Automation Survey Finds Network Engineers Need to Learn How to Code

Senior leaders, IT operations, and network engineers agree automation is a priority to keep the lights on as 68% of automation projects are commissioned to maintain network availability:

  •  71% of organizations are implementing automation to increase productivity, 68% to reduce cost
  •  68% of IT projects leading to automation implementation are focused on Network Availability
  •  Talent for automation initiatives (57%) and existing network management responsibilities (50%) are preventing implementation of automation

Programming Knowledge Needed

Automation Survey Finds Network Engineers Need to Learn How to Code

Indeni, provider of the crowd-sourced network automation platform, in partnership with GNS3, the world’s largest open source networking community and a subsidiary of SolarWi…

Source: venturebeat.com/2018/02/06/automation-survey-finds-network-engineers-need-to-learn-how-to-code/

“Is Hypnosis Fake?” Hypnotist stuns TEDX crowd

“Is Hypnosis Fake?” Hypnotist stuns TEDX crowd

Most people think hypnosis is some kind of trick. Religion calls it sinful. Science has questioned its very existence. Hypnotist, Laughologist and acclaimed Filmmaker Albert Nerenberg, (Laughology, You Are What You Act) asks: What happens if you run a series of standard hypnotic inductions on a large crowd such as the audience at TEDXQueens. Is hypnosis fake? Let’s find out. The results are stunning. This comical presentation may finally provide a street science explanation for how hypnosis actually works.

Source: www.youtube.com/watch?v=1RA2Zy_IZfQ

Drake — Using Natural Language Processing to understand his lyrics

Drake — Using Natural Language Processing to understand his lyrics

Introduction:

Every couple of years there is an artist who seems to take the world by storm. In the past, this has been The Beatles and Michael Jackson, among others. These artists have the intrinsic ability to influence millions with their creative genius. It seems that when we started the second decade of the 21st century, a multitude of artists were jockeying to be number one. However, perhaps unexpectedly, a Toronto native by the name of Aubrey Graham ascended to the top under the stage name “Drake.”

Drake’s original claim to fame was from his role on the popular teen sitcom “Degrassi: The Next Generation” in the early 2000s. However, Drake left the show when he figured he wanted to become a rapper. Lil Wayne, one of the most influential rappers at that time, made the Toronto Native his protege. After signing with Wayne’s record, Young Money Entertainment, Drake released his first Studio Album, So Far Gone. It was certified Platinum and expedited Drake’s rapid ascent to the top of the hip hop world. Over the course of the next eight years he dropped four additional studio albums, a mixtape, and a playlist, with Scorpion being his most recent release (source).

We know for a fact that Drake’s work is popular but why are the majority of his songs such a hit? Is it the production? Is it the marketing? It is probably a combination of factors. However, the aspect I will be focusing on is his lyrics. Drake’s work is expansive and well-documented, so getting text data was not a difficult task. However, figuring out how to analyze it was. But thanks to recent improvements in NLP (Natural Language Processing), analyzing text data is now easier than ever.

Shuttershock licensed photo:raindrop74

According to Wikipedia, Natural Language Processing (NLP) “ is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.” NLP is the most interesting field of machine learning in my opinion. Text is produced in so many different forms, its gives us so much data to work with.

Source: towardsdatascience.com/drake-using-natural-language-processing-to-understand-his-lyrics-49e54ace3662

The rise of ‘pseudo-AI’: how tech firms quietly use humans to do bots’ work

The rise of ‘pseudo-AI’: how tech firms quietly use humans to do bots’ work

Using what one expert calls a ‘Wizard of Oz technique’, some companies keep their reliance on humans a secret from investors

It’s hard to build a service powered by artificial intelligence. So hard, in fact, that some startups have worked out it’s cheaper and easier to get humans to behave like robots than it is to get machines to behave like humans.

“Using a human to do the job lets you skip over a load of technical and business development challenges. It doesn’t scale, obviously, but it allows you to build something and skip the hard part early on,” said Gregory Koberger, CEO of ReadMe, who says he has come across a lot of “pseudo-AIs”.

“It’s essentially prototyping the AI with human beings,” he said.

This practice was brought to the fore this week in a Wall Street Journal article highlighting the hundreds of third-party app developers that Google allows to access people’s inboxes.

In the case of the San Jose-based company Edison Software, artificial intelligence engineers went through the personal email messages of hundreds of users – with their identities redacted – to improve a “smart replies” feature. The company did not mention that humans would view users’ emails in its privacy policy.

Source: www.theguardian.com/technology/2018/jul/06/artificial-intelligence-ai-humans-bots-tech-companies

Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe

Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe

From healthcare and security to marketing personalization, despite being at the early stages of development, machine learning has been changing the way we use t

Source: www.altexsoft.com/blog/datascience/choosing-an-open-source-machine-learning-framework-tensorflow-theano-torch-scikit-learn-caffe/