The future of Augmented Reality | Interview with Real Wear CTO Timon Binder
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!
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1:20:48
Building AI Agents Without Code | Interview with Langflow
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.
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24:45
What will the world look like in 2035?
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.
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47:56
What even is AGI?
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.
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1:29:36
Can you trust LLM Leaderboards?
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
Hosted by Mark and Shashank, software engineers and organizers in Silicon Valley. Get their grounded perspective each week as they explore the generative AI landscape through news analysis, tech discussions, hands-on experiments, and clear explanations.
Dive into the latest language models, AI agent capabilities, and RAG techniques. Understand the hardware race, key research, startup trends, benchmarks, and the real-world impact of AI across industries like healthcare, robotics, and creative work. We also test AI limits, explain core concepts, discuss ethics, and interview builders shaping the field.
For engineers, developers, researchers, and anyone seeking a practical understanding of AI’s rapid evolution and its applications.
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