Friday, March 20, 2026
- GSM8Kv11GSM8K (Grade School Math 8K) is an English-language benchmark of grade-school arithmetic word problems released by OpenAI researchers in 2021.
- MT-Benchv9MT-Bench (Multi-Turn Benchmark) is a benchmark of 80 hand-written, two-turn questions that evaluates large language models (LLMs) on multi-turn conversation and instruction following by using a strong model…
- RWKVv7RWKV (pronounced "RwaKuv") is an open-source neural network architecture that combines the parallelizable training of Transformers with the constant-time
- DeBERTav11DeBERTa (Decoding-enhanced BERT with Disentangled Attention) is a family of pre-trained language models developed by Microsoft Research that improves BERT and RoBERTa with two innovations: a disentangled…
- DETRv9DETR (DEtection TRansformer) is an end-to-end object detection model that reframes detection as a direct set prediction problem solved with a transformer encoder-decoder and bipartite matching, removing the…
- Open WebUIv8Open WebUI is a self-hosted, extensible web interface for interacting with large language models (LLMs) both locally and through cloud APIs.
- ALBERTv10ALBERT (A Lite BERT) is a parameter-efficient variant of the BERT language model developed by researchers at Google Research and the Toyota Technological Institute at Chicago (TTIC).
- Neural architecture searchv10Neural architecture search (NAS) is a technique for automating the design of neural network architectures.
- MobileNetv7MobileNet is a family of efficient convolutional neural network (CNN) architectures developed by Google for mobile and edge AI applications.
- ELECTRAv9ELECTRA, which stands for Efficiently Learning an Encoder that Classifies Token Replacements Accurately
- Grounding (artificial intelligence)v8Grounding in artificial intelligence is the process of anchoring an AI system's outputs to verifiable
- ComfyUIv9ComfyUI is a free, open-source node-based graphical user interface and backend for generative AI workflows, primarily focused on image generation using diffusion models such as Stable Diffusion and FLUX.
- GGUFv10GGUF (GPT-Generated Unified Format) is the standard binary file format for storing large language models for local inference, bundling a model's weights, tokenizer, and metadata into a single self-contained…
- LM Studiov14LM Studio is a desktop application for discovering, downloading, and running large language models locally on personal hardware, available free for both personal and commercial use on macOS, Windows, and Linux.
- Swin Transformerv11The Swin Transformer (Shifted Window Transformer) is a hierarchical vision transformer architecture that computes self-attention within local, non-overlapping windows and introduces a shifted window…
- Safetensorsv9Safetensors is an open-source tensor serialization format developed by Hugging Face that stores machine learning model weights as raw tensor data plus a small JSON header
- LAIONv9LAION (Large-scale Artificial Intelligence Open Network) is a German non-profit organization
- Common Crawlv9Common Crawl is a nonprofit 501(c)(3) organization that maintains a free, open repository of web crawl data, and it is the single largest publicly available source of text used to train large language models.
- COCO datasetv9COCO (Common Objects in Context) is a large-scale dataset for object detection, image segmentation, keypoint detection, and image captioning.
- DenseNetv5DenseNet (Densely Connected Convolutional Networks) is a convolutional neural network architecture that connects every layer to every other layer in a feed-forward fashion
- WinoGrandev6WinoGrande is a large-scale benchmark for commonsense reasoning consisting of 44,000 binary fill-in-the-blank pronoun resolution problems, built to test whether language models genuinely understand commonsense…
- Continual learningv6Continual learning, also called lifelong learning or incremental learning, is a machine learning paradigm in which a model learns from a stream of tasks or data distributions over time
- Curriculum learningv6Curriculum learning is a training strategy for machine learning models in which training examples are presented in a meaningful, easy-to-hard order rather than at random
- RoBERTav9RoBERTa (Robustly Optimized BERT Pretraining Approach) is an open-source natural language processing model released in July 2019 by researchers at Facebook AI (now Meta AI) and the University of Washington…
- MLflowv9MLflow is an open-source platform for managing the end-to-end machine learning lifecycle, covering experiment tracking, model packaging, a model registry, deployment, and (since 2025) generative-AI…
- Knowledge Editingv5Knowledge editing (also called model editing) is a family of techniques for updating or correcting specific factual associations stored in the weights of a trained large language model without full retraining…
- Text summarizationv8Text summarization is the natural language processing (NLP) task of automatically producing a shorter version of one or more documents that preserves the most important information from the original text.
