ML and AI Research

by Tristan Miller (AWS Machine Learning Blog) on January 26, 2023

This post is co-authored by Tristan Miller from Best Egg. Best Egg is a leading financial confidence platform that provides lending products and resources focused on helping people feel more confident as they manage their everyday finances. Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed

by Angie Lee (NVIDIA Blog) on January 26, 2023

AI applications are summarizing articles, writing stories and engaging in long conversations — and large language models are doing the heavy lifting. A large language model, or LLM, is a deep learning algorithm that can recognize, summarize, translate, predict and generate text and other content based on knowledge gained from massive datasets. Large language models Read article >

by GeForce NOW Community (NVIDIA Blog) on January 26, 2023

GeForce NOW RTX 4080 SuperPODs are rolling out now, bringing RTX 4080-class performance and features to Ultimate members — including support for NVIDIA Ada Lovelace GPU architecture technologies like NVIDIA DLSS 3.  This GFN Thursday brings updates to some of GeForce NOW’s hottest games that take advantage of these amazing technologies, all from the cloud. Read article >

by Latest News & Stories From Around The World | Uber Blog on January 26, 2023

After leading customer facing teams in Sydney and Singapore, Mike decided to shake things up and take on the challenge of running Customer Operations at Uber in Amsterdam.

by Machine learning : nature.com subject feeds on January 26, 2023

by Machine learning : nature.com subject feeds on January 26, 2023

by Machine learning : nature.com subject feeds on January 26, 2023

by Machine learning : nature.com subject feeds on January 26, 2023

by Machine learning : nature.com subject feeds on January 26, 2023

by Alyssa Hughes (Microsoft Research) on January 25, 2023

Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Revolutionizing Document AI with multimodal document foundation models   Organizations must digitize various documents, many with charts and images, to manage and streamline essential functions. Yet manually The post Research Focus: Week of January 23, 2023 appeared first on […]

by Dhiraj Thakur (AWS Machine Learning Blog) on January 25, 2023

Today, gaining customer loyalty cannot be a one-off thing. A brand needs a focused and integrated plan to retain its best customers—put simply, it needs a customer loyalty program. Earn and burn programs are one of the main paradigms. A typical earn and burn program rewards customers after a certain number of visits or spend.

by Pinak Panigrahi (AWS Machine Learning Blog) on January 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers

by Vivek Madan (AWS Machine Learning Blog) on January 25, 2023

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Today, we announce a new feature that lets you upscale images (resize images without losing quality) with Stable Diffusion models in JumpStart. An image that is low resolution, blurry, and pixelated can be converted

by Angie Lee (NVIDIA Blog) on January 25, 2023

As its name suggests, Orbital Sidekick is creating technology that acts as a buddy in outer space, keeping an eye on the globe using satellites to help keep it safe and sustainable. The San Francisco-based startup, a member of the NVIDIA Inception program, enables commercial and government users to optimize sustainable operations and security with Read article >

by Alyssa Hughes (Microsoft Research) on January 25, 2023

We stand at the threshold of a new era of precision medicine, where health and life sciences data hold the potential to dramatically propel and expand our understanding and treatment of human disease. One of the tools that we believe will help to enable precision medicine is Terra, the secure biomedical research platform co-developed by The post Biomedical Research Platform Terra Now Available on Microsoft Azure appeared first on Microsoft Research.

by Sudip Roy (AWS Machine Learning Blog) on January 25, 2023

It’s an exciting day for the development community. Cohere’s state-of-the-art language AI is now available through Amazon SageMaker. This makes it easier for developers to deploy Cohere’s pre-trained generation language model to Amazon SageMaker, an end-to-end machine learning (ML) service. Developers, data scientists, and business analysts use Amazon SageMaker to build, train, and deploy ML models quickly and easily using its fully managed infrastructure, tools, and […]

by Magnus Weberg (NVIDIA Blog) on January 25, 2023

Jensen Huang headlines Stockholm AI confab, Berzelius supercomputer upgraded to 94 NVIDIA DGX A100 systems.

