Microsoft news – Page 71

Posted on December 1, 2020 by sick skills — Leave a comment

The human side of AI for chess

As artificial intelligence continues its rapid progress, equaling or surpassing human performance on benchmarks in an increasing range of tasks, researchers in the field are directing more effort to the interaction between humans and AI in domains where both are active. Chess stands as a model system for studying how people can collaborate with AI, or learn from AI, just as chess has served as a leading indicator of many central questions in AI throughout the field’s history.

AI-powered chess engines have consistently bested human players since 2005, and the chess world has undergone further shifts since then, such as the introduction of the heuristics-based Stockfish engine in 2008 and the deep reinforcement learning-based AlphaZero engine in 2017. The impact of this evolution has been monumental: chess is now seeing record numbers of people playing the game even as AI itself continues to get better at playing. These shifts have created a unique testbed for studying the interactions between humans and AI: formidable AI chess-playing ability combined with a large, growing human interest in the game has resulted in a wide variety of playing styles and player skill levels.

There’s a lot of work out there that attempts to match AI chess play to varying human skill levels, but the result is often AI that makes decisions and plays moves differently than human players at that skill level. The goal for our research is to better bridge the gap between AI and human chess-playing abilities. The question for AI and its ability to learn is: can AI make the same fine-grained decisions that humans do at a specific skill level? This is a good starting point for aligning AI with human behavior in chess.

Our team of researchers at the University of Toronto, Microsoft Research, and Cornell University has begun investigating how to better match AI to different human skill levels and, beyond that, personalize an AI model to a specific player’s playing style. Our work comprises two papers, “Aligning Superhuman AI with Human Behavior: Chess as a Model System” and “Learning Personalized Behaviors of Human Behavior in Chess,” as well as a novel chess engine, called Maia, which is trained on games played by humans to more closely match human play. Our results show that, in fact, human decisions at different levels of skill can be predicted by AI, even at the individual level. This represents a step forward in modeling human decisions in chess, opening new possibilities for collaboration and learning between humans and AI.

AlphaZero changed how AI played the game by practicing against itself with only knowledge of the rules (“self-play”), unlike previous models that relied heavily on libraries of moves and past games to inform training. Our model, Maia, is a customized version of Leela Chess Zero (an open-source implementation of AlphaZero). We trained Maia on human games with the goal of playing the most human-like moves, instead of being trained on self-play games with the goal of playing the optimal moves. In order to characterize human chess-playing at different skill levels, we developed a suite of nine Maias, one for each Elo rating between 1100 and 1900. (Elo ratings are a system for evaluating players’ relative skill in games like chess.) As you’ll see below, Maia matches human play more closely than any chess engine ever created.

CODE Maia Chess Explore our nine final maia models saved as Leela Chess neural networks, and the code to create more and reproduce our results.

If you’re curious, you can play against a few versions of Maia on Lichess, the popular open-source online chess platform. Our bots on Lichess are named maia1, maia5, and maia9, which we trained on human games at Elo rating 1100, 1500, and 1900, respectively. You can also download these bots and other resources from the GitHub repo.

Measuring human play

What does it mean for a chess engine to match human play? For our purposes, we settled on a simple metric: given a position that occurred in an actual human game, what is the probability that the engine plays the move that the human played in the game?

Making an engine that matches human play according to this definition is a difficult task. The vast majority of positions seen in real games only happen once, because the sheer number of possible positions is astronomical: after just four moves by each player, the number of potential positions enters the hundreds of billions. Moreover, people have a wide variety of styles, even at the same rough skill level. And even the same exact person might make a different move if they see the same position twice!

Creating a dataset

To rigorously compare engines in how well they match human play, we need a good test set to evaluate them with. We made a collection of nine test sets, one for each narrow rating range. Here’s how we made them:

First, we made rating bins for each range of 100 rating points (such as 1200-1299, 1300-1399, and so on).
In each bin, we put all games where both players are in the same rating range.
We drew 10,000 games from each bin, ignoring games played at Bullet and HyperBullet speeds. At those speeds (one minute or less per player), players tend to play lower quality moves to not lose by running out of time.
Within each game, we discarded the first 10 moves made by each player to ignore most memorized opening moves.
We also discarded any move where the player had less than 30 seconds to complete the rest of the game (to avoid situations where players are making random moves).

After these restrictions we had nine test sets, one for each rating range, which contained roughly 500,000 positions each.

Differentiating our work from prior attempts

People have been trying to create chess engines that accurately match human play for decades. For one thing, they would make great sparring partners. But getting crushed like a bug every single game isn’t that fun, so the most popular attempts at engines that match human play have been some kind of attenuated version of a strong chess engine. Attenuated versions of an engine are created by limiting the engine’s ability in some way, such as reducing the amount of data it’s trained on or limiting how deeply it searches to find a move. For example, the “play with the computer” feature on Lichess is a series of Stockfish models that are limited in the number of moves they are allowed to look ahead. Chess.com, ICC, FICS, and other platforms all have similar engines. How well do these engines match human play?

Stockfish: We created several attenuated versions of Stockfish, one for each depth limit (for example, the depth 3 Stockfish can only look 3 moves ahead), and then we tested them on our test sets. In the plot below, we break out the accuracies by rating level so you can see if the engine thinks more like players of a specific skill level.

Figure 1: Accuracy of Stockfish models with depth 1, 3, 5, 7, 9, 11, 13, and 15 shown form 1100 to 1900 Elo ratings. Depth 5 matching is the lowest accuracy, starting at under 35% at 1100 and rising to just above 35% for 1900 rating. The best move matching is at Depth 15, starting at roughly 36% at 1100 and rising to over 40% at 1900. — Figure 1: Move matching accuracy for Stockfish compared with the targeted player’s Elo rating

As you can see, it doesn’t work that well. Attenuated versions of Stockfish only match human moves about 35-40% of the time. And equally importantly, each curve is strictly increasing, meaning that even depth-1 Stockfish does a better job at matching 1900-rated human moves than it does at matching 1100-rated human moves. This means that attenuating Stockfish by restricting the depth it can search doesn’t capture human play at lower skill levels—instead, it looks like it’s playing regular Stockfish chess with a lot of noise mixed in.

Leela Chess Zero: Attenuating Stockfish doesn’t characterize human play at specific levels. What about Leela Chess Zero, an open-source implementation of AlphaZero, which learns chess through self-play games and deep reinforcement learning? Unlike Stockfish, Leela incorporates no human knowledge in its design. Despite this, however, the chess community was very excited by how Leela seemed to play more like human players.

Figure 2: Leela ratings from 800 to 3200 graphed for accuracy. Leela does better than Stockfish for move matching, but as Elo rating gets better, each version of Leela has better or worse accuracy. Accuracy ranges from under 20% (800-rated Leela predicting 1900-level play) to about 47% (3200-rated Leela predicting 1900-level play). — Figure 2: Move matching accuracy for Leela compared with the targeted player’s Elo rating

In the analysis above, we looked at a number of different Leela generations, with the ratings being their relative skill (commentators noted that early Leela generations played particularly similar to humans). People were right in that the best versions of Leela match human moves more often than Stockfish. But Leela still doesn’t capture human play at different skill levels: each version is always getting better or always getting worse as the human skill level increases. To characterize human play at a particular level, we need another approach.

Maia: A better solution for matching human skill levels

Maia is an engine designed to play like humans at a particular skill level. To achieve this, we adapted the AlphaZero/Leela Chess framework to learn from human games. We created nine different versions, one for each rating range from 1100-1199 to 1900-1999. We made nine training datasets in the same way that we made the test datasets (described above), with each training set containing 12 million games. We then trained a separate Maia model for each rating bin to create our nine Maias, from Maia 1100 to Maia 1900.

