Releases

Microsoft agrees to acquire GitHub for $7.5 billion in stock, bringing the developer platform that later launched GitHub Copilot into Microsoft.

NVIDIA introduced the Jetson AGX Xavier embedded AI computer for autonomous machines.

Hugging Face raised a $4 million seed round backed by investors including A.Capital, Betaworks, SV Angel, and Thirty Five Ventures.

Microsoft acquires conversational-AI startup Semantic Machines to advance more natural, context-aware dialogue systems.

Microsoft releases the first public preview of ML.NET, bringing cross-platform machine learning to .NET developers.

Microsoft researchers introduce Fairlearn to assess and mitigate unfairness in machine-learning systems.

Apollo 2.5 added high-speed-road support, lower costs, developer improvements and ApolloScape datasets.

Oracle released the first Autonomous Database cloud service, powered by machine-learning automation.

NVIDIA introduced Clara as a medical imaging and healthcare AI computing platform.

NVIDIA introduced DGX-2 with 16 V100 GPUs connected by NVSwitch for large-scale AI training.

Apollo 2.0 added cloud services, reference hardware and vehicle platforms for simple urban roads.

Runway launched a web platform for accessible machine-learning-powered creative tools.

Runway was founded as an applied AI research company for creative media.

Shield AI deployed its Hivemind-powered autonomy in combat operations.

Quiver became available for time-series and engineering analysis in Foundry.

Contour became available as Foundry's point-and-click analytical application.

NVIDIA launched TITAN V, bringing Volta Tensor Core AI acceleration to desktop systems.

DeepMind publishes AlphaZero, a general self-play reinforcement-learning system for multiple board games.

AWS introduced managed natural-language processing for entity, sentiment, language and topic extraction.

AWS introduced a managed neural machine-translation service.

AWS introduced a managed automatic speech-recognition service.

AWS introduced a programmable deep-learning-enabled video camera for edge computer-vision development.

AWS launched an end-to-end managed platform for building, training and deploying machine-learning models.

Baidu upgraded DuerOS with expanded conversational AI capabilities.

Microsoft and Databricks announced Azure Databricks, a first-party Apache Spark analytics service on Azure.

Baidu launched a no-code interface for training and deploying custom AI models.

Oracle unveiled a self-driving database cloud using machine learning for tuning, patching, security and operations.

Microsoft and Facebook introduce the Open Neural Network Exchange format to improve model interoperability across AI frameworks.

The founders turned an experimental cryptocurrency-mining GPU setup into a business and expanded through opportunistic purchases of GPU hardware.

Michael Intrator, Brian Venturo, and Brannin McBee formed The Atlantic Crypto Corporation LLC, the company that later became CoreWeave.

Databricks raised $140 million in a Series D led by Andreessen Horowitz.

Microsoft introduces Project Brainwave, an FPGA-based architecture for real-time deep-learning inference in cloud and edge systems.

OpenAI released code for training reinforcement-learning agents from human feedback.

OpenAI introduced PPO, a family of policy-gradient methods designed for stability and simplicity.

Scale raised $4.5 million in Series A funding led by Accel to expand its labeled-data infrastructure.

Microsoft launches Seeing AI, an accessibility application that narrates people, text, products and surroundings for blind and low-vision users.

Baidu introduced a production-oriented intelligent-driving solution for automakers.

OpenAI and DeepMind researchers showed how agents can learn complex behavior from human preference comparisons.

Google researchers introduce the Transformer architecture, replacing recurrence with attention and reshaping modern sequence modeling.

OpenAI released Baselines, open-source high-quality implementations of reinforcement-learning algorithms.

At Google I/O, the company frames its strategic transition from mobile-first to AI-first products and computing.

Google announces its second-generation TPU and plans to offer Cloud TPUs to Google Cloud customers.

NVIDIA introduced its GPU Cloud catalog, later branded NGC, for optimized deep-learning containers and software.

NVIDIA introduced the Volta architecture and V100 GPU, including Tensor Cores built for deep learning.

Baidu announced its open autonomous-driving platform.

Facebook released the Caffe2 deep-learning framework for scalable cross-platform training and deployment.

Facebook AI Research released FAISS for efficient similarity search and clustering of dense vectors.

Hugging Face raised approximately $1.2 million in early angel funding to develop its conversational AI startup.

Baidu introduced its voice-assistant experience powered by DuerOS.

Baidu introduced its conversational AI operating system for devices and services.

IBM commercialized enterprise conversational-AI tooling that evolved into watsonx Assistant.