by Machine learning : nature.com subject feeds on January 25, 2023

by Machine learning : nature.com subject feeds on January 25, 2023

by Machine learning : nature.com subject feeds on January 25, 2023

by Machine learning : nature.com subject feeds on January 25, 2023

by Magnus Weberg (NVIDIA Blog) on January 24, 2023

Sweden is outfitting its AI supercomputer for a journey to the cutting edge of machine learning, robotics and healthcare. It couldn’t ask for a better guide than Anders Ynnerman (above). His signature blue suit, black spectacles and gentle voice act as calm camouflage for a pioneering spirit. Early on, he showed a deep interest in Read article >

by Gerardo Delgado (NVIDIA Blog) on January 24, 2023

Artist Ducky 3D creates immersive experiences through vibrant visuals and beautiful 3D environments in the alien-inspired animation Stylized Alien Landscape — this week In the NVIDIA Studio.

by Machine learning : nature.com subject feeds on January 24, 2023

by Machine learning : nature.com subject feeds on January 24, 2023

by Machine learning : nature.com subject feeds on January 24, 2023

by Machine learning : nature.com subject feeds on January 24, 2023

by Nicola Sessions (NVIDIA Blog) on January 23, 2023

Add AI to the list of defenses against identity attacks, one of the most common and hardest breach to prevent. More than 40% of all data compromises involved stolen credentials, according to the 2022 Verizon Data Breach Investigations Report. And a whopping 80% of all web application breaches involved credential abuse. “Credentials are the favorite Read article >

by OpenAI (OpenAI) on January 23, 2023

We're happy to announce that OpenAI and Microsoft are extending our partnership. This multi-year, multi-billion dollar investment from Microsoft follows their previous investments in 2019 and 2021, and will allow us to continue our independent research and develop AI that is increasingly safe, useful, and powerful. In pursuit

by Latest News & Stories From Around The World | Uber Blog on January 23, 2023

As a General Manager of Uber Eats in Northern, Central and Eastern Europe, Aukeline Tolman is on the forefront of bringing on demand deliciousness to people across the region.

by Isha Salian (NVIDIA Blog) on January 23, 2023

For the past 500 years, the National Library of Sweden has collected virtually every word published in Swedish, from priceless medieval manuscripts to present-day pizza menus. Thanks to a centuries-old law that requires a copy of everything published in Swedish to be submitted to the library — also known as Kungliga biblioteket, or KB — Read article >

by Machine learning : nature.com subject feeds on January 23, 2023

by Machine learning : nature.com subject feeds on January 23, 2023

by Machine learning : nature.com subject feeds on January 21, 2023

by Machine learning : nature.com subject feeds on January 21, 2023

by Christopher Diaz (AWS Machine Learning Blog) on January 20, 2023

This post is co-written by Christopher Diaz, Sam Kinard, Jaime Hidalgo and Daniel Suarez  from CCC Intelligent Solutions. In this post, we discuss how CCC Intelligent Solutions (CCC) combined Amazon SageMaker with other AWS services to create a custom solution capable of hosting the types of complex artificial intelligence (AI) models envisioned. CCC is a

by Rick Merritt (NVIDIA Blog) on January 20, 2023

The abacus, sextant, slide rule and computer. Mathematical instruments mark the history of human progress. They’ve enabled trade and helped navigate oceans, and advanced understanding and quality of life. The latest tool propelling science and industry is AI computing. AI Computing Defined AI computing is the math-intensive process of calculating machine learning algorithms, typically using Read article >

by Latest News & Stories From Around The World | Uber Blog on January 20, 2023

Couriers on Uber Eats who reach Gold status in January can qualify to enter for the chance to win two Super Bowl LVII tickets, two Tailgate tickets, and more.

by Machine learning : nature.com subject feeds on January 20, 2023

by Machine learning : nature.com subject feeds on January 20, 2023

by Machine learning : nature.com subject feeds on January 20, 2023

by Latest News & Stories From Around The World | Uber Blog on January 19, 2023

Brightline is addressing the first-/last-mile challenge by tapping into Uber’s API and including Uber among its shared mobility partners.

