Positively shaping development of artificial intelligence

Positively shaping development of artificial intelligence

  • This wasn’t the first such event – the agricultural revolution had upended human lives 12,000 years earlier.
  • A growing number of experts believe that a third revolution will occur during the 21st century, through the invention of machines with intelligence which far surpasses our own.
  • Rapid progress in machine learning has raised the prospect that algorithms will one day be able to do most or all of the mental tasks currently performed by humans.
  • This could ultimately lead to machines that are much better at these tasks than humans.

Positively shaping development of artificial intelligence
Continue reading “Positively shaping development of artificial intelligence”

The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould

The Theorem Every Data Scientist Should Know (Part 2)  #MachineLearning #DataScience

  • The standard deviation of the population distribution is tied with the standard deviation of the sampling distribution.
  • With the standard deviation of the sampling distribution and the sample size, we are able to calculate the standard deviation of the population distribution.
  • The standard deviation of the sampling distribution is called the standard error.
  • The mean of the sampling distribution will cluster around the population mean.
  • If we collect a large number of different samples mean, the distribution of those samples mean should take the shape of a normal distribution no matter what the population distribution is.

Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.
Continue reading “The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould”

The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould

The Theorem Every Data Scientist Should Know (Part 2)  #MachineLearning #DataScience

  • The standard deviation of the population distribution is tied with the standard deviation of the sampling distribution.
  • With the standard deviation of the sampling distribution and the sample size, we are able to calculate the standard deviation of the population distribution.
  • The standard deviation of the sampling distribution is called the standard error.
  • The mean of the sampling distribution will cluster around the population mean.
  • If we collect a large number of different samples mean, the distribution of those samples mean should take the shape of a normal distribution no matter what the population distribution is.

Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.
Continue reading “The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould”

The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould

The Theorem Every Data Scientist Should Know (Part 2)  #MachineLearning #DataScience

  • The standard deviation of the population distribution is tied with the standard deviation of the sampling distribution.
  • With the standard deviation of the sampling distribution and the sample size, we are able to calculate the standard deviation of the population distribution.
  • The standard deviation of the sampling distribution is called the standard error.
  • The mean of the sampling distribution will cluster around the population mean.
  • If we collect a large number of different samples mean, the distribution of those samples mean should take the shape of a normal distribution no matter what the population distribution is.

Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.
Continue reading “The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould”

The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould

The Theorem Every Data Scientist Should Know (Part 2)  #MachineLearning #DataScience

  • The standard deviation of the population distribution is tied with the standard deviation of the sampling distribution.
  • With the standard deviation of the sampling distribution and the sample size, we are able to calculate the standard deviation of the population distribution.
  • The standard deviation of the sampling distribution is called the standard error.
  • The mean of the sampling distribution will cluster around the population mean.
  • If we collect a large number of different samples mean, the distribution of those samples mean should take the shape of a normal distribution no matter what the population distribution is.

Read the full article, click here.


@MikeTamir: “The Theorem Every Data Scientist Should Know (Part 2) #MachineLearning #DataScience”


Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.


The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould

ISC High Performance 2016

Intel #XeonPhi is latest technology for high-performance computing & machine learning  #ISC16

  • Now in its 31st year, ISC High Performance is the world’s oldest and Europe’s most important conference and networking event for the high performance computing community.
  • Intel’s first bootable host processor is specifically designed for highly parallel workloads.
  • A bootable x86 CPU, the Intel Xeon Phi processor offers greater scalability and is capable of handling a wider variety of workloads and configurations than accelerator products.
  • It is also the first to integrate both memory and fabric technologies.
  • Among this year’s new products is the Intel® Xeon Phi™ processor.

Read the full article, click here.


@intelnews: “Intel #XeonPhi is latest technology for high-performance computing & machine learning #ISC16”


Now in its 31st year, ISC High Performance is the world’s oldest and Europe’s most important conference and networking event for the high performance computing community. At this year’s show, Intel will introduce and showcase a range of new technologies helping to fuel the path to deeper insight and HPC’s next frontier.


ISC High Performance 2016

Smart Home Hub Brings Artificial Intelligence Into Your Home – News Center

#SmartHome hub by @ai_build brings #AI into your home with the help of NVIDIA Jetson TX1

  • A new AI-powered device will be able to replace all of your various smart home control apps, as well as being able to recognize specific people and respond to a range of emotions and gestures.
  • The startup plans to launch a crowd-funding campaign later this year to and sell the device for about $1,000 each.
  • AI Build is a London-based startup focused on making your smart home more natural and intuitive.
  • It learns your preferences, recognizes your body language , and adapts its actions with your comfort in mind.
  • Powered by an NVIDIA Jetson TX1 and six cameras, the aiPort keeps track of your daily activities and uses this knowledge to get better at helping you.

Read the full article, click here.


@GPUComputing: “#SmartHome hub by @ai_build brings #AI into your home with the help of NVIDIA Jetson TX1”


A new AI-powered device will be able to replace all of your various smart home control apps, as well as being able to recognize specific people and respond to a range of emotions and gestures.


Smart Home Hub Brings Artificial Intelligence Into Your Home – News Center

Artificial Intelligent Art May Soon be on the Cards for Google

Artificial Intelligent Art May Soon be on the Cards for Google  #AI

  • Google’s new project, Magenta is due to be released on June 1 and is set to take the world of art by storm.
  • Currently listed on GitHub, the project is soon to spark interest and may be developed faster than Google expected.
  • The necessity of public safety has driven Google to patent…
  • Artificial Intelligent Art May Soon be on the Cards for Google
  • The project is part of the Google Brain group, which is a deep learning project that has been operating since 2011 and is focused on solving the problems scientist face with artificial intelligence.

Read the full article, click here.


@adamfalat: “Artificial Intelligent Art May Soon be on the Cards for Google #AI”


Google’s new project, Magenta is due to be released on June 1 and is set to take the world of art by storm. The project is part of the Google Brain group, which


Artificial Intelligent Art May Soon be on the Cards for Google