Google begins using machine learning to help with spell check at scale in Search.
Google launches Google Translate using machine learning to automatically translate languages, starting with Arabic-English and English-Arabic.
A new era of AI begins when Google researchers improve speech recognition with Deep Neural Networks, which is a new machine learning architecture loosely modeled after the neural structures in the human brain.
In the famous “cat paper,” Google Research begins using large sets of “unlabeled data," like videos and photos from the internet, to significantly improve AI image classification. Roughly analogous to human learning, the neural network recognizes images (including cats!) from exposure instead of direct instruction.
Introduced in the research paper “Distributed Representations of Words and Phrases and their Compositionality,” Word2Vec catalyzed fundamental progress in natural language processing -- going on to be cited more than 40,000 times in the decade following, and winning the NeurIPS 2023 “Test of Time” Award.
AtariDQN is the first Deep Learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. It played Atari games from just the raw pixel input at a level that superpassed a human expert.
Google acquires DeepMind, one of the leading AI research labs in the world.
Google presents Sequence To Sequence Learning With Neural Networks, a powerful machine learning technique that can learn to translate languages and summarize text by reading words one at a time and remembering what it has read before.
Distillation allows complex models to run in production by reducing their size and latency, while keeping most of the performance of larger, more computationally expensive models. It has been used to improve Google Search and Smart Summary for Gmail, Chat, Docs, and more.
At its annual I/O developers conference, Google introduces Google Photos, a new app that uses AI with search capability to search for and access your memories by the people, places, and things that matter.
Google deploys RankBrain in Search and Ads providing a better understanding of how words relate to concepts.
Google introduces TensorFlow, a new, scalable open source machine learning framework used in speech recognition.
AlphaGo, a computer program developed by DeepMind, plays the legendary Lee Sedol, winner of 18 world titles, famed for his creativity and widely considered to be one of the greatest players of the past decade. During the games, AlphaGo played several inventive winning moves. In game two, it played Move 37 — a creative move helped AlphaGo win the game and upended centuries of traditional wisdom.
Google publicly announces the Tensor Processing Unit (TPU), custom data center silicon built specifically for machine learning. After that announcement, the TPU continues to gain momentum:
• TPU v2 is announced in 2017
• TPU v3 is announced at I/O 2018
• TPU v4 is announced at I/O 2021
• At I/O 2022, Sundar announces the world’s largest, publicly-available machine learning hub, powered by TPU v4 pods and based at our data center in Mayes County, Oklahoma, which runs on 90% carbon-free energy.
Developed by researchers at DeepMind, WaveNet is a new deep neural network for generating raw audio waveforms allowing it to model natural sounding speech. WaveNet was used to model many of the voices of the Google Assistant and other Google services.
Google announces the Google Neural Machine Translation system (GNMT), which uses state-of-the-art training techniques to achieve the largest improvements to date for machine translation quality.
In a paper published in the Journal of the American Medical Association, Google demonstrates that a machine-learning driven system for diagnosing diabetic retinopathy from a retinal image could perform on-par with board-certified ophthalmologists.
Google Research proposes a new, decentralized approach to training AI called Federated Learning that promises improved security and scalability.
Google releases "Attention Is All You Need,” a research paper that introduces the Transformer, a novel neural network architecture particularly well suited for language understanding, among many other things.
Introduced DeepVariant, an open-source genomic variant caller that significantly improves the accuracy of identifying variant locations. This innovation in Genomics has contributed to the fastest ever human genome sequencing, and helped create the world's first human pangenome reference.
Google Research releases JAX – a Python library designed for high-performance numerical computing, especially machine learning research.
Google announces Smart Compose, a new feature in Gmail that uses AI to help users more quickly reply to their email. Smart Compose builds on Smart Reply, another AI feature.
Google publishes its AI Principles – a set of guidelines that the company follows when developing and using artificial intelligence. The principles are designed to ensure that AI is used in a way that is beneficial to society and respects human rights.