by Latest News & Stories From Around The World | Uber Blog on January 19, 2023

Uber heavily relies on open source technologies for the Data analytics stack. In this blog post, we dive into the technical details behind solutions that helped us scale the adoption of Kerberos for authentication for the entire Data analytics infrastructure.

by Scott Martin (NVIDIA Blog) on January 19, 2023

Robots are finally getting a grip. Developers have been striving to close the gap on robotic gripping for the past several years, pursuing applications for multibillion-dollar industries. Securely gripping and transferring fast-moving items on conveyor belts holds vast promise for businesses. Soft Robotics, a Bedford, Mass., startup, is harnessing NVIDIA Isaac Sim to help close Read article >

by (AI) on January 19, 2023

Here are nine ways we use AI today to make our products even more helpful.

by GeForce NOW Community (NVIDIA Blog) on January 19, 2023

The Ultimate upgrade begins today: GeForce NOW RTX 4080 SuperPODs are now rolling out, bringing a new level of high-performance gaming to the cloud. Ultimate members will start to see RTX 4080 performance in their region soon, and experience titles like  Warhammer 40,000: Darktide, Cyberpunk 2077, The Witcher 3: Wild Hunt and more at ultimate Read article >

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Machine learning : nature.com subject feeds on January 19, 2023

by Latest News & Stories From Around The World | Uber Blog on January 18, 2023

Athira Menon is a Senior Manager for Public Policy based in Bangalore, India, joining Uber after working in the public sector. “My role has evolved from being an individual contributor to a leader and each step of the way I have had enormously rich experiences to grow.”

by Brian Caulfield (NVIDIA Blog) on January 18, 2023

For insights into the future of generative AI, check out the latest episode of the NVIDIA AI Podcast. Host Noah Kravitz is joined by Pat Grady and Sonya Huang, partners at Sequoia Capital, to discuss their recent essay, “Generative AI: A Creative New World.” The authors delve into the potential of generative AI to enable Read article >

by Brian Caulfield (NVIDIA Blog) on January 18, 2023

As any new mom or dad can tell you, parenting can be a challenge — packed with big worries and small hassles. But it may be about to get a little bit easier thanks to Glüxkind Technologies and their smart stroller, Ella. The company has just been named a CES 2023 Innovation Awards Honoree for Read article >

by Gerardo Delgado (NVIDIA Blog) on January 18, 2023

To celebrate the upcoming Lunar New Year holiday, NVIDIA artist Zhelong Xu, aka Uncle Light, brought Chinese zodiac signs to life this week In the NVIDIA Studio — modernizing the ancient mythology in his signature style.

by Machine learning : nature.com subject feeds on January 18, 2023

by Machine learning : nature.com subject feeds on January 18, 2023

by Machine learning : nature.com subject feeds on January 18, 2023

by Cory Hairston (AWS Machine Learning Blog) on January 17, 2023

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models. In Studio, you can load data, adjust ML models, move in between steps to adjust experiments,

by Xin Huang (AWS Machine Learning Blog) on January 17, 2023

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. Understanding customer behavior is top of mind for every business today. Gaining insights into why and how customers buy can help grow revenue. Customer churn is

by Manuvir Das (NVIDIA Blog) on January 17, 2023

In their largest-ever joint AI initiative, NVIDIA and Dell Technologies today launched a wave of Dell PowerEdge systems available with NVIDIA acceleration, enabling enterprises to efficiently transform their businesses with AI. A total of 15 next-generation Dell PowerEdge systems can draw from NVIDIA’s full AI stack — including GPUs, DPUs and the NVIDIA AI Enterprise Read article >

by (AI) on January 17, 2023

Google is using AI to help people facing disease and natural disasters, and to provide new opportunities for underserved communities.

by (AI) on January 16, 2023

Today we published a paper outlining why we pursue AI. Read on for a preview, or visit ai.google to see the paper in full.

