We now have architected Microsoft Discovery to be extremely extensible, enabling researchers to combine the most recent Microsoft improvements with their very own fashions, instruments, and datasets in addition to a variety of companion and open-source options.
We’re saying a brand new enterprise agentic platform known as Microsoft Discovery to speed up analysis and growth (R&D) at Microsoft Construct 2025.
Our purpose is to carry the ability of AI to scientists and engineers to rework the complete discovery course of—from superior information reasoning and speculation formulation to experimental simulation and iterative studying. Microsoft Discovery allows researchers to collaborate with a staff of specialised AI brokers mixed with a graph-based information 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 most recent Microsoft improvements with their very own fashions, instruments, and datasets in addition to a variety of companion 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 fast 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 rework R&D in any firm.
We’re working with a notable set of Microsoft prospects who’re desirous about co-innovating in various industries together with chemistry and supplies, silicon design, vitality, manufacturing, and pharma. We’re additionally working with a broad companion base that’s constructing on prime of the platform to drive this acceleration, and we couldn’t be extra excited. The chances are limitless as we notice 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 broaden 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 information 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 exhausting to attach the dots throughout the completely different domains concerned.
- R&D is iterative. There are hardly ever easy, clear-cut solutions. As an alternative, scientific information evolves by proof, discourse, and refinement.
This complexity calls for a brand new paradigm—one which isn’t aimed toward doing the identical experiments quicker, however moderately basically altering the paradigm of how we method R&D.
Think about if each researcher may collaborate with a tireless staff of clever, synergistic AI brokers with the only 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 methodology.
On this new world, individuals and specialised AI brokers will cooperatively refine information 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 comprehend this imaginative and prescient, scientific AI brokers should be capable to:
- Cause over a fancy and contextual graph connecting all information sources.
- Specialize throughout distinct domains and duties.
- Study from outcomes and adapt whole 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 most recent improvements from Microsoft and the broader scientific ecosystem.
Graph-based scientific co-reasoning
The appearance of huge language fashions (LLMs) hinted at this new period, providing capabilities to hurry up sure scientific duties, notably for info retrieval and speculation technology. Nevertheless, LLMs typically lack the contextual understanding required to deeply purpose over distributed, nuanced, and sometimes contradictory scientific knowledge.
Microsoft Discovery is constructed on prime of a strong graph-based information engine. As an alternative of merely retrieving details, this engine builds graphs of nuanced relationships between proprietary knowledge 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 also be clear. Relatively than outputting monolithic solutions, it retains the knowledgeable within the loop with detailed supply monitoring and reasoning, offering the extent of transparency in AI programs that builds belief, ensures accountability, and permits consultants to validate and perceive each step or make any changes as wanted.
Specialised discovery brokers for conducting analysis
As an alternative of siloed and static pipelines, Microsoft Discovery implements a steady and iterative R&D cycle the place researchers can information and orchestrate a staff of specialised AI brokers that study and adapt over time—not only for reasoning, however for conducting analysis itself. The definition of those specialised brokers captures each area information and course of logic, merely by pure language.
R&D groups will be capable to construct a customized AI staff aligned to their particular processes and information, 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 right now’s digital simulation instruments, which regularly are extremely specialised and lack streamlined integration with others, and it signifies that analysis groups not require computational experience to drive impression. For example, customers can entry and outline numerous brokers’ specialties, equivalent to ‘molecular properties simulation specialist’ or ‘literature evaluation specialist.’ They’ll 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 fashion that may really amplify human ingenuity—seeing each the forest and the bushes without delay.
On the middle of this collaboration is Microsoft Copilot, appearing as a scientific AI assistant that orchestrates these specialised brokers based mostly on the researcher’s prompts. Copilot is conscious of all of the instruments, fashions, and information bases in a buyer’s catalog on the platform, can establish 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 by 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 progressive options from prospects 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 selection of computational instruments, fashions, and information bases—whether or not they’re customized developments, open-source, or industrial options. As we carry to market new capabilities in dependable quantum computing and embodied AI, the platform will stay future-proofed with one of the best applied sciences obtainable at Microsoft and throughout the trade.
Actual impression: Discovering a novel, non-PFAS coolant prototype
Over the previous months, we’ve made vital strides aiding computational scientists of their analysis and incorporating cutting-edge improvements from Microsoft Analysis. This has led to exceptional breakthroughs, equivalent to discovering a novel solid-state electrolyte candidate that makes use of 70% much less lithium in collaboration with the Division of Vitality’s Pacific Northwest Nationwide Laboratory (PNNL) and enabling fast 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 instances 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 complicated chemical separations—a vital 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 complicated process. Sooner or later, the staff goals to make use of these developments to cut back the time scientists should spend in hazardous radioactive environments, whereas enhancing yields and purity, enhancing each security and effectivity.
