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Using AI for Dynamic Pricing: The Smarking Example
What do the airlines, hotels, parking, and cloud computing have in common? You invest in assets upfront and render them out as slices of time. While parking assets exist in the physical space, and cloud computing exists in a virtual space, the principle is the same. Dr. Maokai Lin ... Read more
Mastering A/B Testing: From Design to Analysis
A/B testing is a critical tool leveraged by data scientists to estimate the expected outcome of a certain action like updating software, adding new features, or deploying a new web layout. Proper experimental design is crucial to realizing the benefits of A/B testing and avoiding the pitfalls that detract... Read more
Model Evaluation in the Land of Deep Learning
Applications for machine learning and deep learning have become increasingly accessible. For example, Keras provides APIs with TensorFlow backend that enable users to build neural networks without being fluent with TensorFlow. Despite the ease of building and testing models, deep learning has suffered from a lack of interpretability; deep... Read more
The Logistics of Starting Deep Learning
Deep learning models can be intimidating and rightfully so; in their raw form they are highly complex algorithms that need to be engineered with expertise. However, deep learning is very accessible to individuals with a background in technical skills thanks to organizations and individuals that have packaged deep learning... Read more
4 Examples of Businesses Solving Problems with AI
In her talk at ODSC West 2018, “Reality Check: How Businesses are using Human in the Loop Processes to Drive Real Value,” Alyssa Simpson Rochwerger, the VP of Product at Figure Eight, explains how companies can begin solving creating value and solving problems with AI. [Related Article: Problem Solving... Read more
Redefining Robotics: Next Generation Warehouses
People picture robots changing to look more like humans, but in reality, the evolution of robotics involves things you can’t actually see. For Bastiane Huang at Osaro, the development of robots means greater advances in autonomy. Building brains for robots gives them more flexibility for tasks and creates more... Read more
Generating Neural Networks to Detect Alzheimer’s
AI is showing so much promise in the medical field. It’s an excellent example of how AI combines with human intelligence to create a “super brain” capable of predicting disease, uncovering patterns, and testing solutions for persistent problems. Precision Medicine is a medical nonprofit using this super combination of... Read more
10 Things Learned From Deploying AI in Human Environments
Deploying AI in human environments requires some finesse, unlike the pure environments you often encounter in school. Cameron Turner of Datorium is an expert at blending the world of business with AI deployment and is here to tell us ten things he’s learned so far.  [Related Article: How to... Read more
Scaling Humans With AI
One of the most persistent problems within many fields is the lack of communication. We have access to vast amounts of data, but all that information is siloed. You have so many different systems and hundreds of ways to access various pieces of data, but nothing really communicates. AI... Read more
Most Data-Driven Cultures… Aren’t
For Cassie Kozyrkov, Chief Decision Scientist at Google, reducing the instances of errors in statistics is the top priority. Many organizations think of themselves as data-driven, but in reality, it’s at the mercy of good leadership at your organization. If your organization isn’t good at getting and using data,... Read more