Autonomous Vehicle Science



Science for self-driving vehicles based on what it means to be human


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Solve your Autonomous Vehicles for a new vision of autonomobiles

In spite of significant effort and achievements, self-driving cars remain a challenge in practice. Limited trials of vehicles running along predetermined, hyper-limited routes abound, and face significant hurdles.

Much innovation and work remains to support a complex environment filled with and built by and planned by humans and communities. Some limitations have to do with a disconnect between technology and stakeholders that can itself be bridged and fed into design

Machine Learning X Doing integrates the human condition into autonomous vehicles and initiatives

What we need is AI based on what it means to be human

Next-level AI

You set the standard for everyone else. By not allowing the box to define you, you’ve become the box for others. They might not admit it, but the industry is depending on you.

As you’ve grown however, it’s naturally a little harder to keep doing what has never been done. Standard algorithmic approaches have a role to play, but these are only taking you so far. The stakes are high. Errors can be costly over time. The world is changing. What if next-level AI could take you further than you ever imagined?

Welcome to your next level. Welcome to the future of your industry

How can innovation evolve in a way that takes self-driving cars to the next level?

Feed your progress with evidence. Get out of the traffic of technological skepticism and blaze a new path

Be you. Sustain and improve your innovation

It is up to us all to make the world a better place, starting with your vehicle autonomy

Introducing the next-generation of AI, designed around the fundamental question of what it means to be human

Together, we will inspire change in the world, by first introducing your organization to its true potential

Kweku Opoku-Agyemang, Ph.D.

Kweku Opoku-Agyemang, Ph.D., is founder and director of Machine Learning X Doing. An economist, he has independently advised several stakeholders in the technology industry; given seminars at the world’s best universities such as Stanford University and presented to government officials from several countries and many others, such as the World Bank.

A former session Chair at the Canadian Economic Association, Kweku believes that his next-generation Machine Learning X Doing approach can help organizations and countries to do better by their people by meeting or exceeding their potential and taking their culture to its real potential. He is based in Toronto, Canada.