ML and AI Research

by Joe Morotti (AWS Machine Learning Blog) on October 4, 2022

Near-real-time delivery of data and insights enable businesses to rapidly respond to their customers’ needs. Real-time data can come from a variety of sources, including social media, IoT devices, infrastructure monitoring, call center monitoring, and more. Due to the breadth and depth of data being ingested from multiple sources, businesses look for solutions to protect

by Paul Hargis (AWS Machine Learning Blog) on October 4, 2022

Creating robust and reusable machine learning (ML) pipelines can be a complex and time-consuming process. Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. Creating and running a full pipeline during experimentation adds unwanted overhead and cost to the development lifecycle. In this post, we

by Alyssa Hughes (Microsoft Research) on October 4, 2022

Research Focus highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. The post Research Focus: Week of September 26, 2022 appeared first on Microsoft Research.

by Angie Lee (NVIDIA Blog) on October 4, 2022

Planes taxiing for long periods due to ground traffic — or circling the airport while awaiting clearance to land — don’t just make travelers impatient. They burn fuel unnecessarily, harming the environment and adding to airlines’ costs. Searidge Technologies, based in Ottawa, Canada, has created AI-powered software to help the aviation industry avoid such issues, Read article > The post Searidge Technologies Offers a Safety Net for Airports appeared first on […]

by Gerardo Delgado (NVIDIA Blog) on October 4, 2022

TwitchCon — the world’s top gathering of live streamers – kicks off Friday with the new line of GeForce RTX 40 Series GPUs bringing incredible new technology — from AV1 to AI — to elevate live streams for aspiring and professional Twitch creators alike. The post Creator EposVox Shares Streaming Lessons, Successes This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.

by Jasleen Grewal (AWS Machine Learning Blog) on October 3, 2022

Machine learning (ML) has improved business across industries in recent years—from the recommendation system on your Prime Video account, to document summarization and efficient search with Alexa’s voice assistance. However, the question remains of how to incorporate this technology into your business. Unlike traditional rule-based methods, ML automatically infers patterns from data so as to

by Bosco Albuquerque (AWS Machine Learning Blog) on October 3, 2022

This post is a joint collaboration with Andries Engelbrecht and James Sun of Snowflake, Inc. The cloud computing revolution has enabled businesses to capture and retain corporate and organizational data without capacity planning or data retention constraints. Now, with diverse and vast reserves of longitudinal data, companies are increasingly able to find novel and impactful

by Ankur Srivastava (AWS Machine Learning Blog) on October 3, 2022

Amazon Elastic Compute Cloud (Amazon EC2) G5 instances are the first and only instances in the cloud to feature NVIDIA A10G Tensor Core GPUs, which you can use for a wide range of graphics-intensive and machine learning (ML) use cases. With G5 instances, ML customers get high performance and a cost-efficient infrastructure to train and

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 3, 2022

by Machine learning : nature.com subject feeds on October 1, 2022

by Kimberly Madia (AWS Machine Learning Blog) on September 30, 2022

Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM – 10:30 AM PT.  The first 1,500 people to register will receive $50 of AWS credits. Register here. Over the past 20 years, Amazon has delivered many world firsts for artificial intelligence (AI) and machine learning (ML). ML

by Vinod Raman (AWS Machine Learning Blog) on September 30, 2022

AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision to on-premises internet protocol (IP) cameras. AWS Panorama device options include the AWS Panorama Appliance and the Lenovo ThinkEdge SE70, powered by AWS Panorama. These device options provide you choices in price and performance, depending

by Kanwaljit Khurmi (AWS Machine Learning Blog) on September 30, 2022

In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training deep learning models at scale on both Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon SageMaker utilizing a hybrid architecture approach.

by Simon Rolfes (AWS Machine Learning Blog) on September 30, 2022

Pressing or pressure in football is a process in which a team seeks to apply stress to the opponent player who possesses the ball. A team applies pressure to limit the time an opposition player has left to make a decision, reduce passing options, and ultimately attempt to turn over ball possession. Although nearly all

by Simon Rolfes (AWS Machine Learning Blog) on September 30, 2022

Ten years from now, the technological fitness of clubs will be a key contributor towards their success. Today we’re already witnessing the potential of technology to revolutionize the understanding of football. xGoals quantifies and allows comparison of goal scoring potential of any shooting situation, while xThreat and EPV models predict the value of any in-game

by Geremy Cohen (AWS Machine Learning Blog) on September 30, 2022

Depending on the quality and complexity of data, data scientists spend between 45–80% of their time on data preparation tasks. This implies that data preparation and cleansing take valuable time away from real data science work. After a machine learning (ML) model is trained with prepared data and readied for deployment, data scientists must often

by Machine learning : nature.com subject feeds on September 30, 2022

by Machine learning : nature.com subject feeds on September 30, 2022

by Machine learning : nature.com subject feeds on September 30, 2022

by Machine learning : nature.com subject feeds on September 30, 2022

by Machine learning : nature.com subject feeds on September 30, 2022

by Salma Taoufiq (AWS Machine Learning Blog) on September 29, 2022

This post is co-authored by Salma Taoufiq and Harini Kannan from Sophos. As a leader in next-generation cybersecurity, Sophos strives to protect more than 500,000 organizations and millions of customers across over 150 countries against evolving threats. Powered by threat intelligence, machine learning (ML), and artificial intelligence from Sophos X-Ops, Sophos delivers a broad and

by Latest News & Stories From Around The World | Uber Blog on September 29, 2022

Uber’s Data team discusses how they used CLP to scale log ingestion, retention, and analytics for Petabytes of Spark logs, reducing log storage and management costs by 169x.

by Angie Lee (NVIDIA Blog) on September 29, 2022

NVIDIA artists ran their engines at full throttle for the stunning Racer RTX demo, which debuted at last week’s GTC keynote, showcasing the power of NVIDIA Omniverse and the new GeForce RTX 4090 GPU. “Our goal was to create something that had never been done before,” said Gabriele Leone, creative director at NVIDIA, who led Read article > The post The Wheel Deal: ‘Racer RTX’ Demo Revs to Photorealistic Life, Built on NVIDIA Omniverse appeared first on NVIDIA […]

by GeForce NOW Community (NVIDIA Blog) on September 29, 2022

It’s good to be a GeForce NOW member. Genshin Impact’s new Version 3.1 update launches this GFN Thursday, just in time for the game’s second anniversary. Even better: GeForce NOW members can get an exclusive starter pack reward, perfect for their first steps in HoYoverse’s open-world adventure, action role-playing game. And don’t forget the nine Read article > The post All This and Mor-a Are Yours With Exclusive ‘Genshin Impact’ GeForce NOW Membership Reward […]

by Machine learning : nature.com subject feeds on September 29, 2022

by Machine learning : nature.com subject feeds on September 29, 2022

by Machine learning : nature.com subject feeds on September 29, 2022

by Machine learning : nature.com subject feeds on September 29, 2022

by Machine learning : nature.com subject feeds on September 29, 2022

by Machine learning : nature.com subject feeds on September 29, 2022

by Latest News & Stories From Around The World | Uber Blog on September 28, 2022

Two weeks ago, U.S. supply chains dodged a rail strike which could have had dire economic effects and hampered our supply chains. These disruptions could have extended beyond the rail sector itself, and affected other transportation modes, primarily trucking.

by Jessica Ho (AWS Machine Learning Blog) on September 28, 2022

The rise of artificial intelligence technologies enables organizations to adopt and improve self-service capabilities in contact center operations to create a more proactive, timely, and effective customer experience. Voice bots, or conversational interactive voice response systems (IVR), use natural language processing (NLP) to understand customers’ questions and provide relevant answers. Businesses can automate responses to

by Sean Morgan (AWS Machine Learning Blog) on September 28, 2022

As businesses and IT leaders look to accelerate the adoption of machine learning (ML), there is a growing need to understand spend and cost allocation for your ML environment to meet enterprise requirements. Without proper cost management and governance, your ML spend may lead to surprises in your monthly AWS bill. Amazon SageMaker is a

by OpenAI (OpenAI) on September 28, 2022

New users can start creating straight away. Lessons learned from deployment and improvements to our safety systems make wider availability possible. Sign up Starting today, we are removing the waitlist for the DALL·E beta so users can sign up and start using it immediately. More than 1.5M

by Gerardo Delgado (NVIDIA Blog) on September 28, 2022

NVIDIA artist Sabour Amirazodi demonstrates his video editing workflows featuring AI this week in a special edition of In the NVIDIA Studio. The post Video Virtuoso Sabour Amirazodi Shares AI-Powered Editing Tips This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.

