-
Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuningby 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
-
What Are Large Language Models Used For?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 >
-
DLSS 3 Delivers Ultimate Boost in Latest Game Updates on GeForce NOWby 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 >
-
A search for adventure brought Mike to Uberby 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.
-
Hallucinating functional protein sequencesby Machine learning : nature.com subject feeds on January 26, 2023
-
Research Focus: Week of January 23, 2023by 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 […]
-
Build a loyalty points anomaly detector using Amazon Lookout for Metricsby 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.
-
Explain text classification model predictions using Amazon SageMaker Clarifyby 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
-
Upscale images with Stable Diffusion in Amazon SageMaker JumpStartby 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
-
Braced From Space: Startup Keeps Watchful Eye on Gas Pipeline Leaks Across the Globeby 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 >
-
Biomedical Research Platform Terra Now Available on Microsoft Azureby 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.
-
Cohere brings language AI to Amazon SageMakerby 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 […]
-
NVIDIA CEO Ignites AI Conversation in Stockholmby Magnus Weberg (NVIDIA Blog) on January 25, 2023
Jensen Huang headlines Stockholm AI confab, Berzelius supercomputer upgraded to 94 NVIDIA DGX A100 systems.
-
Supersizing AI: Sweden Turbocharges Its Innovation Engineby 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 >
-
3D Artist Enters the Node Zone, Creating Alien Artifacts This Week ‘In the NVIDIA Studio’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.
-
Fresh AI on Security: Digital Fingerprinting Deters Identity Attacksby 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 >
-
OpenAI and Microsoft Extend Partnershipby 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
-
This Uber GM’s advice for aspiring female leadersby 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.
-
Booked for Brilliance: Sweden’s National Library Turns Page to AI to Parse Centuries of Databy 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 >
-
Leveraging the power of crowdsby Machine learning : nature.com subject feeds on January 23, 2023
-
Deep learning to estimate brain ageby Machine learning : nature.com subject feeds on January 23, 2023
-
How CCC Intelligent Solutions created a custom approach for hosting complex AI models using Amazon SageMakerby 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
-
What Is AI Computing?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 >
-
The Uber One Super Bowl LVII Sweepstakes for Couriersby 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.
-
How Brightline transforms customer experience at all steps of the journey, with Brightline+ and Uberby 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.
-
Scaling Adoption of Kerberos at Uberby 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.
-
AI’s Leg Up: Startup Accelerates Robotics Simulation for $8 Trillion Food Marketby 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 >
-
9 ways we use AI in our productsby (AI) on January 19, 2023
Here are nine ways we use AI today to make our products even more helpful.
-
The Ultimate Upgrade: GeForce RTX 4080 SuperPOD Rollout Begins Todayby 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 >
-
Why Athira joined Uber from the social sectorby 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.”
-
Sequoia Capital’s Pat Grady and Sonya Huang on Generative AIby 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 >
-
Roll Model: Smart Stroller Pushes Its Way to the Top at CES 2023by 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 >
-
Artist Zhelong Xu Brings Chinese Zodiac to Life for Lunar New Year This Week ‘In the NVIDIA Studio’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.
-
Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDKby 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,
-
Churn prediction using multimodality of text and tabular features with Amazon SageMaker Jumpstartby 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
-
NVIDIA and Dell Technologies Expand AI Portfolioby 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 >
-
7 ways Google is using AI to help solve society's challengesby (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.
-
Why we focus on AI (and to what end)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.
-
Leveraging artificial intelligence and machine learning at Parsons with AWS DeepRacerby 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
-
How Thomson Reuters built an AI platform using Amazon SageMaker to accelerate delivery of ML projectsby 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
-
Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2by 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
-
Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1by 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
-
Multilingual customer support translation made easy on Salesforce Service Cloud using Amazon Translateby 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
-
Redacting PII data at The Very Group with Amazon Comprehendby 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
-
Advancing human-centered AI: Updates on responsible AI researchby 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 […]
-
NVIDIA, Evozyne Create Generative AI Model for Proteinsby 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 >
-
GFN Thursday Adds New Titles From THQ Nordic to GeForce NOWby 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 >
-
NVIDIA Helps Retail Industry Tackle Its $100 Billion Shrink Problemby 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 >
-
Enriching real-time news streams with the Refinitiv Data Library, AWS services, and Amazon SageMakerby 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.
