Can AI uncook an egg?

The Generative AI Meetup Podcast

The Generative AI Meetup Podcast

22:49

Jonathan Jones is an NFL cornerback for the Washington Commanders who rose from the undrafted ranks to become two-time Super Bowl champion with the New England Patriots, a businessman, philanthropist, and licensed pilot. In 2019, Jonathan founded the Jonathan Jones Next Step Foundation in 2019, a platform dedicated to empowering youth through education, professional development, and mentorship. The foundation works to alleviate food insecurity, promote women in stem and sports, and to promote professional development in the communities where he lives. Jay and Jonathan talk about investing in the communities they live in, acknowledging the people who helped you become the person you are, and paying that same investment forward to the next generation. Episode Chapters 0:00 intro 1:24 Building local connections 4:25 Jonathan’s mentors and mentees 10:54 Jonathan’s pride in his mentees’ successes 13:04 how Jonathan chooses his causes 14:08 Jonathan’s support for girls and young women 17:19: Jonathan’s passion for flying 19:40 The Next Step Foundation 20:29 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/ Looking for more insights into the world of activism? Be sure to check out Jay’s brand new book, Find Your Fight , in which Jay teaches the next generation of activists and advocates how to step up and bring about lasting change. You can find Find Your Fight wherever you buy your books, and you can learn more about it at www.jayruderman.com .…

for ca. et år siden 1:23:52

M4A•Episode hjem

China is leading in AI breakthroughs with models like Manus.
Manus represents a shift towards more comprehensive AI solutions.
The Gaia benchmark is crucial for evaluating AI performance.
Manus scored impressively on the Gaia benchmark, nearing human performance.
Future advancements in AI will focus on tool use and reasoning capabilities.
The cost of training AI models is becoming a significant concern.
AI can automate tedious tasks, impacting job markets.
The marginal cost of software development is decreasing rapidly.
AI has the potential to solve complex human problems.
The evolution of AI will lead to more creative and powerful applications.

Chapters
00:00
AI Breakthroughs: China's Lead in Agentic Computing
02:53
Understanding Manus: More Than Just a Model
06:05
Benchmarking AI: The Gaia Benchmark Explained
08:54
Human-Level Performance: Manus vs. Human Intelligence
11:45
The Future of AI: Tool Use and Reasoning Capabilities
14:59
Data and Integration: The Key to AI Success
17:46
Manus in Action: Real-World Applications
20:57
The Importance of Real-Time Data in AI
24:00
The Role of Human Oversight in AI Development
27:10
The Future of API Integration with AI
29:59
Building Modular AI Systems for Enhanced Functionality
44:22
The Evolution of AI in Software Engineering
48:06
The Rise of Smaller, Efficient AI Models
51:30
The Future of AI in Everyday Devices
57:09
The Cost of AI Agents vs Human Labor
01:01:30
AI in Customer Service and Beyond
01:10:07
The Impact of AI on Freelance Developers
01:17:35
The Future of AI: Solving Humanity's Problems

Keywords: AI, Manus, China, agentic models, Gaia benchmark, human-level performance, tool use, reasoning capabilities, software development, customer service, AI agents, future of work, coding, creativity, philosophical implications

53 episoder

#Tech #Mark And Shashank

Can AI uncook an egg?

published for ca. et år siden

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M4A•Episode hjem

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The Generative AI Meetup Podcast

1
The future of Augmented Reality | Interview with Real Wear CTO Timon Binder 1:20:48

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https://www.realwear.com/ Timon Binder: https://www.linkedin.com/in/timon-binder/ Join us for a special episode as we sit down with Timon Binder, CTO of Realware, a leading AR hardware company transforming the enterprise landscape. Timon shares his journey from co-founding a startup in Switzerland to leading innovation in the US, revealing how Realware’s AR headsets are revolutionizing industries like manufacturing, logistics, and healthcare. We dive deep into: Realware’s approach to solving real-world problems with AR The challenges and opportunities in global hardware manufacturing How AI and voice assistants are reshaping user interaction The future of consumer AR and the transition from B2B to B2C Startup lessons, work culture differences, and advice for aspiring founders Whether you’re a tech enthusiast, entrepreneur, or curious about the future of augmented reality, this episode is packed with insights, practical advice, and candid stories from the frontlines of innovation. Call to Action: If you’re interested in AR, app development, or want to connect with Realware, check out the links in the episode description for open roles and collaboration opportunities!…

