We now have architected Microsoft Discovery to be extremely extensible, enabling researchers to combine the newest Microsoft improvements with their very own fashions, instruments, and datasets in addition to a variety of associate and open-source options.
We’re asserting a brand new enterprise agentic platform known as Microsoft Discovery to speed up analysis and improvement (R&D) at Microsoft Construct 2025.
Our purpose is to carry the facility of AI to scientists and engineers to rework your complete discovery course of—from superior data reasoning and speculation formulation to experimental simulation and iterative studying. Microsoft Discovery allows researchers to collaborate with a group of specialised AI brokers mixed with a graph-based data engine, to drive scientific outcomes with pace, scale, and accuracy.
We now have architected Microsoft Discovery to be extremely extensible, enabling researchers to combine the newest Microsoft improvements with their very own fashions, instruments, and datasets in addition to a variety of associate and open-source options. Constructed on prime of Microsoft Azure, belief, compliance, transparency, and governance are key design rules of this enterprise-ready platform to allow accountable innovation, preserving the researcher in management.
At Microsoft, our researchers have leveraged the superior AI fashions and high-performance computing (HPC) simulation instruments in Microsoft Discovery to find a novel coolant prototype with promising properties for immersion cooling in datacenters in about 200 hours—a course of that in any other case would have taken months, if not years. This speedy discovery lays the groundwork for future developments in safer and sustainable options throughout a number of industries and is an illustration of how Microsoft Discovery can doubtlessly remodel R&D in any firm.
We’re working with a notable set of Microsoft clients who’re keen on co-innovating in various industries together with chemistry and supplies, silicon design, power, manufacturing, and pharma. We’re additionally working with a broad associate base that’s constructing on prime of the platform to drive this acceleration, and we couldn’t be extra excited. The probabilities are infinite as we understand the total potential of AI in R&D and we’re simply getting began!
The agentic imaginative and prescient for science
At Microsoft, we wish to amplify the ingenuity of scientists to usher in a brand new period of accelerating discovery and develop the horizons of analysis. Doing so requires empowering R&D groups with transformative applied sciences that may drive significant enterprise impression. Nevertheless, R&D has very particular challenges in comparison with different domains:
- Scientific data is huge, nuanced, and distributed.
- The invention course of is various and dynamic, involving a number of extremely specialised strategies and duties, making it very arduous to attach the dots throughout the completely different domains concerned.
- R&D is iterative. There are hardly ever easy, clear-cut solutions. As a substitute, scientific data evolves via proof, discourse, and refinement.
This complexity calls for a brand new paradigm—one which isn’t aimed toward doing the identical experiments quicker, however reasonably essentially altering the paradigm of how we method R&D.
Think about if each researcher may collaborate with a tireless group of clever, synergistic AI brokers with the only real function of accelerated innovation. That is our imaginative and prescient for a brand new agentic R&D paradigm, embedding AI in each stage of the scientific technique.
On this new world, individuals and specialised AI brokers will cooperatively refine data and experimentation in actual time in a steady, iterative cycle of discovery—all whereas sustaining the management, transparency, and belief that enterprises and governmental establishments require. This requires a complete platform the place AI can seize each the scientific area and the cognitive processes concerned in managing scientific thought. To appreciate this imaginative and prescient, scientific AI brokers should be capable to:
- Purpose over a fancy and contextual graph connecting all data sources.
- Specialize throughout distinct domains and duties.
- Be taught from outcomes and adapt complete analysis plans accordingly.
Introducing Microsoft Discovery
We’re taking an enormous step towards realizing this imaginative and prescient with Microsoft Discovery, bringing agentic R&D to life by leveraging the newest improvements from Microsoft and the broader scientific ecosystem.
Graph-based scientific co-reasoning
The arrival of huge language fashions (LLMs) hinted at this new period, providing capabilities to hurry up sure scientific duties, notably for data retrieval and speculation technology. Nevertheless, LLMs typically lack the contextual understanding required to deeply cause over distributed, nuanced, and sometimes contradictory scientific information.