by Jenn Bergstrom (AWS Machine Learning Blog) on January 13, 2023

This post is co-written with Jennifer Bergstrom, Sr. Technical Director, ParsonsX. Parsons Corporation (NYSE:PSN) is a leading disruptive technology company in critical infrastructure, national defense, space, intelligence, and security markets providing solutions across the globe to help make the world safer, healthier, and more connected. Parsons provides services and capabilities across cybersecurity, missile defense, space ground

by Ramdev Wudali (AWS Machine Learning Blog) on January 13, 2023

This post is co-written by Ramdev Wudali and Kiran Mantripragada from Thomson Reuters. In 1992, Thomson Reuters (TR) released its first AI legal research service, WIN (Westlaw Is Natural), an innovation at the time, as most search engines only supported Boolean terms and connectors. Since then, TR has achieved many more milestones as its AI

by Vidya Sagar Ravipati (AWS Machine Learning Blog) on January 13, 2023

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a

by Olivia Choudhury (AWS Machine Learning Blog) on January 13, 2023

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a

by Mark Lott (AWS Machine Learning Blog) on January 12, 2023

This post was co-authored with Mark Lott, Distinguished Technical Architect, Salesforce, Inc. Enterprises that operate globally are experiencing challenges sourcing customer support professionals with multi-lingual experience. This process can be cost-prohibitive and difficult to scale, leading many enterprises to only support English for chats. Using human interpreters for translation support is expensive, and infeasible since

by Andy Whittle (AWS Machine Learning Blog) on January 12, 2023

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. At The Very Group, which operates digital retailer Very, security is a top priority in handling data for millions of customers. Part of how The Very Group secures and tracks business operations is through activity logging

by Alyssa Hughes (Microsoft Research) on January 12, 2023

Artificial intelligence, like all tools we build, is an expression of human creativity. As with all creative expression, AI manifests the perspectives and values of its creators. A stance that encourages reflexivity among AI practitioners is a step toward ensuring that AI systems are human-centered, developed, and deployed with the interests and well-being of individuals and society front and center. This is the focus of research scientists and engineers affiliated with […]

by Rick Merritt (NVIDIA Blog) on January 12, 2023

Using a pretrained AI model from NVIDIA, startup Evozyne created two proteins with significant potential in healthcare and clean energy. A joint paper released today describes the process and the biological building blocks it produced. One aims to cure a congenital disease, another is designed to consume carbon dioxide to reduce global warming. Initial results show Read article >

by GeForce NOW Community (NVIDIA Blog) on January 12, 2023

GFN Thursday kicks each weekend off with new games and updates straight from the cloud. This week adds more games from publisher THQ Nordic to the GeForce NOW library, as part seven total additions. Members can gear up to play these new titles the ultimate way with the upcoming release of the new Ultimate membership, Read article >

by Azita Martin (NVIDIA Blog) on January 12, 2023

The global retail industry has a $100 billion problem. “Shrinkage” — the loss of goods due to theft, damage and misplacement — significantly crimps retailers’ profits. An estimated 65% of shrinkage is due to theft, according to the National Retail Federation’s 2022 Retail Security Survey, conducted in partnership with the Loss Prevention Research Council. And Read article >

by Marios Skevofylakas (AWS Machine Learning Blog) on January 11, 2023

This post is co-authored by Marios Skevofylakas, Jason Ramchandani and Haykaz Aramyan from Refinitiv, An LSEG Business. Financial service providers often need to identify relevant news, analyze it, extract insights, and take actions in real time, like trading specific instruments (such as commodities, shares, funds) based on additional information or context of the news item.

by (AI) on January 11, 2023

Looking back at Google’s 2022 progress in principled AI innovation and ahead to 2023 and beyond.

by Latest News & Stories From Around The World | Uber Blog on January 11, 2023

“Believe it or not, but I took my first interview in an Uber,” shares Prapti Singh, who left a marketeers dream job to join Uber in 2017 as a marketing manager in Gurgaon, India. “It was definitely the best decision to step out of my comfort zone and try something new.”