IBM launched an AI-powered enterprise search and document-understanding service.

Scale began building distributed contributor platforms and training operations to support large-scale annotation, expert-data, and evaluation programs.

Scale launched Remotasks to train and coordinate distributed contributors performing data annotation and review tasks.

Databricks raised a $60 million Series C led by New Enterprise Associates.

Amazon unveiled a checkout-free store using computer vision, sensor fusion and deep learning.

OpenAI released Universe, a software platform for training intelligent agents across games, websites, and applications.

AWS introduced a managed text-to-speech service with natural-sounding voices.

AWS introduced the conversational AI service built from the speech recognition and language understanding technology behind Alexa.

AWS introduced managed image analysis for object, scene and face detection.

AWS selected MXNet as its preferred deep-learning framework and committed engineering investment to the open-source project.

Microsoft creates the AI and Research Group, combining research, information-platform and AI product teams under Harry Shum.

Oracle introduced the infrastructure platform that became OCI, later forming the base for its managed AI services and GPU cloud.

DeepMind introduces WaveNet, a neural generative model for raw audio waveforms that substantially improves speech synthesis.

Baidu launched its core AI technology engine and open-capability platform.

Baidu opened PaddlePaddle to the global developer community for deep learning, vision, speech and NLP.

Facebook AI Research released PyTorch, a Python-first tensor and dynamic neural-network framework.

Facebook AI Research released fastText, a library for efficient text classification and word representations.

Scale launched the data infrastructure that became its core Data Engine, combining APIs, machine assistance, and human review to create high-quality training data.

Scale launched an API that let developers submit human-powered data tasks with one line of code, establishing the foundation of its AI data business.

Alexandr Wang and Lucy Guo founded Scale in San Francisco and entered Y Combinator to build an API for routing human work, which evolved into AI data infrastructure.

Google publicly reveals the TPU, a custom accelerator designed to speed machine-learning workloads in its data centers.

Amazon open-sourced its Deep Scalable Sparse Tensor Network Engine for recommendation workloads.

Facebook introduced FBLearner Flow, its internal platform for managing the full lifecycle of machine-learning models.

OpenAI released the public beta of Gym, a toolkit for developing and comparing reinforcement-learning algorithms.

The Pascal-based Tesla P100 accelerator debuted alongside DGX-1 for deep learning and HPC.

NVIDIA unveiled DGX-1, its first integrated deep-learning supercomputer.

Microsoft launches Cognitive Services APIs for adding vision, speech, language, knowledge and search capabilities to applications.

Microsoft takes the Tay social chatbot offline after coordinated abuse caused it to produce offensive content, prompting a public review of safeguards and social-AI deployment.

AlphaGo wins its landmark five-game match against 18-time world champion Lee Sedol by four games to one.

Microsoft releases its Computational Network Toolkit under an open-source license for deep neural-network training.

Replit launched its browser-based development workspace.

Replit was founded to make programming accessible through an online, collaborative computing environment.

Shield AI introduced Nova for autonomous reconnaissance in buildings and GPS-denied environments.

Palantir established the Ontology as Foundry's semantic and operational layer.

Data Connection became Foundry's connector and ingestion layer.

Palantir introduced Foundry as its enterprise data operations platform.

Co-founder Ali Ghodsi became chief executive officer of Databricks.

Clément Delangue, Julien Chaumond, and Thomas Wolf founded Hugging Face in New York, initially building a conversational AI companion before pivoting toward open machine learning.

OpenAI launched as a nonprofit artificial intelligence research company with a mission to ensure artificial general intelligence benefits all of humanity.

Baidu reported a milestone in fully autonomous road testing under complex conditions.

Google releases TensorFlow as an open-source machine-learning framework, making internal deep-learning infrastructure broadly available.

AlphaGo becomes the first computer program to defeat a professional Go player without handicaps on a full-sized board.

Google completes its reorganization under Alphabet Inc.; Google becomes the principal operating subsidiary while Alphabet becomes the publicly traded parent.

Baidu began building enterprise cloud services that evolved into Baidu AI Cloud.

Amazon opened Alexa to developers through the Alexa Skills Kit and Alexa Voice Service.

IBM created Watson Health to apply data and cognitive-computing technologies across healthcare and life sciences.

AWS launched its first managed machine-learning service for building predictive models from data in S3, Redshift and RDS.

Microsoft makes Azure Machine Learning generally available as a cloud platform for creating and deploying predictive models.

Amazon agreed to acquire chip-design company Annapurna Labs, strengthening its ability to build custom silicon for AWS.