Microsoft Discovery is constructed on prime of a strong graph-based data engine. As a substitute of merely retrieving information, this engine builds graphs of nuanced relationships between proprietary information in addition to exterior scientific analysis. This permits the platform to have a deep understanding of conflicting theories, various experimental outcomes, and even underlying assumptions throughout disciplines.
This contextual reasoning can be clear. Quite than outputting monolithic solutions, it retains the skilled within the loop with detailed supply monitoring and reasoning, offering the extent of transparency in AI techniques that builds belief, ensures accountability, and permits specialists to validate and perceive each step or make any changes as wanted.
Specialised discovery brokers for conducting analysis
As a substitute of siloed and static pipelines, Microsoft Discovery implements a steady and iterative R&D cycle the place researchers can information and orchestrate a group of specialised AI brokers that be taught and adapt over time—not only for reasoning, however for conducting analysis itself. The definition of those specialised brokers captures each area data and course of logic, merely via pure language.
R&D groups will be capable to construct a customized AI group aligned to their particular processes and data, simply encoding these brokers with their experience and methodologies to make sure they’ll adapt and orchestrate as analysis progresses. This method is much extra versatile than hard-coding behaviors of as we speak’s digital simulation instruments, which regularly are extremely specialised and lack streamlined integration with others, and it implies that analysis groups not require computational experience to drive impression. For example, customers can entry and outline numerous brokers’ specialties, corresponding to ‘molecular properties simulation specialist’ or ‘literature overview specialist.’ They will even recommend which instruments or fashions the brokers ought to use or create, and the way they need to collaborate with others.
This natural, bidirectional collaboration is a game-changer for managing R&D: brokers will not be solely able to working for the researchers, however with them in a way that may really amplify human ingenuity—seeing each the forest and the bushes without delay.
On the heart of this collaboration is Microsoft Copilot, appearing as a scientific AI assistant that orchestrates these specialised brokers primarily based on the researcher’s prompts. Copilot is conscious of all of the instruments, fashions, and data bases in a buyer’s catalog on the platform, can determine which brokers to leverage, and might arrange end-to-end workflows that cowl the total discovery course of by combining superior AI and HPC simulations via the joint work of those brokers.
Extensible and enterprise-ready
Microsoft Discovery is constructed on prime of Azure infrastructure and companies, leveraging by design the belief, compliance, and governance controls on the core of Microsoft’s safe cloud basis.
We imagine within the energy of an open ecosystem that leverages the strengths of Microsoft’s newest developments together with different modern options from clients and companions. Microsoft Discovery permits R&D groups to increase the platform’s catalog by bringing their toolkit of option to cowl their particular analysis wants in a complete scientific bookshelf. This extensibility on the core of Microsoft Discovery simplifies the onboarding of their alternative of computational instruments, fashions, and data bases—whether or not they’re customized developments, open-source, or business options. As we carry to market new capabilities in dependable quantum computing and embodied AI, the platform will stay future-proofed with the perfect applied sciences accessible at Microsoft and throughout the business.
Actual impression: Discovering a novel, non-PFAS coolant prototype
Over the previous months, we have now made important strides aiding computational scientists of their analysis and incorporating cutting-edge improvements from Microsoft Analysis. This has led to exceptional breakthroughs, corresponding to discovering a novel solid-state electrolyte candidate that makes use of 70% much less lithium in collaboration with the Division of Power’s Pacific Northwest Nationwide Laboratory (PNNL) and enabling speedy computational simulations that speed up scientific discoveries at Unilever. Microsoft Discovery is designed to carry these improvements to each scientist—not solely these with deep computational experience.
One of many extra thrilling early use circumstances of Microsoft Discovery is unfolding on the Pacific Northwest Nationwide Laboratory, the place scientists are utilizing Microsoft Discovery’s superior generative AI and HPC capabilities to additional develop machine studying fashions that predict and optimize advanced chemical separations—a crucial course of in nuclear science. These separations are important for successfully isolating radioactive components after the nuclear fission course of, a notoriously time-sensitive and extremely chemically advanced process. Sooner or later, the group goals to make use of these developments to cut back the time scientists should spend in hazardous radioactive environments, whereas bettering yields and purity, enhancing each security and effectivity.
