As we continue to deliver on our customer commitments to cloud and AI innovation, we remain resolute in our commitment to advancing sustainability. A critical part of achieving our company goal of becoming carbon negative by 2030 is reimagining our cloud and AI infrastructure with power and energy efficiency at the forefront.

We’re pursuing our carbon negative goal through three primary pillars: carbon reduction, carbon-free electricity, and carbon removal. Within the pillar of carbon reduction, power efficiency and energy efficiency are fundamental to sustainability progress, for our company and for the industry as a whole.

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Although the terms “power” and “energy” are generally used interchangeably, power efficiency has to do with managing peaks in power utilization, whereas energy efficiency has to do with reducing the overall amount of power consumed over time.

This distinction becomes important to the specifics of research and application because of the type of efficiency in play. For an example of energy efficiency, you might choose to explore small language models (SLMs) with fewer parameters that can run locally on your phone, using less overall processing power. To drive power efficiency, you might look for ways to improve the utilization of available power by improving predictions of workload requirements.  

From datacenters to servers to silicon and throughout code, algorithms, and models, driving efficiency across a hyperscale cloud and AI infrastructure system comes down to optimizing the efficiency of every part of the system and how the system works as a whole. Many advances in efficiency have come from our research teams over the years, as we seek to explore bold new ideas and contribute to the global research community. In this blog, I’d like to share a few examples of how we’re bringing promising efficiency research out of the lab and into commercial operations.

Silicon-level power telemetry for accurate, real-time utilization data

We’ve made breakthroughs in delivering power telemetry down to the level of the silicon, providing a new level of precision in power management. Power telemetry on the chip uses firmware to help us understand the power profile of a workload while keeping the customer workload and data confidential. This informs the management software that provides an air traffic control service within the datacenter, allocating workloads to the most appropriate servers, processors, and storage resources to optimize efficiency.

Working collaboratively to advance industry standards for AI data formats

Inside the silicon, algorithms are working to solve problems by taking some input data, processing that data through a series of defined steps, and producing a result. Large language models (LLMs) are trained using machine learning algorithms that process vast amounts of data to learn patterns, relationships, and structures in language.

Simplified example from Microsoft Copilot: Imagine teaching a child to write stories. The training algorithms are like the lessons and exercises you give the child. The model architecture is the child’s brain, structured to understand and create stories. Inference algorithms are the child’s thought process when writing a new story, and evaluation algorithms are the grades or feedback you give to improve their writing.¹

One of the ways to optimize algorithms for efficiency is to narrow the precision of floating-point data formats, which are specialized numerical representations used to handle real numbers efficiently. Working with the Open Compute Project, we’ve collaborated with other industry leaders to form the Microscaling Formats (MX) Alliance with the goal of creating and standardizing next-generation 6- and 4-bit data types for AI training and inferencing. 

Narrower formats allow silicon to execute more efficient AI calculations per clock cycle, which accelerates model training and inference times. These models take up less space, which means they require fewer data fetches from memory, and can run with better performance and efficiency. Additionally, using fewer bits transfers less data over the interconnect, which can enhance application performance or cut network costs. 

Driving efficiency of LLM inferencing through phase-splitting

Research also shows promise for novel approaches to large language model (LLM) inference, essentially separating the two phases of LLM inference onto separate machines, each well suited to that specific phase. Given the differences in the phases’ resource needs, some machines can underclock their AI accelerators or even leverage older generation accelerators. Compared to current designs, this technique can deliver 2.35 times more throughput under the same power and cost budgets.²

Learn more and explore resources for AI efficiency

In addition to reimagining our own operations, we’re working to empower developers and data scientists to build and optimize AI models that can achieve similar outcomes while requiring fewer resources. As mentioned earlier, small language models (SLMs) can provide a more efficient alternative to large language models (LLMs) for many use cases, such as fine-tuning experimentation on a variety of tasks or even grade school math problems.

In April 2024, we announced Phi-3, a family of open, highly capable, and cost-effective SLMs that outperform models of the same and larger sizes across a variety of language, reasoning, coding, and math benchmarks. This release expands the selection of high-quality models for customers, offering practical choices for composing and building generative AI applications. We then introduced new models to the Phi family, including Phi-3.5-MoE, a Mixture of Experts model that combines 16 smaller experts into one, and Phi-35-mini. Both of these models are multi-lingual, supporting more than 20 languages.

Learn more about how we’re advancing sustainability through our Sustainable by design blog series, starting with Sustainable by design: Advancing the sustainability of AI.

¹Excerpt from prompting Copilot with: please explain how algorithms relate to LLMs.

²Splitwise: Efficient generative LLM inference using phase splitting, Microsoft Research.

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Today, we’re announcing a power purchase agreement (PPA) with Constellation that will enable the restart of an 835 megawatt (MW) nuclear facility in Pennsylvania that was retired in 2019. This will bring a significant supply of net-new, reliable, carbon-free electricity to the PJM power grid, the regional transmission organization covering 13 states, recognizing the importance of nuclear energy and complementing our 34 gigawatt (GW) contracted renewable energy portfolio in 24 countries.

As highlighted by the International Energy Agency, complete grid decarbonization will require a multi-technology approach with a broad range of carbon-free technologies such as wind, solar, geothermal, clean hydrogen, sustainable biomass, nuclear, fusion, energy efficiency, and storage, as well as transmission infrastructure to connect these technologies to the grids that need them.¹ Alongside our extensive work on carbon reduction and carbon removal, Microsoft embraces this multi-technology approach as an essential pathway to achieving our goal of becoming carbon negative by 2030.

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As we continue to expand our portfolio of solutions to accelerate the energy transition, we collaborate with governments, communities, developers, and energy service providers in many ways. In this blog, I’ll share more about how we approach our work to (1) shape market demand for carbon-free electricity and (2) advance energy policy through advocacy.

Shaping market demand to accelerate the addition of carbon-free electricity

We employ a wide range of contracting mechanisms to meet our goals and secure carbon-free electricity, crafting innovative agreement structures alongside our large portfolio of renewable PPAs. A few examples:

• Our recently announced five-year global agreement with Brookfield Renewable Partners provides a pathway for the development of more than 10.5 gigawatts of new renewable energy capacity in the United States and Europe, almost eight times larger than the largest corporate PPA ever signed. This agreement provides an incentive for Brookfield to build a large portfolio of new renewable energy projects in the coming years, contributing to the decarbonization of the grid, and matched to the locations where Microsoft consumes electricity.
• In Washington state, our agreement with Powerex matches hourly datacenter demand with direct deliveries of carbon-free hydro, solar, and wind power on a 24-hour basis throughout the year. During the day, when our contracted renewable resources produce more power than needed, Powerex takes the surplus renewable power, conserving water from hydropower reservoirs and effectively storing it like a battery. This energy can then be delivered back to the datacenter in later hours, for example at night when wind and solar sources may be offline.
• As a global company committed to decarbonization on a global level, Microsoft also has worked to develop renewable energy in communities and locations that often are not prioritized. An example of this unique approach was our five-year framework agreement with Pivot Energy to develop up to 500 MW of community-scale solar energy projects across the US between 2025 and 2029. The agreement will enable Pivot to develop approximately 150 US solar projects in roughly 100 communities across 20 states, including Colorado, Maryland, Illinois, Delaware, Pennsylvania, and Ohio, with each solar project including significant community benefits.  

Advancing carbon-free electricity through policy advocacy

Our public policy advocacy relating to the electrical grid is focused on accelerating the transition to clean electricity generation, modernizing and improving grid infrastructure, and encouraging an equitable energy future. A grid mix that includes adding and retaining firm carbon-free energy technologies as well as renewables will be pivotal to providing electricity access across the globe and progressing decarbonization.

In December 2023, we published a policy brief on advanced nuclear and fusion energy that highlights the importance of carbon-free electricity and the role advanced nuclear and fusion energy will have in a decarbonized energy future. As advanced carbon-free energy technologies are developed, each comes with its own set of considerations, benefits, risks, regulatory dynamics, and acceptance. Our policy priorities are focused on advancing research, development, and demonstration projects; enabling safe deployment of technologies; and encouraging an efficient and effective regulatory process for new technologies to be deployed.

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Discover more about how Microsoft is advancing the sustainability of cloud and AI through our blog series on the topic:

• Sustainable by design: Advancing the sustainability of AI
• Sustainable by design: Transforming datacenter water efficiency
• Sustainable by design: Innovating for energy efficiency in AI, part 1

¹The path to limiting global warming to 1.5 °C has narrowed, but clean energy growth is keeping it open, IEA, 2023.

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Earlier this summer, my colleague Noelle Walsh published a blog detailing how we’re working to conserve water in our datacenter operations: Sustainable by design: Transforming datacenter water efficiency, as part of our commitment to our sustainability goals of becoming carbon negative, water positive, zero waste, and protecting biodiversity.

At Microsoft, we design, build, and operate cloud computing infrastructure spanning the whole stack, from datacenters to servers to custom silicon. This creates unique opportunities for orchestrating how the elements work together to enhance both performance and efficiency. We consider the work to optimize power and energy efficiency a critical path to meeting our pledge to be carbon negative by 2030, alongside our work to advance carbon-free electricity and carbon removal.

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The rapid growth in demand for AI innovation to fuel the next frontiers of discovery has provided us with an opportunity to redesign our infrastructure systems, from datacenters to servers to silicon, with efficiency and sustainability at the forefront. In addition to sourcing carbon-free electricity, we’re innovating at every level of the stack to reduce the energy intensity and power requirements of cloud and AI workloads. Even before the electrons enter our datacenters, our teams are focused on how we can maximize the compute power we can generate from each kilowatt-hour (kWh) of electric power.

