🔥 𝗠𝗼𝘀𝘁 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝘁𝗲𝗮𝗺𝘀 𝘀𝗽𝗲𝗻𝗱 𝗺𝗼𝗻𝘁𝗵𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗻𝗲𝘃𝗲𝗿 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗵𝗮𝗱 - 𝗯𝘂𝘁 𝘁𝗵𝗲𝗿𝗲’𝘀 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝘄𝗮𝘆 𝘁𝗼 𝗳𝗶𝘅 𝘁𝗵𝗶𝘀.

🚶 When I walked through Barcelona last week, I spotted something that made me stop dead in my tracks…

𝗔 𝗱𝗼𝗼𝗿 𝘄𝗶𝘁𝗵 𝗮 𝗳𝗼𝗼𝘁-𝗼𝗽𝗲𝗿𝗮𝘁𝗲𝗱 𝗵𝗮𝗻𝗱𝗹𝗲.

💡 Here’s what blew my mind: Instead of just slapping metal plates on doors to prevent kick damage (the lazy solution), someone actually designed for the real behavior.

This morning I was late for work, but I got “diffused” by something worthwhile. I stumbled across a beautifully crafted video that provides excellent intuition on how AI-based image generation actually works.

In the video, Stephen Welch takes us on a tour starting with the CLIP model, explaining how this model combines vision and language, then dives deeper into diffusion models. He finishes by providing intuition on how prompts guide image and video generation models toward desired outcomes.

I like Adrian’s 2nd thought. Amazing to see how technology advancement keeps lifting the level of abstraction.

While I learned some assembler back in the old days, pretty soon it wasn’t anything I was spending time on. Back at Siemens Mobile I was an App guy, purely writing application code in good old plain C, while our device driver guys were still coding in assembler. Clash of worlds when we had a production line standing still due to non-booting phones. Me and the device driver guy staring at the hardware debugger screen. He was wondering about those bloated C-structures the application stack created, then quickly pointed out an issue in the assembly code being shown right next to the C code. I never looked at it when I was debugging app issues. I would have never been able to spot the issue.

My long, little uncomfortably, flight yesterday turned out to by my personal time travel back to my roots, the time where keys became soft and eventually touch…

I watched the movie “Blackberry” and have been teleported into times, where I frequently loosely soldered prototype phone in my pockets. Big shout out to my former colleagues at Siemens Mobile, some of which moved from there to Nokia and eventually to Research In Motion RIM.

AlphaEvolve - takes me back into - my - history and into a bright future …

This month Google DeepMind released AlphaEvolve a new AI Agent which evolves algorithms for math and practical applications. In its core it’s combining evolutionary algorithms(SA) with the power of LLM.

Back in university, ouch we talk like 25y back, I studied evolutionary algorithms. EAs are in short an optimization techniques inspired by natural evolution . I tried to prove upper and lower bounds and the positive impact of providing and maintaining diversity in the populations. Hard work, with very limited success on my end. Since then I really looked back into EAs, but they are more relevant than ever.

Another great feature based on GenAI released right on time. Easy language is a key feature to ensure that everyone can keep up to date in those complex times. Absolutely thrilled. Big Kudos to Alessandro Alviani, Carmen Heger, Sabrina Ebitsch and team!

direct link (German): https://lnkd.in/eThGZDSK

Only made it through 2 out of the 5 hours of this insightful podcast between Lex Fridman, Dylan Patel and Nathan Lambert where the dive deep into Deep Seek’s AI model architectures, highlight and explain innovations. Later they dive into politics and good insights into chip factories on the back of US export regulations.

Highly recommend podcast - it will take a while though to bump up my training volume until I can consume those in just a single run. But you can consume it in bites :)

👀 Just watched the interview of Anthropic CEO Dario Amodei at WSJ Journal House Davos. Highly recommended! While obviously not mentioning any exact targeted launch dates for features, he gave some good insight in his thinking of policies over politics, safety and navigate-able challenges for the future of work. Mindset of collaboration over of replacement. 30 mins of time well invested.

A few things I noted: 🗺️ Product Roadmap • Web browsing capabilities coming in next 3-6 months • Memory features and virtual collaborator functionality in development • Voice interaction planned for future releases • Focus remains on enterprise solutions while expanding consumer offerings 🏗️ AI Development • Anthropic’s revenue grew 10x in 2024, reaching ~$1B • Partnership with Amazon to deploy hundreds of thousands of Trainium 2 chips • Novel approach to reasoning capabilities, focusing on continuous improvement rather than separate models 📈 Future of Work • AI expected to match or exceed human capabilities in most tasks by 2027 • Focus on complementary AI deployment rather than replacement • Emphasis on comparative advantage - humans leveraging the 10% AI can’t do 👓 Industry Perspective • Call for serious dialogue about AI’s societal impact • Strong focus on responsible scaling and security testing • Bipartisan approach to AI policy and regulation

I woke up with some loose ends in my mind about binary encoding and impacts on human life. Needed to reflect on this: Binary encoding is simultaneously powerful for computers yet limiting for human decision-making, creating an interesting paradox worth exploring.

Binary encoding is incredibly effective in computing because it maps perfectly to the fundamental nature of electronic circuits - they can be either on or off. This two-state system is simple to build, highly reliable, and less prone to errors compared to systems with multiple state.

Go ugly to be successful ?!

🎯 Just watched a fantastic TEDx talk by Prof. Martin J. Eppler about unleashing the power of visualization at work(available at YouTube: [1]). He outlines three Key Practices for Better Visual Communication:

1.	Make it intentionally “ugly” - polished visuals can inhibit collaboration. Rough sketches invite participation and improvement.
2.	Lead with visual metaphors instead of bullet points - they tap into existing knowledge and spark new solutions. A simple bridge or mountain trail can convey complex ideas more effectively than slides.
3.	Use visual variations - create a series of related images that others can build upon. This invites collaboration and deeper understanding.

💡 The most powerful insight: Beauty can be the enemy of collaboration. When something looks too perfect, people stop thinking critically and contributing ideas.