Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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المحتوى المقدم من TWIML and Sam Charrington. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة TWIML and Sam Charrington أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
مشابه لـThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
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The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
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This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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Material is a weekly discussion about the Google and Android universe. Your intrepid hosts try to answer the question, “What holds up the digital world?” The answer, so far, is that it’s Google all the way down. Hosted by Andy Ihnatko and Florence Ion.
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Show notes are at https://stevelitchfield.com/sshow/chat.html
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The 21st Century began with the rise of the Internet and social media. The next decade will mark the rise of the Intelligent Machines. AI will inhabit all our devices from cars and appliances to smart phones and robots. The Intelligent Machines podcast explores the most exciting revolution humanity has ever seen, filled with promise and peril. More than ever we need to understand what these new devices will bring to our lives and how to make best use of them as the 21st century unfolds. On t ...
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Hanselminutes is Fresh Air for Developers. A weekly commute-time podcast that promotes fresh technology and fresh voices. Talk and Tech for Developers, Life-long Learners, and Technologists.
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Why do only 10% of companies succeed with AI? In this series by MIT SMR and BCG, we talk to the leaders who've achieved big wins with AI in their companies and learn how they did it. Hear what gets experts from companies like NASA, Github, and others excited to do their jobs every day and what they consider the keys to their success.
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Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
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All About Change
1 Chris Nowinski - Protecting Athletes from Head Injuries & Preventing CTE 27:28
27:28 
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احبChris Nowinski is a former football player at Harvard University and professional wrestler with WWE, World Wrestling Entertainment. After enduring a career-ending head injury, Chris has dedicated his professional life to serving patients and families affected by brain trauma, particularly Chronic traumatic encephalopathy, or CTE, a progressive neurodegenerative disease that develops after repeated head injuries. Jay and Chris discuss the state of head injuries in American athletics, the difference between advocating for head safety at youth and professional levels, Chris’ newest research, and much more. Episode Chapters (00:00) Intro (00:50) changes in the culture around concussions in the past two decades (02:39) padded helmet technology (03:55) concussion reporting in the NFL (10:35) Chris’ career path and concussion history (14:52) connecting with activists who haven’t themselves suffered a traumatic brain injury (17:42) SHAAKE - a new sign to identify concussions (20:53) Unions can help players advocate for safety policies (23:10) final thoughts and goodbye For video episodes, watch on www.youtube.com/@therudermanfamilyfoundation Stay in touch: X: @JayRuderman | @RudermanFdn LinkedIn: Jay Ruderman | Ruderman Family Foundation Instagram: All About Change Podcast | Ruderman Family Foundation To learn more about the podcast, visit https://allaboutchangepodcast.com/…
AI Engineering Pitfalls with Chip Huyen - #715
Manage episode 462354343 series 2355587
المحتوى المقدم من TWIML and Sam Charrington. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة TWIML and Sam Charrington أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Today, we're joined by Chip Huyen, independent researcher and writer to discuss her new book, “AI Engineering.” We dig into the definition of AI engineering, its key differences from traditional machine learning engineering, the common pitfalls encountered in engineering AI systems, and strategies to overcome them. We also explore how Chip defines AI agents, their current limitations and capabilities, and the critical role of effective planning and tool utilization in these systems. Additionally, Chip shares insights on the importance of evaluation in AI systems, highlighting the need for systematic processes, human oversight, and rigorous metrics and benchmarks. Finally, we touch on the impact of open-source models, the potential of synthetic data, and Chip’s predictions for the year ahead.
The complete show notes for this episode can be found at https://twimlai.com/go/715.
740 حلقات
AI Engineering Pitfalls with Chip Huyen - #715
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
مشاركةManage episode 462354343 series 2355587
المحتوى المقدم من TWIML and Sam Charrington. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة TWIML and Sam Charrington أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Today, we're joined by Chip Huyen, independent researcher and writer to discuss her new book, “AI Engineering.” We dig into the definition of AI engineering, its key differences from traditional machine learning engineering, the common pitfalls encountered in engineering AI systems, and strategies to overcome them. We also explore how Chip defines AI agents, their current limitations and capabilities, and the critical role of effective planning and tool utilization in these systems. Additionally, Chip shares insights on the importance of evaluation in AI systems, highlighting the need for systematic processes, human oversight, and rigorous metrics and benchmarks. Finally, we touch on the impact of open-source models, the potential of synthetic data, and Chip’s predictions for the year ahead.
The complete show notes for this episode can be found at https://twimlai.com/go/715.
