Warren McCulloch and Walter Pitts published "A Logical Calculus of the Ideas Immanent in Nervous Activity," describing the first mathematical model of a neural network.
Alan Turing published "Computing Machinery and Intelligence," proposing the Turing Test as a measure of machine intelligence.
John McCarthy organized the Dartmouth Conference, coining the term "artificial intelligence" and marking the birth of AI as a field.
Frank Rosenblatt created the Perceptron, the first neural network implementation, while John McCarthy developed LISP, which became the dominant AI programming language.
Edward Feigenbaum developed DENDRAL, the first expert system, followed by MYCIN by Edward Shortliffe. These rule-based systems attempted to encode human expertise into software.
Funding and interest in AI declined after the Lighthill Report criticized AI progress, leading to the first "AI winter" where research funding was reduced.
Geoffrey Hinton, David Rumelhart, and Ronald Williams published a paper on the backpropagation algorithm, which enabled efficient training of multi-layer neural networks.
IBM's Deep Blue became the first computer to defeat a reigning world chess champion, beating Garry Kasparov in a six-game match.
Geoffrey Hinton published "A Fast Learning Algorithm for Deep Belief Nets," helping to revive interest in neural networks and laying groundwork for deep learning.
Fei-Fei Li created ImageNet, a massive dataset of labeled images. In 2012, AlexNet by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton won the ImageNet competition by a significant margin, sparking the deep learning revolution.
Demis Hassabis co-founded DeepMind, which was acquired by Google. DeepMind would later develop AlphaGo, AlphaFold, and other breakthrough AI systems.
DeepMind's AlphaGo defeated 18-time world champion Lee Sedol in the complex game of Go, a feat previously thought to be decades away from being possible.
Vaswani et al. at Google published "Attention is All You Need," introducing the Transformer architecture that would revolutionize NLP and become the foundation for modern LLMs.
Google's BERT and OpenAI's GPT-2 demonstrated dramatic improvements in language understanding and generation, signaling the beginning of the modern LLM era.
OpenAI released GPT-3, a 175-billion parameter language model, and DALL-E, showcasing unprecedented text-to-image generation capabilities.
OpenAI released ChatGPT, bringing LLMs to mainstream attention. Stability AI released Stable Diffusion, an open-source image generation model, democratizing access to AI art creation.
OpenAI released GPT-4, followed by multimodal models from various companies including Anthropic's Claude and Google's Gemini, enabling AI to process both text and images.
Progress in autonomous AI agents and multimodal models capable of reasoning across text, images, video, and audio, bringing research closer to artificial general intelligence.
Known as the "Godfather of Deep Learning," pioneered backpropagation and deep belief networks, contributing fundamentally to neural network research.
Learn moreDeveloped Convolutional Neural Networks (CNNs), transforming computer vision and earning him the Turing Award alongside Hinton and Bengio.
Learn moreMade significant contributions to deep learning, particularly in language models and generative models, completing the trio of deep learning pioneers.
Learn moreCo-founded Google Brain, former chief scientist at Baidu, founder of deeplearning.ai, and pioneer in AI education through Coursera.
Learn moreCreated ImageNet, the dataset that catalyzed the deep learning revolution in computer vision, and works on AI ethics and human-centered AI.
Learn moreCo-founded DeepMind, which created AlphaGo, AlphaFold, and Gemini, with a research focus on artificial general intelligence.
Learn moreOpenAI's multimodal model with improved reasoning and real-time capabilities, powering ChatGPT and available via API.
Learn moreAnthropic's latest model with improved reasoning capabilities, available via web interface and API.
Learn moreGoogle's flagship model featuring 1,000,000 token context windows, enabling very long-context analysis and reasoning.
Learn moreMeta's open-source large language model available in various sizes for local deployment and fine-tuning.
Learn moreHigh-performance commercial model from Mistral AI, available through API and Le Chat interface.
Learn moreOpenAI's text-to-image model with high detail accuracy and improved text rendering capabilities.
Learn moreSubscription-based AI art generator with strong artistic capabilities and distinct aesthetic qualities.
Learn moreOpen-source image generation model from Stability AI with improved text rendering and composition.
Learn moreCommercial generative AI model focused on creative workflows and integration with Adobe products.
Learn moreGoogle's text-to-image diffusion model with enhanced photorealism and text rendering capabilities.
Learn moreOpenAI's text-to-video model capable of generating high-quality videos up to 60 seconds long with complex scenes and movements.
Learn moreVideo generation platform with text-to-video capabilities and advanced editing features for creative professionals.
Learn moreText-to-video platform with specialized animation capabilities and style control features.
Learn moreAI video creation platform specialized in generating talking head videos for business and educational content.
Learn moreGoogle's AI video generation model focusing on realistic motion synthesis with space-time diffusion.
Learn moreAI music generation platform that creates complete songs with vocals and instrumentals from text prompts.
Learn moreGoogle's text-to-music model capable of generating high-fidelity music from natural language descriptions.
Learn moreMeta's suite of AI models for audio generation including MusicGen for music creation from text prompts.
Learn moreAI composer focused on creating royalty-free music for films, games, and commercials with various style controls.
Learn moreAI music generation platform with style transfer capabilities and vocal generation features.