- DeiTv6DeiT (Data-efficient Image Transformers) is a family of vision transformer models that proved Vision Transformers can be trained to state-of-the-art image classification accuracy on ImageNet alone
- Information Retrievalv10Information retrieval (IR) is the study and engineering of systems that identify material likely to satisfy an information need.
- Amazon Qv7Amazon Q is a family of generative AI-powered assistants from Amazon Web Services (AWS), announced on November 28, 2023, at the AWS re:Invent conference and made generally available on April 30, 2024.
- BIG-Benchv7BIG-Bench (Beyond the Imitation Game Benchmark) is a large-scale, collaborative benchmark of 204 tasks, contributed by 450 authors across 132 institutions, built to measure and extrapolate the capabilities of…
- ConvNeXtv9ConvNeXt is a family of pure convolutional neural network (CNN) models that match or beat Vision Transformers on standard vision benchmarks
- Mambav12Mamba is a neural network architecture for sequence modeling that uses selective state space models (SSMs) to process sequential data in linear time with respect to sequence length
- GPU computingv8GPU computing is the use of a graphics processing unit (GPU) to perform general-purpose computation that was traditionally handled by the central processing unit (CPU).
- Wav2Vecv7Wav2Vec is a family of self-supervised learning models from Meta AI (formerly Facebook AI Research) that learn speech representations directly from raw audio waveforms
- AI Safety Institutesv6AI Safety Institutes are government-established organizations that test, evaluate, and research the safety and security risks of advanced artificial intelligence systems
- Mixture of Agentsv5Mixture of Agents (MoA) is a multi-model collaboration framework that combines multiple large language models (LLMs) in a layered architecture
- GLUE benchmarkv6The General Language Understanding Evaluation (GLUE) benchmark is a collection of nine natural language understanding (NLU) tasks designed to evaluate and compare the performance of language models across a…
- SQuADv8SQuAD (the Stanford Question Answering Dataset) is a large-scale reading comprehension benchmark from Stanford University in which a model must answer a question by extracting the exact span of text that…
- Existential risk from AIv9Existential risk from artificial intelligence (also called AI x-risk) is the hypothesis that the development of sufficiently advanced artificial intelligence could cause human extinction, permanent…
- Kling (video generation)v9Kling is an AI video generation model developed by Kuaishou Technology, a Chinese short-video platform company publicly traded on the Hong Kong Stock Exchange.
- Pika (video generation)v7Pika is an artificial intelligence video generation platform developed by Pika Labs, Inc. that lets users create and edit short videos from text prompts, images, and existing clips, and it is best known for…
- AI artv8AI art is artwork created with the assistance of artificial intelligence systems, spanning visual images, music, video, and other creative outputs generated or co-created by algorithms, neural networks, and…
- Gradiov5Gradio is an open-source Python library that lets developers build interactive web interfaces for machine learning models, APIs, and arbitrary Python functions in a few lines of code.
- Model mergingv5Model merging combines the parameters of multiple trained neural networks into a single unified model without any additional training.
- Autonomous drivingv9Autonomous driving is the sustained performance by a vehicle system of part or all of the dynamic driving task.
- AI governancev7AI governance is the collection of frameworks, norms, standards, policies, and institutional arrangements that guide the development, deployment, and use of artificial intelligence systems so that they are…
- XLNetv7XLNet is a generalized autoregressive pretraining method for natural language processing that combines the strengths of autoregressive and autoencoding language models.