by Machine learning : nature.com subject feeds on September 28, 2022

by Ashish Lagwankar (AWS Machine Learning Blog) on September 27, 2022

Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should

by Davide Gallitelli (AWS Machine Learning Blog) on September 27, 2022

The proliferation of machine learning (ML) across a wide range of use cases is becoming prevalent in every industry. However, this outpaces the increase in the number of ML practitioners who have traditionally been responsible for implementing these technical solutions to realize business outcomes. In today’s enterprise, there is a need for machine learning to

by Jerry Peng (AWS Machine Learning Blog) on September 27, 2022

Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. You can automate the entire model build workflow, including data preparation, feature engineering, model training, model tuning, and model validation, and catalog

by Kirit Thadaka (AWS Machine Learning Blog) on September 27, 2022

Data scientists often train their models locally and look for a proper hosting service to deploy their models. Unfortunately, there’s no one set mechanism or guide to deploying pre-trained models to the cloud. In this post, we look at deploying trained models to Amazon SageMaker hosting to reduce your deployment time. SageMaker is a fully

by Machine learning : nature.com subject feeds on September 27, 2022

by Anjan Biswas (AWS Machine Learning Blog) on September 26, 2022

Today, we’re excited to announce self-service quota management support for Amazon Textract via the AWS Service Quotas console, and higher default service quotas in select AWS Regions. Customers tell us they need quick turnaround times to process their requests for quota increases and visibility into their service quotas so they may continue to scale their

by Latest News & Stories From Around The World | Uber Blog on September 26, 2022

A new on-demand mobility option in Pflugerville, Texas.

by Brenda Potts (Microsoft Research) on September 26, 2022

AI systems are becoming increasingly complex as we move from visionary research to deployable technologies such as self-driving cars, clinical predictive models, and novel accessibility devices. Unlike singular AI models, it is more difficult to assess whether these more complex AI systems are performing consistently and as intended to realize human benefit. How do we The post Assessing AI system performance: thinking beyond models to deployment contexts appeared first on […]

by Latest News & Stories From Around The World | Uber Blog on September 26, 2022

The grocery delivery experience on Uber Eats is built with your business in mind. Explore products to expand your reach, fulfill orders with ease, and grow on your terms.

by Machine learning : nature.com subject feeds on September 26, 2022

by Machine learning : nature.com subject feeds on September 26, 2022

by DeepMind Blog on September 26, 2022

We’re partnering with six education charities and social enterprises in the United Kingdom (UK) to co-create a bespoke education programme to help tackle the gaps in STEM education and boost existing programmes.

by Machine learning : nature.com subject feeds on September 26, 2022

by Machine learning : nature.com subject feeds on September 24, 2022

by Danny Shapiro (NVIDIA Blog) on September 23, 2022

Editor’s Note: This post has been updated to reflect the XPENG G9 launch. It was originally published in November 2021. You don’t need a private plane to be at the forefront of personal travel. Electric automaker XPENG launched the G9 SUV this week during NVIDIA GTC. The intelligent, software-defined vehicle is built on the high-performance Read article > The post An Elevated Experience: XPENG Launches G9 EV, Taking Innovation Even Higher with NVIDIA DRIVE Orin […]

by Goktug Cinar (AWS Machine Learning Blog) on September 23, 2022

This post is co-written by Goktug Cinar, Michael Binder, and Adrian Horvath from Bosch Center for Artificial Intelligence (BCAI). Revenue forecasting is a challenging yet crucial task for strategic business decisions and fiscal planning in most organizations. Often, revenue forecasting is manually performed by financial analysts and is both time consuming and subjective. Such manual

by Isha Salian (NVIDIA Blog) on September 23, 2022

The massive virtual worlds created by growing numbers of companies and creators could be more easily populated with a diverse array of 3D buildings, vehicles, characters and more — thanks to a new AI model from NVIDIA Research. Trained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. Read article > The post World-Class: NVIDIA Research Builds AI Model to Populate Virtual Worlds With 3D Objects, Characters […]

by Machine learning : nature.com subject feeds on September 23, 2022

by Latest News & Stories From Around The World | Uber Blog on September 22, 2022

Uber Freight hosted Deliver 2022, an annual conference that brought three days of engagement to San Antonio, Texas, providing shippers and our customers with insights from some of the most notable freight and logistics experts in the industry.

by GeForce NOW Community (NVIDIA Blog) on September 22, 2022

When it rains, it pours. And this GFN Thursday brings a downpour of news for GeForce NOW members. The Logitech G CLOUD is the latest gaming handheld device to support GeForce NOW, giving members a brand new way to keep the gaming going. But that’s not all: Portal with RTX joins GeForce NOW in November, Read article > The post Go Hands On: Logitech G CLOUD Launches With Support for GeForce NOW appeared first on NVIDIA Blog.

by Katie Burke (NVIDIA Blog) on September 22, 2022

Autonomous vehicle sensors require the same rigorous testing and validation as the car itself, and one simulation platform is up to the task. Global tier-1 supplier Continental and software-defined lidar maker AEye announced this week at NVIDIA GTC that they will migrate their intelligent lidar sensor model into NVIDIA DRIVE Sim. The companies are the Read article > The post Continental and AEye Join NVIDIA DRIVE Sim Sensor Ecosystem, Providing Rich Capabilities for AV […]

by DeepMind Blog on September 22, 2022

In our latest paper, we introduce Sparrow – a dialogue agent that’s useful and reduces the risk of unsafe and inappropriate answers. Our agent is designed to talk with a user, answer questions, and search the internet using Google when it’s helpful to look up evidence to inform its responses.

by Machine learning : nature.com subject feeds on September 22, 2022

by Machine learning : nature.com subject feeds on September 22, 2022

by Machine learning : nature.com subject feeds on September 22, 2022

by Machine learning : nature.com subject feeds on September 22, 2022

by Machine learning : nature.com subject feeds on September 22, 2022

by Katie Burke (NVIDIA Blog) on September 21, 2022

As personal transportation becomes electrified and automated, time in the vehicle has begun to resemble that of a living space rather than a mind-numbing commute. Companies are creating innovative ways for drivers and passengers to make the most of this experience, using the flexibility and modularity of NVIDIA DRIVE IX. In-vehicle technology companies Cerence, Smart Read article > The post Inside AI: NVIDIA DRIVE Ecosystem Creates Pioneering In-Cabin Features With NVIDIA […]

by Katie Burke (NVIDIA Blog) on September 21, 2022

Breakthroughs in centralized, high performance computing aren’t just opening up new functionality for autonomous driving, but for the in-vehicle experience as well. With the introduction of NVIDIA DRIVE Thor, automakers can build unified AI compute platforms that combine advanced driver-assistance systems and in-vehicle infotainment. The centralized NVIDIA DRIVE architecture supports novel features in the vehicle, Read article > The post HARMAN to Deliver Immersive […]

by Alec Radford (OpenAI) on September 21, 2022

We’ve trained and are open-sourcing a neural net called Whisper that approaches human level robustness and accuracy on English speech recognition. Read Paper View Code View Model Card Whisper examples: Reveal Transcript Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of […]

by Scott Martin (NVIDIA Blog) on September 21, 2022

Whether for virtual assistants, transcriptions or contact centers, voice AI services are turning words and conversations into bits and bytes of business magic. At GTC this week, NVIDIA announced new additions to NVIDIA Riva, a GPU-accelerated software development kit for building and deploying speech AI applications. Riva’s pretrained models are now offered in seven languages, Read article > The post Now You’re Speaking My Language: NVIDIA Riva Sets New Bar for Fully […]

by Brian Caulfield (NVIDIA Blog) on September 21, 2022

Dentists get a bad rap. Dentists also get more people out of more aggravating pain than just about anyone. Which is why the more technology dentists have, the better. Overjet, a member of the NVIDIA Inception program for startups, is moving fast to bring AI to dentists’ offices. On this episode of the NVIDIA AI Read article > The post A Podcast With Teeth: How Overjet Brings AI to Dentists’ Offices appeared first on NVIDIA Blog.