In this blog, I’d like to share some examples of how we’re advancing the power and energy efficiency of AI. This includes a whole-systems approach to efficiency and applying AI, specifically machine learning, to the management of cloud and AI workloads. Learn more about how we’re bringing efficiency research from the lab into commercial operations in Sustainable by design: innovating for energy efficiency in AI, part 2.

Driving efficiency from datacenters to servers to silicon

Maximizing hardware utilization through smart workload management

True to our roots as a software company, one of the ways we drive power efficiency within our datacenters is through software that enables workload scheduling in real time, so we can maximize the utilization of existing hardware to meet cloud service demand. For example, we might see greater demand when people are starting their workday in one part of the world, and lower demand across the globe where others are winding down for the evening. In many cases, we can align availability for internal resource needs, such as running AI training workloads during off-peak hours, using existing hardware that would otherwise be idle during that timeframe. This also helps us improve power utilization.

We use the power of software to drive energy efficiency at every level of the infrastructure stack, from datacenters to servers to silicon.

Historically across the industry, executing AI and cloud computing workloads has relied on assigning central processing units (CPUs), graphics processing units (GPUs), and processing power to each team or workload, delivering a CPU and GPU utilization rate of around 50% to 60%. This leaves some CPUs and GPUs with underutilized capacity, potential capacity that could ideally be harnessed for other workloads. To address the utilization challenge and improve workload management, we’ve transitioned Microsoft’s AI training workloads into a single pool managed by a machine learning technology called Project Forge.

Currently in production across Microsoft services, this software uses AI to virtually schedule training and inferencing workloads, along with transparent checkpointing that saves a snapshot of an application or model’s current state so it can be paused and restarted at any time. Whether running on partner silicon or Microsoft’s custom silicon such as Maia 100, Project Forge has consistently increased our efficiency across Azure to 80 to 90% utilization at scale.

Safely harvesting unused power across our datacenter fleet

Another way we improve power efficiency involves placing workloads intelligently across a datacenter to safely harvest any unused power. Power harvesting refers to practices that enable us to maximize the use of our available power. For example, if a workload is not consuming the full amount of power allocated to it, that excess power can be borrowed by or even reassigned to other workloads. Since 2019, this work has recovered approximately 800 megawatts (MW) of electricity from existing datacenters, enough to power approximately 2.8 million miles driven by an electric car.¹  

Over the past year, even as customer AI workloads have increased, our rate of improvement in power savings has doubled. We’re continuing to implement these best practices across our datacenter fleet in order to recover and re-allocate unused power without impacting performance or reliability.

Driving IT hardware efficiency through liquid cooling

In addition to power management of workloads, we’re focused on reducing the energy and water requirements of cooling the chips and the servers that house these chips. With the powerful processing of modern AI workloads comes increased heat generation, and using liquid-cooled servers significantly reduces the electricity required for thermal management versus air-cooled servers. The transition to liquid cooling also enables us to get more performance out of our silicon, as the chips run more efficiently within an optimal temperature range.

A significant engineering challenge we faced in rolling out these solutions was how to retrofit existing datacenters designed for air-cooled servers to accommodate the latest advancements in liquid cooling. With custom solutions such as the “sidekick,” a component that sits adjacent to a rack of servers and circulates fluid like a car radiator, we’re bringing liquid cooling solutions into existing datacenters, reducing the energy required for cooling while increasing rack density. This in turn increases the compute power we can generate from each square foot within our datacenters.

Learn more and explore resources for cloud and AI efficiency

Stay tuned to learn more on this topic, including how we’re working to bring promising efficiency research out of the lab and into commercial operations. You can also read more on how we’re advancing sustainability through our Sustainable by design blog series, starting with Sustainable by design: Advancing the sustainability of AI and Sustainable by design: Transforming datacenter water efficiency. 

For architects, lead developers, and IT decision makers who want to learn more about cloud and AI efficiency, we recommend exploring the sustainability guidance in the Azure Well-Architected Framework. This documentation set aligns to the design principles of the Green Software Foundation and is designed to help customers plan for and meet evolving sustainability requirements and regulations around the development, deployment, and operations of IT capabilities.  

¹Equivalency assumptions based on estimates that an electric car can travel on average about 3.5 miles per kilowatt hour (kWh) x 1 hour x 800.

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AI is reshaping our world as the fastest adopted technology in history—a global phenomenon with profound local implications. As we witnessed during the Microsoft AI Tour event in São Paulo, Brazil is quickly emerging as a world-class AI innovation hub, a testament to the country’s collective ambition and optimism in the power of AI to deliver economic results, foster inclusive development, and ultimately benefit markets, organizations, communities, and individuals. In fact, “By massively adopting AI, Brazil can experience productivity gains that will add a few percentage points to its GDP in the near future,” said Tânia Cosentino, General Manager of Microsoft Brazil.

AI technology harbors significant potential for our customers and partners, echoing the transformative impact envisioned by Microsoft founder Bill Gates when he first sought to place a personal computer in every home worldwide. I am proud and excited to continue this vision of driving digital transformation across the globe alongside Microsoft. At the same time, it is crucial to embrace of this innovation through responsible usage.

As Brazil takes the lead during its G20 presidency in 2024, it faces a significant opportunity to spearhead discussions on establishing global AI governance guidelines. This will help maximize AI’s benefits while addressing matters related to privacy, security, and employment, thus supporting equitable and inclusive growth. The report, AI in Brazil: Exploring Opportunities, examines this junction and illustrates Microsoft’s dedication to making AI technology beneficial and sustainable, considering economic, social, and environmental factors. Together with our customers and partners, we are not merely observers but active participants in a technological revolution that fosters global unity, economic mobility, and local transformation.

The creativity and ingenuity of Brazilian organizations in leveraging cutting-edge AI technology for tangible, real-world impact are incredibly inspiring. As showcased by the companies and public entities featured here, AI presents unlimited opportunities across all sectors. These are inspiring examples of how we can reimagine what we can achieve with AI.

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Petrobras enhances productivity and decision-making with ChatPetrobras AI tool

Petrobras, a leading company in the global energy sector, has formed a partnership with Microsoft to create ChatPetrobras, an internal tool powered by AI. Utilizing the GPT model and AI technologies from Microsoft Azure OpenAI Service, ChatPetrobras aims to facilitate faster decision-making, provide valuable business insights, and improve internal workflow efficiency for more than 100,000 Petrobras workers, while ensuring compliance with strict information security standards, data protection laws, and Brazilian government regulations.

Azure OpenAI Service powers ChatPetrobras with capabilities in natural language understanding and generation, translation, and code generation. This tool is set to benefit a wide range of business and administrative tasks, including Exploration and Production (E&P), Reservoirs and Wells, Commercialization, Information and Communication Technology, Engineering, Legal, and Human Resources. Its versatility demonstrates the potential of generative AI to revolutionize both technical and corporate segments of the company. In addition, ChatPetrobras incorporates advanced security and protection layers native to Azure OpenAI Service, ensuring all data remains under the company’s internal domain.

In keeping with the company’s commitment to pursuing innovative solutions to industry challenges, “ChatPetrobras represents our latest effort to harness artificial intelligence to enhance the productivity, quality, and efficiency of our processes,” said Carlos Augusto Barreto, Executive Manager of Information and Communications Technology at Petrobras.

ChatPetrobras is not just a standalone tool but part of a broader strategy to incorporate AI usage within the company, empowering every employee to leverage data science capabilities. Petrobras envisions a future where all employees can easily access advanced tools and technical skills, driving value creation through AI.

SEDUC-SP aims to enhance efficacy of education with AI copilot

The Government of the State of São Paulo has partnered with Microsoft to integrate AI Copilot into daily classroom activities, in a move that aims to benefit teachers and over 3 million students across São Paulo by streamlining tasks such as assignment corrections, test scoring, and providing student guidance.

The integration of Azure OpenAI Service is designed to serve as a comprehensive record center, offering a range of functionalities from analyzing student texts to suggesting potential grades for assignments. For instance, a student can write a text on a computer, and upon completion, the app provides suggestions for improvement and identifies errors. This immediate feedback mechanism is followed by personalized guidance from the teacher, ensuring a holistic learning experience. According to Secretary of Education of São Paulo, Renato Feder, this approach not only streamlines the educational process but also enriches learning outcomes.

The partnership between the Government of São Paulo and Microsoft, through the deployment of Generative AI, marks a significant step forward in leveraging technology to support education. By automating routine tasks and providing immediate, actionable feedback, this initiative promises to enhance the efficiency of teaching and the quality of learning for millions of students in Brazil.

Comgás: Fueling efficiencies with AI-driven data management

Comgás, the largest natural gas distributor in Brazil, is leveraging AI to enhance data utilization, aiming to improve decision-making and customer service. In partnership with Microsoft, the company embarked on a significant digital transformation journey that sought to not only migrate to the cloud but to also create a sophisticated data environment that could leverage AI for better customer understanding and service.

“We realized the possibility of extracting data more efficiently with the use of AI,” said Thiago Rolemberg, Head of Data and AI at Comgás, “and, thus, better understand our customers for more assertive decision-making.”

AI algorithms, alongside standardized data presentation facilitated by Power BI, have streamlined data extraction processes from a duration of 8 to 15 days to real-time in certain areas. As a result, greater operational efficiency enabled Comgás to better understand and meet customer needs, resulting in a more personalized and efficient service.