Figure 3: Maia trained models from 1100 to 1900 ratings. These are shown predicting player moves at 1100 to 1900 ratings. Maia’s worst accuracy is 46% when a 1900-rated Maia model predicts moves of a 1100-rated player. The highest is 52%, far greater than prior AI chess models. — Figure 3: Move matching accuracy for Maia compared with the targeted player’s Elo rating

As you can see, the Maia results are qualitatively different from Stockfish and Leela. First off, the move matching performance is much higher: Maia’s lowest accuracy, when it is trained on 1900-rated players but predicts moves made by 1100-rated players, is 46%—as high as the best performance achieved by any Stockfish or Leela model on any human skill level we tested. Maia’s highest accuracy is over 52%. Over half the time, Maia 1900 predicts the exact move a 1900-rated human played in an actual game.

Figure 4: Figures 1, 2, and 3 combined showing that Maia’s accuracy greatly surpasses prior models’ performance. — Figure 4: Move matching accuracy for all the models compared with the targeted player’s Elo rating

Importantly, every version of Maia uniquely captures a specific human skill level since every curve achieves its maximum accuracy at a different human rating. Even Maia 1100 achieves over 50% accuracy in predicting 1100-rated moves, and it’s much better at predicting 1100-rated players than 1900-rated players!

This means something deep about chess: there is such a thing as “1100-rated style.” And furthermore, it can be captured by a machine learning model. This was surprising to us: it would have been possible that human play is a mixture of good moves and random blunders, with 1100-rated players blundering more often and 1900-rated players blundering less often. Then it would have been impossible to capture 1100-rated style, because random blunders are impossible to predict. But since we can predict human play at different levels, there is a reliable, predictable, and maybe even algorithmically teachable difference between one human skill level and the next.

Maia’s predictions

You can find all of the juicy details in the paper, but one of the most exciting things about Maia is that it can predict mistakes. Even when a human makes an absolute howler—“hanging” a queen, in other words letting an opponent capture it for free, for example—Maia predicts the exact mistake made more than 25% of the time. This could be really valuable for average players trying to improve their game: Maia could look at your games and tell which blunders were predictable and which were random mistakes. If your mistakes are predictable, you know what to work on to hit the next level.

Figure 5: Matching accuracy (predicting move quality) of Maia versus Leela. Quality prediction is much more consistent and consistently higher across the full range of Maia models, at its height above 60%, when compared with Leela, which has a much broader range of accuracy when looking at the full range of models. — Figure 5: Move matching accuracy as a function of the quality of the move played in the game

Modeling individual players’ styles with Maia

In current work, we are pushing the modeling of human play to the next level: can we actually predict the moves a particular human player would make?

It turns out that personalizing Maia gives us our biggest performance gains. Whereas base Maia predicts human moves around 50% of the time, some personalized models can predict an individual’s moves with accuracies up to 75%!

We achieve these results by fine-tuning Maia. Starting with a base Maia, say Maia 1900, we update the model by continuing training on an individual player’s games. Below, you can see that for predicting individual players’ moves, the personalized models all show large improvements over the non-personalized models. The gains are so large that the personalized models are almost non-overlapping with the non-personalized ones: the personalized model for the hardest-to-predict player still gets almost 60% accuracy, whereas even the non-personalized models don’t achieve this accuracy on even the easiest-to-predict players.

Personalized Maia models show a greatly improved range of mean accuracy when compared to non-personalized Maia models: anywhere from just under 60% at the low end to just over 80% at the high end.

The personalized models are so accurate that given just a few games, we can tell which player played them! In this stylometry task—where the goal is to recognize an individual’s playing style—we train personalized models for 400 players of varying skill levels, and then have each model predict the moves from 4 games by each player. For 96% of the 4-game sets we tested, the personalized model that achieved the highest accuracy (that is, predicted the player’s actual moves most often) was the one that was trained on the player who played the games. With only 4 games of data, we can pick out who played the games from a set of 400 players. The personalized models are capturing individual chess-playing style in a highly accurate way.

Using AI to help improve human chess play

We designed Maia to be a chess engine that predicts human moves at a particular skill level, and it has progressed into a personalized engine that can identify the games of individual players. This is an exciting step forward in our understanding of human chess play, and it brings us closer to our goal of creating AI chess-teaching tools that help humans improve. Among the many capabilities of a good chess teacher, two of them are understanding how students at different skill levels play and recognizing the playing styles of their students. Maia has shown that these capabilities are realizable using AI.

The ability to create personalized chess engines from publicly available, individual player data opens an interesting discussion on the possible uses (and misuses) of this technology. We initiate this discussion in our papers, but there is a long road ahead in understanding the full potential and implications of this line of research. As in countless times before, Chess will be one model AI system that sets the stage for this discussion.

Acknowledgments

Many thanks to Lichess.org for providing the human games that we trained on, and hosting our Maia models that you can play against. Ashton Anderson was supported in part by an NSERC grant, a Microsoft Research gift, and a CFI grant. Jon Kleinberg was supported in part by a Simons Investigator Award, a Vannevar Bush Faculty Fellowship, a MURI grant, and a MacArthur Foundation grant.

Posted on December 1, 2020 by sick skills — Leave a comment

GitHub to the rescue for developers facing ‘too many options’

Abel

December 1st, 2020

By Isaac Levin & Abel Wang

Let’s face it, as the demands of writing software increase, more pressure is put on devs to be as productive as humanly possible. And with this demand, the landscape for being a developer has never been more challenging.

With increased responsibilities and technology options, developers are asked to not just worry about the code they write, but all other aspects of the application development life cycle.

The plethora of tools at a developer’s disposal has also made developer responsibilities even more challenging. Determining what tools and platforms to develop on and with have caused a “too many options” scenario in lots of cases.

GitHub To The Rescue

As challenging as this landscape is, there are solutions. One thing that’s abundantly clear, GitHub is the place where developers go to learn and collaborate with the community.

GitHub has enabled developers to have the power of the entire Open-Source community at their disposal and the freedom to learn from the work of others to better themselves as a developer. GitHub has unveiled many tools aside from hosting source code to make the ecosystem as comfortable as possible.

One of those tools I am fired up about is “GitHub Actions”. Look, as you all know, I’m a DevOps guy , and I think about DevOps every time I put on my developer hat. I believe that no matter the app, if you are going to send it somewhere that isn’t your local machine, that app deserves to have some continuous integration and continous delivery (CI/CD), simple as that.

The question becomes, if my code is already in GitHub, what is the easiest way to hook CI/CD into my app? The answer is GitHub Actions.

GitHub Actions allow us to easily configure custom workflows, using a bounty of existing community-created workflows to fulfill the needs of our app. It isn’t just starting from scratch as there are workflows to do nearly everything, and your goal is to just build your Action in the way YOU need it. With GitHub Actions, getting your app to the Cloud is super easy.

But What About Developing My App?

Talking about where it goes before I write and compile my app seems non-sensical, but I believe that thinking about these things early will allow us to choose the technology/tools we need to be most productive.

In my opinion, one of the best tools to write the code that powers our software is Visual Studio Code. Visual Studio Code is a cross-platform, multi-language editor that provides extensive extensibility to create the perfect environment to write code.

Whether you are writing express apps in Node.js, multi-thread highly scalable applications in Go, or writing cutting-edge modules on your Raspberry Pi with Python, VS Code gives you the ability to work in the way that benefits you the most.

The best part, VS Code offers deep integrations with GitHub, which allows you to clone/pull/push your repositories as well as manage your work on issues and pull requests, without leaving the editor, HOW COOL IS THAT! Once you have your repo in VS Code, the editor gives you access to an oversupply of Open-Source extensions to do everything from configure your experience, down to your font and background of choice. Nearly anything is possible with VS Code, and with first-class GitHub support, it truly is one of the best options.