by Angie Lee (NVIDIA Blog) on September 20, 2022

South Korea’s most popular AI voice assistant, GiGA Genie, has conversed with 8 million people. The AI-powered speaker from telecom company KT can control TVs, offer real-time traffic updates and complete a slew of other home-assistance tasks based on voice commands. It has mastered its conversational skills in the highly complex Korean language thanks to Read article > The post No Hang Ups With Hangul: KT Trains Smart Speakers, Customer Call Centers With NVIDIA AI […]

by Tony Paikeday (NVIDIA Blog) on September 20, 2022

At GTC today, NVIDIA unveiled a number of updates to its DGX portfolio to power new breakthroughs in enterprise AI development. NVIDIA DGX H100 systems are now available for order. These infrastructure building blocks support NVIDIA’s full-stack enterprise AI solutions. With 32 petaflops of performance at FP8 precision, NVIDIA DGX H100 delivers a leap in Read article > The post New NVIDIA DGX System Software and Infrastructure Solutions Supercharge Enterprise AI […]

by Brian Caulfield (NVIDIA Blog) on September 20, 2022

New cloud services to support AI workflows and the launch of a new generation of GeForce RTX GPUs featured today in NVIDIA CEO Jensen Huang’s GTC keynote, which was packed with new systems, silicon, and software. “Computing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,” Read article > The post Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud appeared first on NVIDIA […]

by Stephanie Rubenstein (NVIDIA Blog) on September 20, 2022

Meet Violet, an AI-powered customer service assistant ready to take your order. Unveiled this week at GTC, Violet is a cloud-based avatar that represents the latest evolution in avatar development through NVIDIA Omniverse Avatar Cloud Engine (ACE), a suite of cloud-native AI microservices that make it easier to build and deploy intelligent virtual assistants and Read article > The post NVIDIA Omniverse ACE Enables Easier, Faster Deployment of Interactive Avatars appeared […]

by Delilah Liu (NVIDIA Blog) on September 20, 2022

The latest release of NVIDIA Maxine is paving the way for real-time audio and video communications. Whether for a video conference, a call made to a customer service center, or a live stream, Maxine enables clear communications to enhance virtual interactions. NVIDIA Maxine is a suite of GPU-accelerated AI software development kits (SDKs) and cloud-native Read article > The post New NVIDIA Maxine Cloud-Native Architecture Delivers Breakthrough Audio and Video Quality at […]

by Latest News & Stories From Around The World | Uber Blog on September 20, 2022

Your business deserves a frictionless experience working with Uber Eats. Explore education resources that can help you make the most of the platform.

by Latest News & Stories From Around The World | Uber Blog on September 19, 2022

Sustainability insights in the Uber for Business dashboard give global corporate clients the ability to track carbon emissions.

by Alyssa Hughes (Microsoft Research) on September 19, 2022

As AI becomes more deeply integrated into every aspect of our lives, it is essential that AI systems perform appropriately for their intended use. We know AI models can never be perfect, so how do we decide when AI performance is ‘good enough’ for use in a real life application? Is level of accuracy a The post AI Models vs. AI Systems: Understanding Units of Performance Assessment appeared first on Microsoft Research.

by Latest News & Stories From Around The World | Uber Blog on September 19, 2022

Eligible vehicles for the launch of Uber Premier in Philadelphia.

by Latest News & Stories From Around The World | Uber Blog on September 15, 2022

Uber’s infrastructure engineers deep dive into how they leverage Infrastructure as code to manage hundreds of thousands of servers across multiple cloud and on-prem providers.

by (AI) on September 15, 2022

I joined Google earlier this year to lead a new function: Technology & Society. Our aim is to help connect research, people and ideas across Google to shape the future of our technology innovations and their impact on society for the better. A key area of focus is AI, a field I have studied and immersed myself in over the years. I recently met with a team at the Google AI Center in Ghana that is using advanced technology to address an ancient problem: detecting locust […]

by Latest News & Stories From Around The World | Uber Blog on September 15, 2022

Crown Royal and Uber Eats are matching tips up to $5 during the NFL season. Let’s celebrate generous delivery drivers!

by Alyssa Hughes (Microsoft Research) on September 14, 2022

Today, we are experiencing waves of breakthroughs in computing that are transforming just about every aspect of our lives. Artificial intelligence is changing the way we develop and create. Human language technologies are revolutionizing the workflows of healthcare professionals. Deep learning is accelerating our ability to understand and predict natural phenomena, from atomic to galactic The post Microsoft Research Summit 2022: What’s Next for Technology and Humanity? […]

by Brenda Potts (Microsoft Research) on September 14, 2022

Online trust has come a long way since the time of centralized databases, where information was concentrated in one location and the security and validation of that information relied on a core set of people and systems. While convenient, this model of centralized management and oversight had a number of drawbacks. Trust depended on how The post CCF: Bringing efficiency and usability to a decentralized trust model appeared first on Microsoft Research.

by DeepMind Blog on September 14, 2022

Our Operating Principles have come to define both our commitment to prioritising widespread benefit, as well as the areas of research and applications we refuse to pursue. These principles have been at the heart of our decision making since DeepMind was founded, and continue to be refined as the AI landscape changes and grows. They are designed for our role as a research-driven science company and consistent with Google’s AI principles.

by Latest News & Stories From Around The World | Uber Blog on September 9, 2022

The Pinellas Suncoast Transit Authority taps into Uber to connect 3 counties and extend transit service on nights and weekends

by DeepMind Blog on September 9, 2022

Colin, CBO at DeepMind, discusses collaborations with Alphabet and how we integrate ethics, accountability, and safety into everything we do.

by Latest News & Stories From Around The World | Uber Blog on September 8, 2022

Today, Uber partner LISC opens Health Access Fund applications to organizations across the U.S., helping tackle health inequality.

by Latest News & Stories From Around The World | Uber Blog on September 8, 2022

One of the most noteworthy events of the year for our shippers—Deliver 2022—is just a couple of days away. 

by Latest News & Stories From Around The World | Uber Blog on September 8, 2022

Our engineers discuss how we dedupe and store millions of product images at Uber Eats using a content-addressable caching layer, which saves millions of image downloads every hour and ensures that every image is only stored once.

by DeepMind Blog on September 8, 2022

Former intern turned intern manager, Richard Everett, describes his journey to DeepMind, sharing tips and advice for aspiring DeepMinders. The 2023 internship applications will open on the 16th September, please visit https://dpmd.ai/internshipsatdeepmind for more information.

by Alyssa Hughes (Microsoft Research) on September 7, 2022

Despite increasingly widespread use of machine learning (ML) in all aspects of our lives, a broad class of scenarios still rely on automation designed by people, not artificial intelligence (AI). In real-world applications that involve making sequences of decisions with long-term consequences, from allocating beds in an intensive-care unit to controlling robots, decision-making strategies to The post A game-theoretic approach to provably correct and scalable offline RL […]

by Latest News & Stories From Around The World | Uber Blog on September 7, 2022

Uber’s Autonomous Mobility and Delivery team shares its safety guidelines for autonomous vehicles to deploy and operate on the Uber Platform.

by Latest News & Stories From Around The World | Uber Blog on September 6, 2022

Uber Eats & Yankees Legendary Order Sweepstakes Official Rules

by DeepMind Blog on September 6, 2022

Our new paper, In conversation with AI: aligning language models with human values, explores a different approach, asking what successful communication between humans and an artificial conversational agent might look like and what values should guide conversation in these contexts.