by Alyssa Hughes (Microsoft Research) on January 11, 2023

Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation Jan P. Unsleber, Hongbin Liu, Leopold Talirz, Thomas Weymuth, Maximilian Mörchen, Adam Grofe, Dave The post Research Focus: Week of January 9, 2023 appeared first on […]

by OpenAI (OpenAI) on January 11, 2023

OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Internet Observatory to investigate how large language models might be misused for disinformation purposes. The collaboration included an October 2021 workshop bringing together 30 disinformation researchers, machine learning experts, and policy analysts, and

by Marc Karp (AWS Machine Learning Blog) on January 10, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so

by Abhinav Jawadekar (AWS Machine Learning Blog) on January 10, 2023

If you’ve had the opportunity to build a search application for unstructured data (i.e., wiki, informational web sites, self-service help pages, internal documentation, etc.) using open source or commercial-off-the-shelf search engines, then you’re probably familiar with the inherent accuracy challenges involved in getting relevant search results. The intended meaning of both query and document can

by Dhawalkumar Patel (AWS Machine Learning Blog) on January 9, 2023

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Use cases such as fraud detection, product recommendations, and traffic prediction are examples where milliseconds matter and are critical for business success. Strict service level agreements (SLAs) need to be met,

by Gillian Armstrong (AWS Machine Learning Blog) on January 6, 2023

Designing and building an intelligent conversational interface is very different than building a traditional application or website. These best practices for Amazon Lex interaction models will help you develop those new skills as you design and optimize your next bot.

by Divya Bhargavi (AWS Machine Learning Blog) on January 6, 2023

This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office Mojo Movies/TV/OTT licensable data package, which provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million

by Latest News & Stories From Around The World | Uber Blog on January 6, 2023

Uber for Business and JetBlue Vacations are teaming up to offer travelers $20 vouchers for rides with Uber at select airports.

by Latest News & Stories From Around The World | Uber Blog on January 5, 2023

Joakim Recht is an Aarhus-based, Linux-using distinguished engineer who has spent 8 years at Uber “making myself obsolete.”

by Latest News & Stories From Around The World | Uber Blog on December 30, 2022

Notice of Rights for all Washington state drivers per new legislation House Bill 2076

by Latest News & Stories From Around The World | Uber Blog on December 30, 2022

Introducing In-car Tablets designed to help drivers earn more.

by (AI) on December 29, 2022

A recap of Google’s top announcements and initiatives in 2022.

by Brenda Potts (Microsoft Research) on December 19, 2022

2022 has seen remarkable progress in foundational technologies that have helped to advance human knowledge and create new possibilities to address some of society’s most challenging problems. Significant advances in AI have also enabled Microsoft to bring new capabilities to customers through our products and services, including GitHub Copilot, an AI pair programmer capable of turning natural language prompts into code, and a preview of Microsoft Designer, a graphic design […]

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

Requesters sometimes need drivers to help with an extra task beyond just delivering items with Uber Connect. With Errands by the hour, you earn for your time driving and in-store.

by Ryan Greene (OpenAI) on December 15, 2022

We are excited to announce a new embedding model which is significantly more capable, cost effective, and simpler to use. The new model, text-embedding-ada-002, replaces five separate models for text search, text similarity, and code search, and outperforms our previous most capable model, Davinci, at most tasks, while being priced

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

Errands by the hour is an option that allows you to request a trip for at least 1 hour and up to 4 hours to help you with item delivery Errands. Instead of having to request individual one-way Uber Connect trips, you can now add multiple stops!

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

This holiday season, members of our Employee Resource Groups partnered with organizations in communities around the world to showcase our values and give back.

by Latest News & Stories From Around The World | Uber Blog on December 13, 2022

In this blog, we share how we improved the daily edit-build-run developer experience using DevPods, Uber’s remote development environment. We cover the challenges, pain points, our architecture, and lastly the future of remote development at Uber.

by (AI) on December 13, 2022

A look at how Transformers are helping robots become more useful.

by Latest News & Stories From Around The World | Uber Blog on December 13, 2022

Explore the leaps of faith, chance encounters, and hard earned lessons that helped 4 EMEA Operations leaders drive their growth and build our rides business across the region.

