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Diagram: The proposed SOLOIST model architecture and training objectives. Dialog history, Belief state, DB state, and Response make up the pipeline. Task 1, belief state prediction, corresponds with belief state. Task 2 and Task 3, grounded response generation and contrastive objective correspond with response. A user is shown thinking a goal, which points from the dialog history to the user (response), and then back to dialog history (input). Belief state points down to an image of a computer server (Belief state query) and then back to DB State (DB state results). The server points to readouts labeled “entity.”
Microsoft Research Blog

SOLOIST: Pairing transfer learning and machine teaching to advance task bots at scale 

June 16, 2021 | Baolin Peng, Chunyuan Li, Jinchao Li, Lars Liden, and Jianfeng Gao

The increasing use of personal assistants and messaging applications has spurred interest in building task-oriented dialog systems (or task bots) that can communicate with users through natural language to accomplish a wide range of tasks, such as restaurant booking, weather…

Dr. Hunt Allcott and Evan Rose on the Microsoft Research Podcast
Microsoft Research Podcast

Econ4: Uncovering how decision-making shapes individuals and society through behavioral public economics featuring Evan Rose and Hunt Allcott 

June 16, 2021

In this episode, Senior Principal Researcher Hunt Allcott talks with Postdoctoral Researcher Evan Rose about Allcott’s work exploring the everyday decisions people face, like buying fuel-efficient cars or taking out payday loans, and how a clearer understanding of these decisions…

jumping and dancing happy people
Articles

Designing for delight: Five patterns to building delightful UX 

June 15, 2021

Delight might seem like an unimportant component, but it is the icing on the cake of a remarkable customer experience. For me and my team, delivering delightful UX requires us to collectively reimagine every experience we build. Delightful UX isn’t just a bolt on, and…

In the news | Future from a16z

On Workplace Productivity 

June 15, 2021

What does it mean to be productive? At the beginning of the pandemic, when many workers went remote, some managers were tempted to start counting things — whether hours, objects, or other things. But they’re about 100 years and two…

In the news | King 5 | New Day Northwest

Going Hybrid? What will the future workplace look like? 

June 15, 2021

SEATTLE — "Well, we're going to need to be really flexible about thinking about our workspaces as we move forward,” Jaime Teevan, chief scientist for Microsoft’s experiences and devices said. “And actually, you see, something like two-thirds of businesses are…

Photograph of two men: Akhay (LH) and Ajay (RH)
Microsoft Research India Podcast

Podcast: Dependable IoT- Making data from IoT devices dependable and trustworthy for good decision making 

June 14, 2021

 Episode 009 | June 15, 2021 The Internet of Things has been around for a few years now and many businesses and organizations depend on data from these systems to make critical decisions. At the same time, it is…

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In the news | Microsoft Research India Podcast

Podcast: Dependable IoT- Making data from IoT devices dependable and trustworthy for good decision making 

June 14, 2021

The Internet of Things has been around for a few years now and many businesses and organizations depend on data from these systems to make critical decisions. At the same time, it is also well recognized that this data- even…

A chart showing a GAN comparing fake images with real images, filtering them through a discriminator to produce a value indicating how fake the image is.
Microsoft Research Blog

How can generative adversarial networks learn real-life distributions easily 

June 10, 2021 | Zeyuan Allen-Zhu and Yuanzhi Li

A Generative adversarial network, or GAN, is one of the most powerful machine learning models proposed by Goodfellow et al. (opens in new tab) for learning to generate samples from complicated real-world distributions. GANs have sparked millions of applications, ranging…

Dr. Hunt Allcott and Economist David Rothschild on the Microsoft Research Podcast
Microsoft Research Podcast

Econ3: Understanding the media ecosystem and how it informs public opinion in the internet age featuring Hunt Allcott and David Rothschild 

June 10, 2021

Interviewed by Senior Principal Researcher Hunt Allcott, Economist David Rothschild discusses how the news media has evolved alongside social media and the internet, from story development to distribution of news via aggregators and wire services. Rothschild illuminates how and where…

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