The Generative AI Meetup Podcast

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Building AI Agents Without Code | Interview with Langflow 24:45

for 23 dage siden24:45

24:45

Langflow: https://www.langflow.org/ https://www.producthunt.com/products/langflow Langflow Desktop: https://www.langflow.org/desktop In this insightful interview, Rodrigo from Langflow discusses the evolution and future of their low-code agent building platform. Starting with his background in machine learning and data science, Rodrigo explains how Langflow began as a vision to connect specialized AI models years before ChatGPT existed. The conversation covers Langflow's journey from open-source project to being acquired by DataStacks while maintaining its commitment to open-source principles. Rodrigo announces the exciting launch of Langflow Desktop, designed to democratize AI development by eliminating technical barriers through an intuitive drag-and-drop interface. Rodrigo details how Langflow serves both technical and non-technical users, supporting three main application types: LLM pipelines, RAG systems, and multi-agent applications. The interview highlights Langflow's integration with the new MCP protocol for more structured and efficient tool usage by AI agents. Looking to the future, Rodrigo envisions advanced agent orchestration systems where AI agents can assign tasks to each other, with humans serving as collaborators in the process. This episode offers valuable insights for anyone interested in the rapidly evolving landscape of AI agent development and deployment.…

The Generative AI Meetup Podcast

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What will the world look like in 2035? 47:56

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47:56

In this special episode, hosts Mark and Shashank take a break from their usual news coverage to explore the rapidly evolving world of AI agents. They define what agents are, examine their current capabilities, and make bold predictions about how these technologies will transform our lives over the next 1, 5, and 10 years. The hosts discuss how AI agents are already revolutionizing software development, research, and reasoning tasks, while exploring the imminent impact on knowledge work, self-driving vehicles, and scientific breakthroughs. Looking further ahead, they predict the widespread adoption of humanoid robots, the "YouTubeification" of product creation, and fundamental shifts in employment patterns. Whether you're new to AI or a seasoned professional, this episode offers fascinating insights into how exponential growth in AI capabilities will reshape our society, economy, and daily lives in ways we're only beginning to imagine.…

The Generative AI Meetup Podcast

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What even is AGI? 1:29:36

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1:29:36

In this episode, hosts Mark and Shashank dive into recent developments in generative AI technology. They begin with NVIDIA's latest GTC announcements, including partnerships with GM for self-driving technology and advancements in robotics with Google DeepMind and Disney. The hosts debate the merits of camera-only versus LiDAR-based autonomous driving systems, referencing Mark Rober's viral comparison video. They also discuss NVIDIA's upcoming Ruben chip, which promises a 10-15x performance increase over the current Blackwell architecture. The conversation shifts to a correction about the DeepSeek model's computational requirements before culminating in a thought-provoking discussion about the challenges of creating generalized robotics systems and how simulation environments might accelerate development. Throughout the episode, the hosts share insights on what these technological advancements might mean for the future of AI and robotics.…

The Generative AI Meetup Podcast

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Can you trust LLM Leaderboards? 1:29:48

