Microsoft and MIT have partnered on a project to fix so-called virtual'blind spots' which lead driverless cars to make errors. Roads, especially while shared with human drivers, are unpredictable places. Training a self-driving car for every possible situation is a monumental task. The AI developed by Microsoft and MIT compares the action taken by humans in a given scenario to what the driverless car's own AI would do. Where the human decision is more optimal, the vehicle's behaviour is updated for similar future occurrences.

This research spans academia, militaries (though it can be difficult to suss out the actual breakthroughs from government propaganda), and private enterprise. Perhaps the most well known privately-owned robotics developer is Boston Dynamics, makers of the Atlas. You may remember this bipedal robot from September when it showed off its uncanny parkour abilities, which the robot can pull off 80 percent of the time. The Atlas is able to move so fluidly thanks to a novel optimization algorithm that breaks down complex movements into smaller reference motions for its arms, torso, and legs. However, while Boston Dynamics' Big Dog was developed as a quadrupedal cargo carrier for military operations, the Atlas is strictly for use as an emergency first responder.

OPINION: Last week about 60 rally teams, close to 500 volunteers and a small organising group staged the Targa Rally of New Zealand. Billed as the ultimate road race, this year's Targa was the 25th running of the iconic event which sees close to 1200 km of public road closed and turned into race-track. Last May my Targa team were doing great until stage three of the second day when some Gentle Annie shingle shredded the Kevlar cambelt on our Type R, rapidly followed by 16 valves and four pistons. So this year we were back with a new top end and a new state of tune. And the good news is that it worked.

OPINION: Last week about 60 rally teams, close to 500 volunteers and a small organising group staged the Targa Rally of New Zealand. Billed as the ultimate road race, this year's Targa was the 25th running of the iconic event which sees close to 1200 km of public road closed and turned into race-track. Last May my Targa team were doing great until stage three of the second day when some Gentle Annie shingle shredded the Kevlar cambelt on our Type R, rapidly followed by 16 valves and four pistons. So this year we were back with a new top end and a new state of tune. And the good news is that it worked.

After decades of study and significant data collection of time-varying swash on sandy beaches, there is no single deterministic prediction scheme for wave runup that eliminates prediction error – even bespoke, locally tuned predictors present scatter when compared to observations. Scatter in runup prediction is meaningful and can be used to create probabilistic predictions of runup for a given wave climate and beach slope. This contribution demonstrates this using a data-driven Gaussian process predictor; a probabilistic machine-learning technique. The runup predictor is developed using 1 year of hourly wave runup data (8328 observations) collected by a fixed lidar at Narrabeen Beach, Sydney, Australia. The Gaussian process predictor accurately predicts hourly wave runup elevation when tested on unseen data with a root-mean-squared error of 0.18 m and bias of 0.02 m.

Google has launched the second iteration of its no-code Teachable Machine so that inexperienced users can take their bespoke machine learning (ML) models and apply them to projects such as classroom activities. Teachable Machine 2.0 carries over the features from the original, allowing users to record images and video from a webcam and use them to train ML models for tasks like pattern recognition. Now, these same models can be taken and exported to websites, apps and physical machines. Open source curriculums are making use of the tool to give children their first taste of ML, without the intimidating aspect of learning to code. One such example is a program run out of MIT's Media Lab by education researcher Blakeley H. Payne for 6 to 10 year olds.

Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values. Our goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the centre, changing the course of the ongoing AI revolution. By providing intelligent artificial collaborators that interact with people we strengthen our human capacity for learning, reasoning, decision making and problem solving. This interaction has the potential to amplify both human and machine intelligence by combining their complementary strengths.

TMX Group (TSX:X) released news on Friday that its revenue for the third quarter of 2019 hit a new record due to higher derivatives trading and clearing. The company's energy trading platform Trayport, in particular, brought in most of the additional revenue. Still, the stock was down this morning by 5.39% to $107.53 from yesterday's close of $113.66. The fall in price represents a significant buying opportunity for Canadian savers. Your Tax-Free Savings Account and Registered Retirement Savings Plan will thank you 20 years from now if you invest in the TMX Group today.

The AI Organization's AI bio-metric scans of the human brain have decoded a bio-logical structure in the pineal gland that interconnects throughout the neural network of the human brain. We have termed the entire interconnection as the Human Bio-Digital Network, as outlined in the book ARTIFICIAL INTELLIGENCE Dangers to Humanity. Google researchers, some CIA operatives and Air Force prototype fighter pilots have used wearable devices that interconnects with the pineal gland in order to control IoT's, networks or an airplane with their mere thought alone. Historically it was deemed as a process of connecting with brain waves on wearable devices, yet the Pineal Gland is a very key component to this process. For decades scientists have been baffled as to the reason why the Pineal Gland carries components similar to an eye, yet no real physical eye exists in the forehead. Some scientist claim before humans evolved to modern humans, we may have had one single eye.

Shaun Patel has such a tranquil voice that it's easy to see how he convinces patients to let him experiment in the depth of their brains. On the phone, in his office at Massachusetts General Hospital (he is also on faculty at Harvard Medical School), the neuroscientist spoke about gray matter almost as if he were guiding me in meditation. Or perhaps that was just the heady effect of him detailing a paper he had just published in Brain, showing how, using implants on his patients, he could enhance learning by stimulating the caudate nucleus, which lies near the center of the brain.1 You have to time the electric pulse just right, he told me, based on the activity of certain neurons firing during an active learning phase of a game. A perfectly timed pulse could speed up how quickly his patients made the right associations. Using similar methods, he said he has induced people to make more financially conservative bets.