Another week of robotics marketing loops versus harsh field realities. In this week's breakdown, we are looking past investor decks to audit the actual friction of automating physical labor. Here is what we are covering in this episode: Figure’s 55/Week Ramp-Up: Production is accelerating, but commercial use cases are still in continuous development. Is scaling ahead of general application a massive capital gamble, or does their package-sorting livestream prove they're ready for structured work? Verobotics at NVIDIA Campus: A massive 100,000 sq ft facade deployment that ended up in a strict 60/40 operational compromise with human window washing crews because of live construction site dust. The 8.1B Parameter Bottleneck: Looking at RLWRLD’s new RLDX-1 model. Why graph optimization and real-time memory bandwidth constraints—not raw compute power—are the real bottlenecks for dexterous robotic hands. Spot's Purely Visual Blind Spots: Boston Dynamics paired Spot with DeepMind’s Gemini 1.6. What a sideways-crushed soda can proves about semantic reasoning models running without tactile force integration. FANUC x Google: Industrial giants bringing physical AI to factory floors, but keeping implementation highly conservative. submitted by /u/ButterscotchTiny1114 [link] [Kommentare]

Has anyone received IROS results? The results are supposed to be out next week but I see my submission status currently changed to undisclosed, which, as far as I know, this happens usually at the day of sending out the notification. Any idea? Did anyone get any notification? submitted by /u/Street_Night_4344 [link] [Kommentare]

Everyone seems convinced the 4-year Bitcoin cycle is guaranteed at this point. The more I read Bitcoin Twitter, Reddit, and YouTube, the more it feels like the cycle is treated as a fact rather than a theory. Historically, markets love making the majority look foolish. What if this is the cycle where it breaks? submitted by /u/2smart2gentle [link] [Kommentare]

I read and collected Arxiv whitepapers starting after the launch of ChatGPT. I copied and pasted excerpts into Word to track them. Then migrated to Obsidian. That vault of some 1700 papers is now online. I figured it was time to see if others would find the collection useful. My whitepapers were organized into some 90 categories, all of which emerged from paper topics. New categories became necessary with the discussion of new methods, techniques, models etc. If I wanted to write about a topic, I'd upload an md file containing research excerpts on that topic to ChatGPT. This worked to a degree but maxxed out context pretty quickly. And I always had related research in multiple categories, according to how the research was framed. (Personas research in Aligment, Psychology, HCI, etc). So I used a plugin to create topic notes that built in and outbound wikilinks across the papers centered on shared concepts. When I ported this all online I added another layer of synthesis: Inquiring Lines as I call them. These cover cross-cutting, tension-surfacing, synthesizing, and frontier-opening research frames. There's 6,000 of them in my collection. Each is a page to itself that's a useful description of a research line of inquiry. These now also have prompts you can run yourself that will find related (and more recent) research - (I can't adequately maintain each topic with new research). It's all at https://inquiringlines.com/inquiring-lines/ if you want to poke around. As is everything in the age of AI, it's a work in progress. But there's a lot of rich material in there. Have a look. submitted by /u/Barton5877 [link] [Kommentare]