for 6 weeks siden1:29:48

1:29:48

This conversation delves into the latest developments in AI, particularly focusing on Google's Gemma models and their capabilities. The discussion covers the differences between various types of language models, the significance of multimodal inputs, and the training techniques employed in AI models. The hosts also explore the implications of open-source versus proprietary models, the hardware requirements for running these models, and the limitations of benchmarks in evaluating AI performance. Additionally, they touch on the future of robotics and the cultural differences in AI adoption, particularly between Japan and the United States. takeaways Open source models are pushing the boundaries of AI. Gemma models are capable of multimodal inputs. Different types of LLMs serve different purposes. Benchmarks can be misleading and should be approached with caution. Training techniques like RLHF are crucial for model performance. The hardware requirements for AI models vary significantly. Cultural differences affect the adoption of robotics and AI. Robots are increasingly filling labor gaps in societies with declining populations. AI benchmarks should be tailored to specific use cases. The future of robotics and AI feels imminent and exciting. Chapters 00:00 Introduction to the Week's AI Developments 00:50 Exploring Google's Gemma Models 03:21 Understanding Different Types of LLMs 05:32 Gemma's Multimodal and Multilingual Capabilities 08:45 Training Techniques Behind Gemma 15:48 Open Source Models and Their Impact 20:34 Benchmarking AI Models 28:30 Gaming Benchmarks in AI 34:10 The Ethics of Benchmarking in AI 44:56 Language Learning and AI Models 49:12 The Importance of Benchmarks 52:35 Vibe Checks and User Preferences 01:01:09 Top AI Models and Their Performance 01:13:35 Robotics and the Future of AI 01:27:20 Cultural Perspectives on Automation…

The Generative AI Meetup Podcast

1
Can AI uncook an egg? 1:23:52

for 7 weeks siden1:23:52

1:23:52

In this conversation, Mark and Shashank discuss the latest advancements in AI, particularly focusing on China's lead in developing agentic models like Manus. They explore the capabilities of Manus, its performance on the Gaia benchmark, and the implications of AI in various sectors, including software development and customer service. The discussion also delves into the philosophical aspects of AI's potential to solve humanity's problems and the future of work as AI continues to evolve. takeaways China is leading in AI breakthroughs with models like Manus. Manus represents a shift towards more comprehensive AI solutions. The Gaia benchmark is crucial for evaluating AI performance. Manus scored impressively on the Gaia benchmark, nearing human performance. Future advancements in AI will focus on tool use and reasoning capabilities. The cost of training AI models is becoming a significant concern. AI can automate tedious tasks, impacting job markets. The marginal cost of software development is decreasing rapidly. AI has the potential to solve complex human problems. The evolution of AI will lead to more creative and powerful applications. Chapters 00:00 AI Breakthroughs: China's Lead in Agentic Computing 02:53 Understanding Manus: More Than Just a Model 06:05 Benchmarking AI: The Gaia Benchmark Explained 08:54 Human-Level Performance: Manus vs. Human Intelligence 11:45 The Future of AI: Tool Use and Reasoning Capabilities 14:59 Data and Integration: The Key to AI Success 17:46 Manus in Action: Real-World Applications 20:57 The Importance of Real-Time Data in AI 24:00 The Role of Human Oversight in AI Development 27:10 The Future of API Integration with AI 29:59 Building Modular AI Systems for Enhanced Functionality 44:22 The Evolution of AI in Software Engineering 48:06 The Rise of Smaller, Efficient AI Models 51:30 The Future of AI in Everyday Devices 57:09 The Cost of AI Agents vs Human Labor 01:01:30 AI in Customer Service and Beyond 01:10:07 The Impact of AI on Freelance Developers 01:17:35 The Future of AI: Solving Humanity's Problems Keywords: AI, Manus, China, agentic models, Gaia benchmark, human-level performance, tool use, reasoning capabilities, software development, customer service, AI agents, future of work, coding, creativity, philosophical implications…