-
Responsible AI: Looking back at 2022, and to the futureby (AI) on January 11, 2023
Looking back at Google’s 2022 progress in principled AI innovation and ahead to 2023 and beyond.
-
Prapti joined Uber for the company, but stays for the peopleby 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.”
-
Research Focus: Week of January 9, 2023by 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 […]
-
Forecasting Potential Misuses of Language Models for Disinformation Campaigns—and How to Reduce Riskby 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
-
Best practices for load testing Amazon SageMaker real-time inference endpointsby 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
-
Get smarter search results with the Amazon Kendra Intelligent Ranking and OpenSearch pluginby 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
-
Model hosting patterns in Amazon SageMaker, Part 1: Common design patterns for building ML applications on Amazon SageMakerby 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,
-
Best practices for creating Amazon Lex interaction modelsby 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.
-
Power recommendations and search using an IMDb knowledge graph – Part 3by 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
-
JetBlue Vacations offers travelers rides with Uberby 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.
-
8 years on this distinguished engineer’s work is just getting startedby 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.”
-
Washington State TNC Notice of Rightsby 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
-
Introducing in-car tabletsby Latest News & Stories From Around The World | Uber Blog on December 30, 2022
Introducing In-car Tablets designed to help drivers earn more.
-
Google's 2022 year in reviewby (AI) on December 29, 2022
A recap of Google’s top announcements and initiatives in 2022.
-
Research @ Microsoft 2022: A look back at a year of accelerating progress in AIby 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 […]
-
What is Errands by the hour?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.
-
New and Improved Embedding Modelby 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
-
What is Errands by the hour?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!
-
Employee resource groups partner to give back for the holidaysby 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.
-
Devpod: Improving Developer Productivity at Uber with Remote Developmentby 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.
-
Helping robots learn from each otherby (AI) on December 13, 2022
A look at how Transformers are helping robots become more useful.
-
4 Uber leaders share their recipes for career successby 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.
-
Microsoft Soundscape – New Horizons with a Community-Driven Approachby 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 […]
-
Research Focus: Week of December 5, 2022by 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.
-
IOM and Microsoft release first-ever differentially private synthetic dataset to counter human traffickingby 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 […]
-
Competitive programming with AlphaCodeby DeepMind Blog on December 8, 2022
Solving novel problems and setting a new milestone in competitive programming.
-
How startups can help build a sustainable futureby (AI) on December 6, 2022
Google's Startups for Sustainable Development program supports impact-driven startups who are building a more sustainable future.
-
AI for the board game Diplomacyby 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 […]
-
NeurIPS 2022: Seven Microsoft Research Papers Selected for Oral Presentationsby 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 […]
-
Mastering Stratego, the classic game of imperfect informationby 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.
-
ChatGPT: Optimizing Language Models for Dialogueby 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
-
Research Focus: Week of November 28, 2022by 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 […]
-
Partnering with iCAD to improve breast cancer screeningby (AI) on November 28, 2022
Our partnership with iCAD Inc. marks the first time we are licensing our mammography AI model in clinical practice.
-
DeepMind’s latest research at NeurIPS 2022by 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.
-
Building interactive agents in video game worldsby 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 […]
-
Benchmarking the next generation of never-ending learnersby 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 […]
-
Using AI to study 12 years of representation in TVby (AI) on November 18, 2022
A new report from the Geena Davis Institute, Google Research and USC uses AI to analyze representation in media.
-
Best practices for data enrichmentby 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.
-
A conversation with Thomas Friedman about AIby (AI) on November 15, 2022
Watch Thomas Friedman and James Manyika discuss AI
-
Hear what Google’s first Responsible Innovation intern learnedby (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.