by Brenda Potts (Microsoft Research) on December 12, 2022

For more than six years, Microsoft Research has been honored to develop the Soundscape research project, which was designed to deliver information about a person’s location and points of interest and has guided individuals to desired places and in unfamiliar spaces using augmented-reality and three-dimensional audio. While not a traditional turn-by-turn navigation mobile app, the The post Microsoft Soundscape – New Horizons with a Community-Driven Approach appeared […]

by Brenda Potts (Microsoft Research) on December 8, 2022

This special edition of Research Focus highlights some of the 100+ papers from Microsoft Research that were accepted for publication at NeurIPS 2022 – the thirty-sixth annual Conference on Neural Information Processing Systems. In this issue, we continue to feature some of our 100+ papers accepted at NeurIPS 2022. Outstanding paper: Gradient Estimation with Discrete Stein The post Research Focus: Week of December 5, 2022 appeared first on Microsoft Research.

by Alyssa Hughes (Microsoft Research) on December 8, 2022

Microsoft is home to a diverse team of researchers focused on supporting a healthy global society, including finding ways technology can address human rights problems affecting the most vulnerable populations around the world. With a multi-disciplinary background in human-computer interaction, data science, and the social sciences, the research team partners with community, governmental, and nongovernmental organizations to create open technologies that enable scalable […]

by DeepMind Blog on December 8, 2022

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

by (AI) on December 6, 2022

Google's Startups for Sustainable Development program supports impact-driven startups who are building a more sustainable future.

by DeepMind Blog on December 6, 2022

Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial […]

by Alyssa Hughes (Microsoft Research) on December 5, 2022

Microsoft is proud to be a platinum sponsor of the 36th annual conference on Neural Information Processing Systems (NeurIPS), which is widely regarded as the world’s most prestigious research conference on artificial intelligence and machine learning. Microsoft has a strong presence at NeurIPS again this year, with more than 150 of our researchers participating in the The post NeurIPS 2022: Seven Microsoft Research Papers Selected for Oral Presentations appeared first on […]

by DeepMind Blog on December 1, 2022

Game-playing artificial intelligence (AI) systems have advanced to a new frontier. Stratego, the classic board game that’s more complex than chess and Go, and craftier than poker, has now been mastered. Published in Science, we present DeepNash, an AI agent that learned the game from scratch to a human expert level by playing against itself. 

by OpenAI (OpenAI) on November 30, 2022

We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction

by Alyssa Hughes (Microsoft Research) on November 29, 2022

This special edition of Research Focus highlights some of the 100+ papers from Microsoft Research that were accepted for publication at NeurIPS 2022 – the thirty-sixth annual Conference on Neural Information Processing Systems. Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed The post Research Focus: Week of November 28, 2022 appeared […]

by (AI) on November 28, 2022

Our partnership with iCAD Inc. marks the first time we are licensing our mammography AI model in clinical practice.

by DeepMind Blog on November 25, 2022

NeurIPS is the world’s largest conference in artificial intelligence (AI) and machine learning (ML), and we’re proud to support the event as Diamond sponsors, helping foster the exchange of research advances in the AI and ML community. Teams from across DeepMind are presenting 47 papers, including 35 external collaborations in virtual panels and poster sessions.

by DeepMind Blog on November 23, 2022

Most artificial intelligence (AI) researchers now believe that writing computer code which can capture the nuances of situated interactions is impossible. Alternatively, modern machine learning (ML) researchers have focused on learning about these types of interactions from data. To explore these learning-based approaches and quickly build agents that can make sense of human instructions and safely perform actions in open-ended conditions, we created a research framework […]

by DeepMind Blog on November 22, 2022

Our new paper, NEVIS’22: A Stream of 100 Tasks Sampled From 30 Years of Computer Vision Research, proposes a playground to study the question of efficient knowledge transfer in a controlled and reproducible setting. The Never-Ending Visual classification Stream (NEVIS’22) is a benchmark stream in addition to an evaluation protocol, a set of initial baselines, and an open-source codebase. This package provides an opportunity for researchers to explore how models can […]

by (AI) on November 18, 2022

A new report from the Geena Davis Institute, Google Research and USC uses AI to analyze representation in media.

