Microsoft Excel is one of the world’s most important software tools, relied upon by users worldwide to create, understand, model, predict, and collaborate. As the Excel team works to leverage new areas of computer science – advancements in programming languages, NLP,…
In the news | MICROSOFT AZURE BLOG
For operators, many challenges can be involved in their journey to the cloud, some more complex than others. Here, it is important to note that when it comes to operators’ path to cloud migration, there is no such thing as…
This is a common story among experimenters: you have a hypothesis to test, you code the change you want to deploy, and you design an A/B test to properly measure the impact of the change on the user. After the…
Producing great product insights is bolstered by understanding what motivates stakeholders to learn, how they retain information, how to build on prior knowledge, and what experiences can activate behaviors. This helps ensure that research is acted upon and encourages colleagues…
In the news | Volastra
Collaboration will integrate Microsoft Azure AI and Volastra’s insights into tumor biology to develop machine learning tools to detect drivers of tumor growth and predict metastatic risk.
The intersection of desirability, feasibility, and viability is seen as the sweet spot for innovation; these attributes are the cornerstones of Design Thinking. But what else should be considered? Here are some ideas to approach innovation responsibly, so you can…
In the news | KUOW
If you’re one of the many white-collar workers who left the office behind a year ago, you’re probably wondering just what’s in store when you go back. We get some insight on lessons learned from a year of remote work…
In the news | The Hill
When our team at Duke Health launched a bilingual COVID-19 symptom monitoring program last March, we noticed over 90 percent of participants enrolling were white. We quickly started collaborating with nonprofit design studio IDEO.org on the question: how can we…
| Misha Khodak, Neil Tenenholtz, Lester Mackey, and Nicolo Fusi
From BiT (928 million parameters (opens in new tab)) to GPT-3 (175 billion parameters (opens in new tab)), state-of-the-art machine learning models are rapidly growing in size. With the greater expressivity and easier trainability of these models come skyrocketing training…