Learn moreAI pair programmer based on OpenAI's models, offering code suggestions, completions, and debugging assistance in real-time.
Learn moreAnthropic's agentic command line tool for developers, delegating coding tasks directly from the terminal.
Learn moreAI coding assistant from AWS providing code suggestions with security scans and AWS service integration.
Learn moreAI coding assistant integrated with Replit's online IDE, offering code completion, explanation, and debugging features.
Learn moreAI code completion tool supporting multiple programming languages and development environments with privacy-focused features.
Learn moreAnthropic's multimodal AI capable of understanding and analyzing images alongside text with strong reasoning capabilities.
Learn moreOpenAI's vision-capable model that can analyze images and provide detailed descriptions and insights.
Learn moreGoogle's multimodal AI with capabilities across text, images, audio, and now video analysis.
Learn moreOpen-source multimodal model for visual and language tasks with flexible image and text understanding.
Learn moreDeepMind's AI system for predicting protein structures, protein-ligand interactions, and molecular dynamics.
Learn moreDeepMind's generalist AI agent capable of performing hundreds of different tasks using a single transformer network.
Learn moreOpenAI's speech recognition system with multilingual capabilities and robust performance across diverse audio.
Learn moreMeta's computer vision model for image segmentation with zero-shot capabilities across various domains.
Learn moreHumanoid robot being developed by Tesla, designed for general-purpose tasks with vision-based AI control.
Learn moreGeneral-purpose humanoid robot with advanced mobility and manipulation capabilities powered by language models.
Learn moreAdvanced humanoid robot with dynamic control and manipulation capabilities using computer vision and AI.
Learn moreGoogle DeepMind's system for training robotic skills across different robot platforms using a single system.
Learn moreCEO of OpenAI, leading the development of GPT models and navigating AI governance and deployment strategies, including advancing multi-modal systems.
Learn moreCEO and co-founder of Anthropic, focused on developing Claude and AI safety research with constitutional AI approaches.
Learn moreCEO overseeing Google DeepMind and Google's AI initiatives including Gemini and Bard, focusing on responsible AI deployment.
Learn moreCEO leading Meta's AI research and open-source LLM initiatives including Llama and other open-source models.
Learn moreCEO of NVIDIA, pioneering AI hardware and infrastructure that underpins modern AI development including GPUs and AI accelerators.
Learn moreFounder of Midjourney, driving innovation in AI-generated art with unique aesthetic qualities and focus on creative applications.
Learn moreFounder of Stability AI, advocating for open-source AI development through Stable Diffusion and other generative models.
Learn moreCEO and co-founder of Mistral AI, developing efficient and powerful language models with a European perspective on AI.
Learn moreCo-founder of AI4ALL promoting diversity in AI, while continuing research leadership at Stanford HAI (Human-Centered AI Institute).
Learn moreFounder of Figure AI, developing autonomous humanoid robots for commercial applications with LLM-powered intelligence.
Learn moreFounder of Distributed AI Research Institute focused on ethical AI, algorithmic bias, and accountability in AI systems.
Learn moreAI pioneer advocating for building AI systems that align with human values, author of "Human Compatible" on AI safety.
Learn moreAI ethics researcher focusing on bias in AI systems and developing methods for more accountable and transparent AI systems.
Learn moreAI safety researcher and founder of MIRI warning about existential risks from advanced AI systems and alignment challenges.
Learn moreFounder of the Algorithmic Justice League, researching and advocating against bias in facial recognition systems and other AI technologies.
Learn moreEconomist examining AI's impact on economic growth, productivity, and labor markets with a generally optimistic outlook.
Learn moreCo-founder of the AI Now Institute and author of "Atlas of AI," examining the political, social, and environmental impacts of AI.
Learn moreEconomist researching how AI and digital technologies are reshaping economies, labor markets, and productivity.
Learn moreEconomist studying how AI affects labor markets, inequality, and productivity, advocating for human-complementing AI.
Learn moreVenture capitalist and author of "AI Superpowers," analyzing the global AI competition and economic implications of AI adoption.
Learn moreAI ethics researcher and president of Signal Foundation, critiquing Big Tech's concentration of AI power and advocating for public interest alternatives.
Learn moreCo-founder of the Center for Humane Technology, warning about AI's potential to amplify attention economics and manipulative technologies.
Learn moreCognitive scientist and AI researcher offering critical perspectives on current AI limitations and potential alternative approaches.
Learn moreComputational linguist critiquing fundamental limitations of LLMs, co-author of influential "Stochastic Parrots" paper on LLM limitations.
Learn moreComputer scientist, VR pioneer and author offering humanistic perspectives on technology and advocating for alternative economic models.
Learn moreLaw professor specializing in AI regulation, robotics law, and privacy, examining legal frameworks for emerging AI technologies.
Learn moreFormer EU Parliament member and international policy director at Stanford, focused on democratic governance of AI and tech policy.
Learn moreProfessor researching AI ethics, algorithmic fairness, and data protection law, advocating for counterfactual explanations in AI systems.
Learn moreAI ethics researcher and practitioner focusing on algorithmic accountability and auditing systems for bias and harmful effects.
Learn moreCo-founder of AI safety-focused Anthropic and former leader of Stanford's AI Index tracking AI development, advocating for thoughtful AI governance.