The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books
May 3, 2019 • 59min
Fighting Fake News and Deep Fakes with Machine Learning w/ Delip Rao - TWiML Talk #260
Delip Rao, Vice President of Research at the AI Foundation and co-author of Natural Language Processing with PyTorch, dives into the complex world of fake news and deep fakes. He discusses innovative strategies for detecting artificial content across various media, including text and audio. Rao highlights the role of GANs in both creating and combating misinformation. He also shares insights from his journey in AI, emphasizing the collaboration needed among researchers and journalists to tackle these pressing challenges.
May 1, 2019 • 38min
Maintaining Human Control of Artificial Intelligence with Joanna Bryson - TWiML Talk #259
Joanna Bryson, a Reader at the University of Bath, dives into the fascinating world of AI ethics and the interplay between natural and artificial intelligence. She discusses the crucial need for human oversight in AI development, unpacking ethical implications and misconceptions. Bryson emphasizes empowering AI engineers to engage with societal impacts and the importance of governance in AI accountability. Her insights advocate for a sustainable approach to technology, reminding us that AI is ultimately a tool shaped by our moral responsibilities.
Apr 29, 2019 • 45min
Intelligent Infrastructure Management with Pankaj Goyal & Rochna Dhand - TWiML Talk #258
Pankaj Goyal, Vice President for AI and HPC Product Management at HPE, and Rochna Dhand, Director of Product Management for HPE InfoSight, dive into the transformative power of AI in enterprise IT. They explore HPE's vision for AI, emphasizing real-world deployment through InfoSight’s self-management capabilities. The conversation touches on the importance of sensors in storage devices and how AI and IoT fuel operational efficiency. They also address the shift to service-oriented IT models and the critical role of robust data management in successful AI adoption.
Apr 26, 2019 • 52min
Organizing for Successful Data Science at Stitch Fix with Eric Colson - TWiML Talk #257
Eric Colson, Chief Algorithms Officer at Stitch Fix, shares insights from his journey in data science, emphasizing the need for a robust organizational framework. He reveals three key principles for structuring data science teams that enhance decision-making. The conversation dives into the role of data science in recommendation systems, inventory management, and demand forecasting, showcasing how over 800 algorithms optimize operations. Colson also discusses the importance of collaboration and adaptability in developing innovative solutions.
Apr 24, 2019 • 49min
End-to-End Data Science to Drive Business Decisions at LinkedIn with Burcu Baran - TWiML Talk #256
Burcu Baran, a Senior Data Scientist at LinkedIn, shares her insights on using data science to influence business decisions. She discusses the end-to-end data science process, covering essential aspects like problem formulation, collaborative strategies, and model performance monitoring. Burcu highlights the critical role of A/B testing and feature monitoring in maintaining model effectiveness. She also emphasizes the transition from theoretical knowledge to practical applications in data science, and the importance of simplifying processes for enhanced team efficiency.
Apr 22, 2019 • 44min
Learning with Limited Labeled Data with Shioulin Sam - TWiML Talk #255
In this conversation, Shioulin Sam, a Research Engineer at Cloudera Fast Forward Labs, sheds light on the challenges of machine learning with limited labeled data. She discusses active learning as a powerful approach to enhance model accuracy while reducing costly manual labeling. The discussion delves into measuring uncertainty in deep neural networks and effective strategies for implementing active learning across enterprises. Shioulin also highlights the significance of integrating labeled data into models to drive optimal performance in real-world applications.
Apr 19, 2019 • 38min
cuDF, cuML & RAPIDS: GPU Accelerated Data Science with Paul Mahler - TWiML Talk #254
Join Paul Mahler, a senior data scientist at NVIDIA, discussing the RAPIDS open-source project designed to enhance GPU acceleration in data science. He shares his journey from philosophy to machine learning, highlighting tools like cuDF and cuML that boost data processing efficiency. Discover how GPUs revolutionize algorithms like ridge regression with impressive speed and explore innovations in natural language processing and graph algorithms. Paul also emphasizes the importance of community involvement in shaping the future of these pivotal technologies.
Apr 18, 2019 • 39min
Edge AI for Smart Manufacturing with Trista Chen - TWiML Talk #253
Trista Chen, Chief Scientist of Machine Learning at Inventec, brings her extensive experience in AI and smart manufacturing to the discussion. She dives into the challenges and innovations within Industry 4.0, particularly focusing on defect detection and operational optimization. Trista explains the advantages of edge AI over cloud computing and discusses the complexities of ROI in AI projects. Her insights on integrating digital and physical systems highlight the transformative potential of automation in enhancing efficiency and production processes.
Apr 16, 2019 • 42min
Machine Learning for Security and Security for Machine Learning with Nicole Nichols - TWiML Talk #252
Nicole Nichols is a senior research scientist at Pacific Northwest National Lab, specializing in the intersection of machine learning and security. In this discussion, she shares insights from her presentation on using machine learning for cybersecurity, including detecting insider threats through advanced language models. The conversation also dives into software fuzz testing enhanced by deep learning, issues with algorithm efficiency, and the vulnerabilities in object recognition systems, highlighting the critical balance between detection accuracy and human analysis.
Apr 15, 2019 • 32min
Domain Adaptation and Generative Models for Single Cell Genomics with Gerald Quon - TWiML Talk #251
Gerald Quon, an assistant professor at UC Davis, specializes in leveraging deep learning for genomics and single-cell data analysis. He shares his insights on how deep domain adaptation and generative models are revolutionizing disease identification and treatment. Discover the novel methodologies he's developing to analyze complex diseases like schizophrenia and cancer. Quon also discusses the challenges of integrating multimodal data to enhance genomic analysis and the importance of user-friendly tools for biologists in this intricate field.