-
The pursuit of AI education - past, present, and futureby 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.
-
DALL·E API Now Available in Public Betaby OpenAI (OpenAI) on November 3, 2022
Starting today, developers can begin building apps with the DALL·E API.
-
How we're using AI to help address the climate crisisby (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.
-
3 ways AI is scaling helpful technologies worldwideby (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.
-
A new genome sequencing tool powered with our technologyby (AI) on October 26, 2022
PacBio introduces Revio, a tool that will help advance genomic sequencing and incorporates our DeepConsensus technology.
-
How AI can help in the fight against breast cancerby (AI) on October 21, 2022
Google recently completed research on AI and breast cancer screening. Learn more from the scientists behind the work.
-
Digital transformation with Google Cloudby 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.
-
How AI is helping African communities and businessesby (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…
-
Measuring perception in AI modelsby 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 […]
-
How we’re using machine learning to understand proteinsby (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.
-
How mapping the world’s buildings makes a differenceby (AI) on October 11, 2022
Open Buildings is an open-access dataset pinpointing the locations and geometry of buildings in Africa and Asia.
-
Meeting global mental health needs, with technology's helpby (AI) on October 10, 2022
On World Mental Health Day, learn how we're helping connect people with mental health support.
-
How undesired goals can arise with correct rewardsby 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 […]
-
Discovering novel algorithms with AlphaTensorby 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 […]
-
DALL·E Now Available Without Waitlistby 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
-
Supporting the next generation of AI leadersby 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.
-
Building safer dialogue agentsby 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.
-
Introducing Whisperby 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 […]
-
Our commitment on using AI to accelerate progress on global development goalsby (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.
-
How our principles helped define AlphaFold’s releaseby 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.
-
Maximising the impact of our breakthroughsby 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.
-
My journey from DeepMind intern to mentorby 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.
-
In conversation with AI: building better language modelsby 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.
-
DALL·E: Introducing Outpaintingby 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
-
From motor control to embodied intelligenceby DeepMind Blog on August 31, 2022
-
Advancing conservation with AI-based facial recognition of turtlesby 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 […]
-
Our Approach to Alignment Researchby 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
-
Discovering when an agent is present in a systemby 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 […]
-
Realising scientists are the real superheroesby 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.
-
New and Improved Content Moderation Toolingby 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
-
AlphaFold reveals the structure of the protein universeby 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.
-
DALL·E Now Available in Betaby 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
-
The virtuous cycle of AI researchby 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.
-
Reducing Bias and Improving Safety in DALL·E 2by 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
-
Perceiver AR: general-purpose, long-context autoregressive generationby 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.
-
DeepMind’s latest research at ICML 2022by 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.
-
DALL·E 2: Extending Creativityby 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
-
Working together with YouTubeby DeepMind Blog on July 14, 2022
-
Intuitive physics learning in a deep-learning model inspired by developmental psychologyby 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.
-
Human-centred mechanism design with Democratic AIby 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.
-
DALL·E 2 Pre-Training Mitigationsby 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
-
Learning to Play Minecraft with Video PreTraining (VPT)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
-
Leading a movement to strengthen machine learning in Africaby DeepMind Blog on June 23, 2022
-
BYOL-Explore: Exploration with Bootstrapped Predictionby 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 […]
-
Unlocking High-Accuracy Differentially Private Image Classification through Scaleby 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 […]
-
Bridging DeepMind research with Alphabet productsby 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.
-
Advocating for the LGBTQ+ community in AI researchby 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.
-
Evaluating Multimodal Interactive Agentsby 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.
-
Kyrgyzstan to King’s Cross: the star baker cooking up codeby 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.
-
Dynamic language understanding: adaptation to new knowledge in parametric and semi-parametric modelsby 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 […]
-
Building a culture of pioneering responsiblyby 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 […]
-
Open-sourcing MuJoCoby 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 […]
-
From LEGO competitions to DeepMind's robotics labby 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 […]
-
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learningby 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.