Google introduces a new technique for natural language processing pre-training called Bidirectional Encoder Representations from Transformers (BERT), helping Search better understand users’ queries.
AlphaZero, a general reinforcement learning algorithm, masters chess, shogi, and Go through self-play.
Google’s Quantum AI demonstrates for the first time a computational task that can be executed exponentially faster on a quantum processor than on the world’s fastest classical computer -- just 200 seconds on a quantum processor compared to the 10,000 years it would take on a classical device.
Google Research proposes using machine learning itself to assist in creating computer chip hardware to accelerate the design process.
DeepMind’s AlphaFold is recognized as a solution to the 50-year “protein-folding problem.” AlphaFold can accurately predict 3D models of protein structures and is accelerating research in biology.
At I/O 2021, Google announces MUM, multimodal models that are 1,000 times more powerful than BERT and allow people to naturally ask questions across different types of information.
At I/O 2021, Google announces LaMDA, a new conversational technology short for “Language Model for Dialogue Applications.”
Google announces Tensor, a custom-built System on a Chip (SoC) designed to bring advanced AI experiences to Pixel users.
At I/O 2022, Sundar announces PaLM – or Pathways Language Model – Google’s largest language model to date, trained on 540 billion parameters.
Sundar announces LaMDA 2, Google’s most advanced conversational AI model.
Google announces Imagen and Parti, two models that use different techniques to generate photorealistic images from a text description.
The AlphaFold Database--which included over 200 million proteins structures and nearly all cataloged proteins known to science--is released.
Google announces Phenaki, a model that can generate realistic videos from text prompts.
Google developed Med-PaLM, a medically fine-tuned LLM, which was the first model to attain a passing score on a medical licensing exam-style question benchmark, demonstrating its ability to accurately answer medical questions.
Google introduces MusicLM, an AI model that can generate music from text.
Google’s Quantum AI achieves the world’s first demonstration of reducing errors in a quantum processor by increasing the number of qubits.
Google releases Bard, an early experiment that lets people collaborate with generative AI, first in the US and UK — followed by other countries.
DeepMind and Google's Brain team merge to form Google DeepMind.
Google launches PaLM 2, our next generation large language model, that builds on Google’s legacy of breakthrough research in machine learning and responsible AI.
GraphCast, an AI model for faster and more accurate global weather forecasting, is introduced.
GnoMe Deep Learning is used to discover 2.2 million new crystals, including 380,000 stable materials that could power future technologies.
Google introduces Gemini, our most capable and general model, built from the ground up to be multimodal. Gemini is able to generalize and seamlessly understand, operate across, and combine different types of information including text, code, audio, image and video.
Google expands the Gemini ecosystem to introduce a new generation: Gemini 1.5, and brings Gemini to more products like Gmail and Docs. Gemini Advanced launched, giving people access to Google’s most capable AI models.
Gemma is a family of lightweight state-of-the art open models built from the same research and technology used to create the Gemini models.
Introduced AlphaFold 3, a new AI model developed by Google DeepMind and Isomorphic Labs that predicts the structure of proteins, DNA, RNA, ligands and more. Scientists can access the majority of its capabilities, for free, through AlphaFold Server.
Google Research and Harvard published the first synaptic-resolution reconstruction of the human brain. This achievement, made possible by the fusion of scientific imaging and Google's AI algorithms, paves the way for discoveries about brain function.
NeuralGCM, a new machine learning-based approach to simulating Earth's atmosphere, is introduced. Developed in partnership with the European Centre for Medium-Range Weather Forecasts (ECMWF), NeuralGCM combines traditional physics-based modeling with ML for improved simulation accuracy and efficiency.
Our combined AlphaProof and AlphaGeometry 2 systems solved four out of six problems from this year’s International Mathematical Olympiad (IMO), achieving the same level as a silver medalist in the competition for the first time. This is the oldest, largest and most prestigious competition for young mathematicians, and has also become widely recognized as a grand challenge in machine learning.