Since the implementation, Comgás has processed over 55 TB of information, with the platform encompassing 60% of the company’s representative data. A third of the company’s employees have already utilized the environment, with expectations to increase to 55% by the end of the year. This strategic use of AI has not only facilitated a more dynamic use of data but also positioned Comgás at the forefront of the industry in terms of innovation and customer satisfaction.

Atento streamlines customer communications with customer service copilot

One of the world’s leading Customer Relationship Management and Business Process Outsourcing providers, Atento, has unveiled a new AI-driven solution designed to improve customer service and enhance the company’s service agent productivity. Developed with Azure OpenAI Service, the tool automates the distribution of processes and ensures swift, appropriate responses during negotiations. It oversees system formalization steps and update statuses, integrating smoothly with the communication channels preferred by customers. “The new solution enhances the consumer-brand experience and aligns with the demand for increasingly efficient and personalized service. During a pilot program, we observed a more than 20% increase in customer satisfaction within the first few weeks,” stated Eduardo Aguirre, Chief Information Officer of Atento.

In addition, Power Automate facilitated the integration of legacy systems, reducing manual labor and improving response times. This integration led to a 30% boost in team productivity and nearly a 20% decrease in operational errors.

A key focus during the solution’s development was ensuring data security, privacy, and compliance. Leveraging Azure OpenAI Service, Atento was able to anonymize information and maintain data within its own environment, adhering to strict confidentiality standards.

“The project’s success began with a detailed analysis of the customer and employee relationship cycle,” Aguirre added, highlighting the vital role of Atento’s team of experienced consultants in this endeavor.

Brasilprev unlocks new business with a GPT tool for consultants

Brasilprev’s deployment of its AI tool, Brasilprev GPT, marks a transformative leap in using data to empower over 20,000 consultants and relationship managers. This not only facilitates new business but also enables the delivery of more personalized services to end customers. The private pension firm’s collaboration with Microsoft builds upon data-focused digital transformation, leveraging Azure OpenAI Service and ChatGPT within their data hub to streamline interactions and make platform data more accessible and user-friendly.

This integration, a first in Brazil, features the creation of an API that not only stores queries for further analysis but also enhances the user experience by tailoring responses to user profiles, utilizing Azure’s API Management and Azure Cosmos DB. This integration illustrates how the powerful collaboration between human expertise and technological innovation can boost the company’s performance, contributing to a remarkable 28% conversion rate and surpassing $9.86 billion in business.

“Users have embraced the opportunity to explore, understand, and apply generative AI to access information and boost their productivity. This engagement has a profoundly positive effect on the end customer, who enjoys a more personalized and comprehensive response to their needs,” notes Bruno Venceslau, Superintendent of Data and Digital Business at Brasilprev, “that’s what AI has made possible.”

This innovation has not only driven exceptional business outcomes but also reinforced Brasilprev’s commitment to data governance and the strategic application of AI, setting a new standard for the integration of technology in enhancing business and technical operations.

B3 democratizes access to capital market through AI-powered financial education

B3, the Brazilian stock exchange, has launched the first AI tool dedicated to supporting the public in conscious investment. The free tool, developed by B3 in partnership with Microsoft, is part of B3’s purpose to democratize access to the capital market through financial education.

“The financial market is constantly evolving, and so is the way we communicate with investors. Our mission is to simplify the world of investments and show that B3 is for everyone. The financial education chat joins other initiatives as an open and uninhibited dialogue channel. We want individuals to clear their doubts in a light and interactive way, demystifying the idea that investing is complicated,” explains Felipe Paiva, director of Customer Relations at B3.

Based on information from a database curated by experts from the Brazilian stock exchange, the platform’s questions and responses have undergone significant testing. The tool is constantly evolving as the database continues to expand, resulting in more refined answers for investors.

In addition to verifying information, another advantage of this search format is that it minimizes ‘shyness’ when asking questions, which can often inhibit novice investors from asking basic questions. “The answers generated by the chat can serve as a starting point to better understand the concepts of the financial market and encourage investors to deepen their knowledge in other channels”, reinforces Paiva.

“Artificial intelligence can be a great ally in the search for quality information, analyzing huge volumes of data quickly and objectively. This simple and summarized answer format serves as a gateway for those interested in the world of investments, adapting in a light and interactive way to the needs of the user,” says Rodrigo Nardoni, Vice President of Technology at B3.

AI for everyone in Brazil

Brazil has shifted into high gear in terms of AI innovation, propelling not only Latin America but also having an impact on international markets. Microsoft is committed to empowering key Brazilian organizations like Petrobras, SECUC-SP, Comgás, Atento, Brasilprev, and B3, supporting their ongoing digital transformation journeys and unlocking potential across various sectors. This level of engagement is positioning Brazil as a potential leader on AI innovation, capable of setting benchmarks for the region and beyond by influencing global AI strategies and practices.

We work at the forefront of AI evolution, ensuring our advancements align with the needs of customers, partners, and society. Our commitment is to harness AI’s potential to empower every individual, including upskilling employees, guiding students, and supporting vulnerable communities. This approach ensures that technology serves as a catalyst for equitable and inclusive progress worldwide.

Take the next step in your AI journey by exploring Microsoft AI solutions, diving into The AI Strategy Roadmap, and skilling up with Microsoft Learn’s AI learning hub to ensure you’re ready to leverage Microsoft AI to its fullest potential.

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AI is currently at the forefront of global technological advancement, permeating various sectors from insurance to energy, driving efficiency, innovation, and transformative changes in society. With ongoing developments in machine learning and natural language processing, AI continues to reshape industries, offering a glimpse into a future where technology and human ingenuity intersect in exciting new ways. The expanding footprint of AI promises both unprecedented opportunities and considerations for responsible implementation.  

For me personally, one of the most exciting aspects is seeing the revolution of industries set into motion as sector-specific use cases begin to emerge. The number of Azure AI customers continues to grow with more than 65% of the Fortune 500 companies now using Microsoft Azure OpenAI Service, which underscores the critical role of partnerships and industry innovation to scale AI solutions to full potential across sectors.

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This willingness of industry leaders to be pioneers of AI was on bold display during the Microsoft AI Tour stop in Paris, part of the global event series designed to help decision makers and developers discover new opportunities with AI and advance their knowledge. Organizations such as Schneider Electric, The Groupama Group, Amadeus, Onepoint, AXA, and TotalEnergies are not just adopting AI; they’re redefining its potential. These groundbreaking use cases are shedding light on a future where AI is not just a tool, but a catalyst for a richer, more efficient, and more sustainable world.

Groupama’s virtual assistant optimizes policyholder service management

The Groupama Group, a premier mutual insurance group in France, has introduced a cutting-edge virtual assistant within its Employee Savings unit, harnessing the power of Azure OpenAI Service, Azure AI Search, and the Microsoft Bot Framework, to streamline customer managers’ interactions with policyholders. First ideated during an AI hackathon, the assistant has been embraced by the unit’s entire staff and boasts an impressive 80% success rate in providing accurate, dependable, and verifiable information.

“Our managers save a considerable amount of time and are able to carry out their work in much better conditions,” shared François-Xavier Enderlé, Head of Digital Transformation, “and this clearly enhances the quality of the relationship we maintain with our customers.”

Groupama has also stood up an interdepartmental AI-centered think tank, AI Factory, which is currently exploring more than 25 AI use cases aimed at revolutionizing claims processing, enhancing customer service through tools like a new FAQ chatbot, and streamlining the underwriting process for efficiency. Further, Groupama aims to democratize AI technology through training on AI prompting, empowering employees to innovate and improve operational efficiency and customer engagement.

Amadeus enhances employee efficiency with Copilot for Microsoft 365

Amadeus, a global technology provider for the travel industry, has deployed Copilot for Microsoft 365 to streamline work and free employees to focus on value-added tasks. Seamlessly integrated into Microsoft Teams, Word, PowerPoint, and Outlook, Amadeus’ Copilot solution has significantly improved operational efficiency.

“One of the challenges for large-scale, global organizations is the collaboration and the data management,” explains Marco Ruiz González, Product Manager and Solution Architect who supervised the deployment. “We are generating a large amount of data from different countries, and it’s very useful to have quick access to all this data.”

Early results are promising: pilot users reported substantial time savings in communication drafting, enhanced efficiency in email and meeting management, and improved information gathering and content translation capabilities.

With a 90% adoption rate among the initial 300 pilot users, half of whom engage with Copilot weekly, Amadeus plans to extend Copilot to 3,000 employees over the next six months, prioritizing adoption training tailored to diverse user profiles.

Schneider Electric leads the charge in sustainable energy management with AI

Schneider Electric is tackling the complex issue of optimizing energy use and performance with its EcoStruxure platform. By combining Azure OpenAI Service and Internet of Things (IoT), EcoStruxures merges Schneider Electric’s industry knowledge with Microsoft AI technology, enabling sustainable energy solutions and efficient energy management on a global scale. This includes dynamic control of energy performance, decision-making on the use of renewable energy sources, and overall energy optimization.

“People are using sustainable energy solutions to both produce and consume energy, and they can optimize how to produce or store that energy on the grid as it makes sense,” says Yoann Bersihand, Vice President of AI Technology at Schneider Electric. “Without AI, there is no way that we could address a problem as complex as this.”

The platform is designed with a layered architecture, planning future enhancements to integrate AI directly into hardware for efficient and sustainable energy management, especially beneficial for customers with limitations on using cloud services.