by OpenAI (OpenAI) on August 31, 2022

Extend creativity and tell a bigger story with DALL-E images of any size Original outpainting by Emma Catnip Today we’re introducing Outpainting, a new feature which helps users extend their creativity by continuing an image beyond its original borders — adding visual elements in the same style, or

by DeepMind Blog on August 31, 2022

by (AI) on August 25, 2022

As AI technologies continue to advance, they have the potential to unlock new experiences that support more natural human-computer interactions. We see a future where you can find the information you’re looking for in the same conversational way you speak to friends and family. While there’s still lots of work to be done before this type of human-computer interaction is possible, recent research breakthroughs in generative language models — inspired by the natural […]

by Alyssa Hughes (Microsoft Research) on August 25, 2022

What would it take to get humanoid, bipedal robots to dance like Mick Jagger? Indeed, for something more mundane, what does it take to get them to simply stand still? Sit down? Walk? Move in myriads of other ways many people take for granted? Bipedalism provides unparalleled versatility in an environment designed for and by The post MoCapAct: Training humanoid robots to “Move Like Jagger” appeared first on Microsoft Research.

by DeepMind Blog on August 25, 2022

We came across Zindi – a dedicated partner with complementary goals – who are the largest community of African data scientists and host competitions that focus on solving Africa’s most pressing problems. Our Science team’s Diversity, Equity, and Inclusion (DE&I) team worked with Zindi to identify a scientific challenge that could help advance conservation efforts and grow involvement in AI. Inspired by Zindi’s bounding box turtle challenge, we landed on a […]

by Jan Leike (OpenAI) on August 24, 2022

Our approach to aligning AGI is empirical and iterative. We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems. Introduction Our

by (AI) on August 18, 2022

If you’re like me, you may have noticed that AI has become a part of daily life. I wake up each morning and ask my smart assistant about the weather. I recently applied for a new credit card and the credit limit was likely determined by a machine learning model. And while typing the previous sentence, I got a word choice suggestion that “probably” might flow better than “likely,” a suggestion powered by AI.As a member of Google’s Responsible Innovation team, I […]

by DeepMind Blog on August 18, 2022

We want to build safe, aligned artificial general intelligence (AGI) systems that pursue the intended goals of its designers. Causal influence diagrams (CIDs) are a way to model decision-making situations that allow us to reason about agent incentives. By relating training setups to the incentives that shape agent behaviour, CIDs help illuminate potential risks before training an agent and can inspire better agent designs. But how do we know when a CID is an accurate model […]

by (AI) on August 16, 2022

Even the simplest human tasks are unbelievably complex. The way we perceive and interact with the world requires a lifetime of accumulated experience and context. For example, if a person tells you, “I am running out of time,” you don’t immediately worry they are jogging on a street where the space-time continuum ceases to exist. You understand that they’re probably coming up against a deadline. And if they hurriedly walk toward a closed door, you don’t brace for a […]

by DeepMind Blog on August 11, 2022

Meet Edgar Duéñez-Guzmán, a research engineer on our Multi-Agent Research team who’s drawing on knowledge of game theory, computer science, and social evolution to get AI agents working better together.

by Todor Markov (OpenAI) on August 10, 2022

We are introducing a new-and-improved content moderation tool: The Moderation endpoint improves upon our previous content filter, and is available for free today to OpenAI API developers. To help developers protect their applications against possible misuse, we are introducing the faster and more accurate Moderation endpoint. This endpoint provides OpenAI

by DeepMind Blog on July 28, 2022

Today, in partnership with EMBL’s European Bioinformatics Institute (EMBL-EBI), we’re now releasing predicted structures for nearly all catalogued proteins known to science, which will expand the AlphaFold DB by over 200x - from nearly 1 million structures to over 200 million structures - with the potential to dramatically increase our understanding of biology.

by OpenAI (OpenAI) on July 20, 2022

We’ll invite 1 million people from our waitlist over the coming weeks. Users can create with DALL·E using free credits that refill every month, and buy additional credits in 115-generation increments for $15. Join DALL·E 2 waitlist DALL·E, the AI system that

by Alyssa Hughes (Microsoft Research) on July 20, 2022

Large-scale models are revolutionizing deep learning and AI research, driving major improvements in language understanding, generating creative texts, multi-lingual translation and many more. But despite their remarkable capabilities, the models’ large size creates latency and cost constraints that hinder the deployment of applications on top of them. In particular, increased inference time and memory consumption The post DeepSpeed Compression: A composable library for […]

by DeepMind Blog on July 19, 2022

We recently caught up with Petar Veličković, a research scientist at DeepMind. Along with his co-authors, Petar is presenting his paper The CLRS Algorithmic Reasoning Benchmark at ICML 2022 in Baltimore, Maryland, USA.

by OpenAI (OpenAI) on July 18, 2022

Today, we are implementing a new technique so that DALL·E generates images of people that more accurately reflect the diversity of the world’s population. This technique is applied at the system level when DALL·E is given a prompt describing a person that does not

by Alyssa Hughes (Microsoft Research) on July 18, 2022

For many organizations, trusting their data to the cloud requires having a complete understanding of and control over the environment in which that data resides and how it’s being processed. Microsoft understands this, and we are committed to building a trustworthy cloud—one in which security, privacy, and transparency are built into its core. A key The post Confidential Containers: Verifiably secure computation in the cloud appeared first on Microsoft Research.

by DeepMind Blog on July 16, 2022

We develop Perceiver AR, an autoregressive, modality-agnostic architecture which uses cross-attention to map long-range inputs to a small number of latents while also maintaining end-to-end causal masking. Perceiver AR can directly attend to over a hundred thousand tokens, enabling practical long-context density estimation without the need for hand-crafted sparsity patterns or memory mechanisms.

by DeepMind Blog on July 15, 2022

Starting this weekend, the thirty-ninth International Conference on Machine Learning (ICML 2022) is meeting from 17-23 July, 2022 at the Baltimore Convention Center in Maryland, USA, and will be running as a hybrid event. Researchers working across artificial intelligence, data science, machine vision, computational biology, speech recognition, and more are presenting and publishing their cutting-edge work in machine learning.

by OpenAI (OpenAI) on July 14, 2022

As part of our DALL·E 2 research preview, more than 3,000 artists from more than 118 countries have incorporated DALL·E into their creative workflows. The artists in our early access group have helped us discover new uses for DALL·E and have served as

by DeepMind Blog on July 14, 2022

by DeepMind Blog on July 11, 2022

Despite significant effort, current AI systems pale in their understanding of intuitive physics, in comparison to even very young children. In the present work, we address this AI problem, specifically by drawing on the field of developmental psychology.

by Alyssa Hughes (Microsoft Research) on July 7, 2022

Over the coming decade, deep learning looks set to have a transformational impact on the natural sciences. The consequences are potentially far-reaching and could dramatically improve our ability to model and predict natural phenomena over widely varying scales of space and time. Could this capability represent the dawn of a new paradigm of scientific discovery? The post AI4Science to empower the fifth paradigm of scientific discovery appeared first on Microsoft Research.

by (AI) on July 6, 2022

Over the last year, we’ve seen artificial intelligence (AI) systems advance our work in areas like inclusive product development and support for small businesses and job seekers. We’ve also seen its potential to be helpful in addressing major global needs — like forecasting and planning humanitarian responses to natural disasters, addressing global environmental challenges, and delivering groundbreaking scientific research.AI is exciting — both from a technical […]

by DeepMind Blog on July 4, 2022

In our recent paper, published in Nature Human Behaviour, we provide a proof-of-concept demonstration that deep reinforcement learning (RL) can be used to find economic policies that people will vote for by majority in a simple game. The paper thus addresses a key challenge in AI research - how to train AI systems that align with human values.

