Explore various roles in AI development workflow from scoping solutions to technical tasks. Discover resources for addressing bias and monitoring fairness in data/models. Discuss AI ethics, Streamlit advancements, GPU acceleration in Windows, and Microsoft's support for open source. Learn about integrating AI into software development, benefits of collaboration, and challenges in AI/ML development. Adoption of AI ethical principles across industries and expressing gratitude to the audience.
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Quick takeaways
AI development involves diverse roles like scoping, experimentation, and technical engineering tasks.
AI professionals can contribute to societal challenges by developing beneficial applications and engaging in AI ethics discussions.
Deep dives
AI Development within Software Development
Viewing AI development as a component of software development offers a broader context for managing the production process. The speaker emphasizes that these activities happen simultaneously, creating a larger interconnected ecosystem.
Impacts of Current World Events on AI Discussions
The podcast addresses recent social and global challenges such as the need for meaningful discussions around Black Lives Matter and racial injustice issues. The impact of COVID-19, economic fallout, and unemployment are highlighted, showcasing how these events are not disconnected from the realm of AI and technology.
Exploring Opportunities in AI Contributions
Encouraging listeners to engage with AI-related issues beyond technical skills, the hosts discuss ways AI professionals can contribute to societal challenges. Opportunities lie in developing beneficial AI applications, contributing to AI ethics discussions, and engaging in open-source projects to address diverse issues.
Adapting AI Workflow to Various Domains
The discussion delves into the flexibility required in AI workflows across different domains and verticals. Highlighting the importance of specialized approaches based on the context, the conversation emphasizes the need to adapt tools, methods, and communities based on the specific requirements of each domain.
This full connected has it all: news, updates on AI/ML tooling, discussions about AI workflow, and learning resources. Chris and Daniel breakdown the various roles to be played in AI development including scoping out a solution, finding AI value, experimentation, and more technical engineering tasks. They also point out some good resources for exploring bias in your data/model and monitoring for fairness.
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