What Should Host My App?

With our code being built in VS Code and stored in GitHub and DevOps’d with GitHub Actions, the last thing we need to think about is now what?

Personally, I think Azure is the ultimate Cloud for GitHub. There is no other Cloud that best enables developers to be the most productive, and with integrations to VS Code AND GitHub, you truly have “best of breed” capabilities at your disposal.

Let’s start with VS Code Integrations, and boy there are a ton of them. Existing extensions enable developers to seamlessly connect to their Azure tenants and have full management capability of the resources in their subscriptions, including creation, scaling, configuration, debugging and if we want, even deployment!

Microsoft has built an extension pack called “Azure Tools” which includes extensions to manage every major Azure resource type as well as Azure CLI support AND Docker. There are also other extensions published by Microsoft that connect and manage nearly every Azure Resource. This means when new features come to the platform, they will be coming to the Microsoft published extensions.

Azure Loves GitHub

Finally, it is safe to say that Azure loves GitHub and the integrations are plentiful. From Azure Portal authentication with GitHub Ids, to individual services interfacing with GitHub (one great example of this is Azure Static Web Apps, which allow CI/CD to be configured on creation of the resource).

There is no better integration story between GitHub and Azure than “GitHub Actions for Azure” a set of pre-built GitHub Action workflows that helps you automate your app’s story on Azure, from deployment to monitoring and everything in between.

The team has built over 30 of these workflows and they are documented in a way that you will be able to use them without hesitation. One of my favorite examples is container image scan which allows you to scan the container images you are using for known vulnerabilities as well as linting to ensure you are using best practices.

GitHub Universe 2020

This is the messaging we’re delivering at GitHub Universe 2020. Check out our booth video:

[youtube https://www.youtube.com/watch?v=hr-qu_VQ1Ho?feature=oembed&w=640&h=360]

Conclusion

GitHub + Visual Studio Code + Azure ensures you as a developer can just trust the tools and get your work done. There are tons of more features that I didn’t talk about here, so please take a look at some of the resources below to get started enhancing your developer productivity.

More Resources

GitHub Actions for Azure | Create workflows to build, test, package, release and deploy to Azure

GitHub Actions for Azure | Microsoft Docs

Automate your workflow with GitHub Actions | Microsoft Learn

Visual Studio Code Azure Extensions

Create free services with Azure free account | Microsoft Docs

Abel Wang

Posted on December 1, 2020 by sick skills — Leave a comment

Microsoft, Code.org partner to teach AI + ethics from elementary to high school

Microsoft and Code.org are excited to announce a partnership that gives every student from elementary school to high school the opportunity to learn about artificial intelligence (AI).

We’re excited to unveil our new video series on artificial intelligence and machine learning. Microsoft CEO Satya Nadella introduces the series.

At a time when AI and machine learning are changing the very fabric of society and transforming entire industries, it is more important than ever to give every student the opportunity to not only learn how these technologies work, but also to think critically about the ethical and societal impacts of AI.

AI is used everywhere, from voice assistants to self-driving cars, and it’s rapidly becoming the most important technological innovation of current times. AI has the potential to play a major role in addressing global problems, such as detecting and curing diseases, cleaning oceans, eliminating poverty, or harnessing clean energy.

At the same time, with great power comes great responsibility, and budding computer scientists must learn to consider technology’s ethical impacts. How does algorithmic bias impact social justice or deep fakes impact democracy? How does society cope with rapid job automation? By learning how to consider the ethical issues that AI raises, these future computer scientists will be better able to envision the appropriate safeguards that help to maximize the benefits of AI technologies and reduce their risks.

Made possible by Microsoft’s latest donation of $7.5 million, Code.org plans a comprehensive and age-appropriate approach to teaching how AI works along with the social and ethical considerations, from elementary school through high school.

Available on December 1:

A new video series on AI, featuring Microsoft CEO Satya Nadella along with leading technologists across industry and academia

See the playlist with all videos here.

AI for Oceans is available in 25+ languages and is optimized for mobile devices.

Within the coming year, AI and machine learning lessons will be integrated into Code.org’s CS Discoveries curriculum, which is one of the most widely-used computer science courses for students in grades 6–10, and in App Lab, Code.org’s popular app-creation platform used throughout middle school and high school.

In CS Discoveries, students will learn to work with datasets to create machine learning models that they can incorporate into their apps, and explore how advances in new technologies such as computer vision and neural networks require new ethical computer scientists to avoid bias and harm. Curated datasets will help students better understand the real-world impact that these technologies have.

Code.org will also help students and teachers find additional educational resources from a variety of partners and the broader community behind AI education.

A look at a new lesson in Minecraft: Education Edition. In these new lessons, students use AI in a range of exciting real-world scenarios: to preserve wildlife and ecosystems, help people in remote areas, and research climate change.

Additionally, last month the Microsoft AI for Earth team partnered with Minecraft: Education Edition to release five lessons challenging students to use the power of AI in a range of exciting real-world scenarios: to preserve wildlife and ecosystems, help people in remote areas, and research climate change.

What’s more, Microsoft’s Imagine Cup Junior 2021 challenge provides students aged 13 to 18 the opportunity to learn about technology and how it can be used to positively change the world.

The global challenge is focused on Artificial Intelligence (AI), introducing students to AI and Microsoft’s AI for Good initiatives so they can come up with ideas to solve social, cultural and environmental issues.

Microsoft’s Imagine Cup Junior challenge is geared towards students ages 13 to 18. Learn more and join the competition here.

On Code.org, 45% of students are young women, and in the US, 50% are students from underrepresented racial and ethnic groups and 45% are in high needs schools. Reaching the tens of millions of students in Code.org’s courses and on its platform, the partnership between Microsoft and Code.org works to democratize access to learning AI because all students deserve the opportunity to shape the world they live in — and because creating an equitable and socially just future will take all of us.

-Code.org CEO Hadi Partovi and Microsoft President Brad Smith

Posted on November 30, 2020 by sick skills — Leave a comment

How tech can support secure, safe and equitable vaccine distribution

How technology can help meet the challenge of our lifetime

As several COVID-19 vaccines near regulatory approval in the U.S., the E.U., Japan, and other countries, governments around the world must establish systems to ensure effective and equitable distribution within their countries. At Microsoft, we have been working with public and private sector organizations around the world to help support this monumental task.

In some ways, the challenges related to the distribution and administration of the COVID-19 vaccine are similar to other vaccines. There are logistical challenges of supply procurement and demand forecasting, distribution, adverse reaction tracking and reporting, and integration with immunization records. But there are unique challenges as well: fair allocation, prioritization and phased eligibility, registration, tracking, as needed cold-chain storage supply, and the need to vaccinate a critical mass of the world’s population of over seven billion people in short order during a global pandemic.

This is a complex and multifaceted challenge. Government and public health officials will need to track multi-dose vaccinations, assess how public skepticism may impact demand, and coordinate with hospitals, clinics, nursing homes, pharmacies, and other vaccination sources to ensure public safety. This is on top of all the other challenges health workers are grappling with during the pandemic which includes overloaded hospitals, lack of Personal Protective Equipment (PPE), staff suffering from burnout, and much more.

chart, bubble chart

The World Economic Forum states that logistics around the COVID-19 vaccines are “The challenge of a lifetime” and that to achieve global distribution, “technology will play a vital role in ensuring the smooth execution along every step of the supply chain … currently, no platform exists that covers all those visibility needs.”¹

“The goal is to enable a fair, equitable, and efficient distribution of the COVID-19 vaccine,” remarks Dr. David Rhew, Microsoft’s Worldwide Chief Medical Officer. “In response to this urgent need, we need a secure and interoperable platform that balances the complexities of the registration, scheduling, and supply chain distribution, with the broader public health mission to deliver a safe and effective vaccine in a prioritized manner.”