by (AI) on June 30, 2022

Five years ago, information designer Mahima Pushkarna joined Google to make data easier to understand. As a senior interaction designer on the People + AI Research (PAIR) team, she designed Data Cards to help everyone better understand the contexts of the data they are using. The Data Cards Playbook puts Google’s AI Principles into practice by providing opportunities for feedback, relevant explanations and appeal.Recently, Mahima’s paper on Data Cards (co-written with […]

by (AI) on June 29, 2022

Natural language processing (NLP) is a form of artificial intelligence that teaches computer programs how to take in, interpret, and produce language from large data sets. For example, grammar checkers use NLP to come up with grammar suggestions that help people write grammatically correct phrases. But as Google’s AI Principles note, it’s sometimes necessary to have human intervention to identify risks of unfair bias.Sunipa Dev is a research scientist at Google who […]

by Alex Nichol (OpenAI) on June 28, 2022

In order to share the magic of DALL·E 2 with a broad audience, we needed to reduce the risks associated with powerful image generation models. To this end, we put various guardrails in place to prevent generated images from violating our content policy. This post focuses on pre-training

by Bowen Baker (OpenAI) on June 23, 2022

We trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using only a small amount of labeled contractor data. With fine-tuning, our model can learn to craft diamond tools, a task that usually takes proficient humans over

by DeepMind Blog on June 23, 2022

by (AI) on June 22, 2022

Have you ever seen a puppy in a nest emerging from a cracked egg? What about a photo that’s overlooking a steampunk city with airships? Or a picture of two robots having a romantic evening at the movies? These might sound far-fetched, but a novel type of machine learning technology called text-to-image generation makes them possible. These models can generate high-quality, photorealistic images from a simple text prompt.Within Google Research, our scientists and engineers […]

by DeepMind Blog on June 20, 2022

We present BYOL-Explore, a conceptually simple yet general approach for curiosity-driven exploration in visually-complex environments. BYOL-Explore learns a world representation, the world dynamics, and an exploration policy all-together by optimizing a single prediction loss in the latent space with no additional auxiliary objective. We show that BYOL-Explore is effective in DM-HARD-8, a challenging partially-observable continuous-action hard-exploration benchmark with […]

by DeepMind Blog on June 17, 2022

According to empirical evidence from prior works, utility degradation in DP-SGD becomes more severe on larger neural network models – including the ones regularly used to achieve the best performance on challenging image classification benchmarks. Our work investigates this phenomenon and proposes a series of simple modifications to both the training procedure and model architecture, yielding a significant improvement on the accuracy of DP training on standard image […]

by DeepMind Blog on June 15, 2022

Today we caught up with Gemma Jennings, a product manager on the Applied team, who led a session on vision language models at the AI Summit, one of the world’s largest AI events for business.

by Jan Leike (OpenAI) on June 13, 2022

Showing model-generated critical comments to humans helps them find flaws in summaries.

by Lilian Weng (OpenAI) on June 9, 2022

Large neural networks are at the core of many recent advances in AI, but training them is a difficult engineering and research challenge which requires orchestrating a cluster of GPUs to perform a single synchronized calculation. As cluster and model sizes have grown, machine learning practitioners have developed an increasing

by (AI) on June 9, 2022

At Google we use technologies like machine learning (ML) to build more useful products — from filtering out email spam, to keeping maps up to date, to offering more relevant search results. Chrome is no exception: We use ML to make web images more accessible to people who are blind or have low vision, and we also generate real-time captions for online videos, in service of people in noisy environments, and those who are hard of hearing.This work in Chrome continues, so we […]

by OpenAI (OpenAI) on June 2, 2022

Cohere, OpenAI, and AI21 Labs have developed a preliminary set of best practices applicable to any organization developing or deploying large language models. Computers that can read and write are here, and they have the potential to fundamentally impact daily life. The future of human–machine interaction is full

by DeepMind Blog on June 1, 2022

Research scientist, Kevin McKee, tells how his early love of science fiction and social psychology inspired his career, and how he’s helping advance research in ‘queer fairness’, support human-AI collaboration, and study the effects of AI on the LGBTQ+ community.

by DeepMind Blog on May 27, 2022

In this paper, we assess the merits of these existing evaluation metrics and present a novel approach to evaluation called the Standardised Test Suite (STS). The STS uses behavioural scenarios mined from real human interaction data.

by DeepMind Blog on May 26, 2022

My day can vary, it really depends on which phase of the project I'm on. Let’s say we want to add a feature to our product – my tasks could range from designing solutions and working with the team to find the best one, to deploying new features into production and doing maintenance. Along the way, I’ll communicate changes to our stakeholders, write docs, code and test solutions, build analytics dashboards, clean-up old code, and fix bugs.

by DeepMind Blog on May 26, 2022

To study how semi-parametric QA models and their underlying parametric language models (LMs) adapt to evolving knowledge, we construct a new large-scale dataset, StreamingQA, with human written and generated questions asked on a given date, to be answered from 14 years of time-stamped news articles. We evaluate our models quarterly as they read new articles not seen in pre-training. We show that parametric models can be updated without full retraining, while avoiding […]

by OpenAI (OpenAI) on May 24, 2022

Codex is now powering 70 different applications across a variety of use cases through the OpenAI API.

by DeepMind Blog on May 24, 2022

When I joined DeepMind as COO, I did so in large part because I could tell that the founders and team had the same focus on positive social impact. In fact, at DeepMind, we now champion a term that perfectly captures my own values and hopes for integrating technology into people’s daily lives: pioneering responsibly. I believe pioneering responsibly should be a priority for anyone working in tech. But I also recognise that it’s especially important when it comes to […]

by DeepMind Blog on May 23, 2022

In October 2021, we announced that we acquired the MuJoCo physics simulator, and made it freely available for everyone to support research everywhere. We also committed to developing and maintaining MuJoCo as a free, open-source, community-driven project with best-in-class capabilities. Today, we’re thrilled to report that open sourcing is complete and the entire codebase is on GitHub! Here, we explain why MuJoCo is a great platform for open-source collaboration and share […]

by (AI) on May 19, 2022

Editor’s note: Today is Global Accessibility Awareness Day. We’re also sharing how we’re making education more accessibleand launching a newAndroid accessibility feature.Over the past nine years, my job has focused on building accessible products and supporting Googlers with disabilities. Along the way, I’ve been constantly reminded of how vast and diverse the disability community is, and how important it is to continue working alongside this community to build […]

by DeepMind Blog on May 19, 2022

If you want to be at DeepMind, go for it. Apply, interview, and just try. You might not get it the first time but that doesn’t mean you can’t try again. I never thought DeepMind would accept me, and when they did, I thought it was a mistake. Everyone doubts themselves – I’ve never felt like the smartest person in the room. I’ve often felt the opposite. But I’ve learned that, despite those feelings, I do belong and I do deserve to work at a place like this. And […]

by Joanne Jang (OpenAI) on May 18, 2022

Early users have created over 3 million images to date and helped us improve our safety processes. We're excited to begin adding up to 1,000 new users from our waitlist each week.

by DeepMind Blog on May 16, 2022

In our recent paper, we explore how populations of deep reinforcement learning (deep RL) agents can learn microeconomic behaviours, such as production, consumption, and trading of goods. We find that artificial agents learn to make economically rational decisions about production, consumption, and prices, and react appropriately to supply and demand changes.

by DeepMind Blog on May 12, 2022

Inspired by progress in large-scale language modelling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button […]

by (AI) on May 11, 2022

Seeing yourself reflected in the world around you — in real life, media or online — is so important. And we know that challenges with image-based technologies and representation on the web have historically left people of color feeling overlooked and misrepresented. Last year, we announced Real Tone for Pixel, which is just one example of our efforts to improve representation of diverse skin tones across Google products.Today, we're introducing a next step in our […]

by (AI) on May 11, 2022

For years, Google Translate has helped break down language barriers and connect communities all over the world. And we want to make this possible for even more people — especially those whose languages aren’t represented in most technology. So today we’ve added 24 languages to Translate, now supporting a total of 133 used around the globe.Over 300 million people speak these newly added languages — like Mizo, used by around 800,000 people in the far northeast of […]

by (AI) on May 11, 2022

[TL;DR]Nearly 24 years ago, Google started with two graduate students, one product, and a big mission: to organize the world’s information and make it universally accessible and useful. In the decades since, we’ve been developing our technology to deliver on that mission.The progress we've made is because of our years of investment in advanced technologies, from AI to the technical infrastructure that powers it all. And once a year — on my favorite day of the year 🙂 […]