—Scott Godwin, Director, Middle for Cloud Computing, Pacific Northwest Nationwide Laboratory
By leveraging superior AI fashions and HPC instruments for simulation that will probably be accessible on Microsoft Discovery, Microsoft researchers found a novel, non-PFAS, immersion datacenter coolant prototype in about 200 hours.1 Present coolants typically take a few years to develop and might include dangerous PFAS-based chemical substances that make them unviable to make use of, as there’s a world push to ban these “without end chemical substances” in favor of extra environmentally pleasant choices on this business and plenty of others.
After the digital discovery course of, we efficiently synthesized this coolant prototype in below 4 months, and it’s at present below additional evaluation and refinement. We now have already examined a number of the major properties of this materials and so they align to the AI predictions, which is a testomony to the accuracy of the predictive fashions used. Whereas this undertaking is simply an experiment, it lays the groundwork for future developments and enhancements in coolant expertise and demonstrates how the mix of HPC and specialised AI fashions can speed up and remodel R&D processes.
In keeping with Daniel Pope, founding father of Submer, an organization whose mission is to construct datacenters with a powerful deal with sustainability, effectivity, and a wiser utilization of assets:
The pace and depth of molecular screening achieved by Microsoft Discovery would’ve been inconceivable with conventional strategies. What as soon as took years of lab work and trial and error, Microsoft Discovery can accomplish in simply weeks, and with higher confidence.
A rising ecosystem
We’re placing this enterprise-grade platform into the arms of worldwide innovators to show real-world impression throughout industries—from chemistry and pharma to manufacturing and silicon design.
It’s solely with a powerful ecosystem that we’ll be capable to understand the total potential of Microsoft Discovery, and it’s why we’re working with clients, companions, and different Microsoft groups to carry first-party developments along with main business instruments and area experience.
Clients and inner collaborators
GSK is working to revolutionize healthcare, uniting science, expertise and expertise—together with world-class partnerships—to get forward of illness collectively. The corporate makes use of tech to advance science and speed up the event and supply of medicines and vaccines to positively impression the well being of individuals at scale.
GSK’s depth and breadth of knowledge and built-in use of tech throughout each a part of its enterprise—from early scientific exploration via to fabricate and supply of medicines and vaccines in market—present a singular providing when working with others. The corporate appears ahead to a attainable partnership with Microsoft with the intent of additional advancing GSK’s generative platforms for parallel prediction and testing, creating new medicines with higher pace and precision, and doubtlessly remodeling medicinal chemistry to new unimaginable ranges. The probabilities forward are thrilling, and collectively, we are able to try for probably the most modern options for sufferers and for well being.
The Estée Lauder Firms has gained a worldwide repute for high-quality skincare, make-up, haircare and perfume merchandise that ship extremely efficient outcomes demonstrated by in depth analysis and product analysis. The corporate is happy to harness the facility of Microsoft Discovery to additional speed up the event of merchandise that uphold the best requirements of excellence.
Our proprietary R&D information, stemming from the minds of our sensible scientists and almost 80 years of analysis, improvement, and experimentation, is a key aggressive benefit. The Microsoft Discovery platform will assist us to unleash the facility of our information to drive quick, agile, breakthrough innovation and high-quality, personalised merchandise that can delight our shoppers.
—Kosmas Kretsos, PhD, MBA, Vice President, R&D and Innovation Know-how, The Estée Lauder Firms
Moreover, Microsoft is releasing a medical analysis agent that makes use of the identical graph-based data engine accessible in Microsoft Discovery to boost data retrieval by synthesizing insights from trusted medical journals. As a part of a broader set of specialised brokers within the healthcare agent orchestrator code pattern in Azure AI Foundry, this agent allows researchers and builders to ship actionable and evidence-based steering tailor-made particularly to advanced, multi-disciplinary healthcare workflows—corresponding to most cancers care.