How technology can support this global challenge

In our discussions with public health officials and customers, we have identified several imperatives that any vaccine management offering should include:

Purpose-driven solutions designed for a fair, equitable, and efficient procurement and distribution of the vaccine.
Comprehensive use cases that support cold chain supply chain management, patient/provider/clinic registration followed by a phased vaccination scheduling and management with forecasting tools. The platform also needs to enable automated reporting to local, regional, and national agencies related to vaccination progress and capture of potential side effects from the vaccine.
Leverage existing data systems and interoperability standards to facilitate rapid implementation at the lowest cost. By leveraging interoperability standards such as HL7/FHIR, clinical data can be shared in a scalable manner.
Security, privacy, and compliance are non-negotiable characteristics of any platform used by public sector and health entities.

Partnerships are essential to meet the challenges ahead

Given the scale and complexity, no single government or organization can solve this vaccine distribution challenge on its own. It will take strategic alliances, an ecosystem of delivery partners, and interoperable technology offerings that are secure, transparent, and can scale to meet global demand. Data and artificial intelligence (AI) solutions will be especially important to provide insights and enable public health and government officials to make informed decisions about the virus and facilitate cross-agency collaboration, enable remote work, and deliver trusted services without interruption.

At Microsoft, we have a proven track record of partnering with governments, public health agencies, healthcare organizations, pharmaceutical companies, logistics providers, and other key stakeholders to tackle tough challenges. In the early part of the COVID-19 pandemic, we observed a massive influx of inquiries related to concerns about COVID-19 flooding health care agencies. This led to subsequent overloading of call centers and the crowding of urgent care clinics and hospital emergency rooms, which further increased the risk of spreading the infection. To address these urgent issues, we partnered with governments, public health agencies, and healthcare organizations across the globe to develop and deploy AI-based chatbot technology that could deliver individualized COVID-19 guidance. Today, over 680 million individualized COVID-19 messages have been delivered worldwide since March. The U.S. Centers for Disease Control and Prevention has adopted Microsoft technology and delivered over 37 million messages in October alone.

This same bot technology has been adopted by pharmaceutical companies and researchers to enable large-scale recruitment of donors for clinical trials. With the “The Fight is In Us” campaign, Microsoft in collaboration with the Bill and Melinda Gates Foundation is partnering with academic medical centers, plasma companies, national blood donor organizations, and several other stakeholders to advance the study of convalescent plasma to improve outcomes for patients with COVID-19 infection.² Microsoft is also partnering with Adaptive Biotechnologies to facilitate the evaluation of the immune response in patients exposed to COVID-19 as part of the Immune Race clinical trial.³

Through a collaboration with the American Hospital Association, Kaiser Permanente, Kearney, Merit Solutions, and UPS, we are facilitating the equitable donation and distribution of PPE and other medical supplies to places that have the greatest need.⁴

For decades, Microsoft has cultivated a robust ecosystem of technology partners from global system integrators to local independent software vendors. These partners build industry-specific solutions using Microsoft cloud services and other technologies. Microsoft’s Data and AI technologies, Business Applications, and Modern Workplace offerings can provide powerful analytics, relevant applications, and collaboration tools—and those capabilities are amplified when they are customized by Microsoft’s partners. Today, Microsoft Consulting Services along with several of Microsoft’s partners are helping public health customers address aspects of COVID-19 such as contact tracing, testing, return to work, return to school, and most recently the planning and preparation for vaccination distribution and administration.

Microsoft’s commitment

Microsoft CEO Satya Nadella says “We are adopting a first responder mindset across the company, working with so many customers on the front lines, including governments, health providers, schools, food suppliers, and other commercial customers critical to the continuity and stability of services in every country.” Let us work together during this pandemic to embrace the power of digital, and the power of human innovation to move global vaccination further forward so not only are COVID-19 vaccines available and accessible to all but come when people truly need them most.

We will continue to do our part to help our customers and the global community address this historic challenge.

Microsoft is committed to supporting public health and safety by equipping governments with the resources they need. For further information, use these resources:

Learn more about Microsoft in Government and how you can realize the true transformational power of AI.

References:

¹ The challenge of a lifetime: how to get billions of COVID-19 vaccines around the world

² THE FIGHT IS IN US

³ Help us understand how different people respond to the COVID-19 virus

⁴ Coalition of organizations launch the ‘Protecting People Everywhere’ initiative answering the call to source safe and effective PPE for front-line health care workers

Posted on November 30, 2020 by sick skills — Leave a comment

Medical imaging, AI and the cloud: what’s next?

Today marks the start of RSNA 2020, the annual meeting of the Radiological Society of North America. I participated in my first RSNA 35 years ago and I am super excited—as I am every year—to reconnect with my radiology colleagues and friends and learn about the latest medical and scientific advances in our field. Of course, RSNA will be very different this year. Instead of traveling to Chicago to attend sessions and presentations, and wander the exhibits, I’ll experience it all online. While I will miss the fun, excitement, and opportunities to connect that come with being there in person, I am amazed by what a rich and comprehensive conference the organizers of RSNA 2020 have put together using the advanced digital tools that we have at hand now.

It would be an understatement to say that this has been a year in which nearly everything is very different. From the tragic loss of life and rampant sickness to the economic disruption and the impact on our professions and our children’s education, so much of what we have been through because of COVID-19 has been extremely difficult. But the resilience of the response that so many people and institutions have shown in the face of all these challenges has been remarkable. And if it is possible to say there has been some good in all this, it would have to be the unprecedented transformation of the global healthcare ecosystem as hospitals, clinicians, and researchers have embraced a new generation of advanced digital health technologies that have helped them respond to the coronavirus crisis and laid the foundation for a more effective, affordable, and equitable future for healthcare.

Trends

As we move forward and the digital transformation of healthcare continues to accelerate, I see three significant trends that will influence the future of health and wellness.

One is the rapid emergence of virtual care through digital tools such as telehealth and remote monitoring that have made it safer and more convenient for patients to connect with their doctors during the pandemic, and that is empowering individuals to take charge of their health in entirely new ways. Virtual care has the capacity to personalize, accelerate, and augment treatment and prevention, saving time and money while improving outcomes. The ability to engage patients without requiring an in-person visit to a clinic will help ensure that they receive the right level of care and enable healthcare facilities to better manage the flow of patients into clinics and emergency rooms.

The second trend is the growing clarity of the promise of AI-driven precision medicine to serve as a major catalyst for improving health outcomes. As platforms for precision medicine and real-world evidence mature, we’ll see exciting opportunities to improve treatment and prevention as we personalize patient care and transform how we diagnose infectious disease, cancer, and autoimmune disorders.

And, finally, where healthcare organizations have long been reluctant to move data offsite due to security, trust, and privacy concerns, we have seen a historic shift to the cloud over the last nine months. Now, driven by regulatory changes, the massive increase in medical data, and the critical need to access and analyze all that data by providers, payers, public health agencies, and researchers, it’s clear to everyone that moving to the cloud is both essential and hugely beneficial, both to providers and to patients.

Microsoft Cloud for Healthcare

As part of Microsoft’s ongoing commitment to help healthcare customers and partners continue to make progress toward recovery and build more resilient and effective systems of care, in late October we announced the general availability of Microsoft Cloud for Healthcare. This powerful industry-specific solution provides integrated capabilities for automated and efficient high-value workflows, and advanced data analysis functionally for structured and unstructured data so that healthcare organizations can truly transform information into insight and insight into action.

