[These] robots are made entirely of hydrogel — a tough, rubbery, nearly transparent material that’s composed mostly of water. Each robot is an assemblage of hollow, precisely designed hydrogel structures, connected to rubbery tubes. When the researchers pump water into the hydrogel robots, the structures quickly inflate in orientations that enable the bots to curl up or stretch out.
Earlier this year, Berliner Newspaper Der Tagesspiegel reported in Berliner Grundschule kapituliert vor Rasern (article in German) about schools in Berlin Schöneberg taking down their school patrols because the job became too dangerous. Apparently parents bringing their children to schoolby car because traffic in Berlin is dangerous are driving so recklessly that traffic in Berlin too dangerous. Also, said parents were giving a shit about school patrols orders and signage, speed limits or other traffic rules.
The saga continued with a second article (article in German) about schools in Spandau having the same problem. Because of the situation, parents instead of pupils have been employed as school patrol, but to no effect.
First reactions from politics are in (article in German) – now the police are posting speed cams in front of schools, and are doing school patrol work in some particularly affected schools. Also, temporary road blocks (1/2 hour before school begins) are being suggested.
Not just in front of schools, but throughout the city, cycleways are often blocked (article in German, many pics) by parked cars in an extremely dangerous fashion.
Deutsche See has dieselfied their fleet in 2010, using Volkswagen cars with BlueMotion. Volkswagen got the contract specifically because they claimed to be greener than the competition, which turned out to be a lie. They now want leasing fees and support cost back, for a fleet of 500 Volkswagen cars.
Unlearning Descriptive Statistics explains many things you should know about working with Numbers that your Statistics Class in University probably did not explain properly.
If they did, maybe Graphite would not hurt so much, with all the Averaging going on where it shouldn’t, and maybe Gill Tene would not have had to give talks like How NOT to measure latency (which is awesome, by the way and if you haven’t seen this talk, do it right now).
From the Intro of Unlearning:
If you’ve ever used an arithmetic mean, a Pearson correlation or a standard deviation to describe a dataset, I’m writing this for you. Better numbers exist to summarize location, association and spread: numbers that are easier to interpret and that don’t act up with wonky data and outliers.
Statistics professors tend to gloss over basic descriptive statistics because they want to spend as much time as possible on margins of error and t-tests and regression. Fair enough, but the result is that it’s easier to find a machine learning expert than someone who can talk about numbers. Forget what you think you know about descriptives and let me give you a whirlwind tour of the real stuff.
So not every charge of an electric car has to be a fast charge. A small scale pilot in the Netherlands tries to orchestrate the charging of the6000 Teslas, electrek reports, but has been starting with 40 participating owners and their cars only.
The smart charging app has now been opened up to all Testla owners in the Netherlands, and allows them to charge cheaper and greener by in turn allowing the App to orchestrate the charge load on the network.
The Tesla fleet in the Netherlands at the moment represents a charge load total of 60 MW, and is anticipated to approach 10 GW in 2020, but these estimates are probably already invalid and too low.