AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711

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Sweat and Resilience: Balancing Chronic Migraine with Fitness Goals 35:02

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The healing power of fitness goes far beyond physical benefits—for today’s guest, it’s a form of self-expression and a celebration of what the body can do. In this episode, host Nora McInerny sits down with fitness personality Ivylis Rivera, who shares her deeply personal journey of navigating life with Chronic Migraine while holding onto her passion for movement. Ivylis opens up about the struggle of staying active while facing the fear of triggering a headache or migraine attack and the resilience it takes to keep pushing forward—a resilience that carried her through the challenging journey of finding a Chronic Migraine treatment plan that worked for her. Join Nora and Ivylis as they explore the concept of “soft living,” a philosophy Ivylis embraces—staying active, listening to your body, and building trust in oneself. Click here for Product Information, including Boxed Warning and Medication Guide, or visit https://abbv.ie/prescribing_info See omnystudio.com/listener for privacy information.…

حدود یک سال پیش 54:47

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Today, we're joined by Arash Behboodi, director of engineering at Qualcomm AI Research to discuss the papers and workshops Qualcomm will be presenting at this year’s NeurIPS conference. We dig into the challenges and opportunities presented by differentiable simulation in wireless systems, the sciences, and beyond. We also explore recent work that ties conformal prediction to information theory, yielding a novel approach to incorporating uncertainty quantification directly into machine learning models. Finally, we review several papers enabling the efficient use of LoRA (Low-Rank Adaptation) on mobile devices (Hollowed Net, ShiRA, FouRA). Arash also previews the demos Qualcomm will be hosting at NeurIPS, including new video editing diffusion and 3D content generation models running on-device, Qualcomm's AI Hub, and more!

The complete show notes for this episode can be found at https://twimlai.com/go/711.

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#Artificial Intelligence #Tech News #Artificialintelligence #Machinelearning #Samcharrington #Technology #Thisweekinmachinelearning #Sam Charrington #Thetwimlaipocast #Twimlaipodcast #Tech #News #China #TWIML #Datascience #Science

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

AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711

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

1,761 subscribers

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The complete show notes for this episode can be found at https://twimlai.com/go/711.

751 قسمت

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

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RAG Risks: Why Retrieval-Augmented LLMs are Not Safer with Sebastian Gehrmann - #732 57:09

۴ روز پیش57:09

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Today, we're joined by Sebastian Gehrmann, head of responsible AI in the Office of the CTO at Bloomberg, to discuss AI safety in retrieval-augmented generation (RAG) systems and generative AI in high-stakes domains like financial services. We explore how RAG, contrary to some expectations, can inadvertently degrade model safety. We cover examples of unsafe outputs that can emerge from these systems, different approaches to evaluating these safety risks, and the potential reasons behind this counterintuitive behavior. Shifting to the application of generative AI in financial services, Sebastian outlines a domain-specific safety taxonomy designed for the industry's unique needs. We also explore the critical role of governance and regulatory frameworks in addressing these concerns, the role of prompt engineering in bolstering safety, Bloomberg’s multi-layered mitigation strategies, and vital areas for further work in improving AI safety within specialized domains. The complete show notes for this episode can be found at https://twimlai.com/go/732 .…

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

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

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Today, we're joined by Josh Tobin, member of technical staff at OpenAI, to discuss the company’s approach to building AI agents. We cover OpenAI's three agentic offerings—Deep Research for comprehensive web research, Operator for website navigation, and Codex CLI for local code execution. We explore OpenAI’s shift from simple LLM workflows to reasoning models specifically trained for multi-step tasks through reinforcement learning, and how that enables agents to more easily recover from failures while executing complex processes. Josh shares insights on the practical applications of these agents, including some unexpected use cases. We also discuss the future of human-AI collaboration in software development, such as with "vibe coding," the integration of tools through the Model Control Protocol (MCP), and the significance of context management in AI-enabled IDEs. Additionally, we highlight the challenges of ensuring trust and safety as AI agents become more powerful and autonomous. The complete show notes for this episode can be found at https://twimlai.com/go/730 .…

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

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25 روز پیش56:18

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Today, we're joined by Nidhi Rastogi, assistant professor at Rochester Institute of Technology to discuss Cyber Threat Intelligence (CTI), focusing on her recent project CTIBench—a benchmark for evaluating LLMs on real-world CTI tasks. Nidhi explains the evolution of AI in cybersecurity, from rule-based systems to LLMs that accelerate analysis by providing critical context for threat detection and defense. We dig into the advantages and challenges of using LLMs in CTI, how techniques like Retrieval-Augmented Generation (RAG) are essential for keeping LLMs up-to-date with emerging threats, and how CTIBench measures LLMs’ ability to perform a set of real-world tasks of the cybersecurity analyst. We unpack the process of building the benchmark, the tasks it covers, and key findings from benchmarking various LLMs. Finally, Nidhi shares the importance of benchmarks in exposing model limitations and blind spots, the challenges of large-scale benchmarking, and the future directions of her AI4Sec Research Lab, including developing reliable mitigation techniques, monitoring "concept drift" in threat detection models, improving explainability in cybersecurity, and more. The complete show notes for this episode can be found at https://twimlai.com/go/729 .…

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

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

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

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

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

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

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

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14 weeks پیش52:30

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

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AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711