What is AI Coaching Actually? (Better than ChatGPT)

What is AI Coaching Actually? (Better than ChatGPT)

Introduction

Hi, my name is Dr. Jacob Goodin, and today I want to discuss artificial intelligence (AI), specifically how we utilize AI in our flagship product, Evolve AI. This app leverages an expert system framework to guide the training process for powerlifting and anyone striving to get stronger.

Understanding Artificial Intelligence

Before diving into expert systems, let’s first define artificial intelligence. The term AI was coined in 1956 and refers to the science and engineering of creating intelligent machines. Nowadays, people often think of AI in terms of robot overlords or iconic characters from popular media. In reality, AI is much more mundane.

There are four distinct levels of AI, ranked from least to most complex:

1. Reactive Machines
2. Limited Memory Machines
3. Theory of Mind Machines
4. Self-Aware Machines

Currently, our technology falls into the first two categories—reactive and limited memory machines.

Limited Memory Machines

A limited memory machine is a computer algorithm with a constrained memory that updates itself with each iteration. A prime example is Tesla’s self-driving cars, which improve continually as more data is collected. Evolve AI operates similarly to these limited memory machines.

Expert Systems

Expert systems belong to the limited memory category and consist of three parts: a database, an inference engine, and a user interface. The aim is to provide domain-specific knowledge by mimicking a human expert’s decision-making abilities.

• Database: Contains every decision a coach might make, including set reps, exercise prescriptions, and intensity adjustments.
• Inference Engine: Utilizes training principles founded in science and cutting-edge coaching practices to make decisions.
• User Interface: Allows users to input real-time biometric data, feedback ratings, sleep data, and more.

Evolving AI with Expert Systems

Evolve AI uses these expert systems to solve complex training problems by reasoning through a comprehensive database, then filtering it through an inference engine that reflects coaching expertise. The user interacts with both components through an app, ensuring a personalized and timely training program.

Why Not Machine Learning?

Unlike machine learning, which trains a neural network on a dataset in a Black Box approach, Evolve AI employs a White Box approach for transparency. This approach allows us to monitor every aspect of the training process, including factors such as sleep quality, nutritional status, and life stressors, ensuring that the inputs and outputs are clear and optimal results are achieved.

Conclusion

In summary, Evolve AI’s expert system comprises three main components: a growing database of coaching decisions, an inference engine based on scientific principles, and a user-friendly mobile app. This system enables users to input their data and goals, allowing the AI to create an optimal training program tailored to individual needs.

Keywords

• Artificial Intelligence
• Expert Systems
• Powerlifting
• Training Process
• Limited Memory Machines
• Database
• Inference Engine
• User Interface
• Personalized Training
• Evolve AI
• Machine Learning
• White Box Approach

FAQ

What is a limited memory machine?

A limited memory machine is a type of AI algorithm that updates itself based on new data it receives. Examples include self-driving cars that improve with increased data collection.

What are the components of an expert system?

An expert system comprises a database, an inference engine, and a user interface. The database includes all possible decisions, the inference engine applies scientific principles to these decisions, and the user interface allows for real-time user input.

Why does Evolve AI prefer expert systems over machine learning?

Evolve AI uses expert systems because they offer transparency in monitoring both the training inputs and outputs. This White Box approach aligns better with sports science principles, ensuring optimal and transparent training results.

How does Evolve AI ensure the training program is personalized?

Evolve AI takes user input such as biometric data, perceived exertion ratings, sleep quality, and motivation levels through the user interface. This data is then processed through the expert system to tailor a personalized training program.

What makes an expert system different from a Black Box approach in machine learning?

An expert system uses a transparent White Box approach, allowing users and developers to understand and monitor all aspects of the training process. In contrast, a Black Box approach in machine learning makes it difficult to trace how specific outputs are generated from inputs.