Schneider Electric has expanded its partnership with Microsoft, integrating Azure OpenAI Service into its operations to enhance efficiency and innovation across various processes. The integration enables the creation of solutions such as the Resource Advisor Copilot, leveraging large language model technology for data analysis and decision support, and Jo-Chat GPT, an internal tool enhancing employee productivity through generative AI. Further innovations include a programmable logic controller (PLC) code generation assistant that helps engineers quickly create high-quality, tested, and validated code, the Finance Advisor and Knowledge Bot, aimed at improving financial decision-making and customer service, respectively, as well as plans to incorporate GitHub Copilot to boost offer creation and Microsoft Copilot for Sales to support frontline staff. These advancements signify Schneider Electric’s commitment to leveraging generative AI for operational excellence and innovation.

“We didn’t want AI just to be an extra layer on top of the data teams. We decided to really go all-in on AI and not simply create proofs of concepts,” explained Yoann Bersihand, Schneider Electric’s Vice President of AI Technology, capturing Schneider Electric’s commitment to fully integrating AI into its operations to lead innovation in the energy sector.

Onepoint unlocks productivity company-wide with generative AI

An early adopter of AI, technology and consulting firm, Onepoint, is infusing AI at every level of the company with Microsoft’s turnkey generative AI solutions: Azure OpenAI Service, GitHub Copilot, and Copilot for Microsoft 365.

Neo, Onepoint’s secure conversational agent built on Azure OpenAI Service, leverages a library of prompts and business-oriented solutions to quickly generate reports and analyses, increasing productivity for 3,300 employees across the company. Onepoint has also piloted GitHub Copilot, resulting in higher-quality code, better documentation, and productivity gains around 40% on code production.

“The pilot showed us that if developers were properly acculturated to the product, it was really possible to make a quantum leap in productivity,” asserts François Binder, Partner Data & AI for Onepoint.

Addressing the challenge of acculturating employees to AI technology and practices, Onepoint has instituted an “AI Office” to ensure both technical and non-technical staff understand and adopt AI effectively. By providing structured training, fostering an AI community, and overseeing the deployment of AI solutions, the unit seeks to bridge knowledge gaps and biases related to AI among both technical and non-technical employees.

“We’re doing everything we can to fully embark our team in the generative AI adventure and give each of our consultants the means to become augmented consultants,” insists Binder.

What’s more, Onepoint is strategically integrating generative AI solutions into its offerings, along with personalized training to ensure customers are well-versed in AI’s capabilities and best practices, extending the benefits of AI to their customers as well.

AXA’s secure generative AI platform boost productivity of global employees

AXA, a global leader in insurance and asset management, is embracing the digital future through generative AI with the launch of AXA Secure GPT. Developed in collaboration with Microsoft and powered by Azure OpenAI Service, this AXA Secure GPT is designed to equip AXA’s 140,000 employees with cutting-edge AI tools in a secure and efficient manner.

Addressing the challenge of safely integrating public AI advancements within the corporate environment, AXA Secure GPT ensures the utmost privacy and control over data by employing robust filtering and classification, alongside secure cloud tenancy to keep all data and interactions within a controlled environment. Stringent authentication protocols and comprehensive security controls monitor and protect against potential threats. By leveraging Microsoft’s content filtering and adding an extra layer of security, AXA Secure GPT exceeds the current standards for data privacy and security, ensuring a reliable and secure tool for its employees.

With the goal to scale from 1,000 current users to all 140,000 global employees by mid-2024, AXA provides comprehensive AI support and training which includes leveraging Microsoft consulting services for optimal technological use and architecture design, alongside a dedicated change management program in each country to ensure smooth integration.

“As an employer, it is our responsibility to provide our employees with the best tools to enhance their comfort and enable them to focus on high-value activities,” said Vincent De Ponthaud, Head of Software & AI Engineering at AXA. Tailored training sessions and a specially curated prompt library, aimed at enhancing productivity across various departments, empower AXA employees to focus on high-value activities.

TotalEnergies supports operational transformation with AI and low-code solutions

Multi-energy company, TotalEnergies, has implemented Copilot for Microsoft 365 to support operational transformation. In the initial testing phase involving 300 employees, the company observed enhanced operational efficiency and improved user experience. Concurrently, TotalEnergies is empowering its workforce with Microsoft Power Platform, enabling them to develop low-code/no-code solutions integrated with other company applications and databases, thereby streamlining the resolution of various day-to-day challenges.

“In line with our pioneering spirit, TotalEnergies is committed to digital transformation and supports its employees so that they can make the most of it,” said Patrick Pouyanné, CEO of TotalEnergies. “The new technologies of generative artificial intelligence and of ‘low code no code’ will provide them with the simplification and autonomy they need to put their skills and creativity even further at the service of our company’s transition strategy.” In pursuit of this objective, TotalEnergies employees will receive training dedicated to the understanding and utilization of the new AI tools effectively.

AI for everyone

The Microsoft AI Tour provided a compelling opportunity to witness firsthand the pinnacle of regional innovation and to glimpse the far-reaching global impact poised to shape our future. Reflecting on the transformative journey of AI within France alone, it becomes evident that we’re venturing into an unprecedented era of technological advancement. The success stories of companies like Schneider Electric, Groupama, Amadeus, Onepoint, and TotalEnergies illustrate how the synergy between AI and human ingenuity propels progress and transformation across diverse sectors, transformation that will doubtlessly reach beyond borders to the benefit of organizations across the globe.

It’s also important to recognize that our exploration with AI is in its infancy and the horizon for transformative impact is limitless. It’s critical that business leaders scaffold AI innovation within an architecture of responsible AI, which include the development of ethical guidelines that address transparency, equity, accountability, and privacy; building diverse teams; investing in employee education around responsible AI use; and collaboration with industry bodies and policymakers to establish regulatory frameworks that can guide responsible deployment. When innovation and responsibility are aligned, we draw closer to ensuring that the potential for transformational impact of AI will be harnessed for the benefit of society as a whole.

Take the next step in your AI journey by exploring Microsoft AI solutions, diving into The AI Strategy Roadmap, and getting skilled up with Microsoft Learn’s AI learning hub to ensure you’re ready to leverage Microsoft AI to its fullest potential.

The post Groundbreaking AI innovation is transforming industries across France appeared first on The Microsoft Cloud Blog.

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Innovate, Connect, Cultivate

The Cloud Cultures series is an exploration of the intersection between cloud innovation and culture across the globe. 

Malaysia accelerates growth through digital transformation

Amidst the swiftly changing digital landscape, Malaysia stands out as a dynamic force capturing global attention. This nation—enriched by its diverse population comprised of Malays, Indians, Chinese, and more—is home to people and companies that have adeptly embraced innovative technologies, ensuring the benefits extend to all, not just the tech-savvy elite.

Malaysia has established a culture of digital acceleration through industries like energy, farming, and education by striking a balance between growth and the needs of their people. During my travels, I learned how they’ve embraced cloud innovation in a way that allows them to navigate the modern world with confidence and ensure that everyone is along for the ride.

Before setting out to meet with local companies, I joined General Manager of Energy and Utilities for Microsoft Malaysia, Shereeta (full name: Datin Sharifah Shereeta Syed Sheh), for a traditional Malaysian breakfast at her favorite restaurant. We sat down to talk about our upcoming interviews over nasi lemak—a delicious combination of fried anchovies, fish, hard-boiled egg, cucumber, and sambal on fragrant coconut rice, alongside pancakes, coconut grits, and colorful baked treats. Delighted by the food and excited for the day, we parted ways after breakfast. Shereeta headed out to a local chicken farm while I ventured further into the city.

PETRONAS is building a more sustainable world

I began my visit in the heart of Kuala Lumpur at the Golden Triangle, a hub for shopping, commerce, and entertainment. Standing 88-stories tall with a 17-acre park at its base, the PETRONAS Twin Towers are a wonder to behold. The skyscrapers are complete with malls, museums, a philharmonic orchestra, and a skybridge with views of the vibrant city. This is where I met Phuah Aik-Chong, CEO of Petronas Digital, to learn how PETRONAS utilizes the cloud to accelerate digital transformation.

PETRONAS is a dynamic global energy group with presence in over 100 countries. They produce and deliver energy and solutions that power society’s progress, enriching lives for a sustainable future. PETRONAS’ commitment to sustainability starts at the core of their operations and extends throughout their value chain. People are their strength and partners for growth, driving innovation to deliver a unique spectrum of solutions. PETRONAS’ commitment to Malaysia’s progress doesn’t stop at providing oil and gas—they make a concerted effort to provide development opportunities to underserved populations. One such initiative is the BeDigital Bootcamp, which involves upskilling students from various universities in Malaysia. Partnering with Microsoft, they have collaborated on multiple initiatives that reflect the mutual goal of empowering Malaysians to benefit in tandem with the rapid pace of innovation and digital advancements.

Chop Cheong Bee uses e-farming to feed Malaysia

While I stayed in the city, Shereeta took a break from the bustling metropolis and turned down a quiet dirt road. There, she learned about a local company that helps independent chicken farmers use cloud technology to turn their operations into smart farms—improving food security across Malaysia with affordable, high-quality chicken.

Founded in 1985, Chop Cheong Bee began as a poultry trading company, supplying chicken to local markets and establishments in Malaysia. After a brief period of time, they had to close due to an overwhelming number of manual tasks. However, in the late 2000s, they reopened focusing on technology and e-farming practices.

Cloud technology enables Chop Cheong Bee to create environments where chickens can thrive, utilizing a closed and climate-controlled farming system. The solution they developed collects data to inform how much feed is being consumed and the meat conversion ratios, all in real time. Today, Chop Cheong Bee is a crucial poultry supplier that facilitates a sizable portion of the chicken supply in Malaysia.