Google begins using machine learning to help with spell check at scale in Search.
Google launches Google Translate using machine learning to automatically translate languages, starting with Arabic-English and English-Arabic.
A new era of AI begins when Google researchers improve speech recognition with Deep Neural Networks, which is a new machine learning architecture loosely modeled after the neural structures in the human brain.
In the famous “cat paper,” Google Research begins using large sets of “unlabeled data," like videos and photos from the internet, to significantly improve AI image classification. Roughly analogous to human learning, the neural network recognizes images (including cats!) from exposure instead of direct instruction.
Introduced in the research paper “Distributed Representations of Words and Phrases and their Compositionality,” Word2Vec catalyzed fundamental progress in natural language processing -- going on to be cited more than 40,000 times in the decade following, and winning the NeurIPS 2023 “Test of Time” Award.
AtariDQN is the first Deep Learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. It played Atari games from just the raw pixel input at a level that superpassed a human expert.
Google acquires DeepMind, one of the leading AI research labs in the world.
Google presents Sequence To Sequence Learning With Neural Networks, a powerful machine learning technique that can learn to translate languages and summarize text by reading words one at a time and remembering what it has read before.
Distillation allows complex models to run in production by reducing their size and latency, while keeping most of the performance of larger, more computationally expensive models. It has been used to improve Google Search and Smart Summary for Gmail, Chat, Docs, and more.
At its annual I/O developers conference, Google introduces Google Photos, a new app that uses AI with search capability to search for and access your memories by the people, places, and things that matter.
Google deploys RankBrain in Search and Ads providing a better understanding of how words relate to concepts.
Google introduces TensorFlow, a new, scalable open source machine learning framework used in speech recognition.
AlphaGo, a computer program developed by DeepMind, plays the legendary Lee Sedol, winner of 18 world titles, famed for his creativity and widely considered to be one of the greatest players of the past decade. During the games, AlphaGo played several inventive winning moves. In game two, it played Move 37 — a creative move helped AlphaGo win the game and upended centuries of traditional wisdom.
Google publicly announces the Tensor Processing Unit (TPU), custom data center silicon built specifically for machine learning. After that announcement, the TPU continues to gain momentum:
• TPU v2 is announced in 2017
• TPU v3 is announced at I/O 2018
• TPU v4 is announced at I/O 2021
• At I/O 2022, Sundar announces the world’s largest, publicly-available machine learning hub, powered by TPU v4 pods and based at our data center in Mayes County, Oklahoma, which runs on 90% carbon-free energy.
Developed by researchers at DeepMind, WaveNet is a new deep neural network for generating raw audio waveforms allowing it to model natural sounding speech. WaveNet was used to model many of the voices of the Google Assistant and other Google services.
Google announces the Google Neural Machine Translation system (GNMT), which uses state-of-the-art training techniques to achieve the largest improvements to date for machine translation quality.
In a paper published in the Journal of the American Medical Association, Google demonstrates that a machine-learning driven system for diagnosing diabetic retinopathy from a retinal image could perform on-par with board-certified ophthalmologists.
Google Research proposes a new, decentralized approach to training AI called Federated Learning that promises improved security and scalability.
Google releases "Attention Is All You Need,” a research paper that introduces the Transformer, a novel neural network architecture particularly well suited for language understanding, among many other things.
Introduced DeepVariant, an open-source genomic variant caller that significantly improves the accuracy of identifying variant locations. This innovation in Genomics has contributed to the fastest ever human genome sequencing, and helped create the world's first human pangenome reference.
Google Research releases JAX – a Python library designed for high-performance numerical computing, especially machine learning research.
Google announces Smart Compose, a new feature in Gmail that uses AI to help users more quickly reply to their email. Smart Compose builds on Smart Reply, another AI feature.
Google publishes its AI Principles – a set of guidelines that the company follows when developing and using artificial intelligence. The principles are designed to ensure that AI is used in a way that is beneficial to society and respects human rights.
