Mu Python IDE 1.0 to be Released

According to the developers, Mu can be a good tool for beginners, but they do not expect to make this platform universal
26 July 2018   176

British developer Nicholas Tollervey announced the release of Mu version 1.0, a new IDE for Python. The tool is positioned as a development environment for beginners and is available for Windows, MacOS, Linux and Raspbian, the official OS of the Raspberry Pi platform. To ensure an easy start, the developers have prepared a guide for beginners working with the new IDE.

When you start the development environment, you can choose one of the following modes of operation:

  • Python 3 programmming;
  • micro: bit programming;
  • games development using Pygame Zero;
  • CircuitPython boards operations using Adafruit.

Mu Interface
Mu Interface

The development environment has the following capabilities:

  • markup of syntax;
  • automatic indents;
  • built-in help;
  • code checking;
  • error tracking.

According to the developers, Mu can be a good tool for beginners, but they do not expect to make this platform universal. Having enough experience, the programmer can choose a more advanced IDE.

Students to Beat Google’s Machine-Learning Code

Student programmers' image classification algorithm successfully identifies the object in 93% of cases
13 August 2018   394

Developers-students from which organize free online computer training courses have created an image classification algorithm that successfully identifies the object in 93% of cases and copes with it faster than a similar Google algorithm with a similar configuration. The authors argue that "the creation of breakthrough technologies is not just for big companies". This is reported by MIT Technology Review.

When evaluating performance, the DAWNBench test was used, which calculates the speed and cost of teaching the neural network. During the experiment, the neural network was launched on 16 virtual AWS nodes, each contained 8 NVIDIA V100 graphics cards. This configuration achieved accuracy of 93% in 18 minutes, and the cost of machine time was estimated at $ 40. The result of is faster than the development of Google engineers by 40%, but the corporation uses its own clusters TPU Pod, so the comparison is not entirely objective.

The developers used the PyTorch Python library, as well as their own development - fastai. They were able to achieve this learning speed with the new method of cropping images from the ImageNet dataset: instead of square pictures, they began to use rectangular:

Fast AI
Fast AI

State-of-the-art results are not the exclusive domain of big companies. These are the obvious, dumb things that many researchers wouldn’t even think to do.

Jeremy Howard

Founder, Fast.AI

The authors tried to make the project accessible to everyone, so they simplified its infrastructure, refusing to use distributed computing systems and containers. To implement it, developers teamed up with engineers from the innovative division of the Pentagon (DIU) to release software to quickly create and support distributed models on AWS.