General Manager of Chop Cheong Bee, Datuk Jeffrey Ng Choon Ngee shared how e-farming is the future:

“With our solution, we can improve the broiler production index by 20 to 30 points. That’s easily a 10 percent improvement. If more farms can achieve this, then the cost of production will drop. And then hopefully, more Malaysians can afford quality poultry.”

Chop Cheong Bee built a system that can produce about 280 to 340 million chickens annually and supply 80 to 100 customers daily. This new way of farming not only provides millions of people with affordable and nutritious meat, but has also attracted a younger, more technology-focused generation of farmers to this vital industry.

Bersama Malaysia ensures citizens are part of the country’s digital acceleration

My final stop in Malaysia was a basketball court to shoot hoops with a recent graduate, Vaashini Palaniappan, who took part in the Bersama Malaysia (Together with Malaysia) program. Alongside sponsors like the Ministry of Education and Microsoft, the initiative teaches students digital skilling, inspiring young students, and women to dream outside the norm and build careers in tech.

Vaashini Palaniappan, data scientist and recent graduate, shared her future aspirations:

“There are so many women in this data and AI field that want to invent something, that want a brighter future. Because of this, I’m inspired to do something different. I want to be inventive using AI.”

Growing up in a small town, Vaashini didn’t have a lot of exposure to technology. But by participating in university programs, she was able to study sciences, learn technical skills, and understand the impact of advanced technologies on medicine. After seeing a close friend pass from cancer, Vaashini said she was determined to become a doctor and leverage innovative technology for good—specifically, to use AI to detect early signs of cancer and build a hyper-personalized treatment plan for patients.

Bersama Malaysia, along with Microsoft’s Code with Barriers program, were created to ensure citizens of Malaysia are a part of the digital acceleration of the country. These programs are empowering Malaysia’s inclusive digital economy and advancing the nation’s digital transformation across the private and public sectors. Malaysia has consistently been a trailblazer in fostering opportunities for its citizens. Through initiatives like Bersama Malaysia, the nation ensures that no one is left behind in the dynamic landscape of transformation.

If we’d prefer to quote faculty of the program, instead of Vaashini we could also use this one:

“Even before this partnership with Microsoft, we were aware that the Microsoft Learn platform offers a vast selection of professional certifications related to digital skills, but what really stood out was that Microsoft also supports institutions to manage the certification process independently. This way, we can customize the upskilling program according to a timeline and cost that works best for our students”—Dr. Hamizah binti Mohd Safuan, Deputy Dean of FAST

Innovating together makes change happen

Later that evening, Shereeta and I discussed our journey over my first experience with a popular local fruit: the durian. After getting used to the infamous smell, I snacked on the custard-like meat and reflected on Malaysia’s inspiring commitment to extending growth far beyond the gleaming skyscrapers and urban epicenters. This version of cloud culture ensures that as the pace of progress quickens, it doesn’t come at the cost of anyone being sidelined. As is often the case, I saw in Malaysia that the best way to accelerate growth isn’t racing ahead; it’s moving forward together.

In this ever-changing world, there is always more to experience. See you on my next adventure!

Learn more:

• Watch more Cloud Cultures episodes
• Find the Azure geography that meets your needs

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The post Cloud Cultures, Part 6: Accelerating collective growth in Malaysia appeared first on The Microsoft Cloud Blog.

Coworkers reviewing photographs
Dentsu drives creativity and growth for brands, supported by Microsoft Copilot.
Enriching employee experiences and shaping the future of work with copilot technology

Bayer employees are collaborating better on worldwide research projects and saving time on daily tasks with Copilot for Microsoft 365, while Finnish company Elisa is helping knowledge workers across finance, sales and customer service streamline routine tasks. Banreservas is driving employee productivity and enhancing decision-making, and Hong Kong’s largest transportation companies — Cathay and MTR — are streamlining workflows, improving communications, and reducing time-consuming administrative tasks. Across professional services, KPMG has seen a 50% jump in employee productivity, Dentsu is saving hundreds of employees up to 30 minutes per day on creative visualization processes, and EY is making it easier to generate reports and access insights in near real-time with Copilot for Microsoft 365. In Malaysia, financial services organization PNB is saving employees time searching through documents and emails and AmBank employees are enhancing the quality and impact of their work. At Hargreaves Lansdown, financial advisers are using Copilot for Microsoft 365 and Teams to drive productivity and make meetings more inclusive. Avanade is helping sellers save time updating contact records and summarizing email threads with Copilot for Dynamics 365, while HSO Group, Vixxo, and 9altitudes are streamlining work for field and service teams.

Employee and customer in store
Organizations are creating their own Generative AI assistants to help employees improve customer service.
Reinventing customer engagement with generative AI to deliver greater value and increased satisfaction

MECOMS is making it possible for utility customers to ask questions and get suggestions about how to reduce power consumption using Microsoft Fabric and copilot on their Power Pages portal. Schneider Electric has built a Resource Advisor copilot to equip customers with enhanced data analysis, visualization, decision support and performance optimization. California State University San Marcos is finding ways to better understand and personalize the student journey while driving engagement with parents and alumni using Dynamics 365 Customer Insights and Copilot for Dynamics 365. With Azure OpenAI Service, Adecco Group is bolstering its services and solutions to enable worker preparedness as generative AI reshapes the workforce, UiPath has already helped one of its insurance customers save over 90,000 hours through more efficient operations, and Providence has developed a solution for clinicians to respond to patient messages up to 35% faster. Organizations are building generative AI assistants to help employees save time, improve customer service and focus on more complex work, including Domino’s, LAQO and OCBC. Within a few weeks of introducing its copilot to personalize customer service, Atento has increased customer satisfaction by 30% while reducing operational errors by nearly 20%, and Turkey-based Setur is personalizing travel planning with a chatbot to customize responses in multiple languages for its 60,000 daily users. In the fashion industry, Coats Digital launched an AI assistant in six weeks to make customer onboarding easier. Greece-based ERGO Insurance partnered with EBO to provide 24/7 personalized assistance with its virtual agent, and H&R Block introduced AI Tax Assist to help individuals and small business owners file and manage their taxes confidently while saving costs.

Man and woman working in lab
Novo Nordisk is building out GitHub Copilot integration to decrease repetitive research and engineering tasks.
Reshaping business processes to uncover efficiencies, improve developer creativity and spur AI innovation

Siemens built its own industrial copilot to simplify virtual collaboration of design engineers and front-line workers, accelerate simulation times and reduce tasks from weeks to minutes. With help from Neudesic, Hanover Research designed a custom AI-powered research tool to streamline workflows and identify insights up to 10 times faster. With Microsoft Fabric, organizations like the London Stock Exchange Group and Milliman are reshaping how teams create more value from data insights, while Zeiss is streamlining analytics workflows to help teams make more customer-centric decisions. Volvo Group has saved more than 10,000 manual hours by launching a custom solution built with Azure AI to simplify document processing. By integrating GitHub Copilot, Carlsberg has significantly enhanced productivity across its development team; and Hover, SPH Media, Doctolib and CloudZero have improved their workflows within an agile and secure environment. Mastery Logistics Systems and Novo Nordisk are using GitHub Copilot to automate repetitive coding tasks for developers, while Intertech is pairing it with Azure OpenAI Service to enhance coding accuracy and reduce daily emails by 50%. Swiss AI-driven company Unique AG is helping financial industry clients reduce administrative work, speed up existing processes and improve IT support; and PwC is simplifying its audit process and increasing transparency for clients with Azure OpenAI Service. By leveraging Power Platform, including AI and Copilot features, Epiq has automated employee processes, saving over $500,000 in annual costs and 2,000 hours of work each month, PG&E is addressing up to 40% of help desk demands to save more than $1 million annually, and Nsure is building automations that reduce manual processing times by over 60% and costs by 50%. With security top of mind, WTW is using Microsoft Copilot for Security to accelerate its threat-hunting capabilities by making it possible for cyber teams to ask questions in natural language, while LTIMindtree is planning on using it to reduce training time and strengthen security analyst expertise.

Man working at multiple screens
VinBrain is harnessing Microsoft’s cutting-edge AI technologies to transform healthcare in Vietnam.
Bending the curve on innovation across industries with differentiated AI offerings

To make disaster response more efficient, nonprofit Team Rubicon is quickly identifying and engaging the right volunteers in the right locations with the help of Copilot for Dynamics 365. Netherlands-based TomTom is bringing the benefits of generative AI to the global automotive industry by developing an advanced AI-powered voice assistant to help drivers with tasks like navigation and temperature control. In Vietnam, VinBrain has developed one of the country’s first comprehensive AI-powered copilots to support medical professionals with enhanced screening and detection processes and encourage more meaningful doctor-patient interactions. Rockwell Automation is delivering industry-first capabilities with Azure OpenAI Service to accelerate time-to-market for customers building industrial automation systems. With a vision to democratize AI and reach millions of users, Perplexity.AI has brought its conversational answer engine to market in six months using Azure AI Studio. India’s biggest online fashion retailer, Myntra, is solving the open-ended search problem facing the industry by using generative AI to help shoppers figure out what they should wear based on occasion. In Japan, Aisin Corp has developed a generative AI app to empower people who are deaf or hard of hearing with tasks like navigation, communication and translation; and Canada-based startup Natural Reader is making education more accessible on-the-go for students with learning differences by improving AI voice quality with Azure AI. To solve one of the most complex engineering challenges — the design process for semiconductors — Synopsys is bringing in the power of generative AI to help engineering teams accelerate time-to-market.