Google introduces a new technique for natural language processing pre-training called Bidirectional Encoder Representations from Transformers (BERT), helping Search better understand users’ queries.
AlphaZero, a general reinforcement learning algorithm, masters chess, shogi, and Go through self-play.
Google’s Quantum AI demonstrates for the first time a computational task that can be executed exponentially faster on a quantum processor than on the world’s fastest classical computer -- just 200 seconds on a quantum processor compared to the 10,000 years it would take on a classical device.
Google Research proposes using machine learning itself to assist in creating computer chip hardware to accelerate the design process.
DeepMind’s AlphaFold is recognized as a solution to the 50-year “protein-folding problem.” AlphaFold can accurately predict 3D models of protein structures and is accelerating research in biology.
At I/O 2021, Google announces MUM, multimodal models that are 1,000 times more powerful than BERT and allow people to naturally ask questions across different types of information.
At I/O 2021, Google announces LaMDA, a new conversational technology short for “Language Model for Dialogue Applications.”
Google announces Tensor, a custom-built System on a Chip (SoC) designed to bring advanced AI experiences to Pixel users.
At I/O 2022, Sundar announces PaLM – or Pathways Language Model – Google’s largest language model to date, trained on 540 billion parameters.
Sundar announces LaMDA 2, Google’s most advanced conversational AI model.
Google announces Imagen and Parti, two models that use different techniques to generate photorealistic images from a text description.
The AlphaFold Database--which included over 200 million proteins structures and nearly all cataloged proteins known to science--is released.
Google announces Phenaki, a model that can generate realistic videos from text prompts.
Google developed Med-PaLM, a medically fine-tuned LLM, which was the first model to attain a passing score on a medical licensing exam-style question benchmark, demonstrating its ability to accurately answer medical questions.
Google introduces MusicLM, an AI model that can generate music from text.
Google’s Quantum AI achieves the world’s first demonstration of reducing errors in a quantum processor by increasing the number of qubits.
Google releases Bard, an early experiment that lets people collaborate with generative AI, first in the US and UK — followed by other countries.
DeepMind and Google's Brain team merge to form Google DeepMind.
Google launches PaLM 2, our next generation large language model, that builds on Google’s legacy of breakthrough research in machine learning and responsible AI.
GraphCast, an AI model for faster and more accurate global weather forecasting, is introduced.
GnoMe Deep Learning is used to discover 2.2 million new crystals, including 380,000 stable materials that could power future technologies.
Google introduces Gemini, our most capable and general model, built from the ground up to be multimodal. Gemini is able to generalize and seamlessly understand, operate across, and combine different types of information including text, code, audio, image and video.
Google expands the Gemini ecosystem to introduce a new generation: Gemini 1.5, and brings Gemini to more products like Gmail and Docs. Gemini Advanced launched, giving people access to Google’s most capable AI models.
Gemma is a family of lightweight state-of-the art open models built from the same research and technology used to create the Gemini models.
Introduced AlphaFold 3, a new AI model developed by Google DeepMind and Isomorphic Labs that predicts the structure of proteins, DNA, RNA, ligands and more. Scientists can access the majority of its capabilities, for free, through AlphaFold Server.
Google Research and Harvard published the first synaptic-resolution reconstruction of the human brain. This achievement, made possible by the fusion of scientific imaging and Google's AI algorithms, paves the way for discoveries about brain function.
NeuralGCM, a new machine learning-based approach to simulating Earth's atmosphere, is introduced. Developed in partnership with the European Centre for Medium-Range Weather Forecasts (ECMWF), NeuralGCM combines traditional physics-based modeling with ML for improved simulation accuracy and efficiency.
Our combined AlphaProof and AlphaGeometry 2 systems solved four out of six problems from this year’s International Mathematical Olympiad (IMO), achieving the same level as a silver medalist in the competition for the first time. This is the oldest, largest and most prestigious competition for young mathematicians, and has also become widely recognized as a grand challenge in machine learning.