The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Sam Charrington
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9 snips
Jul 1, 2024 • 57min

How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

Join Sarah Bird, Chief Product Officer of Responsible AI at Microsoft, as she dives into the essential realms of generative AI testing and safety. Explore the challenges of AI hallucinations and the importance of balancing fairness with security. Hear insights from Microsoft's past failures like Tay and Bing Chat, stressing the need for adaptive testing and human oversight. Sarah also discusses innovative methods like automated safety testing and red teaming, emphasizing a robust governance framework for evolving AI technologies.
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9 snips
Jun 25, 2024 • 46min

Long Context Language Models and their Biological Applications with Eric Nguyen - #690

Eric Nguyen, a PhD student at Stanford, dives deep into his research on long context foundation models, specifically Hyena and its applications in biology. He explains the limitations of traditional transformers in processing lengthy sequences and how convolutional models provide innovative solutions. Nguyen introduces Hyena DNA, designed for long-range DNA dependencies, and discusses Evo, a hybrid model with massive parameters for DNA generation. The podcast touches on exciting applications in CRISPR gene editing and the implications of using AI in biological research.
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Jun 18, 2024 • 48min

Accelerating Sustainability with AI with Andres Ravinet - #689

In this engaging discussion, Andres Ravinet, Sustainability Global Black Belt at Microsoft, shares his insights on harnessing AI for sustainability challenges. He highlights innovative AI applications, like early warning systems for extreme weather and methods to reduce food waste in supply chains. Ravinet also addresses the complexities of ESG compliance reporting and the driving forces behind corporate sustainability efforts. Additionally, he explores how generative AI can further support these initiatives, showcasing a commitment to a greener future.
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Jun 10, 2024 • 1h 11min

Gen AI at the Edge: Qualcomm AI Research at CVPR 2024 with Fatih Porikli - #688

Fatih Porikli, Senior Director of Technology at Qualcomm AI Research, dives into groundbreaking advancements in generative AI and computer vision. He discusses efficient diffusion models for text-to-image generation and real-time 360° image relighting. The conversation also highlights innovative applications like a video-language model for personalized fitness coaching and a Math Search dataset for visual reasoning. Porikli touches on practical demos at CVPR, showcasing multi-modal models and enhancing AI's capabilities for mobile and edge devices.
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11 snips
Jun 3, 2024 • 48min

Energy Star Ratings for AI Models with Sasha Luccioni - #687

Sasha Luccioni, AI and Climate lead at Hugging Face, dives into the environmental impact of AI models. She discusses her groundbreaking research on energy consumption, revealing stark contrasts between generative and task-specific models. The conversation highlights the importance of a standardized Energy Star rating system for AI models, aiming to guide users towards energy-efficient choices. Luccioni also tackles challenges in evaluating model performance and the need for transparency and ethical standards in AI research to promote sustainable practices.
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122 snips
May 27, 2024 • 56min

Language Understanding and LLMs with Christopher Manning - #686

Christopher Manning, a leading figure in machine learning and NLP from Stanford University, dives into the fascinating world of language models. He discusses the balance between linguistics and machine learning, emphasizing how LLMs learn human language structures. The talk covers the evolution and impact of word embeddings and attention mechanisms, along with the reasoning capabilities of these models. Manning also shares insights on emerging architectures and the future of AI research, making for an enlightening conversation on language understanding.
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76 snips
May 20, 2024 • 43min

Chronos: Learning the Language of Time Series with Abdul Fatir Ansari - #685

In this discussion, machine learning scientist Abdul Fatir Ansari from AWS AI Labs dives into his groundbreaking work, Chronos, which applies language models to time series forecasting. He reveals the competitive edge Chronos has over traditional statistical methods and its surprising success in zero-shot forecasting. The conversation also touches on practical challenges like data augmentation and evaluation setups, as well as ongoing efforts to enhance synthetic data quality. Ansari sheds light on the promising future for integrating Chronos into real-world applications.
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May 13, 2024 • 55min

Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

In this discussion, Joel Hestness, a principal research scientist and lead of the core machine learning team at Cerebras, dives into the groundbreaking Wafer Scale Engine 3. He explains how this custom silicon surpasses traditional AI hardware, focusing on its unique architecture and memory capabilities. Joel also covers advancements in large language model training, innovative optimization techniques, and the integration of open-source frameworks like PyTorch. Additionally, he shares exciting research on weight-sparse training and novel optimizers that leverage higher-order statistics.
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24 snips
May 7, 2024 • 50min

AI for Power & Energy with Laurent Boinot - #683

Laurent Boinot, Power and Utilities Lead for the Americas at Microsoft, dives into the fascinating intersection of AI and energy infrastructure. He discusses the challenges of North America's power systems and how AI is enhancing demand forecasting and grid optimization. Highlights include AI's role in securing utility systems and improving customer interactions. Laurent also explores the future of nuclear power and the pivotal role of electric vehicles in American energy management. It's a glimpse into a smarter, more efficient energy future!
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13 snips
Apr 29, 2024 • 42min

Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682

Aza Jalalvand, a research scholar at Princeton University, dives into the fascinating realm of using deep reinforcement learning to stabilize plasma in nuclear fusion reactors. He discusses the development of a model to combat the tearing mode instability while collecting complex data from fusion experiments. Aza highlights the critical role of machine learning in enhancing plasma understanding, the challenges of real-time data management, and the promising future of AI in clean energy production. Tune in for insights on the electrifying intersection of AI and fusion technology!

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