other discrete data introduced by Aaron Lou, Chenlin Meng, and Stefano Ermon at Stanford University in the paper Discrete…
- LLaDA (Large Language Diffusion)v3LLaDA (Large Language Diffusion with mAsking) is a family of non-autoregressive large language models that generate text by iteratively denoising a sequence of mask tokens rather than predicting tokens left to…
- Hybrid searchv4Hybrid search is an information retrieval technique that runs a lexical (sparse) keyword retriever, typically BM25, and a semantic (dense) vector retriever in parallel against the same corpus
- Cross-encoderv4A cross-encoder is a neural network architecture that scores a pair of texts by feeding them jointly into a single transformer (such as BERT) and reading out one scalar score for the pair, for example a…
- HyDE (Hypothetical Document Embeddings)v4HyDE (Hypothetical Document Embeddings) is a zero-shot dense retrieval technique that, instead of searching with the user's query, first prompts an instruction-following large language model to write a…
- SPLADEv5SPLADE (Sparse Lexical and Expansion model) is a learned sparse retrieval model that encodes a query or document as a weighted
- ColBERTv4ColBERT (Contextualized Late Interaction over BERT) is a neural information retrieval model that encodes queries and documents into matrices of token-level vectors and scores them with a late-interaction…
- Optimum-Quantov3Optimum Quanto, commonly referred to as Quanto, is a PyTorch-based quantization toolkit developed and maintained by Hugging Face that provides linear weight and activation quantization across multiple devices…
- SmoothQuantv5SmoothQuant is a training-free, accuracy-preserving post-training quantization (PTQ) method that enables 8-bit weight and 8-bit activation (W8A8) integer inference for large language models without retraining…
- FP4 (4-bit floating point)v4FP4 (4-bit floating point) is a numerical format that stores a real number in just 4 bits, the smallest floating-point type in mainstream use for deep learning.
- NormalFloat 4-bit (NF4)v4NormalFloat 4-bit (NF4) is a 4-bit numerical data type for storing the weights of deep neural networks, introduced in the 2023 QLoRA paper by Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer…
- ExLlamaV2 (EXL2)v4EXL2 (ExLlamaV2 format) is an open-source, mixed-bit weight-quantization format for compressing large language models so they run fast on a single consumer-class NVIDIA GPU.
- YOCO (You Only Cache Once)v4YOCO ("You Only Cache Once") is a decoder-decoder neural network architecture for large language models introduced by researchers at Microsoft Research and Tsinghua University in May 2024.
- EAGLE-2v4EAGLE-2 ("Faster Inference of Language Models with Dynamic Draft Trees") is the second generation of the EAGLE family of speculative decoding methods for accelerating large language model inference, introduced…
- Lookahead Decodingv4Lookahead Decoding is a parallel decoding algorithm for accelerating inference in large language models, introduced in November 2023 by Yichao Fu, Peter Bailis, Ion Stoica, and Hao Zhang from the Hao AI Lab at…
- Rule-Based Rewards (RBR)v4Rule-Based Rewards (RBR) is a safety-alignment technique introduced by OpenAI in July 2024 that replaces large quantities of human-labeled safety preference data with an explicit collection of natural-language…
- Self-Rewarding Language Modelsv6Self-Rewarding Language Models (SRLM) is an iterative alignment method in which a single large language model alternately plays the role of policy (generating candidate responses to user prompts) and reward…
- LIMA (Less Is More for Alignment)v3LIMA, short for "Less Is More for Alignment," is a 2023 research paper by Chunting Zhou and colleagues at Meta AI, Carnegie Mellon University, the University of Southern California, and Tel Aviv University…
- OpenFoldv6OpenFold is an open source, trainable, GPU friendly PyTorch reimplementation of AlphaFold 2, developed initially by the AlQuraishi lab at Columbia University and then governed by the OpenFold Consortium
- RoseTTAFoldv4RoseTTAFold is a deep-learning system for predicting the three-dimensional structures of proteins from amino acid sequence, developed at the Institute for Protein Design (IPD) at the University of Washington…
- Intel Loihiv4Intel Loihi is a family of research neuromorphic processors developed by Intel Labs to implement spiking neural networks (SNNs) in silicon, with the stated goals of energy-efficient inference, online learning…
- BrainChip Akidav5Akida is a family of fully digital, event-based neuromorphic processor intellectual property (IP) cores and reference chips developed by BrainChip Holdings Ltd
- Untether AIv4Untether AI Corp. was a Toronto-based fabless semiconductor startup that designed energy-efficient inference accelerators based on a proprietary "at-memory compute" architecture, in which large arrays of small…
- Rain AIv4Rain AI, originally incorporated as Rain Neuromorphics, is a San Francisco AI accelerator startup founded by Gordon Hirsch Wilson, Jack Kendall, and Juan Claudio Nino, with technical roots in the University of…