Built on the trusted capabilities of Microsoft 365, Microsoft Azure, Microsoft Dynamics 365, and Microsoft Power Platform, Microsoft Cloud for Healthcare is designed to enhance patient engagement to make it easier for patients to interact with caregivers, empower health team collaboration to facilitate more efficient and rich real-time communication and collaboration across the care continuum, and improve clinical and operational data insights with the ability of healthcare organizations to connect data from across their systems to predict risk and help improve patient care and operational efficiencies. Our robust partner ecosystem extends the power of Microsoft Cloud for Healthcare by building and extending advanced health solutions to meet the most demanding challenges in healthcare.

Radiology

All of this makes it a particularly exciting time to be a radiologist. In many ways, our field has always been at the forefront of advances in the technologies that improve the movement, management, and analysis of large amounts of health data. This shouldn’t really be a surprise, given that medical imaging accounts for nearly three-quarters of all health data, and analyzing 3D medical images can require up to 50 GB of bandwidth a day.

At Microsoft, streamlining the flow of health data, including medical imaging data, has been a significant focus of our work over the past few years. With the release of the Medical Imaging Server for DICOM (Digital Imaging and Communications in Medicine) in September, we offer developers powerful tools to ingest and persist medical imaging data in the cloud. Elevating interoperability, this is the first cloud technology to bring together DICOM data standard and FHIR (Fast Healthcare Interoperability Resources) which allows for persisting medical imaging metadata alongside other clinical data and sets the stage for multiple scenarios in research and diagnosis which may be too difficult or expensive to execute today.

Now, with Project InnerEye and the open-source InnerEye Deep Learning Toolkit, we’re making machine learning techniques available to developers, researchers, and partners that they can use to pioneer new approaches by training their own ML models, with the aim of augmenting clinician productivity, helping to improve patient outcomes, and refining our understanding of how medical imaging can be combined with other types of data to advance personalized medicine.

Learn more about our latest medical imaging offerings at the RSNA industry hour lunch and learn on December 3, 12:30 PM – 1:30 PM Central Time.

Partners

Reimagining an industry that is as complex and touches as many lives as healthcare is a massive undertaking and at Microsoft, we have the privilege of working with amazing partners who stand at the forefront of innovation and progress in medical imaging technology.

Our partners are building transformative solutions to address some of the most difficult challenges in medical imaging. The amount of data generated by medical diagnostic imaging and connected devices is growing exponentially. Healthcare stakeholders, therefore, need effective ways of handling these data at scale.

This prompted Siemens Healthineers to build a dedicated cloud environment for Healthcare: The teamplay digital health platform. Through a certified gateway, the teamplay receiver, health data from connected medical devices can be aggregated. The teamplay cloud infrastructure is based on Azure, allowing secured processing of data within or outside a hospital’s network.

GE Healthcare’s Centricity™ Universal Viewer Zero Footprint (ZFP) connects advanced diagnostic tools and system-wide image management platforms across the care continuum to help healthcare organizations improve diagnostic speed and confidence. ZFP users can now open Microsoft Teams with one click and share studies with other clinicians via the secure and compliant channels.¹

SOPHiA GENETICS, the company pioneering the Data-Driven Medicine movement—trusted by over 1000 healthcare institutions in 85 countries—is highlighting their radiomics capabilities through the universal SOPHiA Platform for oncology and COVID CT imaging. Radiomics transforms standard medical imaging into mineable data assets that can be analyzed and combined with genomic data for improved decision support of precision medicine. SOPHiA Radiomics Solutions offer comprehensive workflows for multiple research and disease indication needs. SOPHiA multimodal platform is deployed on Microsoft Azure Cloud.

Microsoft and Sectra are partnering on cloud-based enterprise imaging and AI. In our joint RSNA webinar, Reap the benefits of enterprise imaging in the cloud with Microsoft & Sectra on December 3, we will introduce the brand new all-Azure and hybrid Microsoft Azure Stack offering as well as a demo of how Teams integration will help radiologists to cope in the new virtual world. We will hear Judy Bartlett from our joint customer John Muir share her experiences about moving from on-prem to running the Sectra Enterprise Imaging Solution as a Service on Azure.

With the imminent release of a new version of iConnect Enterprise Archive, IBM Watson Health will start to bring to market solutions that support a containerized deployment, in addition to VMWare, on both the IBM Cloud and Azure. The containerization of this portfolio is one of IBM Watson Health’s key initiatives, starting with their VNA foundation and leveraging IBM’s Red Hat OpenShift technology to ensure build once and deploy anywhere to be cloud native and agnostic.

With NVIDIA Clara Imaging, developers and researchers have the ability to accelerate data annotation, build domain-specialized AI models, and deploy intelligent imaging workflows with state-of-the-art pre-trained models and reference applications. Working closely with Azure, these innovators can jumpstart their development in the cloud and also address tough medical imaging challenges faster with Project InnerEye. During the current pandemic, our partnership is heavily accelerating progress Research in drug discovery (UC, Riverside; UCB Covid Moonshot) using GPUs on Azure for quantum mechanics model as well as using AI for SARS COVID-19 risk evaluation in Italy (Hospital San Raffaele, Milan). This partnership also enables the development and deployment of smart hospital solutions, running on NVIDIA Clara Guardian and Azure.

And finally, Flywheel is a cloud-scale informatics platform for biomedical research and collaboration. What is exciting about our differentiated work is the ability to securely leverage cloud at the edge with Microsoft Azure Stack Hub and transform these image analytics with Microsoft AI enabling tools and Flywheel’s depth in medical imaging data management and automated workflows.

Microsoft is the only cloud that extends to the edge from Microsoft Azure Edge Zone for 5G to Microsoft Azure Sphere for security. We’re removing all barriers by covering all security and data sovereignty concerns in the cloud. With over 168,000 partners around the world, the network for innovation and collaboration runs deep. We cannot wait to see how together we will build solutions that transform healthcare around the world.

For more information on Microsoft Cloud for Healthcare, AI imaging tools, or to learn more about partnership visit the Microsoft virtual booth at RSNA or connect with us at our featured demo on November 29, 2:00 PM – 2:30 PM Central Time.

[1] Technology in development that represents ongoing research and development efforts. These technologies are not products and may never become products. Not for sale. Not cleared or approved by the U.S. FDA or any other global regulator for commercial availability.

Posted on November 30, 2020 by sick skills — Leave a comment

Minecraft: Education Edition at this week’s ISTE20 Live

ISTE20 Live is fully virtual this year, and we’ll be right there to help educators explore ways to use Minecraft: Education Edition to support student learning across the curriculum—whether you’re teaching online or in person. We’ll be joining the Microsoft Education team to beam onto your screen with tips, tricks, and advice for game-based learning.

All of our sessions are 15 minutes long, and they’ll be taking place in the Microsoft Content Room, so all you need to do is tune into the stream when there’s a session that interests you. You’ll find sessions on topics from remote learning and inclusive teaching to computer science and digital citizenship. We’ll have moderators from our team in each of the sessions to make sure we’re answering any questions you might have. We’re excited to connect!

To make things easy for you, here’s an at-a-glance schedule of the sessions featuring Minecraft: Education Edition.

Sunday, November 29

10:45 AM PT: Nathan Richards, Remote learning with Minecraft: Education Edition
With learning models changing in ways we’ve never seen before, teachers are adapting to how students learn, connect, and collaborate with one another. Discover ways that Minecraft: Education Edition can help students explore, build, and learn together online when they can’t share the same physical classroom.

