A.I. Every Day

Microsoft and Darktrace partner on AI-enhanced cloud security Microsoft has announced a new partnership with Cambridge-based AI startup Darktrace that aims to provide AI -enhanced cyber security to organisations transitioning to the cloud. The collaboration will focus on addressing security challenges in the “critical areas” of email security,

Expert.ai adds emotion and style detection tools to natural language API Expert.ai added new tools to its natural language API to help AI developers detect emotions, behaviors, and styles in large-scale texts.

Sleeker Pony.ai self-driving SUV hints at more road-ready autonomous cars Autonomous car headgear keeps getting smaller, with Pony.ai revealing its latest self-driving car design and its much sleeker, Luminar-powered scanning hub. Far from the “upturned

Why AI Projects Are Failing At Your Company To successfully implement data democratization across your organization, you need a data catalog that makes it easy to search and understand data across the business, not just the IT group.

Build an anomaly detection model from scratch with Amazon Lookout for Vision A common problem in manufacturing is verifying that products meet quality standards. You can use manual inspection on a subset of the products, but it’s usually not scalable enough to meet demand as production grows. In this post, I go through the steps of creating an end-to-end machine vision solution

Linear Algebra and Its Applications, 4th Edition Linear algebra is relatively easy for students during the early stages of the course, when the material is presented in a familiar, concrete setting. But when abstract concepts are introduced, students often hit a brick wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations), are not easily understood, and require time to assimilate. Since they are fundamental to the study of linear algebra, students' understanding of these concepts is vital to their mastery of the subject. David Lay introduces these concepts early in a familiar, concrete Rn setting, develops them gradually, and returns to them again and again throughout the text so that when discussed in the abstract, these concepts are more accessible.

Machine Learning With Big Data Learn Machine Learning With Big Data from University of California San Diego. Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine ...

Zscaler Secure, simplify, and transform IT with the world's largest cloud security platform. Join us at #ZenithLive: https://t.co/BABEthjTgO 🚀

Pymetrics Founded by Harvard/MIT-trained PhDs, pymetrics uses neuroscience data and AI to help global clients like Unilever, Accenture and LinkedIn make their hiring and internal mobility more predictive and less biased. pymetrics replaces the resume as a first-pass filter by assessing candidates based on their true potential -- their inherent cognitive and emotional make-up. Using algorithms that are trained on high-performing employees at a company, pymetrics builds a trait profile of a company's top performers to select best fit talent. These algorithms are then audited to remove any gender or ethnic bias. pymetrics also serves as a common application for candidates, ensuring that everyone finds their best-fit job, regardless of where they apply. With over 80 enterprise clients and offices in NYC, London, Sydney and Singapore, pymetrics is powering the future of hiring: efficient, predictive, and bias-free.

Josh Cogan PhD Physics, Stanford University

Rajat Monga Sr. Director/Distinguished Engineer. Leading #TensorFlow at Google.