The Generative AI Meetup Podcast

1
Vibe Coding, Claude 3.7, GPT 4.5, and Alexa+ 1:19:36

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Mark's Channel: https://www.youtube.com/@UCqLp0T6WBwxmuJdmo4mUW5A Databricks Events: https://lu.ma/okxq0bt1 https://lu.ma/n7p3gdx0 In this episode of The Generative AI Meetup Podcast, we dive deep into the evolving landscape of AI coding assistants and their real-world applications. Our hosts explore the capabilities of Cursor, Claude 3.7, and other frontier models, discussing how these tools are transforming development workflows while acknowledging their current limitations. The conversation covers "vibe coding" - how non-developers can now create functional applications through prompt engineering, the challenges of scaling AI-generated code to enterprise levels, and the exciting potential of agentic behaviors in coding assistants. We also examine recent announcements from major tech companies including OpenAI's GPT-4.5, Amazon's Alexa Plus integration with Claude, and the competitive dynamics driving innovation in the AI space. Whether you're a developer looking to enhance your productivity or simply curious about how AI is reshaping software development, this episode offers valuable insights into the current state and future direction of generative AI tools. AI #GenerativeAI #CodingAssistants #Claude #Cursor #VibeCoding #AIAgents #TechTrends #SoftwareDevelopment #SmartAssistants…

The Generative AI Meetup Podcast

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The Path to AGI: Grok 3, Quantum Breakthroughs, and Humanoid Robots 1:43:26

for 8 weeks siden1:43:26

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Youtube: https://www.youtube.com/@GenerativeAIMeetup https://www.anthropic.com/news/the-anthropic-economic-index https://x.com/xai/status/1891699715298730482 - Grok 3 http://x.com/karpathy/status/1891720635363254772 https://news.microsoft.com/source/features/innovation/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/ https://en.wikipedia.org/wiki/Majorana_fermion https://www.youtube.com/watch?v=88vEsL5tgDI Grok 3 -Elon Musk new model - Seems to be a very brute-force approach (which is working) - Definitely a state of the art model - 40 dollars a month now - https://techcrunch.com/2025/02/19/x-doubles-its-premium-plan-prices-after-xai-releases-grok-3/ - 100,000 GPUs Majorana - Uses a particle called the Majorana - https://www.howtopronounce.com/ettore-majorana - https://en.wikipedia.org/wiki/Ettore_Majorana - Ettore Majorana disappeared soon after theorizing this particle in 1937 he disappeared in 1938 although thought to be alive - A majorana is a fermion that has its own antiparticle - this was originally theorized in 1937 - The particle has its own charge... and own antiparticle - it has a new topological state... which is a new state of matter - Has has 8 quibits - Is designed to scale to a million quibits - To break bitcoin you might need ~1500 to 5000 logical quibits - A quibit can be used to represent potentially infinite states Figure AI - Helix - https://www.figure.ai/news/helix - Vision-Language-Action (VLA) - Full-upper-body control - Multi Robot collaboration - Pick up anything - Single neural network to build this, no specific fine tuning - https://www.figure.ai/news/helix - Has a slow System 2 and a fast system 1 neural network - system 2 -- 7B - system 1 -- 80M Get ready to explore the frontiers of technology in this exciting episode! We unpack the latest breakthroughs driving us toward Artificial General Intelligence (AGI) and beyond, with a mix of mind-blowing advancements and thought-provoking discussions: Grok 3 Unveiled: Elon Musk’s xAI has dropped Grok 3, a powerhouse AI model dominating benchmarks and redefining what large language models can achieve. We dive into its stellar performance, its bold “no-filter” approach to information, and how it stacks up against heavyweights like Claude 3.5, OpenAI’s offerings, and Google’s latest. Quantum Leap Forward: Microsoft’s Majorana-based quantum chip is here, promising to scale quantum computing to a million qubits. We simplify the tech behind it, explore its potential to transform everything from cryptography to drug design, and ponder what it means for simulating reality itself. Robots in Action: Figure AI’s Helix brings us two humanoid robots teaming up to tackle chores like grocery unpacking. We marvel at their teamwork, laugh at their quirky moves, and discuss the hurdles and possibilities of general-purpose robotics in our everyday lives. But it’s not all tech demos and breakthroughs. We wrestle with the big stuff too: Are we inching closer to AGI? How do quantum computing, AI, and robotics fuel each other’s progress? And what happens when unrestricted AI or quantum tech shakes up ethics—like privacy or security? Perfect for AI buffs, tech pros, or anyone curious about tomorrow, this episode blends sharp insights, lively debates, and a dash of humor. Jump in to stay ahead in the fast-moving world of generative AI! Listen now and join the discussion! Chapters: 0:00 - Introduction: The AGI RevolutionOpening remarks about how close we are to AGI and the recent breakthroughs 2:15 - Grok 3: The New AI BenchmarkDiscussion of Grok 3's capabilities and performance compared to other models 7:30 - Elon's 122-Day Data CenterHow Elon Musk converted an old Electrolux factory into a massive AI data center 11:45 - The Computing Power Behind GrokDetails about the 100,000+ GPUs and diesel generators powering Grok's training 15:20 - Why Grok "Just Feels Better"Analysis of what makes Grok 3 outperform other models in real-world use cases 19:40 - AI Guardrails: Freedom vs. SafetyThe ethical debate around AI content restrictions and guardrails 25:15 - The Cat and Mouse Game of AI SafetyHow users bypass AI safety measures and what it means for regulation 30:00 - Anthropic's Economic IndexSurprising data about how people actually use AI tools in practice 36:30 - Programming: AI's Killer AppWhy coding dominates AI usage and how models excel at verifiable tasks 42:15 - The $40 AI RevolutionGrok's pricing strategy and why it's disrupting the AI market 47:00 - Microsoft's Quantum Computing BreakthroughThe Majorana One and the mysterious physicist behind it 53:45 - The Path to One Million QubitsHow Microsoft plans to scale quantum computing in the next few years 58:30 - The Future of AI: Multiple Paths to AGIConcluding thoughts on how different technologies are converging toward AGI 1:02:15 - Final Thoughts: Tuesday Will Be InterestingClosing remarks on the rapid pace of AI development…

