Scott Forsyth: Gen AI or Generative Artificial Intelligence – Episode 301

Challenges

  • Integrating generative AI tools into existing workflows.
  • Ensuring the reliability and accuracy of AI-generated content.
  • Addressing ethical concerns and biases in AI models.

Solutions

  • Leveraging advanced AI models for various use cases like chatbots and text-to-speech.
  • Implementing rigorous testing and validation processes.
  • Developing guidelines to mitigate biases and ensure ethical AI use.

Benefits

  • Enhanced productivity with AI-assisted tools.
  • Improved accuracy and consistency in generated content.
  • Greater innovation and efficiency in development processes.

Scott has spent over 25 years in the IT field, working in disciplines such as systems architecture, software development, team growth, and entrepreneurship. He was a Microsoft MVP for 12 years in ASP.NET and IIS. He’s co-authored two books (IIS 7 and IIS 8 Professional), is a Pluralsight author, and has spoken at various conferences, code camps, and user groups. He’s now shifted into the AI space, building AI solutions and supporting others in their AI journey. He’s also co-founding a new startup, so he’s spending much of his time as an Entrepreneur.

Topics of Discussion:
[02:15] Scott’s career path and what steered him into AI.
[05:18] AI development and Scott’s journey learning about generative AI.
[07:15] AI use cases, including chatbots, text-to-speech, and speech-to-text.
[13:14] Flowise AI.
[15:48] RAG, AKA retrieval augmented generation.
[17:32] Code interpreter.
[18:10] How do we know that AI is terrible at math, and what are the other things it’s not good at?
[26:13] Using small language models for natural language processing.
[37:13] Kitchen Co-Pilot app.