—Scott Godwin, Director, Heart for Cloud Computing, Pacific Northwest Nationwide Laboratory
By leveraging superior AI fashions and HPC instruments for simulation that will likely be obtainable 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 compounds that make them unviable to make use of, as there’s a worldwide push to ban these “eternally chemical compounds” in favor of extra environmentally pleasant choices on this trade and plenty of others.
After the digital discovery course of, we efficiently synthesized this coolant prototype in underneath 4 months, and it’s at present underneath additional evaluation and refinement. We now have already examined a few of the major properties of this materials they usually align to the AI predictions, which is a testomony to the accuracy of the predictive fashions used. Whereas this challenge 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 rework R&D processes.
In keeping with Daniel Pope, founding father of Submer, an organization whose mission is to construct datacenters with a powerful concentrate on sustainability, effectivity, and a better 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 fingers 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 notice the total potential of Microsoft Discovery, and it’s why we’re working with prospects, companions, and different Microsoft groups to carry first-party developments along with main trade 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 by to fabricate and supply of medicines and vaccines in market—present a novel providing when working with others. The corporate appears ahead to a potential 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 reworking medicinal chemistry to new unimaginable ranges. The chances forward are thrilling, and collectively, we will try for essentially the most progressive options for sufferers and for well being.
The Estée Lauder Firms has gained a worldwide status for high-quality skincare, make-up, haircare and perfume merchandise that ship extremely efficient outcomes demonstrated by intensive analysis and product analysis. The corporate is worked up to harness the ability of Microsoft Discovery to additional speed up the event of merchandise that uphold the best requirements of excellence.
Our proprietary R&D knowledge, stemming from the minds of our good scientists and practically 80 years of analysis, growth, and experimentation, is a key aggressive benefit. The Microsoft Discovery platform will assist us to unleash the ability of our knowledge to drive quick, agile, breakthrough innovation and high-quality, customized merchandise that can delight our shoppers.
—Kosmas Kretsos, PhD, MBA, Vice President, R&D and Innovation Expertise, The Estée Lauder Firms
Moreover, Microsoft is releasing a medical analysis agent that makes use of the identical graph-based information engine obtainable in Microsoft Discovery to boost info 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 steerage tailor-made particularly to complicated, multi-disciplinary healthcare workflows—equivalent 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 knowledge technology. Biomolecular R&D groups will be capable to speed up Al mannequin growth for drug discovery, leveraging pre-trained BioNeMo Al workflows, all in Microsoft Discovery’s unified, enterprise-grade platform.
Researchers may also deploy their AI brokers on high-performance NVIDIA-accelerated Azure AI Foundry infrastructure, enabling them to effectively course of and synthesize giant volumes of scientific knowledge 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 flexibility to maneuver from knowledge to discovery with unprecedented pace, scale, and effectivity.
—Dion Harris, Senior Director of Accelerated Knowledge Heart Options, NVIDIA
Moreover, we plan to combine Synopsys’ trade 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 complicated, 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 will notice 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 also be working with PhysicsX, planning to combine the corporate’s physics AI basis fashions into Microsoft Discovery so prospects 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 reworking how complicated bodily programs are designed, constructed, and operated throughout superior industries—in aerospace and protection, semiconductors, minerals and supplies, vitality, and automotive. Collectively, PhysicsX and Microsoft are constructing the software program infrastructure that can outline the subsequent period of engineering.
—Jacomo Corbo, Chief Government Officer and Cofounder, PhysicsX
Integration assist
Lastly, we’re excited to companion with a rising record of software program integrators, equivalent to Accenture and Capgemini, to assist prospects 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 progressive 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 notice the laboratory of the longer term, 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 knowledgeable 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 trade 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 purchasers this might imply accelerated discovery and predictive modelling or different aggressive benefits by utilizing knowledge and AI at scale.
—Roshan Gya, Chief Government Officer, Capgemini Invent
Able to take the subsequent steps?
Study extra about how Microsoft Discovery may also help scientists and engineers rework analysis and growth:
¹Based on the definitions of PFAS supplied by the Organisation for Financial Co-operation and Growth (OECD) (2021), the U.S. Environmental Safety Company and Buck et. al. (2011)