Area-specific choices
Combining Microsoft’s and NVIDIA’s strengths in generative Al and scientific computing, we plan to combine Microsoft Discovery with NVIDIA ALCHEMI and NVIDIA BioNeMo NIM microservices to speed up breakthroughs in supplies and life sciences. Supplies researchers will now have entry to state-of-the-art inference capabilities for candidate identification, property mapping, and artificial information technology. Biomolecular R&D groups will be capable to speed up Al mannequin improvement for drug discovery, leveraging pre-trained BioNeMo Al workflows, all in Microsoft Discovery’s unified, enterprise-grade platform.
Researchers can even deploy their AI brokers on high-performance NVIDIA-accelerated Azure AI Foundry infrastructure, enabling them to effectively course of and synthesize massive volumes of scientific information with distinctive pace and responsiveness for accelerated discovery and enhanced analysis outcomes.
AI is dramatically accelerating the tempo of scientific discovery. By integrating NVIDIA ALCHEMI and BioNeMo NIM microservices into Azure Discovery, we’re giving scientists the power to maneuver from information to discovery with unprecedented pace, scale, and effectivity.
—Dion Harris, Senior Director of Accelerated Knowledge Middle Options, NVIDIA
Moreover, we plan to combine Synopsys’ business options in Microsoft Discovery to speed up semiconductor engineering, serving to each {hardware} designers and software program builders ship superior merchandise.
Semiconductor engineering is among the many most advanced, consequential, and high-stakes scientific endeavors of our time, which makes it an especially compelling use case for synthetic intelligence. By integrating Synopsys’ pioneering AI-powered design options with Microsoft Discovery, we are able to understand the potential of agentic AI, re-engineer chip design workflows, supercharge engineering productiveness, and speed up the tempo of expertise innovation.
—Raja Tabet, Senior Vice President, Engineering Excellence Group, Synopsys
Microsoft can be working with PhysicsX, planning to combine the corporate’s physics AI basis fashions into Microsoft Discovery so clients can unlock new ranges of automation, optimization, and efficiency throughout engineering and manufacturing.
The Microsoft Discovery platform represents a seismic shift in how AI can speed up scientific discovery and engineering. That is about remodeling how advanced bodily techniques are designed, constructed, and operated throughout superior industries—in aerospace and protection, semiconductors, minerals and supplies, power, and automotive. Collectively, PhysicsX and Microsoft are constructing the software program infrastructure that can outline the following period of engineering.
—Jacomo Corbo, Chief Govt Officer and Cofounder, PhysicsX
Integration assist
Lastly, we’re excited to associate with a rising record of software program integrators, corresponding to Accenture and Capgemini, to assist clients and collaborators scale customized platform deployments.
Along with Microsoft, we’re shaping a daring AI imaginative and prescient for organizations who use deep science to carry modern merchandise to sufferers and shoppers. Our laboratory transformation methods and Microsoft’s Microsoft Discovery platform create a dynamic ecosystem for scientific development. This collaboration will assist us understand the laboratory of the long run, enabling scientists to push the boundaries of discovery, experimentation, and testing with higher pace and precision.
—Adam Borenstein, Managing Director, International Laboratory Reinvention Lead, Accenture
We’re excited to be bringing the Microsoft Discovery platform and AI brokers to R&D-intensive sectors. We imagine these applied sciences have the potential to allow skilled scientists to unlock step adjustments within the tempo of innovation, bringing transformative advantages to enterprise and society. This partnership will drive productiveness in laboratory-driven R&D by drawing on Capgemini’s business expertise, specialist bodily and organic AI capabilities, and science-led ‘lab-in-the-loop’ mental property, together with that of Cambridge Consultants, the deep tech powerhouse of Capgemini. For our shoppers this might imply accelerated discovery and predictive modelling or different aggressive benefits via utilizing information and AI at scale.
—Roshan Gya, Chief Govt Officer, Capgemini Invent
Able to take the following steps?
Be taught extra about how Microsoft Discovery may help scientists and engineers remodel analysis and improvement:
¹Based on the definitions of PFAS supplied by the Organisation for Financial Co-operation and Improvement (OECD) (2021), the U.S. Environmental Safety Company and Buck et. al. (2011)