Aaron

Over the past few weeks, I have been approached by the Liberals and encouraged to cross the floor. I have firmly rejected their offer.

At this important moment for our country’s future, Canadians with a broad range of experience and perspectives are uniting to build Canada strong. I am honoured to welcome Marilyn Gladu today as the newest member of this government and our Liberal caucus. In a time of global economic uncertainty, Canada’s success will depend on how we build ambition into progress and strengths into sustained advantage. Marilyn brings the practical, results-driven leadership this effort demands. Having spent decades of her career in engineering and international business, she understands what it takes to create good jobs, strengthen supply chains, and ensure Canadian industry can compete in a rapidly changing global economy. She has been elected by the people of Sarnia—Lambton–Bkejwanong in four straight elections since 2015, and repeatedly earned recognition from colleagues across Parliament for her proven willingness to work constructively across party lines. I’m looking forward to working closely with Marilyn to build a stronger and more independent Canadian economy, meeting the challenges of a changing world with lasting opportunities for all.

BREAKING: Tesla has officially released FSD V14.3 I'm downloading it in my Model Y right now. Here's everything that's new: • Improved parking location pin prediction, now shown on a map with a P icon. • Increased decisiveness of parking spot selection and maneuvering. • Rewrote the Al compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed. • Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles. • Mitigated unnecessary lane biasing and minor tailgating behaviors. • Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety. • Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping - driven by training on hard RL examples sourced from the Tesla fleet. • Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios. • Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding. • Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet. • Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements. Upcoming Improvements: • Expand reasoning to all behaviors beyond destination handling. • Add pothole avoidance. • Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.