AI Crash Course for Veterinarians: Part 1 of 4

If you are in VetMed, you've likely heard the buzz around artificial intelligence (AI) and its potential to revolutionize the field. But what exactly is AI, and how can it be applied in veterinary medicine? In this series, I (Gary) will be providing an AI crash course tailored specifically for veterinarians, helping you understand what's currently possible and what's on the horizon.

Understanding the Hype

The short answer to all the hype in AI right now? Transformers. To understand how we got here, let's break down the key concepts:

1. Defining AI: At its core, AI is applied mathematics, implemented through computer science and trained on large amounts of data. It's all about solving problems using math, enabled by computing power and vast datasets.
2. The AI Stack: Picture the modern AI stack as a set of nested layers, each building upon the last.
   1. Artificial Intelligence: Solving problems using symbolic logic or flowcharts.
   2. Machine Learning: Making predictions and classifications based on patterns in training data.
   3. Deep Learning: Using neural architectures to let the computer identify patterns.
   4. Generative AI: AI that can produce open-ended outputs.
   5. Large Language Models: Processing and generating language without guaranteeing understanding.
   6. Transformers: A specific architecture used in large language models
3. Why Now? OpenAI's Bet on Transformers: The current AI boom can be largely attributed to OpenAI's substantial investment in transformer architectures, introduced by Google in 2017. After seven years and millions spent on training, their model proved incredibly powerful, sparking a wave of interest and investment in AI.

The Potential for Veterinary Medicine

So, what does this mean for veterinarians? As AI continues to advance, we can expect to see numerous applications in our field, such as:

• Improved diagnostic tools
• Automated record-keeping and documentation
• Personalized treatment plans
• Predictive models for disease outbreaks

By understanding the foundations of AI, we can better evaluate and implement these tools in our practices, ultimately leading to better patient outcomes and more efficient workflows.

Video Deep Dive

Feel free to watch the original video presentation and leave questions as comments on the video. I'll make sure to answer in subsequent videos.

Stay Tuned

In the next part of this series, we'll dive deeper into the technical aspects of neural networks and transformers, giving you a solid grasp of how these technologies work. Armed with this knowledge, you'll be well-equipped to navigate the rapidly evolving landscape of AI in veterinary medicine.