How Differences in Artificial Intelligence Models Will Impact the Future of the Biotechnology Industry

This capstone project examined how different artificial intelligence (AI) models, particularly machine learning, deep learning, natural language processing, and generative AI differed in there functionality and how those differences influenced their applications within the biotechnology industry. This capstone project evaluated each model’s capabilities, limitations, and current usages in areas such as drug development, data analysis, and process optimization while identifying associated risks like biases, cybersecurity vulnerabilities, and misinformation. The objectives were to provide a balanced, evidence-based then is able to inform anyone how AI can be effectively and responsibly and integrated into biotechnology to maximize innovation while minimizing potential drawbacks.