Thursday, December 3

11:30 AM PT: Felisa Ford, Good Trouble – Teaching Social Justice in Minecraft: Education Edition
Take a trip through time and across the globe with civil rights activist and Congressman John Lewis to learn about people who changed the world by leading social justice movements. Students embark on a journey that includes Black Lives Matter, the US Civil Rights movement, Gandhi’s struggle for Indian independence, and more. This session unpacks the ways that the Good Trouble lesson can help students understand the impact of these movements and their leaders, and explores how learners can contribute to building a better world.

11:45 AM PT: Becky Keene, Experiencing History and Deep-thinking Skills with Minecraft: Education Edition
See how students engage in learning about history, coding, engineering, and more through the immersive experience of the World War I Toybox in Minecraft: Education Edition.

12:00 PM PT: Suzannah Calvery, Mindful Mining – Infusing Social-emotional Learning with Minecraft
We all need to build our social-emotional intelligence, and the tools available through Minecraft: Education Edition provide opportunities to build mindfulness, communication, and collaboration skills. See how the Mindful Knight lesson teaches mindfulness, empathy, self-regulation, and resilience, then discover more lessons that foster creativity and collaboration.

12:15 PM PT: Bob Irving, Promoting Digital Citizenship – Immersive Roleplay in Minecraft: Education Edition
Learn about how Minecraft: Education Edition’s new Digital Citizenship world provides an immersive tool for teaching students about digital theft, media literacy, sharing, and harassment, preparing them to collaborate successfully with peers online.

12:30 PM PT: Sarah Red-Laird, Build with Bees! STEM Lessons in Minecraft: Education Edition
Turn students’ fear of bees into feelings of fascination and fun with the founder and director of the Bee Girl nonprofit. Explore 11 NGSS-aligned STEM lessons designed to help students understand the importance of bees in our ecosystem, their biology, and how we can contribute to bee health!

1:30 PM PT: Felisa Ford, Good Trouble – Teaching Social Justice in Minecraft: Education Edition
Take a trip through time and across the globe with civil rights activist and Congressman John Lewis to learn about people who changed the world by leading social justice movements. Students embark on a journey that includes Black Lives Matter, the US Civil Rights movement, Gandhi’s struggle for Indian independence, and more. This session unpacks the ways that the Good Trouble lesson can help students understand the impact of these movements and their leaders, and explores how learners can contribute to building a better world.

2:15 PM PT: James Protheroe, Minecraft Hour of Code for Elementary Students: Block-based Coding
The world of computer science can be an intimidating place for those of us who come from non-STEM backgrounds, but bringing code and computational thinking into your classroom doesn’t have to be overwhelming. Join this session to learn more about fostering your own understanding while also introducing computer science principles at a beginner level through this year’s Minecraft Hour of Code block-based coding tutorial.

2:30 PM PT: Andrew Balzer, Minecraft Hour of Code for Intermediate Coders: Text-based Python Coding
The world of computer science can be an intimidating place for those of us who come from non-STEM backgrounds, but bringing code and computational thinking into your classroom doesn’t have to be overwhelming. Join this session to learn more about fostering your own understanding while also introducing computer science principles at an intermediate level through this year’s Minecraft Hour of Code Python activities.

2:45 PM PT: Peter Doherty, Coding in Minecraft: Fun Computer Science for Middle School
Coding in Minecraft is a remote-ready computer science credential and CSTA-aligned curriculum program delivered through Minecraft: Education Edition. This curriculum immerses students in a Minecraft world to develop and demonstrate their coding skills using MakeCode and JavaScript or Python. In this session, you’ll hear from educators who are seeing success with this content.

Friday, December 4

12:15 PM PT: Steve Isaacs, Learning Through Creative Competition with eSports in Minecraft: Education Edition
With the number of eSports spectators now eclipsing that of the NFL in the US, how can educators harness students’ passion for competitive gaming to drive learning outcomes in classrooms and after-school clubs? In this session, learn about ways that Minecraft: Education Edition is entering this exciting new arena.

Saturday, December 5

10:45 AM PT: Nathan Richards, Remote Learning with Minecraft: Education Edition
With learning models changing in ways we’ve never seen before, teachers are adapting to how students learn, connect, and collaborate with one another. Discover ways that Minecraft: Education Edition can help students explore, build, and learn together online when they can’t share the same physical classroom.

You can find all of these sessions and more in the Microsoft ISTE20 Live schedule. Come connect with us, bring your questions, and enjoy the virtual conference experience with our team! If you’re curious about Minecraft: Education Edition and want to come to the table with a few questions, explore this powerful tool for game-based learning at education.minecraft.net.

Posted on November 24, 2020 by sick skills — Leave a comment

World Update II: USA for Microsoft Flight Simulator now available for free

In September, we shared our vision for continuously improving Microsoft Flight Simulator by bringing meaningful updates to the simulator on a monthly basis. Today, we are launching our second World Update, and we’re thrilled to provide simmers with an enhanced flight experience in the United States of America. With its motto of “E Pluribus Unum” (“Out of Many, One”), the United States of America is truly a vast collection of diverse territories – from coastal communities to colossal mountain ranges, from verdant plains to metropolitan skylines.

World Update II: USA features an improved digital elevation model with resolution up to one meter, new aerial textures that significantly improve the appearance in several states across the country, and four new hand-crafted airports (Atlanta, Dallas/Fort Worth, Friday Harbor, and New York Stewart). We’ve also made visual improvements to 48 other airports and added 50 new high-fidelity points of interest across the country to make your state-side journey stunning in every way.

And that’s not all – this update also includes exhilarating new activities on each coast. Enjoy a Discovery Flight through some of the most iconic locations on the eastern seaboard, and then jet out west for an epic new Bush Trip across the Alaskan wilderness.

Once you download the latest update for Microsoft Flight Simulator, be sure to head to the in-sim Marketplace to claim World Update II: USA and partake in the majesty on display in the Land of the Free and the Home of the Brave.

World Update II: USA is free to all Microsoft Flight Simulator players starting today on Xbox Game Pass for PC, Windows 10, and Steam.

Posted on November 24, 2020 by sick skills — Leave a comment

Achieving 100 percent renewable energy with 24/7 monitoring in Microsoft Sweden

Earlier this year, we made a commitment to shift to 100 percent renewable energy supply in our buildings and datacenters by 2025. On this journey, we recognize that how we track our progress is just as important as how we get there.

Today, we are announcing that Microsoft will be the first hyperscale cloud provider to track hourly energy consumption and renewable energy matching in a commercial product using the Vattenfall 24/7 Matching solution for our new datacenter regions in Sweden, which will be available in 2021.

Vattenfall and Microsoft are also announcing that the 24/7 hourly matching solution—the first commercial product of its kind—is now generally available. Vattenfall is a leading European energy company with a strong commitment to make fossil-free living possible within one generation. The solution is built using Microsoft’s Azure services, including Azure IoT Central and Microsoft Power BI.

Today’s announcement builds on last year’s partnership announcement with Vattenfall when the 24/7 Matching solution was first introduced. Since then, the solution has been in pilot in Vattenfall headquarters in Solna and the new Microsoft headquarters in Stockholm, which has seen 94 percent of the total office building energy consumption matched with Swedish wind and 6 percent matched with Swedish hydro power.

We continually invest in new ways to make our buildings and datacenters more energy efficient and sustainable. As part of today’s announcement, Microsoft is signing a power purchase agreement (PPA) to cover 100 percent of Microsoft’s energy consumption in Sweden. Microsoft will ensure that the company’s operations in Sweden use renewable energy.

The Vattenfall 24/7 Matching solution enables us to have a more accurate picture of energy used to match with Guarantees of Origin (GOs). This marks another important step in our commitment to be carbon negative by 2030 and use 100 percent renewable energy by 2025.