The Generative AI Meetup Podcast

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The $6 Reasoning Model: Breaking Down Stanford's S1 Paper 1:17:02

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Podcast: https://podcast.genaimeetup.com/ Youtube: https://www.youtube.com/@GenerativeAIMeetup In this episode, we explore Stanford's groundbreaking S1 paper, which introduces a technique to transform any language model into a reasoning model for just $6 in computation costs. We dive deep into the implications of this research, discussing budget forcing techniques, the true costs of AI development, and the philosophical limits of artificial intelligence across different domains - from mathematical reasoning to language translation. The conversation extends to broader questions about superhuman AI capabilities and the fundamental limitations in various fields like translation, history, and agriculture. Join us for an insightful discussion on the future of AI reasoning and its practical applications. 0:00 - Intro and weekly AI news overview 1:06 - Introduction to the S1 paper from Stanford 1:40 - Explanation of reasoning models vs single-shot models 2:22 - Details of Stanford's S1 technique and QEN32B model 3:00 - Cost comparison with other models ($6 training cost) 4:04 - Discussion of model distillation technique 5:00 - Budget forcing explanation 6:33 - Story about building an AI stock research agent 8:22 - Philosophical discussion on reasoning limits…

The Generative AI Meetup Podcast

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The Generative AI Meetup Podcast

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The Generative AI Meetup Podcast

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Bring on the AI doctors and Baby Robots 45:57

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45:57

Meetup Event: https://www.meetup.com/gen-ai/events/305158672 deep seek: https://chat.deepseek.com/ Subscribe to the podcast: https://podcast.genaimeetup.com/ In this week's episode, Mark and Shashank dive into the latest announcements from NVIDIA at CES 2025, including the groundbreaking RTX 50 series GPUs and the emergence of tiny, single-user supercomputers. They explore the implications of TSMC's 4nm chip production in Arizona and its impact on U.S. manufacturing and AI advancements. The conversation shifts to the impressive algorithmic innovations behind DeepSeek v3 and Microsoft's Phi-4, demonstrating how curated and synthetic data are driving efficiency in smaller, more powerful AI models. Mark shares his experience using AI tools like Claude 3.5 for medical insights and reflects on the potential of AI in healthcare. They also discuss NVIDIA’s Cosmos platform for robotics and how self-learning frameworks could shape the future of AGI development. Finally, they highlight an exciting upcoming event with Sentient AI and why it’s a must-attend for anyone in the Generative AI space.…

The Generative AI Meetup Podcast

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The Generative AI Meetup Podcast

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