We will explore what is Intelligence Amplification via brain machine interfaces (BMI), why it matters, and why there may be a future divide between humans who remain unenhanced, and humans who choose to amplify their intelligence by creating a synergetic symbiosis with Artificial Intelligence (AI).

Humans who connect with BMIs will be gifted with enhanced cognitive performance, and increased productivity in the workplace and beyond.

What is Intelligence Amplification?

The concept of Intelligence Amplification was first introduced by William Ross Ashby’s in his groundbreaking book titled Introduction to Cybernetics.

While there are endless articles highlighting the benefits of artificial intelligence (AI), augmented reality and blockchain, there are other emerging technologies that are often neglected by entrepreneurs. These technologies have the potential to completely disrupt the aerospace, health and manufacturing sectors. In this article, will explore five potential breakthrough technologies and how I believe they will converge.

Additive Manufacturing

Additive manufacturing is more commonly known as 3D printing. While the industry was initially hyped with the promise that 3D printers would become prevalent in people’s homes, the real breakthroughs will result from commercial 3D printers.

Entrepreneurs and investors should take note of how artificial intelligence (AI) is disrupting business in every vertical.

As an entrepreneur myself, and the founder of an AI news website, I’ve had a front-row seat to the disruption, and I’d argue that much of it has been achieved by a subfield of AI called machine learning. We define machine learning (ML) as “a method of enabling computers to carry out specific tasks without explicitly coding every line of the algorithms used to accomplish those tasks.”

There are five fields of machine learning that you should be aware of. While some of these may be familiar, others are less commonly known.

The world of AI can be intimidating due to the terminology and different machine learning algorithms that are available. After having read over 50 of the most highly recommended books on machine learning, I have compiled my personal list of must read books.

The books that were chosen are based on the types of ideas that are introduced, and how well different concepts such as deep learning, reinforcement learning, and genetic algorithms are presented. Most importantly the list is based on the books that best pave the path forward for futurists and researchers towards building provably responsible, and explainable AI.

Creating an Artificial General Intelligence (AGI) is the ultimate endpoint for many AI specialists.  An AGI agent could be leveraged to tackle a myriad of the world’s problems. For instance, you could introduce a problem to an AGI agent and the AGI could use deep reinforcement learning combined with its newly introduced emergent consciousness to make real-life decisions.

The difference between an AGI and a regular algorithm is the ability for the AGI to ask itself the important questions. An AGI can formulate the end solution that it wishes to arrive at, simulate hypothetical ways of getting there, and then make an informed decision on which simulated reality best matches the goals that were set.

The White House Office of Science and Technology Policy (OSTP) recently released a whitepaper called “The Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People”. This framework was released one year after OSTP announced the launch of a process to develop “a bill of rights for an AI-powered world.”