Vattenfall and Microsoft 24/7 matching of renewable energy. Source: Vattenfall and Microsoft pilot world’s first hourly matching (24/7) of renewable energy.

Increasing transparency and accuracy of renewable energy matching

Fulfilling our 100 percent renewable energy commitment requires a better way of tracking renewable electricity. Today, the industry is using Energy Attribute Certificates, called Guarantees of Origin (GOs) in Europe and Renewable Energy Certificates (RECs) in the US. These ensure that the amount of electricity sold corresponds to the amount produced. GOs allow end consumers to choose electricity from a specific source; this enables them to choose electricity exclusively from renewable sources such as wind, solar, or hydropower.

While we have seen remarkable progress toward renewable sourcing and commitments, there is a fundamental flaw in monitoring the source and quantity of energy consumed. For any given hour, a business does not know the source of the energy they are consuming. That energy may come from renewable sources, or it may be produced from fossil fuel. The current system has no way of matching the supply of renewable energy with demand for that energy on an hourly basis. And without the transparency of supply and demand, market forces cannot work to ensure that renewable energy demand is supplied from renewable sources.

Through this solution, Microsoft Sweden’s new home is powered by renewable energy through the procurement of GOs, which traces electricity from renewable sources to provide information to electricity customers on the source of their energy—not just on a monthly or yearly basis, but on an hourly basis.

The 24/7 matching of GOs and renewable energy credits (RECs) offers the following benefits:

Businesses can see if their commitment to 100 percent renewable energy cover each hour of consumption and translate sourcing of renewable energy into climate impact.
Energy providers can more easily understand demands for renewable energy hour-by-hour and take action to help production meet demand.
24/7 matching of consumption to production drives true market demand for renewable energy. As 24/7 hourly renewable products are rolled out across the world, they will incentivize investment in energy storage such that energy companies can store renewable energy when it is generating, so they can continue to supply their customers with renewable energy when it is not. Over time, this storage will allow electricity grids to supply 100 percent decarbonized power.
The system can inspire regulatory change in how GOs and RECs are created, acquired and retired.

You can learn more about the advantages of 24/7 monitoring by watching the Vattenfall 24/7 solution video.

IoT for more accurate energy monitoring

IoT enables companies to gain near real-time insights of the physical world, connecting objects to give you insights into the health of a system or process, predict failures before they happen and gain overall efficiencies in operations.

The Vattenfall 24/7 hourly monitoring solution leverages Azure IoT Central to manage the full picture of energy consumption in a given building. Azure IoT Central helps solution builders move beyond proof of concept to building business-critical applications they can brand and sell directly or through Microsoft AppSource. Today, Microsoft offers two IoT Central energy app templates for solar panel and smart meter monitoring to help energy solution builders accelerate development.

Commitment to building world-class, sustainable datacenters

We believe that our datacenters should be positive contributors to the grid, and we continue to innovate in energy technology and monitoring resources to support our corporate commitment to be carbon negative by 2030.

Posted on November 24, 2020 by sick skills — Leave a comment

Making credit flow again in India during the pandemic

When COVID-19 created a massive health crisis across India this year, it also triggered an unprecedented credit freeze. Millions of people were ordered to stay at home for months on-end, so lenders and customers could not meet face-to-face–a traditional prerequisite for doing business.

No meetings meant almost no new loans.

“The lending business came to a standstill to almost zero from April to June as the whole country was under a lockdown,” recalls Gaurav Aggarwal, head of unsecured loans at Paisabazaar.com, India’s largest marketplace for personal lending products.

The worst of the lockdowns appears over, at least for now. But India is far from being out of the pandemic woods and is working hard on two prime tasks–getting on top of the virus and getting its economy going.

To achieve the latter, credit must again flow freely.

Now a six-year-old fintech startup, Paisabazaar.com has stepped up with a new solution. It’s using cloud computing and machine learning to digitally overhaul the processes surrounding personal loan applications and approvals so money that can get to consumers and businesspeople faster.

What used to take anywhere between five days to a week before the pandemic is now being done in less than 24 hours, and in some cases as quickly as five hours.

Applying for a personal bank loan or a credit card in the traditional way can be a drawn-out affair. Either a customer visits a bank, or a bank representative comes to them to verify their identity. Paper application forms are filled out and supporting documents are collected for manually checking.

When the lockdowns were imposed, these physical and in-person processes were broken, and lending more or less stopped.

The time was ripe for disruption and Paisabazaar.com found itself in the right place at the right time.

In August, the startup launched the ‘Paisabazaar Stack’–a solution that enables lending companies, like banks and non-banking financial corporations (NBFCs), to disburse unsecured loans in a presence-less, completely digital manner.

Embracing a culture of innovation

Photo of a man smiling at the camera. — Gaurav Aggarwal, head of unsecured lending business, Paisabazaar.com

The lending process typically consists of four elements–offering the loan seeker the best offer based on their need and eligibility; collecting documents to establish their identity and ability to repay the loan; verifying those documents; and finally, signing the loan agreement and payment terms.

“One of the big realizations that we had that we if we had to change something, it had to be changed from end-to-end,” says Aggarwal.

As the pandemic brought the whole lending industry down to its knees, Paisabazaar.com, which translates into money (paisa) market (bazaar) in Hindi, embarked on its quest to digitize the entire process.

To make it happen, the startup embraced a culture of innovation. A recent study by IDC commissioned by Microsoft identifies this as the synergy between technology, process, data, and people, that allows organizations to drive sustained innovation.

The study looked at organizations that regard a time of crisis as an opportunity for transformation. It found that they are 1.5 times more confident about recovering within six months and growing their revenues compared with their peers. This is clearly the case with Paisabazaar.com.

“We were trying to create this stack for six months before the pandemic hit us. We wanted to create paperless digital programs, but things were not moving because the industry was not ready,” says Mukesh Sharma, Paisabazaar.com’s chief technology officer (CTO.) “But when it (the lockdown) happened, we were the first to launch this digital stack.”

One of the first challenges the startup had to overcome was to improve the loan approval rates. Even before the pandemic, almost 40% of loans were getting rejected on the platform as customers weren’t aware how the lending industry and regulations function. They’d get swayed by marketing gimmicks, and end up submitting multiple loan applications. This had an adverse effect on their credit worthiness and further reduced their chance of approvals.

When Paisabazaar.com’s team studied the data from rejected applications on their platform, they realized they could help customers by guiding them toward other offers, which had a higher chance of approval.

“We kept monitoring our funnels and data on these rejected applications, did detailed retrospection, and spoke to the customers and lenders to find the root cause (of loan rejections). We could clearly see the customers’ pain, especially when they are in dire need for money or a credit card,” says Sharma.

Paisabazaar.com’s machine learning team created a model based on lending data of over 50 partner banks and financial institutions over the last six years.

Photo of the Paisabazaar website on a laptop screen — The chance of approval feature, which gets more intelligent with every loan disbursed through Paisabazaar.com, has helped increase approval rate by nearly 25 percent in the first 12 months (Photo by Amit Verma)

The model, which is built on Microsoft Azure and uses technologies like Azure Kubernetes services, Azure Container Service, and Azure Virtual Machine Scale Sets, matches a borrower’s profile like income, credit score, age, among others, with the various lending criteria of different lenders. It then provides customers with the odds of getting their loan application approved—excellent, good, fair, or poor—against each lender.

The team also looked at how they could digitize the “Know Your Customer” (KYC) process, which involves verifying who they said they were. Using Azure Cognitive Services, Paisabazaar.com created digital KYC processes, including Video KYC, where they not only verify the borrower’s identity but also their location and liveliness—ensuring they were real people and not bots.

