Natalie Pistunovich
MLOps and 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.
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