by DeepMind Blog on November 16, 2022

At DeepMind, our goal is to make sure everything we do meets the highest standards of safety and ethics, in line with our Operating Principles. One of the most important places this starts with is how we collect our data. In the past 12 months, we’ve collaborated with Partnership on AI (PAI) to carefully consider these challenges, and have co-developed standardised best practices and processes for responsible human data collection.

by (AI) on November 15, 2022

Watch Thomas Friedman and James Manyika discuss AI

by (AI) on November 14, 2022

Meet Lieke, the first Responsible Innovation intern, and learn about her path to her current role and her key takeaways from the internship.

by DeepMind Blog on November 8, 2022

Meet Sylvia Christie, our education partnerships manager who’s played a leading role in expanding our scholarship programme, which is marking its five-year anniversary.

by OpenAI (OpenAI) on November 3, 2022

Starting today, developers can begin building apps with the DALL·E API.

by (AI) on November 2, 2022

Here’s a look at how we’re investing in technologies to help communities prepare for and respond to climate-related disasters and threats.

by (AI) on November 2, 2022

Decades of research have led to today’s rapid progress in AI. Today, we’re announcing three new ways people are poised to benefit.

by (AI) on October 26, 2022

PacBio introduces Revio, a tool that will help advance genomic sequencing and incorporates our DeepConsensus technology.

by (AI) on October 21, 2022

Google recently completed research on AI and breast cancer screening. Learn more from the scientists behind the work.

by DeepMind Blog on October 20, 2022

We’ve partnered with Google Cloud over the last few years to apply our AI research for making a positive impact on core solutions used by their customers. Here, we introduce a few of these projects, including optimising document understanding, enhancing the value of wind energy, and offering easier use of AlphaFold.

by (AI) on October 12, 2022

Yossi Matias, VP of Engineering and Research, who oversees research in Africa, talks with Jeff Dean, SVP of Google Research, who championed the opening of the AI Researc…

by DeepMind Blog on October 12, 2022

Perception – the process of experiencing the world through senses – is a significant part of intelligence. And building agents with human-level perceptual understanding of the world is a central but challenging task, which is becoming increasingly important in robotics, self-driving cars, personal assistants, medical imaging, and more. So today, we’re introducing the Perception Test, a multimodal benchmark using real-world videos to help evaluate the perception […]

by (AI) on October 11, 2022

Here’s a look at the work teams are doing at Google to use machine learning to better understand proteins.

by (AI) on October 11, 2022

Open Buildings is an open-access dataset pinpointing the locations and geometry of buildings in Africa and Asia.

by (AI) on October 10, 2022

On World Mental Health Day, learn how we're helping connect people with mental health support.

by DeepMind Blog on October 7, 2022

As we build increasingly advanced artificial intelligence (AI) systems, we want to make sure they don’t pursue undesired goals. Such behaviour in an AI agent is often the result of specification gaming – exploiting a poor choice of what they are rewarded for. In our latest paper, we explore a more subtle mechanism by which AI systems may unintentionally learn to pursue undesired goals: goal misgeneralisation (GMG). GMG occurs when a system's capabilities generalise […]

by DeepMind Blog on October 5, 2022

In our paper, published today in Nature, we introduce AlphaTensor, the first artificial intelligence (AI) system for discovering novel, efficient, and provably correct algorithms for fundamental tasks such as matrix multiplication. This sheds light on a 50-year-old open question in mathematics about finding the fastest way to multiply two matrices. This paper is a stepping stone in DeepMind’s mission to advance science and unlock the most fundamental problems using AI. Our […]

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 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 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 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 (AI) on September 15, 2022

SVP of Technology & Society James Manyika on how AI can accelerate progress on the UN’s SDGs – and an expanded commitment from Google to help.

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 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 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 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 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 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 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

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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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

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 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 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 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 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 September 17, 2021

We argue that merely using curiosity for fast environment exploration or as a bonus reward for a specific task does not harness the full potential of this technique and misses useful skills. Instead, we propose to shift the focus towards retaining the behaviours which emerge during curiosity-based learning. We posit that these self-discovered behaviours serve as valuable skills in an agent’s repertoire to solve related tasks.

by DeepMind Blog on September 15, 2021

In our paper, we focus on LMs and their propensity to generate toxic language. We study the effectiveness of different methods to mitigate LM toxicity, and their side-effects, and we investigate the reliability and limits of classifier-based automatic toxicity evaluation.