To verify documents to determine the customer’s loan eligibility, they created algorithms using Optical Character Recognition APIs on Azure. These identify and confirm a customer’s monthly income from their bank account statements and digitize a lot of backend work that used to be done manually.

A tectonic shift

Paisabazaar.com now offers this entire end-to-end digitization stack to banks and NBFCs on its platform and the results are overwhelming.

The chance of approval feature, which gets more intelligent with every loan disbursed through Paisabazaar.com, has helped increase approval rate by nearly 25 percent in the first 12 months.

Photo of the Paisabazaar website shown on a laptop screen — The Paisabazaar Stack, which did not exist a few months ago, now accounts for more than half of all personal loans disbursed from the platform (Photo by Amit Verma)

Even though many COVID-19 lockdown restrictions have now been eased, lenders continue to rely on the digital process to disburse loans.

The Paisabazaar Stack, which did not exist a few months ago, now accounts for more than half of all personal loans disbursed from the platform and the company is optimistic that business will be back to pre-pandemic levels by early next year.

“The Paisabazaar Stack is a fundamental and tectonic shift in the lending industry,” says Aggarwal, the head of unsecured loans business.

Meanwhile, for Paisabazaar.com’s CTO, the experience has only strengthened his resolve to innovate faster and launch new products. The use of cloud, AI, and machine learning has enabled Sharma to empower his team to experiment and build new experiences and products for their customers and partners. Every member of his team, he reckons, is an entrepreneur, which is core to the company’s DNA.

“We’ve a language-agnostic, idea-agnostic, and platform-agnostic framework where people can come and pitch in. Microsoft Azure not only brings out the best of the industry standards to us but also cutting-edge technologies. We were one of the earliest organizations in the country to use Kubernetes on Azure and Azure Cognitive Services at such a large scale,” says Sharma.

Paisabazaar.com is now working on new models that will provide access to credit to a wider swathe of India’s population. The expectation is that the digitization of processes for existing customers would eventually help them create models that would bring financial inclusion to those who currently fall outside the credit net.

“The flow of credit will eventually move to segments that are currently underserved,” says Aggarwal. “The quality of data we’re getting due to the digitization of processes is much higher than what was being collected physically. These gains will start flowing back into the system and lenders will start getting comfortable with the processes. The “fintech revolution” that was happening in the pre-COVID days now has a high potential of going mainstream.”

Sharma agrees. He recalls how, a couple of years ago, they worked with their fintech lending partners to create alternate models to underwrite small loans ranging from INR 10,000 to INR 50,000 (approximately USD 135 to USD 700) largely to first time salary earners. Most large lenders like banks would not traditionally cater to this segment, due to the small loan size as well as the fact that the borrowers were new to credit and would not meet the banks’ eligibility conditions. This also helped Paisabazaar.com cater to customers from smaller cities and towns.

Now PaisaBazaar.com is developing a new product aimed at owners of small businesses, which would enable them to raise loans in the range of INR 30,000-50,000 (approximately USD 400-650), which they can pay back and keep raising again, for working capital or other needs.

“Technology is the key enabler here,” Sharma says. “The straightforward answer to choosing Microsoft is that we fundamentally believe in what Microsoft does, which is to empower every person and every organization on the planet to achieve more. Both the companies are trying to solve the one common problem, which is how we can use technology to solve customer problems.”

Sambit Satpathy also contributed to this report.

Posted on November 23, 2020 by sick skills — Leave a comment

Research reveals three distinct parent mindsets about remote and hybrid learning

As a veteran teacher, I usually had a pretty good idea of how I could support parents and guardians with their students’ education. But sometimes a family-teacher conference would reveal something I didn’t know. I realized that together, we could work on a solution.

That was before the pandemic—back when the learning environment was still fully in the classroom and educators could meet with families face-to-face. In this new remote and hybrid learning environment, we don’t have the experience to know what our families need from us. And with social distancing in place, it’s more challenging to find out.

So, Microsoft did the asking to find even better solutions for the current environment.

I’m part of an independent research team, Program 11, that reached out to parents to learn more about how families are dealing with remote and hybrid learning. There’s been a lot of speculation about what parents and guardians are struggling with (and our team had our own personal experiences as parents and educators), but we wanted to hear it from a broader audience.

The question was: How could Microsoft tools and technology help parents and families support their students’ remote and hybrid learning even more?

Our interviews and survey results revealed that even though parents share some challenges and beliefs, their experiences are not universal. So, there can be no “one-size-fits-all” approach to supporting families. Luckily, three sizes cover most!

We found that most families fall within one of three different categories. Families feel like they’re either thriving, coping, or overwhelmed. I’ll go over some of the research data^1,2, and describe the three parent mindsets. Then I’ll show you what we’re doing to help educators get families the resources they’ve asked for.

What parents and guardians agree on

To say that educators are working tirelessly is an understatement. You continue to provide amazing instruction, focus on student well-being, and communicate with parents despite all the challenges that accompany remote and hybrid learning. The results of our research show that parents know this, and they appreciate it.

The majority of parents are satisfied or very satisfied with teacher communication, one-on-one time and the resources teachers are providing to support remote learning.

Even though parents and guardians are impressed by teachers, many feel schools and districts are asking too much of parents during remote or hybrid learning. Parents continue to worry about their student’s health, online safety, and social-emotional well-being. They want resources to help them more effectively engage in their student’s learning, especially when they don’t feel confident in their ability to offer support.

About 45 percent of parents “worry a lot” about both COVID-19 and their student staying on track in school.

Different parent mindsets

I’m sure it comes as no surprise that even though parents share some similar opinions, some are having vastly different experiences. You’ve likely witnessed this in your own practice.

Some parents feel like their families are thriving in the remote or hybrid learning environment. These parents are deeply engaged in their student’s learning and are seeking ways to take their student’s academic education to the next level. These parents often have older students or students who perform above grade-level.

Others feel like they are coping. These parents have concerns about their student’s social and emotional well-being and health that sometimes overshadow academic concerns. They feel the pressures of balancing school with other responsibilities but feel more engaged in their student’s learning than ever before.

And other parents feel overwhelmed by the demands placed on them due to remote and hybrid learning. These parents are concerned about meeting their family’s basic needs and do not feel confident they have the skills or resources to support their student’s education right now. These families are more likely to have younger students.

Parent mindsets are not fixed. With support, even the most overwhelmed parents can begin to feel like they’re thriving!

Supporting educators in supporting families

This data really helps us better understand how families are experiencing remote and hybrid learning. But what’s really important to an educator is what education technology companies like Microsoft can do to help.

And here it is: an easy to navigate webpage where you can send your families to learn which parent mindset describes their experience. From there, they can find resources picked specifically for them, based on their needs and preferences.

We hope that these resources help parents and families feel more confident about supporting their student’s education. Teachers, if you’d like to provide the families of your students with more information, please download this infographic to send with your next correspondence, or you can provide them with a link to the parent mindset webpage. You can also urge parents and families to join the free remote learning family workshop series that Microsoft is hosting.

You can download the full Parent and Family Remote and Hybrid Learning research brief here.

About the author:

Teagan Carlson is an education consultant and writer whose work has been featured in Edsurge. She joined the education research team at Program 11 as a subject matter expert, having taught ELA and ELD for fourteen years. She has her M.A. in Educational Psychology.

Footnotes:

1. Microsoft, “Survey Data Helps Microsoft Uncover Three Distinct Parent Mindsets When It Comes to Remote and Hybrid Learning.” https://aka.ms/MSParentSurveyChartsDeck

2. Microsoft, “Microsoft Education Parent and Family Research.” https://aka.ms/MSParentSurveyResearchBrief