- Microsoft’s AI-Assisted Coding (TechCrunch) — What makes IntelliCode different is that the company trained it by feeding it the code of thousands of open source projects from GitHub that have at least 100 stars. Using this data, the tool can then make smarter code-completion suggestions. It also takes the current code and context into account as it makes its recommendations. The first of (hopefully) many AI tools for coders. Interestingly, AI-style centralized training on large data sets isn’t something that’s a natural advantage for open source tools, so I wonder whether this marks the start of a dev tools shift in power to Microsoft.
- Reproducibility as a Vehicle for Engineering Best Practices (Joel Grus) — a talk aimed at machine learning folks, on how delivering reproducibility requires you to use better (more modern) development practices.
- Defining the Dimensions of the Space of Computing (JoDS) — Glass rectangles and black cylinders are not the future. We can imagine other possible futures—paths not taken—by searching within a “space of alternative” computing systems, as Simon has suggested. In this “space,” even though some dimensions are currently less recognizable than others, by investigating and hence illuminating the less-explored dimensions together, we can co-create alternative futures. (via Daniel G. Siegel)
- On Social Media (Tom Coates) — Tom’s Twitter thread about what’s already filtered out in social media platforms in order to make it clear how fundamental it is that platforms filter content online.
Article image: Four short links