slow thoughts

Human factors engineering taught us the importance of building systems that minimise the risk for mode confusion. That’s highly pertinent when designing interaction with robots that are supposed to be perceived as social.

While watching babies and kittens learn by doing is cute, you don’t want to get in the way of a ten ton industrial robot figuring out the fundamentals. You also don’t want a soon-to-be autonomous car cruising your neighbourhood to pick up traffic rules.

These are not your ordinary run of the mill cyber security threats. Adversarial attacks don’t rely on exploiting bugs.

A brief seven years after Gibson’s far fetched futurism, the science fiction had become reality. Does that mean we’re screwed?

Teams like this can follow the tenants of XP and agile to the letter, and still end up building the wrong product. Teams like this need tools on a whole different level. Entire problem spaces need to be explored, before discrete problems are picked out to be solved.

2018 was the watershed year for the open core model, where you build value around a code base that is guaranteed to remain open, and create revenue streams around consulting, hosted services and closed source add-ons.

The professor’s privilege and means that researchers can do what they want with whatever they create. Which if you’re in software usually just means that you publish your code on GitHub under MIT or BSD license and move on to the next research project.

The approach is one of the most promising candidates among “non-Von Neumann” computer architectures. So one hundred years after the idea was first broached, is the time now ready for Coherent Ising Machines to make a dent in the universe? There are three signs that so might be the case.

The ins- and outs of open hardware; the power and perils of building your products on top of FOSS-stacks; the dos and don’ts with design patenting, and so much more.