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Inside s1: An o1-Style Reasoning Model That Cost Under $50 to Train with Niklas Muennighoff - #721 49:29
49:29 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب49:29
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Niklas Muennighoff, a PhD student at Stanford University, to discuss his paper, “S1: Simple Test-Time Scaling.” We explore the motivations behind S1, as well as how it compares to OpenAI's O1 and DeepSeek's R1 models. We dig into the different approaches to test-time scaling, including parallel and sequential scaling, as well as S1’s data curation process, its training recipe, and its use of model distillation from Google Gemini and DeepSeek R1. We explore the novel "budget forcing" technique developed in the paper, allowing it to think longer for harder problems and optimize test-time compute for better performance. Additionally, we cover the evaluation benchmarks used, the comparison between supervised fine-tuning and reinforcement learning, and similar projects like the Hugging Face Open R1 project. Finally, we discuss the open-sourcing of S1 and its future directions. The complete show notes for this episode can be found at https://twimlai.com/go/721 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720 1:07:05
1:07:05 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:07:05
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Ron Diamant, chief architect for Trainium at Amazon Web Services, to discuss hardware acceleration for generative AI and the design and role of the recently released Trainium2 chip. We explore the architectural differences between Trainium and GPUs, highlighting its systolic array-based compute design, and how it balances performance across key dimensions like compute, memory bandwidth, memory capacity, and network bandwidth. We also discuss the Trainium tooling ecosystem including the Neuron SDK, Neuron Compiler, and Neuron Kernel Interface (NKI). We also dig into the various ways Trainum2 is offered, including Trn2 instances, UltraServers, and UltraClusters, and access through managed services like AWS Bedrock. Finally, we cover sparsity optimizations, customer adoption, performance benchmarks, support for Mixture of Experts (MoE) models, and what’s next for Trainium. The complete show notes for this episode can be found at https://twimlai.com/go/720 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 π0: A Foundation Model for Robotics with Sergey Levine - #719 52:30
52:30 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب52:30
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Sergey Levine, associate professor at UC Berkeley and co-founder of Physical Intelligence, to discuss π0 (pi-zero), a general-purpose robotic foundation model. We dig into the model architecture, which pairs a vision language model (VLM) with a diffusion-based action expert, and the model training "recipe," emphasizing the roles of pre-training and post-training with a diverse mixture of real-world data to ensure robust and intelligent robot learning. We review the data collection approach, which uses human operators and teleoperation rigs, the potential of synthetic data and reinforcement learning in enhancing robotic capabilities, and much more. We also introduce the team’s new FAST tokenizer, which opens the door to a fully Transformer-based model and significant improvements in learning and generalization. Finally, we cover the open-sourcing of π0 and future directions for their research. The complete show notes for this episode can be found at https://twimlai.com/go/719 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 AI Trends 2025: AI Agents and Multi-Agent Systems with Victor Dibia - #718 1:44:59
1:44:59 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:44:59
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday we’re joined by Victor Dibia, principal research software engineer at Microsoft Research, to explore the key trends and advancements in AI agents and multi-agent systems shaping 2025 and beyond. In this episode, we discuss the unique abilities that set AI agents apart from traditional software systems–reasoning, acting, communicating, and adapting. We also examine the rise of agentic foundation models, the emergence of interface agents like Claude with Computer Use and OpenAI Operator, the shift from simple task chains to complex workflows, and the growing range of enterprise use cases. Victor shares insights into emerging design patterns for autonomous multi-agent systems, including graph and message-driven architectures, the advantages of the “actor model” pattern as implemented in Microsoft’s AutoGen, and guidance on how users should approach the ”build vs. buy” decision when working with AI agent frameworks. We also address the challenges of evaluating end-to-end agent performance, the complexities of benchmarking agentic systems, and the implications of our reliance on LLMs as judges. Finally, we look ahead to the future of AI agents in 2025 and beyond, discuss emerging HCI challenges, their potential for impact on the workforce, and how they are poised to reshape fields like software engineering. The complete show notes for this episode can be found at https://twimlai.com/go/718 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Speculative Decoding and Efficient LLM Inference with Chris Lott - #717 1:16:30
1:16:30 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:16:30
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Chris Lott, senior director of engineering at Qualcomm AI Research to discuss accelerating large language model inference. We explore the challenges presented by the LLM encoding and decoding (aka generation) and how these interact with various hardware constraints such as FLOPS, memory footprint and memory bandwidth to limit key inference metrics such as time-to-first-token, tokens per second, and tokens per joule. We then dig into a variety of techniques that can be used to accelerate inference such as KV compression, quantization, pruning, speculative decoding, and leveraging small language models (SLMs). We also discuss future directions for enabling on-device agentic experiences such as parallel generation and software tools like Qualcomm AI Orchestrator. The complete show notes for this episode can be found at https://twimlai.com/go/717 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Ensuring Privacy for Any LLM with Patricia Thaine - #716 51:33
51:33 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب51:33
