Insight. Applied.
I tend to listen more to opinions when people have placed money on their espoused outcome—having “skin in the game”, as Nicholas Taleb calls it in his latest book.
However, this robotics developer seems to have gone one better. He literally has skin in the game.
Good scientists aren’t supposed to experiment on themselves, but I will feel better if the first people to use autonomous cars are those who built the guidance systems.
At least it’s more impressive than Test-Driven Development.
Google have created a tool to make it easier to discover datasets—Google Dataset Search.
One potential downside is that it requires dataset owners to provide metadata. While the Google brand means that this might get some traction, not all dataset owners are motivated to help the cause. Publication of datasets is now mandated by some funding bodies, but that doesn’t mean that the datasets have to be discoverable. Ideally we’ll see funding bodies now mandating the addition of metadata.
While we wait for Google Dataset Search to evolve, we can still rely on curated repositories and lists such as
The current hype around artificial intelligence and machine learning brings to mind Amara’s Law.
We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
Python has topped the IEEE Spectrum list of top programming languages again this year—extending its lead in the process.
The sources used to compiled the list cover
contexts that include social chatter, open-source code production, and job postings.
Obviously that list of sources isn’t an accurate reflection of what developers are doing day-to-day in organisations. Any list of top programming languages that puts R (#7) above JavaScript (#8) clearly has some methodological challenges. My belief is that the list reflects the current buzz around data science.
However, interest in Python clearly remains high. As it does in R—#7 is impressive for a domain-specific language.
Microsoft Research have released over 50 free data sets via their Open Data site. They include
Are there actually 1 million celebrities now?! Maybe someone can analyze the data to confirm. As in all data science we’ll need to start with firming up our definitions of terms—e.g “celebrity”.