Machine Learning into Production podcast, interview style
Episodes
24 Feb 2026
The podcast dives into AI development, software engineering, and GPU innovation, focusing on efficient workloads and the trade-offs between quick solutions and scalable systems.
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19 Feb 2026
AI model deployment requires careful planning of infrastructure and scalability to ensure smooth transition from experimental to production stages, considering factors like cost, performance, and control.
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13 Feb 2026
The podcast highlights the importance of context, flexibility, and evolution in workflow tools and data analysis, emphasizing the need for refinement and dynamic interaction with AI agents.
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10 Feb 2026
Software engineers must adopt new approaches to validation and reliability as AI tools become increasingly integrated with traditional engineering, requiring systematic prompt management and careful balancing of AI guidance to prevent over-reliance.
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6 Feb 2026
Researchers are developing a Physical AI platform to create intelligent systems that learn from real-time sensor data to improve applications like machine health monitoring and construction site productivity.
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3 Feb 2026
Experts discuss the challenges of building and maintaining complex AI infrastructure, including power availability, logistics, and component sourcing, and highlight the need for energy-efficient solutions and standardized management tools.
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27 Jan 2026
Regulatory compliance in AI is explored with a focus on the EU's AI Act, emphasizing the need for harmonized standards, observability tools, and cross-functional collaboration to ensure AI systems meet technical, legal, and ethical requirements.
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23 Jan 2026
Hotmart employs AI and machine learning across various business areas, including customer support, content moderation, and sales, to improve efficiency and effectiveness.
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20 Jan 2026
The podcast explores creative repurposing of existing hardware for AI workloads, highlighting initiatives that breathe new life into outdated data centers and miners, and emphasizes the importance of adaptable infrastructure that works with a wide range of hardware.
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16 Jan 2026
MLflow is adapting to support traditional machine learning and emerging agent-based AI systems, tackling challenges in chatbot development such as observability and effective memory management.
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