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(Source: Midjourney v6.1; promp t: two GenAi bots battling it out with smarts and wit) I did a little experiment. I asked ChatGPT 4o (in the cloud) and the Llama 3.1 70b model (locally via Ollama), the same question: "What verse changes did Schiller make for Beethoven's 9th symphony?". Both models got the right answer, in fairness GPT 4.o did it much faster and had a much more elaborate answer than Llama3.1 70b that took a good 2 minutes (running on my desktop PC!). But in the end, I liked the answer from Llama 3.1 better because it was concise, to the point, minimalistic (as you would expect from a 70b model) and in a way more helpful.  If you want to follow the the experiment in real-time, I've recorded it for just that purpose. This is also the reason why this is a blog post and not just an update, because I can upload more than one video file.  ChatGPT 4o: Llama 3.1 (70b) via Ollama (jump to 50 seconds, it takes a while to load the model):  What do you think?

My starting point for this is the evolution of the Android SmartPos and in particular the version at the lowest common denominator also known as SoftPos, which allows most Android phones to become NFC payment terminals. This is the domain of the Android operating system because Google has allowed unrestricted access to NFC since the days of GooglePay (2015ish), hence it doesn't surprise that when we talk about the SmartPOS, we really talk about the Android operating system with custom hardware and software. Now, we have known for some time that Apple will be entering this space (and has in fact in some markets) with the iPhone given the acquisition of Mobeewave. What is different to the Android ecosystem, however, is that Apple is again controlling every aspect surrounding the user experience. Let me try to reach a bit further and just to be clear: I’m not an expert when it comes to Terminal hardware and PCI security. Further I have not signed an NDA with Apple, so a lot of this i

If we listen to the media, business leaders, and the press, we should be getting behind the AI wagon because of its potential to automate many of the processes everyday companies struggle with. I don’t dismiss this notion entirely because I think it’s true if you have the ability to integrate this technology in a meaningful way. For example, the startup company " scrambl " (full disclosure, I’m a minority investor) is making use of gen-AI by "understanding" CVs (curriculum vitae) from applicants and identifying the skills to match them to open positions. This works great – I have seen this in action, and while there are some misses, most of that "normalization of skills" works. There are other promising examples, such as Q&A systems to understand the documentation of a complex environment. When combined with RAG ( retrieval augmented generation ), this has the potential to significantly reduce the time it takes to make complexities understandable. But

I have dabbled a fair amount with all sorts of crypto currencies and their respective permissionless networks. In fact, I have been dabbling since 2012 which is by my last count a whopping 12 years. While I have always maintained that I do believe the general concept for digitization and programmability of assets is on the right path, its implementation, the user experience, the accessibility, the fraudulent activities, and the overall inefficiencies permissionless DLTs have, never made me into a true believer. I have stated that opinion on several occasions, here , here and here . There are still barriers to entry when it comes to digitization of assets: sustainable- and interoperable infrastructure. To illustrate this, I recently asked a notary public here in Zurich, why they can’t store the notarized documents as PDFs, the answer surprised me: because they must keep records for at least 70 years. Now, think about what would have happened if we stored these documents on floppy disks