The study “Attention Is All You Need” is a groundbreaking paper on the enhancement of the large language model (LLM)’s self-attention mechanism.

The study introduces the transformer, a new piece of AI model architecture. This new building block uses an attention mechanism to model input and output dependencies.

I wanted to create a beginner's guide to the architecture for anyone entering this field with little knowledge of the topic.

#Artificial Intelligence (#AI) will be a valuable tool in #healthcare, but it is not yet secure enough for current use. There are way too many risks.

#AI is being merged into healthcare platforms, and providers are using this unregulated tool to aid them with their jobs. This is very resourceful, but not safe, especially since most of the models were not trained for use in healthcare. These instances may seem innocent, but they may be unethical.

My personal goal for ethical AI isn't just to create an environment that we already have, but to use this opportunity to fix humanity's mistakes that currently hinder healthcare.

To establish a usable model that can be trusted in diagnosing, the issue of bias must be addressed. Bias has many facets, but typically, when most people see the word, they associate it with gender, race, or age.

#Artificial Intelligence (AI) is a remarkable tool that can process large amounts of data way faster and more accurately than any human, exceeding all of our analytical capabilities. AI will revolutionize the healthcare industry, but even the most innovative solutions are never without flaws. The biggest obstacle for #AI is ethicality. To function in healthcare, we must hold AI to the same ethical standards to which we hold providers, and in order to remain credible, it must not be biased.

#Artificial intelligence (#AI) is starting to progress into the healthcare industry, we can't stop it, and why should we? It will save us all time, money, and possibly our lives.

Right now, the potential of AI is only hindered by our imagination.  AI could help doctors reach diagnoses in difficult medical cases, perform flawless surgeries, or scan medical journals for treatments. Whatever AI is applied to, it could solve critical issues that have held back the progression of healthcare innovation.

Where is the crack in the current #healthcare system?