-
A Generalist Agentby 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 […]
-
Active offline policy selectionby 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.
-
Tackling multiple tasks with a single visual language modelby 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.
-
When a passion for bass and brass help build better toolsby 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.
-
DeepMind’s latest research at ICLR 2022by 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.
-
An empirical analysis of compute-optimal large language model trainingby 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.
-
GopherCite: Teaching language models to support answers with verified quotesby 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 […]
-
Predicting the past with Ithacaby 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 […]
-
Learning Robust Real-Time Cultural Transmission without Human Databy 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.
-
Probing Image-Language Transformers for Verb Understandingby 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 […]
-
Accelerating fusion science through learned plasma controlby DeepMind Blog on February 16, 2022
Successfully controlling the nuclear fusion plasma in a tokamak with deep reinforcement learning
-
MuZero’s first step from research into the real worldby DeepMind Blog on February 11, 2022
Collaborating with YouTube to optimise video compression in the open source VP9 codec.
-
Red Teaming Language Models with Language Modelsby 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.
-
DeepMind: The Podcast returns for Season 2by 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.
-
Spurious normativity enhances learning of compliance and enforcement behavior in artificial agentsby 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.
-
Simulating matter on the quantum scale with AIby 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.
-
Language modelling at scale: Gopher, ethical considerations, and retrievalby 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.
-
Creating Interactive Agents with Imitation Learningby 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.
-
Improving language models by retrieving from trillions of tokensby 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”.
-
Exploring the beauty of pure mathematics in novel waysby 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.
-
On the Expressivity of Markov Rewardby 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.
-
Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neuronsby 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 […]
-
Real-world challenges for AGIby 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 […]
-
Opening up a physics simulator for roboticsby 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 […]
-
Stacking our way to more general robotsby 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 […]
-
Predicting gene expression with AIby 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 […]
-
Nowcasting the next hour of rainby 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? […]
-
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Explorationby 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.
-
Challenges in Detoxifying Language Modelsby 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.
-
Building architectures that can handle the world’s databy 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 […]
-
Generally capable agents emerge from open-ended playby 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 […]
-
Putting the power of AlphaFold into the world’s handsby 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.
-
Enabling high-accuracy protein structure prediction at the proteome scaleby 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.
-
Melting Pot: an evaluation suite for multi-agent reinforcement learningby 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 […]
-
An update on our racial justice effortsby 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.
-
Advancing sports analytics through AI researchby 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.
-
Game theory as an engine for large-scale data analysisby 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 […]
-
Alchemy: A structured task distribution for meta-reinforcement learningby 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.
-
Data, Architecture, or Losses: What Contributes Most to Multimodal Transformer Success?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.
-
MuZero: Mastering Go, chess, shogi and Atari without rulesby 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 […]
-
Imitating Interactive Intelligenceby 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 […]
-
Using JAX to accelerate our researchby 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.
-
AlphaFold: a solution to a 50-year-old grand challenge in biologyby 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 […]
-
Using Unity to Help Solve Intelligenceby 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.
-
Breaking down global barriers to accessby 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.
-
FermiNet: Quantum Physics and Chemistry from First Principlesby 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 […]
-
Fast reinforcement learning through the composition of behavioursby 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 […]
-
Traffic prediction with advanced Graph Neural Networksby 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.
-
RL Unplugged: Benchmarks for Offline Reinforcement Learningby 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.
-
Applying for technical rolesby 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.
-
dm_control: Software and Tasks for Continuous Controlby 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.
-
Acme: A new framework for distributed reinforcement learningby 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.
-
Using AI to predict retinal disease progressionby 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 […]
-
Simple Sensor Intentions for Explorationby 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 […]
-
Learning to Segment Actions from Observation and Narrationby 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.
-
Specification gaming: the flip side of AI ingenuityby 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 […]
-
Towards understanding glasses with graph neural networksby 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 […]
-
Agent57: Outperforming the human Atari benchmarkby 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.
-
Visual Grounding in Video for Unsupervised Word Translationby 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.