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
92 snips
Feb 18, 2025 • 53min
π0: A Foundation Model for Robotics with Sergey Levine - #719
In this discussion, Sergey Levine, an associate professor at UC Berkeley and co-founder of Physical Intelligence, dives into π0, a groundbreaking general-purpose robotic foundation model. He explains its innovative architecture that combines vision-language models with a novel action expert. The conversation touches on the critical balance of training data, the significance of open-sourcing, and the impressive capabilities of robots like folding laundry effectively. Levine also highlights the exciting future of affordable robotics and the potential for diverse applications.
310 snips
Feb 10, 2025 • 1h 45min
AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718
Victor Dibia, a Principal Research Software Engineer at Microsoft Research, joins to discuss the future of AI agents and multi-agent systems. He highlights how these systems surpass traditional software with their reasoning and adaptability. The conversation dives into the rise of agentic foundation models, evaluating their performance, and the growing enterprise applications. Victor also shares insights on implementing successful AI architectures, the impact on software engineering, and the importance of human-AI collaboration in navigating these advancements.
24 snips
Feb 4, 2025 • 1h 17min
Speculative Decoding and Efficient LLM Inference with Chris Lott - #717
In this discussion, Chris Lott, Senior Director of Engineering at Qualcomm AI Research, dives into the complexities of accelerating large language model inference. He details the challenges of encoding and decoding, alongside hardware constraints like memory bandwidth and performance metrics. Lott shares innovative techniques for boosting efficiency, such as KV compression and speculative decoding. He also envisions the future of AI on edge devices, emphasizing the importance of small language models and integrated orchestrators for seamless user experiences.
71 snips
Jan 28, 2025 • 52min
Ensuring Privacy for Any LLM with Patricia Thaine - #716
Patricia Thaine, co-founder and CEO of Private AI, specializes in privacy-preserving AI techniques. She dives into the critical issues of data minimization, the risks of personal data leakage from large language models (LLMs), and the challenges of redacting sensitive information across different formats. Patricia highlights the limitations of data anonymization, the balance between real and synthetic data for model training, and the evolving landscape of AI regulations like GDPR. She also discusses the ethical considerations surrounding bias in AI and the future of privacy in technology.
152 snips
Jan 21, 2025 • 58min
AI Engineering Pitfalls with Chip Huyen - #715
In this insightful discussion, Chip Huyen, an independent AI researcher and the author of "AI Engineering," dives into the intricacies of AI engineering versus traditional machine learning. She highlights common pitfalls in AI systems and the critical nature of effective planning. The conversation also touches on AI agents, their limitations, and the significance of rigorous evaluation processes. Additionally, Chip explores the growing trend of open-source models and the exciting potential of synthetic data, along with her predictions for AI advancements by 2025.
162 snips
Jan 13, 2025 • 58min
Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714
Abhijit Bose, Head of Enterprise AI and ML platforms at Capital One, shared insights into the evolution of their generative AI platform. He discussed the transition to a platform-centric approach in finance and the integration challenges faced by MLOps. Bose delved into optimizing Llama models for improved customer service and the role of Kubernetes in enhancing machine learning workflows. He also highlighted the significance of cloud architecture in AI experimentation and the new skill sets required for thriving in the generative AI landscape.
159 snips
Dec 16, 2024 • 1h 9min
Why Agents Are Stupid & What We Can Do About It with Dan Jeffries - #713
In this discussion, Dan Jeffries, Founder and CEO of Kentauros AI, sheds light on the complexities of developing intelligent agents. He shares his innovative 'big brain, little brain, tool brain' strategy for tackling AI real-world challenges and explores the trade-offs between general-purpose and task-specific models. Dan emphasizes the significance of open source in advancing AI technologies, the role of human involvement in creating robust agents, and the promising yet challenging future of intelligent agents.
145 snips
Dec 9, 2024 • 57min
Automated Reasoning to Prevent LLM Hallucination with Byron Cook - #712
Byron Cook, VP and distinguished scientist at AWS's Automated Reasoning Group, dives into automated reasoning techniques designed to mitigate hallucinations in LLMs. He discusses the newly announced Automated Reasoning Checks and their mathematical foundations for safeguarding accuracy in generated text. Byron highlights breakthroughs in NP-complete problem-solving, integration with reinforcement learning, and unique applications in security and cryptography. He also shares insights on the future co-evolution of automated reasoning and generative AI, emphasizing collaboration and innovation.
21 snips
Dec 3, 2024 • 55min
AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711
Arash Behboodi, Director of Engineering at Qualcomm AI Research, discusses what's on the agenda for this year's NeurIPS conference. He highlights the challenges of differentiable simulation, particularly in wireless systems, and dives into how uncertainty quantification can enhance machine learning models through conformal prediction and entropy. Behboodi also previews innovative demos like on-device video editing and 3D content generation, showcasing Qualcomm's commitment to making cutting-edge AI accessible.
22 snips
Nov 19, 2024 • 54min
AI for Network Management with Shirley Wu - #710
Shirley Wu, Senior Director of Software Engineering at Juniper Networks, leads the discussion on the transformative power of AI and ML in network management. She shares insights on diagnosing cable issues and proactive coverage monitoring, highlighting the benefits of integrating data science. The conversation covers the evolution of roles for network administrators and the innovative Marvis chatbot, which enhances user engagement. Shirley also discusses future directions like proactive testing and the application of smaller ML models to improve efficiency and cost management.