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Patricia Thaine, co-founder and CEO of Private AI to discuss techniques for ensuring privacy, data minimization, and compliance when using 3rd-party large language models (LLMs) and other AI services. We explore the risks of data leakage from LLMs and embeddings, the complexities of identifying and redacting personal information across various data flows, and the approach Private AI has taken to mitigate these risks. We also dig into the challenges of entity recognition in multimodal systems including OCR files, documents, images, and audio, and the importance of data quality and model accuracy. Additionally, Patricia shares insights on the limitations of data anonymization, the benefits of balancing real-world and synthetic data in model training and development, and the relationship between privacy and bias in AI. Finally, we touch on the evolving landscape of AI regulations like GDPR, CPRA, and the EU AI Act, and the future of privacy in artificial intelligence. The complete show notes for this episode can be found at https://twimlai.com/go/716 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 AI Engineering Pitfalls with Chip Huyen - #715 57:37
57:37 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب57:37
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Chip Huyen, independent researcher and writer to discuss her new book, “AI Engineering.” We dig into the definition of AI engineering, its key differences from traditional machine learning engineering, the common pitfalls encountered in engineering AI systems, and strategies to overcome them. We also explore how Chip defines AI agents, their current limitations and capabilities, and the critical role of effective planning and tool utilization in these systems. Additionally, Chip shares insights on the importance of evaluation in AI systems, highlighting the need for systematic processes, human oversight, and rigorous metrics and benchmarks. Finally, we touch on the impact of open-source models, the potential of synthetic data, and Chip’s predictions for the year ahead. The complete show notes for this episode can be found at https://twimlai.com/go/715 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714 58:08
58:08 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب58:08
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Abhijit Bose, head of enterprise AI and ML platforms at Capital One to discuss the evolution of the company’s approach and insights on Generative AI and platform best practices. In this episode, we dig into the company’s platform-centric approach to AI, and how they’ve been evolving their existing MLOps and data platforms to support the new challenges and opportunities presented by generative AI workloads and AI agents. We explore their use of cloud-based infrastructure—in this case on AWS—to provide a foundation upon which they then layer open-source and proprietary services and tools. We cover their use of Llama 3 and open-weight models, their approach to fine-tuning, their observability tooling for Gen AI applications, their use of inference optimization techniques like quantization, and more. Finally, Abhijit shares the future of agentic workflows in the enterprise, the application of OpenAI o1-style reasoning in models, and the new roles and skillsets required in the evolving GenAI landscape. The complete show notes for this episode can be found at https://twimlai.com/go/714 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Why Agents Are Stupid & What We Can Do About It with Dan Jeffries - #713 1:08:49
1:08:49 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:08:49
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Dan Jeffries, founder and CEO of Kentauros AI to discuss the challenges currently faced by those developing advanced AI agents. We dig into how Dan defines agents and distinguishes them from other similar uses of LLM, explore various use cases for them, and dig into ways to create smarter agentic systems. Dan shared his “big brain, little brain, tool brain” approach to tackling real-world challenges in agents, the trade-offs in leveraging general-purpose vs. task-specific models, and his take on LLM reasoning. We also cover the way he thinks about model selection for agents, along with the need for new tools and platforms for deploying them. Finally, Dan emphasizes the importance of open source in advancing AI, shares the new products they’re working on, and explores the future directions in the agentic era. The complete show notes for this episode can be found at https://twimlai.com/go/713 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Automated Reasoning to Prevent LLM Hallucination with Byron Cook - #712 56:48
56:48 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب56:48
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Byron Cook, VP and distinguished scientist in the Automated Reasoning Group at AWS to dig into the underlying technology behind the newly announced Automated Reasoning Checks feature of Amazon Bedrock Guardrails. Automated Reasoning Checks uses mathematical proofs to help LLM users safeguard against hallucinations. We explore recent advancements in the field of automated reasoning, as well as some of the ways it is applied broadly, as well as across AWS, where it is used to enhance security, cryptography, virtualization, and more. We discuss how the new feature helps users to generate, refine, validate, and formalize policies, and how those policies can be deployed alongside LLM applications to ensure the accuracy of generated text. Finally, Byron also shares the benchmarks they’ve applied, the use of techniques like ‘constrained coding’ and ‘backtracking,’ and the future co-evolution of automated reasoning and generative AI. The complete show notes for this episode can be found at https://twimlai.com/go/712 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 AI at the Edge: Qualcomm AI Research at NeurIPS 2024 with Arash Behboodi - #711 54:47
54:47 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب54:47
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, 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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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 AI for Network Management with Shirley Wu - #710 53:44
53:44 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب53:44