As organizations continue to embrace AI Transformation, it is critical they develop clarity on how best to apply AI to meet their most pressing business needs. Microsoft is committed to helping our customers and partners accelerate pragmatic AI innovation and I am excited by the opportunities before us to enrich employee experiences, reinvent customer engagement, reshape business processes and bend the curve on innovation. As a technology partner of choice — from our differentiated copilot capabilities to our unparalleled partner ecosystem and unique co-innovation efforts with customers — we remain in service to your successful outcomes. We are also dedicated to preserving the trust we have built through our partnership approach, responsible AI solutions and commitments to protecting your data, privacy and IP. We believe this era of AI innovation allows us to live truer to our mission than ever before, and I look forward to continuing on this journey with you to help you achieve more.

The post Embracing AI Transformation: How customers and partners are driving pragmatic innovation to achieve business outcomes with the Microsoft Cloud appeared first on The Microsoft Cloud Blog.

Microsoft and the Pacific Northwest National Laboratory (PNNL) in Richland, Washington, are collaborating to demonstrate how this acceleration can benefit chemistry and materials science – two scientific fields pivotal to finding energy solutions that the world needs.

Scientists at PNNL are testing a new battery material that was found in a matter of weeks, not years, as part of the collaboration with Microsoft to use to advanced AI and high-performance computing (HPC), a type of cloud-based computing that combines large numbers of computers to solve complex scientific and mathematical tasks.

PNNL materials scientist Shannon Lee mixes raw materials to synthesize a new solid electrolyte, one of the promising candidates predicted using AI and HPC tools in the Azure Quantum Elements service. Photo by Dan DeLong for Microsoft.
As part of this effort, the Microsoft Quantum team used AI to identify around 500,000 stable materials in the space of a few days.

The new battery material came out of a collaboration using Microsoft’s Azure Quantum Elements to winnow 32 million potential inorganic materials to 18 promising candidates that could be used in battery development in just 80 hours. Most importantly, this work breaks ground for a new way of speeding up solutions for urgent sustainability, pharmaceutical and other challenges while giving a glimpse of the advances that will become possible with quantum computing.

“We think there’s an opportunity to do this across a number of scientific fields,” says Brian Abrahamson, the chief digital officer at PNNL. “Recent technology advancements have opened up the opportunity to accelerate scientific discovery.”

PNNL is a U.S. Department of Energy laboratory doing research in several areas, including chemistry and materials science, and its objectives include energy security and sustainability. That made it the ideal collaborator with Microsoft to leverage advanced AI models to discover new battery material candidates.

“The development of novel batteries is an incredibly important global challenge,” Abrahamson says. “It has been a labor-intensive process. Synthesizing and testing materials at a human scale is fundamentally limiting.”

Learning through trial and error
The traditional first step of materials synthesis is to read all the published studies of other materials and hypothesize how different approaches might work out. “But one of the main challenges is that people publish their success stories, not their failure stories,” says Vijay Murugesan, materials sciences group lead at PNNL. That means scientists rarely benefit from learning from each other’s failures.

The next traditional scientific step is testing the hypotheses, typically a long, iterative process. “If it’s a failure, we go back to the drawing board again,” Murugesan says. One of his previous projects at PNNL, a vanadium redox flow battery technology, required several years to solve a problem and design a new material.

Vijay Murugesan, material sciences group lead at PNNL, says the Microsoft AI and HPC tools allow scientists to eliminate the time-consuming trial-and-error discovery steps and focus on the best candidates for testing. Photo by Andrea Starr for PNNL.
The traditional method requires looking at how to improve on what has been done in the past. Another approach would be to take all the possibilities and, through elimination, find something new. Designing new materials requires a lot of calculations, and chemistry is likely to be among the first applications of quantum computing. Azure Quantum Elements offers a cloud computing system designed for chemistry and materials science research with an eye toward eventual quantum computing, and is already working on these kinds of models, tools and workflows. These models will be improved for future quantum computers, but they are already proving useful for advancing scientific discovery using traditional computers.

To evaluate its progress in the real world, the Microsoft Quantum team focused on something ubiquitous in our lives – materials for batteries.

Teaching materials science to AI
Microsoft first trained different AI systems to do sophisticated evaluations of all the workable elements and to suggest combinations. The algorithm proposed 32 million candidates – like finding a needle in a haystack. Next, the AI system found all the materials that were stable. Another AI tool filtered out candidate molecules based on their reactivity, and another based on their potential to conduct energy.

The idea isn’t to find every single possible needle in the hypothetical haystack, but to find most of the good ones. Microsoft’s AI technology whittled the 32 million candidates down to about 500,000 mostly new stable materials, then down to 800.

“At every step of the simulation where I had to run a quantum chemistry calculation, instead I’m calling the machine learning model. So I still get the insight and the detailed observations that come from running the simulation, but the simulation can be up to half a million times faster,” says Nathan Baker, Product Leader for Azure Quantum Elements.

AI may be fast, but it isn’t perfectly accurate. The next set of filters used HPC, which provides high accuracy but uses a lot of computing power. That makes it a good tool for a smaller set of candidate materials. The first HPC verification used density functional theory to calculate the energy of each material relative to all the other states it could be in. Then came molecular dynamics simulations that combined AI and HPC to analyze the movements of atoms and molecules inside each material.

This process culled the list to 150 candidates. Finally, Microsoft scientists used HPC to evaluate the practicality of each material – availability, cost and such – to trim the list to 23 – five of which were already known.

Thanks to this AI-HPC combination, discovering the most promising material candidates took just 80 hours.

The HPC portion accounted for 10 percent of the time spent computing – and that was on an already-targeted set of molecules. This intense computing is the bottleneck, even at universities and research institutions that have supercomputers, which not only are not tailored to a specific domain but also are shared, so researchers may have to wait their turn. Microsoft’s cloud-based AI tools relieve this situation.

Broad applications and accessibility
Microsoft scientists used AI to do the vast majority of the winnowing, accounting for about 90 percent of the computational time spent. PNNL materials scientists then vetted the short list down to half a dozen candidate materials. Because Microsoft’s AI tools are trained for chemistry, not just battery systems, they can be used for any kind of materials research, and the cloud is always accessible.

“We think the cloud is a tremendous resource in improving the accessibility to research communities,” Abrahamson says.

Brian Abrahamson, chief digital officer at PNNL. Photo by Andrea Starr for PNNL.
Today, Microsoft supports a chemistry-specific copilot and AI tools that together act like a magnet that pulls possible needles out of the haystack, trimming the number of candidates for further exploration so scientists know where to focus. “The vision we are working toward is generative materials where I can ask for list of new battery compounds with my desired attributes,” Baker says.

The hands-on stage is where the project stands now. The material has been successfully synthesized and turned into prototype batteries that are functional and will undergo multiple tests in the lab. Making the material at this point, before it’s commercialized, is artisanal. One of the first steps is to take solid precursors of the materials and to grind them by hand with a mortar and pestle, explains Shannon Lee, a PNNL materials scientist. She then uses a hydraulic press to compact the material into a dime-shaped pellet. It goes into a vacuum tube and is heated to 450 to 650 degrees Celsius (842 to 1202 degrees Fahrenheit), transferred to a box to keep it away from oxygen or water, and then ground into a powder for analysis.

For this material, the 10-or-more-hour process is “relatively quick,” Lee says. “Sometimes it takes a week or two weeks to make a single material.”

Then hundreds of working batteries must be tested, over thousands of different charging cycles and other conditions, and later different battery shapes and sizes to realize commercial use. Murugesan dreams of the development of a digital twin for chemistry or materials, “so you don’t need to go to a lab and put this material together and make a battery and test it. You can say, ‘this is my anode and this is my cathode and that’s the electrolyte and this is how much voltage I’m going to apply,’ and then it can predict how everything will work together. Even details like, after 10,000 cycles and five years of usage, the material performance will be like this.”

Microsoft is already working on digital tools to speed up the other parts of the scientific process.

The lengthy traditional process is illustrated by lithium-ion batteries. Lithium got attention as a battery component in the early 1900s, but rechargeable lithium-ion batteries didn’t hit the market until the 1990s.

Today, lithium-ion batteries increasingly run our world, from phones to medical devices to electric vehicles to satellites. Lithium demand is expected to rise five to ten times by 2030, according to the U.S. Department of Energy. Lithium is already relatively scarce, and thus expensive. Mining it is environmentally and geopolitically problematic. Traditional lithium-ion batteries also pose safety issues, with the potential to catch fire or explode.

Many researchers are looking for alternatives, both for lithium and for the materials used as electrolytes. Solid-state electrolytes show promise for their stability and safety.

Surprising results
The newly discovered material PNNL scientists are currently testing uses both lithium and sodium, as well as some other elements, thus reducing the lithium content considerably – possibly by as much as 70 percent. It is still early in the process – the exact chemistry is subject to optimization and might not work out when tested at larger scale, Abrahamson cautions. He points out that the story here is not about this particular battery material, but rather the speed at which a material was identified. The scientists say the exercise itself is immensely valuable, and it has revealed some surprises.

The AI-derived material is a solid-state electrolyte. Ions shuttle back and forth through the electrolyte, between the cathode and the anode, ideally with minimal resistance.

Test tubes contain samples of the new material, which looks like fine white salt.
Samples of the new solid electrolyte discovered by Microsoft AI and HPC tools. Solid-state electrolytes are safer than liquid ones. Photo by Dan DeLong for Microsoft.
It was thought that sodium ions and lithium ions couldn’t be used together in a solid-state electrolyte system because they are similarly charged but have different sizes. It was assumed that the structural framework of a solid-state electrolyte material couldn’t support the movement of two different ions. But after testing, Murugesan says, “we found that the sodium and lithium ions seem to help each other.”