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 July 22, 2021

Many novel machine learning innovations contribute to AlphaFold’s current level of accuracy. We give a high-level overview of the system below; for a technical description of the network architecture see our AlphaFold methods paper and especially its extensive Supplementary Information.

by DeepMind Blog on July 14, 2021

Here we introduce Melting Pot, a scalable evaluation suite for multi-agent reinforcement learning. Melting Pot assesses generalisation to novel social situations involving both familiar and unfamiliar individuals, and has been designed to test a broad range of social interactions such as: cooperation, competition, deception, reciprocation, trust, stubbornness and so on. Melting Pot offers researchers a set of 21 MARL “substrates” (multi-agent games) on which to train […]

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 February 8, 2021

There has been rapidly growing interest in developing methods for meta-learning within deep RL. Although there has been substantive progress toward such ‘meta-reinforcement learning,’ research in this area has been held back by a shortage of benchmark tasks. In the present work, we aim to ease this problem by introducing (and open-sourcing) Alchemy, a useful new benchmark environment for meta-RL, along with a suite of analysis tools.

by DeepMind Blog on February 2, 2021

In this work, we examine what aspects of multimodal transformers – attention, losses, and pretraining data – are important in their success at multimodal pretraining. We find that Multimodal attention, where both language and image transformers attend to each other, is crucial for these models’ success. Models with other types of attention (even with more depth or parameters) fail to achieve comparable results to shallower and smaller models with multimodal attention.

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 11, 2020

We first create a simulated environment, the Playroom, in which virtual robots can engage in a variety of interesting interactions by moving around, manipulating objects, and speaking to each other. The Playroom’s dimensions can be randomised as can its allocation of shelves, furniture, landmarks like windows and doors, and an assortment of children's toys and domestic objects. The diversity of the environment enables interactions involving reasoning about space and object […]

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 18, 2020

We present our use of Unity, a widely recognised and comprehensive game engine, to create more diverse, complex, virtual simulations. We describe the concepts and components developed to simplify the authoring of these environments, intended for use predominantly in the field of reinforcement learning.

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 24, 2020

We propose a benchmark called RL Unplugged to evaluate and compare offline RL methods. RL Unplugged includes data from a diverse range of domains including games (e.g., Atari benchmark) and simulated motor control problems (e.g. DM Control Suite). The datasets include domains that are partially or fully observable, use continuous or discrete actions, and have stochastic vs. deterministic dynamics.

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 June 15, 2020

The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides convenient bindings to functions and data structures. The PyMJCF and Composer libraries enable procedural model manipulation and task authoring.

by DeepMind Blog on June 1, 2020

Acme is a framework for building readable, efficient, research-oriented RL algorithms. At its core Acme is designed to enable simple descriptions of RL agents that can be run at various scales of execution — including distributed agents. By releasing Acme, our aim is to make the results of various RL algorithms developed in academia and industrial labs easier to reproduce and extend for the machine learning community at large.

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 May 12, 2020

In this paper we focus on a setting in which goal tasks are defined via simple sparse rewards, and exploration is facilitated via agent-internal auxiliary tasks. We introduce the idea of simple sensor intentions (SSIs) as a generic way to define auxiliary tasks. SSIs reduce the amount of prior knowledge that is required to define suitable rewards. They can further be computed directly from raw sensor streams and thus do not require expensive and possibly brittle state […]

by DeepMind Blog on May 7, 2020

We apply a generative segmental model of task structure, guided by narration, to action segmentation in video. We focus on unsupervised and weakly-supervised settings where no action labels are known during training. Despite its simplicity, our model performs competitively with previous work on a dataset of naturalistic instructional videos.

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 March 11, 2020

Our goal is to use visual grounding to improve unsupervised word mapping between languages. The key idea is to establish a common visual representation between two languages by learning embeddings from unpaired instructional videos narrated in the native language.