by (AI) on May 11, 2022

Language is at the heart of how people communicate with each other. It’s also proving to be powerful in advancing AI and building helpful experiences for people worldwide.From the beginning, we set out to connect words in your search to words on a page so we could make the web’s information more accessible and useful. Over 20 years later, as the web changes, and the ways people consume information expand from text to images to videos and more — the one constant is that […]

by (AI) on May 11, 2022

Google Maps helps over one billion people navigate and explore. And over the past few years, our investments in AI have supercharged the ability to bring you the most helpful information about the real world, including when a business is open and how crowded your bus is. Today at Google I/O, we announced new ways the latest advancements in AI are transforming Google Maps — helping you explore with an all-new immersive view of the world, find the most fuel-efficient route, […]

by (AI) on May 11, 2022

Today at I/O we released the Monk Skin Tone (MST) Scale in partnership with Harvard professor and sociologist Dr. Ellis Monk. The MST Scale, developed by Dr. Monk, is a 10-shade scale designed to be more inclusive of the spectrum of skin tones in our society. We’ll be incorporating the MST Scale into various Google products over the coming months, and we are openly releasing the scale so that anyone can use it for research and product development.The MST Scale is an […]

by DeepMind Blog on May 6, 2022

To make RL more applicable to real-world applications like robotics, we propose using an intelligent evaluation procedure to select the policy for deployment, called active offline policy selection (A-OPS). In A-OPS, we make use of the prerecorded dataset and allow limited interactions with the real environment to boost the selection quality.

by DeepMind Blog on April 28, 2022

We caught up with Kevin Millikin, a software engineer on the DevTools team. He’s in Salt Lake City this week to present at PyCon US, the largest annual gathering for those using and developing the open-source Python programming language.

by DeepMind Blog on April 28, 2022

We introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal tasks.

by DeepMind Blog on April 25, 2022

Beyond supporting the event as sponsors and regular workshop organisers, our research teams are presenting 29 papers, including 10 collaborations this year. Here’s a brief glimpse into our upcoming oral, spotlight, and poster presentations.

by DeepMind Blog on April 12, 2022

We ask the question: “What is the optimal model size and number of training tokens for a given compute budget?” To answer this question, we train models of various sizes and with various numbers of tokens, and estimate this trade-off empirically. Our main finding is that the current large language models are far too large for their compute budget and are not being trained on enough data.

by (AI) on April 11, 2022

It was an honor and a privilege to attend a special event in the Bulgarian capital, Sofia, today to launch INSAIT, the Institute for Computer Science, Artificial Intelligence and Technology. INSAIT is a new AI and computer science research institute that will provide truly world-class facilities.It’s fantastic to see the country where I was born leading the charge in bridging Eastern Europe to the world-stage in computer science research.The institute is modeled on the […]

by (AI) on April 7, 2022

Building a map is complex, and keeping it up-to-date is even more challenging. Think about how often your city, town or neighborhood changes on a day-to-day basis. Businesses and shops open and close, stretches of highway are added, and roadways change. In today’s Maps 101 installment, we’ll dive into two ways Google Maps uses advancements in AI and imagery to help you see the latest information about the world around you every single day.Automatically updating business […]

by (AI) on March 29, 2022

At Google, Marian Croak’s technical research team, The Center for Responsible AI and Human-Centered Technology, and Jen Gennai’s operations and governance team, Responsible Innovation, collaborate often on creating a fairer future for AI systems.The teams complement each other to support computer scientists, UX researchers and designers, product managers and subject matter experts in the social sciences, human rights and civil rights. Collectively, their teams include […]

by (AI) on March 29, 2022

Carrie Cai, Ben Zevenbergen and Johnny Soraker all work on developing artificial intelligence (AI) responsibly at Google, in the larger research community and across the technology industry. Carrie is a research scientist focusing on human-AI interaction, Ben is an ethicist and policy advisor and Johnny is an AI Principles ethicist. They all work within a global team of experts from a variety of fields, including the social sciences and humanities, focused on the ethical […]

by DeepMind Blog on March 16, 2022

Language models like Gopher can “hallucinate” facts that appear plausible but are actually fake. Those who are familiar with this problem know to do their own fact-checking, rather than trusting what language models say. Those who are not, may end up believing something that isn’t true. This paper describes GopherCite, a model which aims to address the problem of language model hallucination. GopherCite attempts to back up all of its factual claims with evidence from […]

by DeepMind Blog on March 9, 2022

The birth of human writing marked the dawn of History and is crucial to our understanding of past civilisations and the world we live in today. For example, more than 2,500 years ago, the Greeks began writing on stone, pottery, and metal to document everything from leases and laws to calendars and oracles, giving a detailed insight into the Mediterranean region. Unfortunately, it’s an incomplete record. Many of the surviving inscriptions have been damaged over the […]

by DeepMind Blog on March 3, 2022

In this work, we use deep reinforcement learning to generate artificial agents capable of test-time cultural transmission. Once trained, our agents can infer and recall navigational knowledge demonstrated by experts. This knowledge transfer happens in real time and generalises across a vast space of previously unseen tasks.

by DeepMind Blog on February 23, 2022

Multimodal Image-Language transformers have achieved impressive results on a variety of tasks that rely on fine-tuning (e.g., visual question answering and image retrieval). We are interested in shedding light on the quality of their pretrained representations--in particular, if these models can distinguish verbs or they only use the nouns in a given sentence. To do so, we collect a dataset of image-sentence pairs consisting of 447 verbs that are either visual or commonly […]

by DeepMind Blog on February 16, 2022

Successfully controlling the nuclear fusion plasma in a tokamak with deep reinforcement learning

by DeepMind Blog on February 11, 2022

Collaborating with YouTube to optimise video compression in the open source VP9 codec.

by DeepMind Blog on February 7, 2022

In our recent paper, we show that it is possible to automatically find inputs that elicit harmful text from language models by generating inputs using language models themselves. Our approach provides one tool for finding harmful model behaviours before users are impacted, though we emphasize that it should be viewed as one component alongside many other techniques that will be needed to find harms and mitigate them once found.

by DeepMind Blog on February 2, 2022

Solving novel problems and setting a new milestone in competitive programming.

by DeepMind Blog on January 25, 2022

We believe artificial intelligence (AI) is one of the most significant technologies of our age and we want to help people understand its potential and how it’s being created.

by DeepMind Blog on January 18, 2022

In our recent paper we explore how multi-agent deep reinforcement learning can serve as a model of complex social interactions, like the formation of social norms. This new class of models could provide a path to create richer, more detailed simulations of the world.

by DeepMind Blog on December 9, 2021

Solving some of the major challenges of the 21st Century, such as producing clean electricity or developing high temperature superconductors, will require us to design new materials with specific properties. To do this on a computer requires the simulation of electrons, the subatomic particles that govern how atoms bond to form molecules and are also responsible for the flow of electricity in solids.

by DeepMind Blog on December 8, 2021

We explore an alternate path for improving language models: we augment transformers with retrieval over a database of text passages including web pages, books, news and code. We call our method RETRO, for “Retrieval Enhanced TRansfOrmers”.

by DeepMind Blog on December 8, 2021

Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memories, and build mutual understanding. These are foundational parts of social intelligence. It’s why our teams at DeepMind study aspects of language processing and communication, both in artificial agents and in humans.

by DeepMind Blog on December 8, 2021

We show that imitation learning of human-human interactions in a simulated world, in conjunction with self-supervised learning, is sufficient to produce a multimodal interactive agent, which we call MIA, that successfully interacts with non-adversarial humans 75% of the time. We further identify architectural and algorithmic techniques that improve performance, such as hierarchical action selection.

by DeepMind Blog on December 1, 2021

Our main results prove that while reward can express many tasks, there exist instances of each task type that no Markov reward function can capture. We then provide a set of polynomial-time algorithms that construct a reward function which allows an agent to optimize tasks of each of these three types, and correctly determine when no such reward function exists.

by DeepMind Blog on December 1, 2021

More than a century ago, Srinivasa Ramanujan shocked the mathematical world with his extraordinary ability to see remarkable patterns in numbers that no one else could see. The self-taught mathematician from India described his insights as deeply intuitive and spiritual, and patterns often came to him in vivid dreams.

