Microsoft Research Lab – New York City
News & features
In the news | Axios Science
1 big thing: Cutting through the BS of AI
A new algorithm, along with a dose of humility, might help generative AI mitigate one of its persistent problems: confident but inaccurate answers. Why it matters: AI errors are especially risky if people overly rely on chatbots and other tools…
In the news | TIME
Microsoft on the TIME100 AI list
This morning, TIME released its first “TIME100 Artificial Intelligence” list online, which includes Kevin Scott, Jaime Teevan, Kate Crawford, and Kalika Bali.
In the news | ACM
danah boyd featured in the “People of ACM”
The August issue of People of ACM featured danah boyd, Partner Researcher in the New York City Lab. She is the author of “It’s Complicated: The Social Lives of Networked Teens” and “Participatory Culture in a Networked Era”. In 2013,…
In the news | Microsoft India Paradigm Shift Podcast
Paradigm Shift, Episode 3: Pitches and Pawns
From analyzing every cricketing shot in the book, to infusing intelligence on the chessboard, to reimagining how fans engage with the players and the game–AI is shaping the next best move in sports.
In the news | Microsoft News Russia
Sber and Microsoft develop a unique AI robot control system
Sber and Microsoft Research summed up the results of a joint project launched in October 2019 to develop a unique AI system that offers the opportunity to teach robots to manipulate physical objects of unstable shape in almost the same…
In the news | The AI Blog
With reinforcement learning, Microsoft brings a new class of AI solutions to customers
Countless companies use online recommendation engines to show customers products and experiences that match their interests. And yet, traditional machine learning models that predict what people might prefer are often based on data from past experience.
In the news | Machine Learning (Theory)
HOMER: Provable Exploration in Reinforcement Learning
Last week at ICML 2020, Mikael Henaff, Akshay Krishnamurthy, John Langford and Dipendra Misra had a paper on a new reinforcement learning (RL) algorithm that solves three key problems in RL: (i) global exploration, (ii) decoding latent dynamics, and (iii) optimizing a given…
In the news | Medium | Machine Learning
HOMER: Provable Exploration in Reinforcement Learning
At ICML 2020, Mikael Henaff, Akshay Krishnamurthy, John Langford and Dipendra Misra published a paper presenting a new reinforcement learning (RL) algorithm called HOMER that addresses three main problems in real-world RL problem: (i) exploration, (ii) decoding latent dynamics, and (iii) optimizing…
In the news | VentureBeat
Microsoft researchers say NLP bias studies must consider role of social hierarchies like racism
As the recently released GPT-3 and several recent studies demonstrate, racial bias, as well as bias based on gender, occupation, and religion, can be found in popular NLP language models. But a team of AI researchers wants the NLP bias…