Stupid TensorFlow tricks – Towards Data Science – Medium

A new take on an old (Thomson) problem using #TensorFlow

  • I wanted to see how far I could push this idea.Electrostatic charge configuration for N=625 in equilibrium.
  • Probably not.The Thomson problem is a classical physics question, “What configuration of N positive charges on the unit sphere minimizes the energy?”
  • N=11 puts the charges in a configuration that completely breaks the symmetry — while the charges are in equilibrium, they are distributed in such a way that there are more on one side than the other; it has a net dipole moment!Solving this in TF is surprisingly easy.
  • For any value of N, we can converge to a stable solution energy minima in a matter of seconds, and we can refine that to the full floating point precision in a matter of minutes by tapering down the learning rate.
  • That’s an impressive 10x speedup!Minimal energy for N=100 charges, prettified.Visualizing the configurations illustrates the regularity and the apparent symmetry, even if we are content knowing that it might not be the global minimum.

Is Google’s machine intelligence library TensorFlow (TF) good for something beyond deep learning? How well can it tackle a classic physics problem?
Continue reading “Stupid TensorFlow tricks – Towards Data Science – Medium”

Using TensorFlow in Windows with a GPU

Using #TensorFlow in @Microsoft #Windows with a #GPU  #DeepLearning

  • Particularly, I was curious about my Windows Surface Book (GPU: GeForce GT 940) performance of using the GPU vs the CPU.
  • When TensorFlow was first released (November 2015) there was no Windows version and I could get decent performance on my Mac Book Pro (GPU: NVidia 650M).
  • Read here to see what is currently supported The first thing that I did was create CPU and GPU environment for TensorFlow.
  • To create my CPU TensorFlow environment, I used:

    To create my CPU TensorFlow environment, I used:

    Your TensorFlow code will not change using a single GPU.

  • You can switch between environments with:

    If you are doing moderate deep learning networks and data sets on your local computer you should probably be using your GPU.

In case you missed it, TensorFlow is now available for Windows, as well as Mac and Linux. This was not always the case. For most of TensorFlow’s first year…
Continue reading “Using TensorFlow in Windows with a GPU”

GitHub

  • Linux GPU: Python 2 ( build history ) / Python 3.4 ( build history ) / Python 3.5 ( build history )
  • Latest commit 55b0159 Jan 1, 2017 yifeif committed on GitHub Merge pull request #6588 from terrytangyuan/run_config_flag
  • TensorFlow is an open source software library for numerical computation using data flow graphs.
  • Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them.
  • TensorFlow also includes TensorBoard, a data visualization toolkit.

tensorflow – Computation using data flow graphs for scalable machine learning
Continue reading “GitHub”

Europe Will Spend €1 Billion to Turn Quantum Physics Into Quantum Technology

Europe Will Spend €1 Billion to Turn Quantum Physics Into Quantum Technology  #Robots #AI

  • Europe Will Spend €1 Billion to Turn Quantum Physics Into Quantum Technology
  • The new technologies included quantum simulation, quantum sensors, quantum imaging, quantum clocks, and quantum software and algorithms.
  • Quantum sensors and quantum imaging will be especially useful in medicine.
  • A 10-year-long megaproject will go beyond quantum computing and cryptography to advance other emerging technologies
  • The 93-petaflop Sunway TaihuLight takes the top ranking 20 Jun

Read the full article, click here.


@wtvox: “Europe Will Spend €1 Billion to Turn Quantum Physics Into Quantum Technology #Robots #AI”


A 10-year-long megaproject will go beyond quantum computing and cryptography to advance other emerging technologies


Europe Will Spend €1 Billion to Turn Quantum Physics Into Quantum Technology