The new material has a bonus, Baker says, because its molecular structure naturally has built-in channels that help both ions move through the electrolyte.

Work on the new material is in early stages but “irrespective of whether it’s a viable battery in the long run, the speed at which we found a workable battery chemistry is pretty compelling,” Abrahamson says.

Additional discoveries are still possible. Murugesan and his team have yet to make and test most of the other new material candidates that the Microsoft models suggested. The collaboration continues, with PNNL computational chemists learning to use the new tools, including a copilot trained on chemistry and other scientific publications.

“With Microsoft and PNNL, this is an enduring collaboration to accelerate scientific discovery, bringing the power of these computational paradigm shifts to bear, with the chemistry and material science that are a hallmark strength of the Pacific Northwest National Laboratory,” Abrahamson says.

“We’re sitting on the precipice of this maturation of the artificial intelligence models, the computational power needed to train and make them useful, and the ability to train them on specific scientific domains with specific intelligence,” he adds. “That, we believe, is going to usher in a new era of acceleration. That is exciting, because these problems matter to the world.”

Related links:

Read Unlocking a new era for scientific discovery with AI: How Microsoft’s AI screened over 32 million candidates to find a better battery
Read Azure Quantum Elements aims to compress 250 years of chemistry into the next 25
Learn more about Azure Quantum Elements
Read: PNNL-Microsoft Collaboration: Accelerating Scientific Discovery
Read the PNNL press release: Energy Storage, Materials Discovery Kick-Off Three-Year Collaboration with Microsoft
Top image: Dan Thien Nguyen, a PNNL materials scientist, assembles a coin cell with the synthesized solid electrolyte. With AI tools guiding researchers, synthesis and testing can be focused in the right direction toward better materials for particular applications. Photo by Dan DeLong for Microsoft.

The post Discoveries in weeks, not years: How AI and high-performance computing are speeding up scientific discovery appeared first on The Microsoft Cloud Blog.

Microsoft Cloud for Retail

Retail is one of the most agile and innovative industries. With ever-evolving consumer demands and shifting supply chains, successful retailers are characteristically adaptable and resilient. Microsoft Cloud for Retail helps retailers accelerate innovation with industry-specific solutions that enable them to maximize the value of their data. Our primary focus of this wave is offering solutions for retailers to provide engaging shopping experiences while empowering store associates to be more productive and customer-focused. In this release, Microsoft Cloud for Retail continues to invest in both Smart Store Analytics and Store Operations with customer-requested features and additional AI and machine learning-based capabilities.

Microsoft Cloud for Retail’s Smart Store Analytics solution provides insights on store performance using anonymized data of store transactions and shoppers’ in-store journeys. Store managers see KPIs, data visualizations, and data science models that help them monitor store performance and make data-driven decisions for optimizing store performance. Working with AiFi, the largest provider of autonomous shopping solutions, we have enabled an end-to-end autonomous store solution. AiFi’s camera-only technology, running on Microsoft Azure, captures anonymized data throughout the shopper’s journey in real-time. Computer vision tracks shopper actions and enables frictionless checkout. In addition to enabling frictionless checkout, this solution helps retailers further improve customer experiences by understanding:

• How customers interact with the products on the shelves.
• How shoppers react to promotions and communications.
• What they choose to take off the shelf and purchase.

With this release, we are adding additional AI and machine learning based insights around product recommendations and foot traffic analysis, to add to existing models and visualizations that are helping store operators optimize store layout, product catalog, and shelf placement for peak performance.

With Store Operations Assist, store associates can be more productive and engage more meaningfully with customers. The application provides employees with the ability to conduct typical business processes such as inventory counts, stock audits, store walks, shift change checks, incident reporting, and safety audits. Associates can also view and use customer insights to schedule follow-up consultations. Store managers can digitally review and provide feedback, support associates, and see their store’s performance. With this release, we are enabling additional features like tablet support, branching logic for survey responses, and enhanced integration with Microsoft Teams front line worker apps.

Azure Data Manager for Agriculture (preview)

Azure Data Manager for Agriculture (preview) helps enable a more sustainable future and a more productive agriculture industry by empowering organizations to drive innovation through insights, reduce their environmental impact, optimize agriculture operations, and build trust rooted in transparency. With access to data and insights from the farm, organizations can drive harvest and production efficiency, reduce food waste, create nutrient-dense and high-quality products, automate and improve environmental, social, and governance (ESG) and Scope 3 emissions reporting, and provide transparency to stakeholders.

Azure Data Manager for Agriculture (preview) extends the Microsoft Intelligent Data Platform with industry-specific data connectors and capabilities to connect farm data from disparate sources, enabling organizations to leverage high-quality datasets and accelerate the development of digital agriculture solutions. Instead of devoting resources to managing unstructured data, customers and partners can focus on product innovation with the ability to reason over readily available and abundant data. Furthermore, organizations can use in-house, third-party, or Microsoft Intelligent Data Platform services to speed the path to analytics and business intelligence solutions. With a connected ecosystem of partners building solutions on top of Azure Data Manager for Agriculture (preview), this is another step towards a connected and collaborative agriculture industry.

With the current wave, we are delivering one-step geospatial and temporal indexing capabilities enabling customers and partners to easily integrate non-harmonized farm machinery activity data from different sources. In addition, the Azure Data Manager for Agriculture (preview) now includes integration of Climate Field View™ by Bayer. Partners like Bayer have used Azure Data Manager for Agriculture to shift from a self-managed data estate to a managed model with Microsoft. The Climate Field View platform harnesses data from Azure Data Manager for Agriculture’s satellite and weather pipelines to enable insights on potential yield-limiting factors in growers’ fields. Our strategic partnership, leverages Bayer’s industry knowledge-as well as data connectors, models, transformations, and workflows-to inform how we strengthen Azure Data Manager for Agriculture and empower organizations to address the challenges in agriculture today. Furthermore, we are improving time to value by enhancing the Azure portal experience for developers and system administrators.

Microsoft Cloud for Healthcare

With this release, Microsoft Cloud for Healthcare continues the development of features that enable patient-centric operating models to ease the burden on providers and help facilitate proactive healthcare. Our healthcare customers and partners are a key part of our development of solutions for providers and payors. We have landed and continued to iterate on several impactful capabilities in this wave: Patient journeys, care management, and virtual health data tables.

Optimizing each touchpoint in a patient’s experience can help providers improve patient satisfaction, retention, and loyalty, while payors can address efficiencies and the return on investment of their health plans. Patient journeys in Patient Outreach enable health organizations to orchestrate trigger-based workflows across patient touchpoints to automate repetitive tasks and allow patients to get personalized care faster.

Microsoft Cloud for Healthcare has also developed solutions and data integration capabilities for health organizations to make it easier for them to provide care anywhere. Our aim is to make it easier for caregivers to access and track patients’ vitals and to gain early insights into patient conditions. Device data support for care management (preview) uses the MedTech service in Azure Health Data Services to normalize data from diverse medical devices and convert it into the fast healthcare interoperability resources (FHIR) format in a secure way. 

Additionally, we are improving the time to value with updates to Virtual Health Data Tables (general availability) to include support for the create, update, and delete FHIR operations. Utilizing this functionality, customers can perform updates to FHIR resource data on the remote FHIR service directly from within Microsoft Power Platform. This enables health customers to leverage the Microsoft no-code and low-code Power Platform to build health applications, simplifying the complexities of the FHIR standard. Learn more about our current and upcoming Microsoft Cloud for Healthcare release.

We have also expanded collaboration with Cognizant to integrate Cognizant’s TriZetto healthcare products. With this integration, we aim to improve efficiency and help customers achieve significantly shorter time-to-value with enhanced patient and member engagement, improved data interoperability, and improved insights. Together we will also develop and run Cognizant’s current and future healthcare software as a service (SaaS) solution on Microsoft Azure, migrate new and existing clients from on-premises environments to streamlined functions managed on the Microsoft Cloud, and support future technologies designed to deliver new insights for payers, providers, and consumers

Microsoft Cloud for Sustainability

Microsoft Cloud for Sustainability continues to empower organizations in their sustainability efforts across our solutions which streamline data ingestion, integration, calculations, reporting, and more. Our offering also includes Environmental Credit Service (preview), bringing efficiency, trust, and transparency to voluntary ecological markets. We continue to extend our data story with the availability of Microsoft Cloud for Sustainability API (preview) which allows organizations to get emissions data for extensibility and customization for solutions and reporting.

This also extends our Scope 3 category calculations for the GHG Protocol, including providing reporting on the following Scope 3 categories:

• Scope 3 category 3: Fuel and energy-related activities not included in Scope 1 or Scope 2.
• Scope 3 category 12 (included in a previous release): End-of-life treatment of sold products.

Additionally, our joint solution with Ecolab, a global sustainability leader in water, hygiene, and infection prevention, combines the power of the ECOLAB3D™ digital platform with Microsoft Sustainability Manager. With this solution, organizations are able to monitor and manage water data so they can gain greater visibility into how they are tracking against water and sustainability goals.

Another highlight is our expanded set of emission factors which now includes the Department for Environment, Food, and Rural Affairs (Defra). Defra emission factors are used by the United Kingdom and other international organizations for reporting greenhouse gas emissions, which help organizations to maintain compliance with industry standards and regulatory requirements.

