MLOps and AI Driven Development

What if an AI could write your unit tests and explain complex code? Discover the new era of AI-driven development.

#1about 5 minutes

A brief history of AI concepts and winters

The history of artificial intelligence is traced from its philosophical origins through periods of intense funding and subsequent "AI winters."

#2about 3 minutes

The evolution of large language models like GPT

Key milestones in AI model development are reviewed, including the founding of DeepMind and OpenAI and the progression of the GPT series.

#3about 5 minutes

The exponential growth of AI model parameters

Recent AI models show exponential growth in parameter count, with models like GPT-4 approaching the scale of the human brain's synapses.

#4about 10 minutes

Demonstrating OpenAI Codex for practical developer tasks

OpenAI's Codex engine is demonstrated to perform tasks like generating unit tests, explaining code, creating complex bash commands, and building a website from comments.

#5about 6 minutes

Why Go is a great choice for AI-generated code

The Go programming language is well-suited for AI-driven development and infrastructure due to its simplicity, concurrency, and ability to avoid the "uncanny valley" of machine-generated code.

#6about 4 minutes

How AI and no-code will change software development

AI-driven development and no-code platforms will automate repetitive tasks and democratize creation, allowing developers to focus on more complex problems.

#7about 2 minutes

The rise of MLOps and AI security considerations

MLOps practices are essential for deploying and maintaining production AI systems, as most of the work involves infrastructure, monitoring, and data management rather than the model itself.

#8about 2 minutes

Actionable steps for developers to get started with AI

Developers can embrace AI by applying for access to engines like Codex, practicing MLOps, and integrating automation and no-code tools into their workflows.

#9about 10 minutes

Q&A on Go, MLOps, and AI-generated code security

Questions from the audience are answered regarding Go's memory management, the security of AI-generated code, and the importance of data governance in MLOps.