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Shirley Wu, senior director of software engineering at Juniper Networks to discuss how machine learning and artificial intelligence are transforming network management. We explore various use cases where AI and ML are applied to enhance the quality, performance, and efficiency of networks across Juniper’s customers, including diagnosing cable degradation, proactive monitoring for coverage gaps, and real-time fault detection. We also dig into the complexities of integrating data science into networking, the trade-offs between traditional methods and ML-based solutions, the role of feature engineering and data in networking, the applicability of large language models, and Juniper’s approach to using smaller, specialized ML models to optimize speed, latency, and cost. Finally, Shirley shares some future directions for Juniper Mist such as proactive network testing and end-user self-service. The complete show notes for this episode can be found at https://twimlai.com/go/710 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Why Your RAG System Is Broken, and How to Fix It with Jason Liu - #709 58:03
58:03 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب58:03
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Jason Liu, freelance AI consultant, advisor, and creator of the Instructor library to discuss all things retrieval-augmented generation (RAG). We dig into the tactical and strategic challenges companies face with their RAG system, the different signs Jason looks for to identify looming problems, the issues he most commonly encounters, and the steps he takes to diagnose these issues. We also cover the significance of building out robust test datasets, data-driven experimentation, evaluation tools, and metrics for different use cases. We also touched on fine-tuning strategies for RAG systems, the effectiveness of different chunking strategies, the use of collaboration tools like Braintrust, and how future models will change the game. Lastly, we cover Jason’s interest in teaching others how to capitalize on their own AI experience via his AI consulting course . The complete show notes for this episode can be found at https://twimlai.com/go/709 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 An Agentic Mixture of Experts for DevOps with Sunil Mallya - #708 1:15:09
1:15:09 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:15:09
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday we're joined by Sunil Mallya, CTO and co-founder of Flip AI. We discuss Flip’s incident debugging system for DevOps, which was built using a custom mixture of experts (MoE) large language model (LLM) trained on a novel "CoMELT" observability dataset which combines traditional MELT data—metrics, events, logs, and traces—with code to efficiently identify root failure causes in complex software systems. We discuss the challenges of integrating time-series data with LLMs and their multi-decoder architecture designed for this purpose. Sunil describes their system's agent-based design, focusing on clear roles and boundaries to ensure reliability. We examine their "chaos gym," a reinforcement learning environment used for testing and improving the system's robustness. Finally, we discuss the practical considerations of deploying such a system at scale in diverse environments and much more. The complete show notes for this episode can be found at https://twimlai.com/go/708 .…
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
1 Building AI Voice Agents with Scott Stephenson - #707 1:01:44
1:01:44 التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احب1:01:44
التشغيل لاحقا التشغيل لاحقا قوائم إعجاب احبToday, we're joined by Scott Stephenson, co-founder and CEO of Deepgram to discuss voice AI agents. We explore the importance of perception, understanding, and interaction and how these key components work together in building intelligent AI voice agents. We discuss the role of multimodal LLMs as well as speech-to-text and text-to-speech models in building AI voice agents, and dig into the benefits and limitations of text-based approaches to voice interactions. We dig into what’s required to deliver real-time voice interactions and the promise of closed-loop, continuously improving, federated learning agents. Finally, Scott shares practical applications of AI voice agents at Deepgram and provides an overview of their newly released agent toolkit. The complete show notes for this episode can be found at https://twimlai.com/go/707 .…
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Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
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The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
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This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
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Material is a weekly discussion about the Google and Android universe. Your intrepid hosts try to answer the question, “What holds up the digital world?” The answer, so far, is that it’s Google all the way down. Hosted by Andy Ihnatko and Florence Ion.
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Show notes are at https://stevelitchfield.com/sshow/chat.html
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The 21st Century began with the rise of the Internet and social media. The next decade will mark the rise of the Intelligent Machines. AI will inhabit all our devices from cars and appliances to smart phones and robots. The Intelligent Machines podcast explores the most exciting revolution humanity has ever seen, filled with promise and peril. More than ever we need to understand what these new devices will bring to our lives and how to make best use of them as the 21st century unfolds. On t ...
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Hanselminutes is Fresh Air for Developers. A weekly commute-time podcast that promotes fresh technology and fresh voices. Talk and Tech for Developers, Life-long Learners, and Technologists.
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Why do only 10% of companies succeed with AI? In this series by MIT SMR and BCG, we talk to the leaders who've achieved big wins with AI in their companies and learn how they did it. Hear what gets experts from companies like NASA, Github, and others excited to do their jobs every day and what they consider the keys to their success.
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Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
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