↳ ScienceDaily.com

Driverless cars change lanes more like humans do

Researchers will present a new lane-change algorithm that splits the difference. It allows for more aggressive lane changes than the simple models do but relies only on immediate information about other vehicles’ directions and velocities to make decisions.
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↳ ArtificialLawyer.com

Legal Data Collaboration Leader HighQ Launches ‘AI Hub’

Legal data collaboration platform HighQ is launching a new offering that it hopes will become ‘the natural interface for multiple AI engines’, called the ‘AI … The post Legal Data Collaboration Leader HighQ Launches ‘AI Hub’ appeared first on Artificial Lawyer.
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↳ Mindvalley.com

Why Top Performers Sleep More Than Average People — And Why You Should Too

So I really messed up on this one. I had fallen for a common myth. “Busy, productive people need less sleep. Sleep is for lazy people.” And for a while, I was attempting to hack my life to survive on 6 hours a day of sleep so I had more time for, well… just about […] The post Why Top Performers Sleep More Than Average People — And Why You Should Too appeared first on Mindvalley Blog.
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↳ News.mit.edu

Making driverless cars change lanes more like human drivers do

In the field of self-driving cars, algorithms for controlling lane changes are an important topic of study. But most existing lane-change algorithms have one of two drawbacks: Either they rely on detailed statistical models of the driving environment, which are difficult to assemble and too complex to analyze on the fly; or they’re so simple that they can lead to impractically conservative decisions, such as never changing lanes at all. At the International Conference on Robotics and Automation tomorrow, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) will present a new lane-change algorithm that splits the difference.
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↳ ScienceDaily.com

Soft machines: Fast, low-voltage actuator for soft and wearable robotics

In the world of robotics, soft robots are the new kids on the block. The unique capabilities of these automata are to bend, deform, stretch, twist or squeeze in all the ways that conventional rigid robots cannot. Today, it is easy to envision a world in which humans and robots collaborate — in close proximity — in many realms. Emerging soft robots may help to ensure that this can be done safely, and in a way that syncs to human environments or even interfaces with humans themselves.
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↳ MachineLearningMastery.com

A Gentle Introduction to k-fold Cross-Validation

Cross-validation is a statistical method used to estimate the skill of machine learning models. It is commonly used in applied machine learning to compare and select a model for a given predictive modeling problem because it is easy to understand, easy to implement, and results in skill estimates that generally have a lower bias than other methods. In this tutorial, you will discover a gentle introduction to the k-fold cross-validation procedure for estimating the skill of machine learning models.
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↳ Sentient.ai

More Experiments are Better

The digital world runs on testing. Online retail managers revamp the look and feel of their website to encourage more sales. Online travel companies test the CTA buttons and their flight listings to guide their customers through the booking process. Financial services companies optimize their landing pages in order to increase the likelihood that a visitor will fill out their form and start the process of applying for a loan. Whatever the desired outcome–companies are testing each and every element and feature on their websites to optimize for the highest conversions.
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