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Hosted by Stuart Hilman · EN · 21 episodes
Established thought leaders with verified media credentials.
Learn AI programming faster than you thought possible! Join us as we break down complex concepts into digestible lessons, explore hands-on projects, and share insider tips from industry experts. Whether you're a coding novice or experienced developer looking to pivot into AI, each episode provides practical strategies to accelerate your learning journey. We'll cover essential frameworks like TensorFlow and PyTorch, navigate the Python ecosystem, and help you avoid the time-wasting pitfalls that slow most learners down. Subscribe now to transform your AI programming skills in record time
Stuart Hilman hosts Building functional AI applications, a technology show with 21 episodes published.
Look ahead to the cutting-edge developments shaping the next generation of AI applications. We'll discuss multimodal AI, few-shot learning, emerging hardware accelerators, edge AI deployment, and how these technologies w
Learn how to build AI applications that work for diverse user populations. We'll cover accessibility considerations, testing with diverse user groups, addressing language barriers, and ensuring your AI application provid
Explore architectural patterns that integrate AI components with conventional software systems. We'll discuss when to use rules-based approaches versus learned models, implementing human-in-the-loop workflows, and design
Compare popular frameworks and tools for building production AI applications. We'll evaluate options like TensorFlow Serving, Pytorch Lightning, Hugging Face Transformers, and MLflow, helping you select the right technol
Tackle the practical aspects of identifying and addressing bias in production AI systems. We'll examine bias detection methodologies, implementing fairness metrics, techniques for bias mitigation, and establishing govern
Design effective APIs that expose AI capabilities to developers and third-party integrations. We'll cover API design patterns specific to AI, handling asynchronous predictions, proper error handling, versioning strategie
Learn comprehensive monitoring approaches for AI systems beyond basic uptime checks. We'll explore detecting data drift, monitoring prediction quality, implementing automated alerts, tracking model degradation, and estab
Walk through the complete deployment lifecycle for AI applications. We'll discuss CI/CD pipelines for machine learning, containerization strategies, environment management, versioning both code and models, and implementi
Master the financial aspects of running AI systems at scale. We'll cover prediction caching, compute optimization, right-sizing infrastructure, implementing auto-scaling policies, and developing monitoring systems that h
Explore privacy-preserving AI techniques like federated learning, differential privacy, and secure multi-party computation. We'll discuss regulatory requirements, implementing privacy by design principles, and balancing
Dive into the security considerations unique to AI applications, from model theft to adversarial attacks. We'll cover securing the model serving infrastructure, preventing data poisoning, implementing proper authenticati
Learn strategies for identifying and managing the edge cases that can break AI systems. We'll discuss techniques for outlier detection, graceful degradation, implementing fallback mechanisms, and systematically improving
Discover how to combine specialized AI models into cohesive applications. We'll examine ensemble techniques, model orchestration patterns, managing dependencies between models, and designing systems where models can effe
Explore practical techniques to balance model accuracy with performance requirements. We'll cover model quantization, knowledge distillation, efficient architecture selection, and when to use approximation techniques to
Compare cloud platforms and services optimized for AI workloads. We'll discuss serverless AI deployment, container orchestration for AI services, cost optimization techniques, and how to design cloud architecture that sc
Learn comprehensive strategies for testing AI applications beyond simple accuracy metrics. We'll explore A/B testing frameworks for AI, monitoring for model drift, implementing canary deployments, and developing robust e
Navigate the ethical dimensions of building AI applications that impact real users. We'll examine responsible AI practices, addressing bias in models, ensuring fairness across user groups, and implementing transparency m
Explore the unique UX challenges in AI applications, from setting appropriate user expectations to handling model uncertainty. We'll discuss techniques for communicating AI limitations, designing intuitive interfaces for
Dive into the critical but often overlooked aspect of AI applications - robust data pipelines. We'll cover data ingestion, cleaning, feature engineering, and how to build pipelines that adapt to changing data patterns. L
In this episode, we explore the challenging journey from a working AI prototype to a fully-scaled product. We'll discuss technical infrastructure requirements, handling increased data volumes, and maintaining model perfo
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Building functional AI applications is hosted by Stuart Hilman. The show is categorised under technology (business) and has published 21 episodes.
Building functional AI applications has published 21 episodes.
Building functional AI applications regularly covers technology, business, careers. It sits in the technology category, with a business focus.
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Episodes of Building functional AI applications average 147 minutes, giving guests a long-form format with plenty of time to expand on their expertise.
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