- llama.cppv10llama.cpp is an open-source large language model inference engine written in C and C++ by Bulgarian software engineer Georgi Gerganov that runs large language models on consumer-grade hardware without…
- Inception (deep learning)v7Inception is a family of convolutional neural network (CNN) architectures developed by researchers at Google, first introduced in 2014.
- Named entity recognitionv6Named entity recognition (NER) is the natural language processing task of locating spans of text that name real-world things, such as people, organizations, and locations, and classifying each span into a…
- Cross-attentionv10Cross-attention is a variant of the attention mechanism in which the queries are derived from one sequence or representation while the keys and values are derived from a different sequence or representation
- Image segmentationv8Image segmentation is the computer vision task of partitioning a digital image into multiple regions by assigning every pixel a label, producing a pixel-level map of what each part of the image contains.
- T5 (language model)v11T5 (Text-to-Text Transfer Transformer) is a family of transformer-based language models released by Google in 2019-2020 that reframes every natural language processing (NLP) task, classification, translation…
- Object detectionv9Object detection is a computer vision task that finds instances of interest in an image and assigns each one a category.
- Machine Translationv7Machine translation (MT) is the automatic translation of text or speech from one human language into another.
- Chinchilla scaling lawsv6The Chinchilla scaling laws are a set of empirical findings published by DeepMind researchers in 2022 showing that, for a fixed compute budget, a large language model trains most efficiently when its number of…
- PaLMv10PaLM (Pathways Language Model) is a family of dense, decoder-only large language models developed by Google Research. Google announced the original family on April 4, 2022.
- Test-time computev10Test-time compute (also called inference-time compute scaling or test-time scaling) is the practice of allocating additional computation while a large language model answers a query
- Byte-Pair Encodingv11Byte-pair encoding (BPE) is a subword tokenization algorithm that splits text into tokens by starting from individual characters or bytes and iteratively merging the most frequent adjacent pair into a new token
- VGGv6VGG (also called VGGNet) is a deep convolutional neural network architecture, introduced in 2014 by Karen Simonyan and Andrew Zisserman of the Visual Geometry Group at the University of Oxford
- YOLO (object detection)v7YOLO (You Only Look Once) is a family of object detection models that treat detection as a single regression problem, predicting bounding boxes and class probabilities directly from full images in one forward…
- EfficientNetv8EfficientNet is a family of convolutional neural network architectures and a model-scaling method that uniformly scales network depth, width, and input resolution with a single compound coefficient, developed…
- Generative adversarial networkv8Generative adversarial networks (GANs) are a family of generative models trained through competition between two learned functions.
- Embeddingsv9In machine learning, an embedding is a learned representation that maps an input into a vector, usually so that a downstream model or comparison rule can use relationships encoded in the vector's geometry.
- AI Agentsv22An AI agent is a software system that selects and performs actions in an environment in pursuit of an objective.
- OpenAI o-seriesv9The OpenAI o-series is a family of large language models developed by OpenAI that are trained with reinforcement learning to reason through an internal chain-of-thought before answering, making them OpenAI's…
Thursday, March 19, 2026
- Sovereign AIv6Sovereign AI is a nation's capability to develop, operate, and control artificial intelligence using its own computing infrastructure, data, workforce, and (often) its own models
- AI for Sciencev10AI for science is the use of artificial intelligence, particularly deep learning and large language models, to accelerate scientific discovery across biology, chemistry, physics, materials science…
- Compound AI Systemv5A compound AI system is an AI system that achieves its objectives by combining multiple interacting components, such as large language models, retrieval mechanisms, external tools, guardrails, and…
- AI Datacenterv7An AI datacenter (also written as AI data center) is a facility designed to run artificial intelligence workloads on dense groups of GPUs or other accelerators.
- NeurIPSv6