Lastly, data capture (preview) helps organizations train and use optical character recognition (OCR) models for processing and ingesting Scope 2 purchased energy invoices to differentiate between energy providers. Data capture uses Microsoft Power Platform’s AI Builder and document intelligence solutions. With this, organizations can now create a seamless workstream to ingest data from within Microsoft Sustainability Manager to use in calculations and reporting.

We are committed to helping our customers meet the needs of new ESG demands and markets and are actively working to extend reporting and sustainability solutions to do so. More updates are coming soon about expanded data management capabilities.

Azure Data Manager for Energy

Azure Data Manager for Energy is a secure, reliable, hyperscale, fully managed cloud-based data platform solution that supports a wide variety of energy solutions compatible with OSDU™ Date Platform. This solution addresses the challenge of data—moving from disparate systems and disconnected applications to a holistic approach. Azure Data Manager for Energy is designed to help organizations get more value from their data by scaling ingestion and data enrichment, providing easy interoperability, and unlocking self-serve data analytics capabilities. The open Microsoft platform enables developers, data managers, and geoscientists alike to innovate the next generation of digital solutions for the energy industry.

Since its preview, the team has addressed multiple customer feedback items that can be seen on the release notes page. Customers can look forward to another heavily requested feature that will allow for scenarios including testing, training, and evaluation of Azure Data Manager for Energy or specific OSDU™ Data Platform features. This will be released as a separate “Developer” Tier in the coming weeks.

Microsoft Cloud for Financial Services

Microsoft Cloud for Financial Services continues to invest in delivering capabilities to manage financial services data at scale and make it easier for financial services institutions to improve customer experience, coordinate engagement, and drive operational efficiency. This wave focuses on strengthening offerings in banking, cross-vertical experiences, and financial services data models. We are prioritizing providing customers and partners with more flexibility in meeting their specific needs through componentization. The components offer individual deployment and configuration capabilities for customer onboarding, document processing, and in how customer financial information is represented. We will enable flexible adaptation of the UI to different scenarios, offer a wealth of tools for document processing and management using AI, and provide various endpoints for partner enablement in the process. We plan to improve the retail banking loan onboarding solution with the new document intelligence feature and offer additional flexibility enhancements as requested by our customers and partners.

In partnership with Microsoft Cloud for Financial Services, KX has released kdb Insights—a robust, integrated data management and time series streaming analytics solution for optimal real-time decisioning. Leverage the capabilities of kdb Insights running on a virtual machine to build and deploy highly performant, data-intensive applications. Kdb Insights allows developers to build real-time analytics with connectivity, tool, and infrastructure ease.

Global partner ecosystem

Our unique value proposition is our global ecosystem of partners. These partners create tailored solutions for organizations by developing connectors and continuing to build on top of our industry cloud offerings. Independent software vendors (ISVs), system integrators, and advisory partners from every industry can extend the capabilities of our Microsoft Cloud for industries to meet the unique needs of customers across the globe. Trusted advisers like Accenture, Avanade, Capgemini, EY, KPMG, and PwC are helping organizations everywhere plan, design, and implement strategies and robust solutions to enable transformation across several industries including Healthcare, Sustainability, and Financial Services. Find a complete list of partners who are developing joint solutions built on our platform that deliver differentiated customer experiences, empower employees, and manage enterprise risk on AppSource and Azure Marketplace.

Learn more

Microsoft Industry Cloud continues to expand our offerings in the industry space. We continue to invest in clouds such as Microsoft Cloud for Nonprofit and Microsoft Cloud for Manufacturing.

Follow us on Industry Cloud blogs for industry-specific news and read more about what’s upcoming on our documentation pages.

MEDICAL DEVICE DISCLAIMER. Microsoft product(s) and service(s) (1) are not designed, intended or made available as a medical device(s), and (2) are not designed or intended to be a substitute for professional medical advice, diagnosis, treatment, or judgment and should not be used to replace or as a substitute for professional medical advice, diagnosis, treatment, or judgment.

The post The latest wave of innovation in Microsoft Industry Cloud appeared first on The Microsoft Cloud Blog.

Organizations doing more with less are using digital innovation to transform business outcomes. Transformative innovation isn’t about replacing people with technology or asking them to do more. In a new era, innovators use technology to turn what you already have and do into a superpower.

“Doing more with less doesn’t mean working harder or longer. It means applying technology to amplify what you can do and ultimately what an organization can achieve amid today’s constraints.”—Satya Nadella, Microsoft Chairman and CEO.

Innovative energy organizations are leveraging the Microsoft Cloud and the transformative technologies that come with it. The metaverse merges technologies like IoT, AI, and digital twins with augmented and virtual realities to provide immersive, 3D experiences of modeled data. These digital representations are used not only for entertainment but to transform real-world business scenarios in multiple industries. Though the metaverse is in its early stages, there are many examples of foundational building blocks, like the ones I describe below.

Advancing operational excellence

The ability to manipulate 3D digital replicas of the physical world enables virtual product design and improves production and supply chain processes. Engineers and designers can collaborate in a digital space to test new concepts and processes or identify new efficiencies. Equinor, a leader in the energy transition and floating offshore wind business, designs, operates, and maintains wind farms remotely before they’re even built. Wind farm developers face significant challenges including remote, harsh environments, the integration of diverse complex systems, and not least of all transmitting energy from offshore locations. By creating a virtual wind farm, Equinor simplifies and accelerates the design-build process by bringing data sets together and testing wind farm concepts based on digital simulations.

Hear from Equinor’s Executive Vice President and Head of Technology, Digital, and Innovation, Hege Skryseth, about how Equinor is using the industrial metaverse (story starts at 8:28).

Improving workplace safety and productivity

The metaverse isn’t just for engineers and business strategists. Interactive simulations and mixed reality tools can also be used to transform your workforce with improved training, support, and safety for field workers and frontline employees. Approximately 80 percent of employees worldwide do not sit behind a desk to do their jobs, especially in sectors like energy, manufacturing, healthcare, and agriculture.¹ This workforce is also historically under-equipped with digital technology, while job roles and skill requirements rapidly evolve as companies struggle to fill even their current positions. Innovative companies are empowering their workforce and ensuring that frontline employees are digitally equipped to acquire new skills, serve customers, and solve problems.

The energy industry has a long history of innovating with Microsoft technologies to improve insights and operations. Energy businesses are already using advanced analytics, connected devices, and AI to make better decisions, monitor diverse operations, and optimize performance. Today, energy leaders are turning to the industrial metaverse to not only increase efficiency and reduce risk but also to accelerate the transition to cleaner energy.

In the power and utilities sector, companies are integrating collaboration software with mixed reality tools to help operational and maintenance workers. For example, German energy firm E.ON is using AI-supported inspection tools to maintain power lines more safely and efficiently. Powered by Microsoft Azure, the virtual inspection tool with drone images helps speed up fault detection and prevent power outages with accurate, predictive maintenance. As more data is collected, the intelligent system continues to improve for a feedback loop that E.ON calls “collaborative AI.” Not only does the technology improve the quality of the inspections, it also increases safety by reducing the need for maintenance workers to physically climb poles to perform visual inspections.

In Japan, Hokkaido Electric Power Company (HEPCO) is transforming the inspection of its thermal power stations with a mixed reality application that leverages the Microsoft Cloud and Microsoft HoloLens 2. HEPCO uses the application to enable real-time collaboration and remote support for patrol inspection operations. In addition to improving the efficiency of inspection over large, remote areas, the solution provides alerts that help workers avoid injury. HEPCO employees equipped with a HoloLens 2 device receive a virtual view of the inspection route. When the worker reaches a site, the mixed reality experience also shows the employee inspection areas along with prior issues for intuitive, easy navigation. The solution will be deployed at multiple thermal power stations to improve inspection processes and help provide a reliable supply of energy across the region. Benefits can include improved operational stability, faster training, and the ability to equip its entire workforce with a more advanced skillset.  

Innovating for a more sustainable future

The energy industry is using Microsoft technologies to do more with less in new ways. Today, the industrial metaverse is creating more opportunities for companies and workers alike and increasing the adoption of greener practices and renewable energy. By enabling energy companies to more efficiently and affordably design new solutions like offshore wind farms, the metaverse helps accelerate the energy transition and our collective path to net zero. With the help of the Microsoft Data Platform and digital twin technology, bp is identifying areas to reduce carbon emissions and model complex new energy solutions. Immersive digital technologies can also help people stay safe and make a bigger impact at work—whether it’s an engineer testing a new design, or a frontline maintenance worker detecting and repairing power lines.

From the earliest days of industrial automation to the modern era of connected devices and edge computing, technology has helped increase operations efficiency and improve productivity, collaboration, and economic growth. Today, technology is more important than ever as we reimagine the world and our roles in more sustainable ways. With the metaverse, energy companies can more efficiently scale data and real-time insights through simulation models and digital twins they have been using for many years. Microsoft, alongside our customers and partners, are innovating together to accelerate the creation and adoption of new, virtual solutions for a cleaner energy future.

Learn more

• Learn more about themes and actions critical for energy transition.

• Read more about how Microsoft partners with energy companies to accelerate digital transformation.

• Read more about how Microsoft brings mixed reality and new immersive collaboration tools to industrial metaverse customers.

• Enable your data to do more in the cloud with our energy data service.

• To learn how to attract, train, and retain employees for your next-generation workforce, visit our transform your workforce employee retention website.

• To learn more about Microsoft for Energy and Resources, visit our future of energy industry solutions website.

The post Discover how Microsoft is innovating in the metaverse for a sustainable, clean energy future appeared first on The Microsoft Cloud Blog.