by DeepMind Blog on November 9, 2021

Our brain has an amazing ability to process visual information. We can take one glance at a complex scene, and within milliseconds be able to parse it into objects and their attributes, like colour or size, and use this information to describe the scene in simple language. Underlying this seemingly effortless ability is a complex computation performed by our visual cortex, which involves taking millions of neural impulses transmitted from the retina and transforming them […]

by DeepMind Blog on November 2, 2021

When people picture a world with artificial general intelligence (AGI), robots are more likely to come to mind than enabling solutions to society’s most intractable problems. But I believe the latter is much closer to the truth. AI is already enabling huge leaps in tackling fundamental challenges: from solving protein folding to predicting accurate weather patterns, scientists are increasingly using AI to deduce the rules and principles that underpin highly complex […]

by DeepMind Blog on October 18, 2021

When you walk, your feet make contact with the ground. When you write, your fingers make contact with the pen. Physical contacts are what makes interaction with the world possible. Yet, for such a common occurrence, contact is a surprisingly complex phenomenon. Taking place at microscopic scales at the interface of two bodies, contacts can be soft or stiff, bouncy or spongy, slippery or sticky. It’s no wonder our fingertips have four different types of touch-sensors. This […]

by DeepMind Blog on October 11, 2021

Picking up a stick and balancing it atop a log or stacking a pebble on a stone may seem like simple — and quite similar — actions for a person. However, most robots struggle with handling more than one such task at a time. Manipulating a stick requires a different set of behaviours than stacking stones, never mind piling various dishes on top of one another or assembling furniture. Before we can teach robots how to perform these kinds of tasks, they first need to learn […]

by DeepMind Blog on October 4, 2021

When the Human Genome Project succeeded in mapping the DNA sequence of the human genome, the international research community were excited by the opportunity to better understand the genetic instructions that influence human health and development. DNA carries the genetic information that determines everything from eye colour to susceptibility to certain diseases and disorders. The roughly 20,000 sections of DNA in the human body known as genes contain instructions about the […]

by DeepMind Blog on September 29, 2021

Our lives are dependent on the weather. At any moment in the UK, according to one study, one third of the country has talked about the weather in the past hour, reflecting the importance of weather in daily life. Amongst weather phenomena, rain is especially important because of its influence on our everyday decisions. Should I take an umbrella? How should we route vehicles experiencing heavy rain? What safety measures do we take for outdoor events? Will there be a flood? […]

by DeepMind Blog on August 3, 2021

Most architectures used by AI systems today are specialists. A 2D residual network may be a good choice for processing images, but at best it’s a loose fit for other kinds of data — such as the Lidar signals used in self-driving cars or the torques used in robotics. What’s more, standard architectures are often designed with only one task in mind, often leading engineers to bend over backwards to reshape, distort, or otherwise modify their inputs and outputs in hopes […]

by DeepMind Blog on July 27, 2021

In recent years, artificial intelligence agents have succeeded in a range of complex game environments. For instance, AlphaZero beat world-champion programs in chess, shogi, and Go after starting out with knowing no more than the basic rules of how to play. Through reinforcement learning (RL), this single system learnt by playing round after round of games through a repetitive process of trial and error. But AlphaZero still trained separately on each game — unable to […]

by DeepMind Blog on July 22, 2021

When we announced AlphaFold 2 last December, it was hailed as a solution to the 50-year old protein folding problem. Last week, we published the scientific paper and source code explaining how we created this highly innovative system, and today we’re sharing high-quality predictions for the shape of every single protein in the human body, as well as for the proteins of 20 additional organisms that scientists rely on for their research.

by DeepMind Blog on June 4, 2021

In June 2020, after George Floyd was killed in Minneapolis (USA) and the solidarity that followed as millions spoke out at Black Lives Matter protests around the world, I – like many others – reflected on the situation and how our organisation could contribute. I then shared some thoughts around DeepMind's intention to help combat racism and advance racial equity.

by DeepMind Blog on May 7, 2021

Creating testing environments to help progress AI research out of the lab and into the real world is immensely challenging. Given AI’s long association with games, it is perhaps no surprise that sports presents an exciting opportunity, offering researchers a testbed in which an AI-enabled system can assist humans in making complex, real-time decisions in a multiagent environment with dozens of dynamic, interacting individuals.

by DeepMind Blog on May 6, 2021

Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an exam. By training on many example problems, they minimise their mistakes over time until they achieve success. But this is a solitary endeavour and only one of the known forms of learning. Learning also takes place by interacting and playing with others. It’s rare that a single individual can solve extremely complex […]

by DeepMind Blog on December 23, 2020

In 2016, we introduced AlphaGo, the first artificial intelligence (AI) program to defeat humans at the ancient game of Go. Two years later, its successor - AlphaZero - learned from scratch to master Go, chess and shogi. Now, in a paper in the journal Nature, we describe MuZero, a significant step forward in the pursuit of general-purpose algorithms. MuZero masters Go, chess, shogi and Atari without needing to be told the rules, thanks to its ability to plan winning […]

by DeepMind Blog on December 4, 2020

DeepMind engineers accelerate our research by building tools, scaling up algorithms, and creating challenging virtual and physical worlds for training and testing artificial intelligence (AI) systems. As part of this work, we constantly evaluate new machine learning libraries and frameworks.

by DeepMind Blog on November 30, 2020

Proteins are essential to life, supporting practically all its functions. They are large complex molecules, made up of chains of amino acids, and what a protein does largely depends on its unique 3D structure. Figuring out what shapes proteins fold into is known as the “protein-folding problem”, and has stood as a grand challenge in biology for the past 50 years. In a major scientific advance, the latest version of our AI system AlphaFold has been recognised as a […]

by DeepMind Blog on November 5, 2020

This week, we welcomed our biggest and most geographically diverse cohort of DeepMind scholars yet. We’re excited to reflect on the journey so far, share more on the next chapter of the DeepMind scholarships – and welcome many more universities from around the world into the programme.

by DeepMind Blog on October 19, 2020

In an article recently published in Physical Review Research, we show how deep learning can help solve the fundamental equations of quantum mechanics for real-world systems. Not only is this an important fundamental scientific question, but it also could lead to practical uses in the future, allowing researchers to prototype new materials and chemical syntheses in silico before trying to make them in the lab. Today we are also releasing the code from this study so that the […]

by DeepMind Blog on October 12, 2020

Imagine if you had to learn how to chop, peel and stir all over again every time you wanted to learn a new recipe. In many machine learning systems, agents often have to learn entirely from scratch when faced with new challenges. It’s clear, however, that people learn more efficiently than this: they can combine abilities previously learned. In the same way that a finite dictionary of words can be reassembled into sentences of near infinite meanings, people repurpose and […]

by DeepMind Blog on September 3, 2020

By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world. From reuniting a speech-impaired user with his original voice, to helping users discover personalised apps, we can apply breakthrough research to immediate real-world problems at a Google scale. Today we’re delighted to share the results of our latest partnership, delivering a truly global impact for the more than one billion people that use Google Maps.

by DeepMind Blog on June 23, 2020

It’s no secret that the gender gap still exists within STEM. Despite a slight increase in recent years, studies show that women only make up about a quarter of the overall STEM workforce in the UK. While the reasons vary, many women report feeling held back by a lack of representation, clear opportunities and information on what working in the sector actually involves.

