AI Lab projects

How can we develop AI systems that support seamless interactive experiences? Platform for Situated Intelligence is a framework that makes it easier for developers to build AI that can perceive, understand, and act in our human-filled world in real time.

We create the systems and platforms for training and deploying large AI models at scale. These advancements can make it faster and easier for developers and data scientists to infuse AI into their applications.

The Artificial Nose experiment is a smart device trained to recognize a variety of smells. With a simple gas sensor and a micro-controller, you can build an AI nose that can identify the smell of bread, coffee, and more.

CoModGAN uses AI to complete an image that is missing significant amounts of visual information. Two neural networks work together to generate and verify a completed image.

Microsoft Math uses optical character recognition (OCR) for handwriting to extract a math equation from a student’s photo of their notes. The problem is then standardized, classified, solved, and returned with solution steps and similar problems.

Snip Insights helps users find intelligent insights from a snip or screenshot. AI services convert a captured image to translated text, automatically detecting and tagging image content.

Machine Reading Comprehension (MRC) answers questions about written text. Using a neural network, MRC mimics the process of human readers. Ask a question and MRC reads a document until an answer is formed.

Data visualizations are an important part of data storytelling but sometimes they tell just a part of the whole story. Datamations help bring data to life by making it easy to create animations that show the process behind a plot or table.

Virtual Stage is a background matting experiment to create high-quality videos from anywhere, improving current virtual green screening techniques with Azure Kinect depth camera.

Sketch2Code converts hand-written drawings to HTML prototypes. Designers share ideas on a whiteboard, then changes are shown instantly in the browser—helping improve collaboration between the designer, developer, and customer.

Altran developed a machine learning classifier that predicts source code files carrying a higher risk of a bug. Developers are presented with explanation and factors used in making the specific prediction.

Unlock insights and discover intelligent connections in unstructured data. The Insights and Discovery Accelerator uses Microsoft AI to speed and scale investigations and research by helping journalists find critical content in a sea of data.

JFK Files takes 34,000 complex files including photos, handwriting, government documents, and more, then extracts readable information. This knowledge is organized to enable new ways to explore the information.

PoseTracker uses deep learning to track the position and orientation of objects. This solution will use your phone camera to measure and track the angle, orientation, and distance of an item in real time.

Angel Eyes is an IOT device that monitors a baby’s sleeping position and environment. Caregivers can view a live stream from anywhere and receive notifications if the device detects any issues.

Clean Water AI uses deep learning to detect dangerous bacteria and particles in water. The device analyzes drinking water with real-time detection and contamination mapping.

Gen Studio is a prototype created with collaborators from The Metropolitan Museum of Art, Microsoft, and MIT. Gen Studio uses AI to visually navigate The Met’s art collection.

PoseTracker uses deep learning to track the position and orientation of objects. This solution will use your phone camera to measure and track the angle, orientation, and distance of an item in real time.

AirSim is a simulation tool that creates a 3D version of a real environment. A simulated drone “flies” to capture images, building a custom vision model. AI uses the vision model to identify objects or people.

Intelligent robotics uses AI to increase collaboration between people and devices. Microsoft AI enables the next generation of robots to adapt to dynamic situations and communicate naturally with people.

Explore the concepts of machine teaching, allowing developers or subject matter experts with little AI expertise to provide abstract concepts to an intelligent system.

How can we empower ML practitioners and business stakeholders to operationalize responsible AI in practice? We created a dashboard that brings together responsible AI tools for model debugging and decision-making.

Sharing data from sensitive sources is critical to research but can put vulnerable data subjects at risk of being identified. We created an open-source pipeline that generates synthetic data to preserve privacy when sharing and analyzing sensitive datasets.

Differential privacy is crucial for machine learning and data privacy. Safeguarding the privacy of people while enabling deeper analysis will empower health research innovations.

HE technology allows computations to be performed directly on encrypted data. Using state-of-the-art cryptology, you can run machine learning on anonymized datasets without losing context.

Conversational AI is a new way for companies to interact with their customers across any channel, like digital assistants, chat or social media. To be effective, conversational bots need to be developed in a way that earns people’s trust.