by DeepMind Blog on May 18, 2020

Vision loss among the elderly is a major healthcare issue: about one in three people have some vision-reducing disease by the age of 65. Age-related macular degeneration (AMD) is the most common cause of blindness in the developed world. In Europe, approximately 25% of those 60 and older have AMD. The ‘dry’ form is relatively common among people over 65, and usually causes only mild sight loss. However, about 15% of patients with dry AMD go on to develop a more serious […]

by DeepMind Blog on April 21, 2020

Specification gaming is a behaviour that satisfies the literal specification of an objective without achieving the intended outcome. We have all had experiences with specification gaming, even if not by this name. Readers may have heard the myth of King Midas and the golden touch, in which the king asks that anything he touches be turned to gold - but soon finds that even food and drink turn to metal in his hands. In the real world, when rewarded for doing well on a homework […]

by DeepMind Blog on April 6, 2020

Under a microscope, a pane of window glass doesn’t look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable structure. Glass is made by starting with a glowing mixture of high-temperature melted sand and minerals. Once cooled, its viscosity (a measure of the friction in the fluid) increases a trillion-fold, and it becomes a solid, resisting tension from stretching or pulling. Yet the molecules in the glass remain in a […]

by DeepMind Blog on March 31, 2020

The Atari57 suite of games is a long-standing benchmark to gauge agent performance across a wide range of tasks. We’ve developed Agent57, the first deep reinforcement learning agent to obtain a score that is above the human baseline on all 57 Atari 2600 games. Agent57 combines an algorithm for efficient exploration with a meta-controller that adapts the exploration and long vs. short-term behaviour of the agent.

by DeepMind Blog on February 10, 2020

Throughout our lives, we build up memories that are retained over a diverse array of timescales, from minutes to months to years to decades. When reading a book, we can recall characters who were introduced many chapters ago, or in an earlier book in a series, and reason about their motivations and likely actions in the current context. We can even put the book down during a busy week, and pick up from where we left off without forgetting the plotline.

by DeepMind Blog on January 15, 2020

In our study published in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and machine learning to apply cutting-edge techniques to predict the 3D structure of a protein based solely on its genetic sequence.

by DeepMind Blog on January 15, 2020

Learning and motivation are driven by internal and external rewards. Many of our day-to-day behaviours are guided by predicting, or anticipating, whether a given action will result in a positive (that is, rewarding) outcome. The study of how organisms learn from experience to correctly anticipate rewards has been a productive research field for well over a century, since Ivan Pavlov's seminal psychological work. In his most famous experiment, dogs were trained to expect food […]

by DeepMind Blog on December 18, 2019

As a teenager, Tim Shaw put everything he had into football practice: his dream was to join the NFL. After playing for Penn State in college, his ambitions were finally realised: the Carolina Panthers drafted him at age 23, and he went on to play for the Chicago Bears and Tennessee Titans, where he broke records as a linebacker. After six years in the NFL, on the cusp of greatness, his performance began to falter. He couldn’t tackle like he once had; his arms slid off the […]

by DeepMind Blog on December 13, 2019

When we train reinforcement learning (RL) agents in the real world, we don’t want them to explore unsafe states, such as driving a mobile robot into a ditch or writing an embarrassing email to one’s boss. Training RL agents in the presence of unsafe states is known as the safe exploration problem. We tackle the hardest version of this problem, in which the agent initially doesn’t know how the environment works or where the unsafe states are. The agent has one source of […]

by DeepMind Blog on December 5, 2019

Since we started DeepMind nearly 10 years ago, our mission has been to unlock answers to the world’s biggest questions by understanding and recreating intelligence itself.

by DeepMind Blog on November 21, 2019

Most people have at least one crossroads moment in their life - when the choice they make defines their personal or professional trajectory. For me, it was being awarded an internship at Intel, the first one ever through Purdue’s Co-Op Engineering program in 1990.

by DeepMind Blog on November 18, 2019

Over the past few years we've applied DeepMind's technology to Google products and infrastructure, with notable successes like reducing the amount of energy needed for cooling data centers, and extending Android battery performance. We're excited to share more about our work in the coming months.

by DeepMind Blog on October 30, 2019

AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar challenged two of the world's top players in StarCraft II, one of the most enduring and popular real-time strategy video games of all time. Since then, we have taken on a much greater challenge: playing the full game at a Grandmaster level under professionally approved conditions.

by DeepMind Blog on October 3, 2019

Decisions based on machine learning (ML) are potentially advantageous over human decisions, as they do not suffer from the same subjectivity, and can be more accurate and easier to analyse. At the same time, data used to train ML systems often contain human and societal biases that can lead to harmful decisions: extensive evidence in areas such as hiring, criminal justice, surveillance, and healthcare suggests that ML decision systems can treat individuals unfavorably […]

by DeepMind Blog on September 18, 2019

Over the last three years, DeepMind has built a team to tackle some of healthcare’s most complex problems—developing AI research and mobile tools that are already having a positive impact on patients and care teams. Today, with our healthcare partners, the team is excited to officially join the Google Health family. Under the leadership of Dr. David Feinberg, and alongside other teams at Google, we’ll now be able to tap into global expertise in areas like app […]

by DeepMind Blog on September 17, 2019

In this special extended episode, Hannah Fry meets Demis Hassabis, the CEO and co-founder of DeepMind.

by DeepMind Blog on September 10, 2019

AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught how.

by DeepMind Blog on September 6, 2019

Our waking and sleeping lives are punctuated by fragments of recalled memories: a sudden connection in the shower between seemingly disparate thoughts, or an ill-fated choice decades ago that haunts us as we struggle to fall asleep. By measuring memory retrieval directly in the brain, neuroscientists have noticed something remarkable: spontaneous recollections, measured directly in the brain, often occur as very fast sequences of multiple memories. These so-called 'replay' […]

by DeepMind Blog on September 3, 2019

While there is a lot of excitement about AI research, there are also concerns about the way it might be implemented, used and abused.

by DeepMind Blog on August 27, 2019

The ambition of AI research is to create systems that can help to solve problems in the real world.

by DeepMind Blog on August 20, 2019

Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMind’s robotics laboratory, Hannah explores what researchers call ‘embodied AI’: robot arms that are learning tasks like picking up plastic bricks, which humans find comparatively easy.

by DeepMind Blog on August 19, 2019

Video games have become a favourite tool for AI researchers to test the abilities of their systems. In this episode, Hannah sits down to play StarCraft II - a challenging video game that requires players to control the onscreen action with as many as 800 clicks a minute.

by DeepMind Blog on August 18, 2019

In March 2016, more than 200 million people watched AlphaGo become first computer program to defeat a professional human player at the game of Go, a milestone in AI research that was considered to be a decade ahead of its time.

by DeepMind Blog on August 17, 2019

What can the human brain teach us about AI? And what can AI teach us about our own intelligence? These questions underpin a lot of AI research.

by DeepMind Blog on August 16, 2019

What’s AI? What can it be used for? Is it safe? And how do I get involved? These are the kinds of questions we often get asked at public events like science festivals, talks and workshops. We love answering them and really value the conversations and thinking they provoke.

by DeepMind Blog on August 8, 2019

The Serengeti is one of the last remaining sites in the world that hosts an intact community of large mammals. These animals roam over vast swaths of land, some migrating thousands of miles across multiple countries following seasonal rainfall. As human encroachment around the region becomes more intense, these species are forced to alter their behaviours in order to survive. Increasing agriculture, poaching, and climate abnormalities contribute to changes in animal […]

by DeepMind Blog on July 31, 2019

Artificial intelligence can now predict one of the leading causes of avoidable patient harm up to two days before it happens, as demonstrated by our latest research published in Nature. Working alongside experts from the US Department of Veterans Affairs (VA), we have developed technology that, in the future, could give doctors a 48-hour head start in treating acute kidney injury (AKI), a condition that is associated with over 100,000 people in the UK every year. These […]

by DeepMind Blog on July 25, 2019

Waymo’s self-driving vehicles employ neural networks to perform many driving tasks, from detecting objects and predicting how others will behave, to planning a car's next moves. Training an individual neural net has traditionally required weeks of fine-tuning and experimentation, as well as enormous amounts of computational power. Now, Waymo, in a research collaboration with DeepMind, has taken inspiration from Darwin’s insights into evolution to make this training more […]

by DeepMind Blog on June 25, 2019

Over the last decade, machine learning has made unprecedented progress in areas as diverse as image recognition, self-driving cars and playing complex games like Go. These successes have been largely realised by training deep neural networks with one of two learning paradigms—supervised learning and reinforcement learning. Both paradigms require training signals to be designed by a human and passed to the computer. In the case of supervised learning, these are the […]