Category Archives: Artificial Intelligence

#AIChat Summary (Wed, Jul 4/18)

This is a summary of #AIChat (it’s a Twitter chat on artificial intelligence).

On Wednesday, July 4th, our guest was Roxana Nasoi.

We talked about artificial intelligence.

And it’s impact on the medical field.

Here’s the link to this conversation:

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Can Artificial Intelligence (AI) Protect Your Content from Hackers?

The Internet.

It’s the key for billions of people to watch your show.

If you’re using a secure cloud technology, someone will try to steal your content.

The problem? Hackers are

  1. targeting your vendors or your servers. To get the movies and TV shows before they’re released and
  2. betting that your vendors have a weak network security. That allows them to steal and hold your content for ransom.

Your goals?


  • disrupt attacks before they occur
  • manage risk and compliance issues and
  • make better use your security resources.

From an anti-piracy point of view, you can use the best technologies to guard your content at every step of the creative process. But these innocent devices will be used to hack your server:

  • bonded cell/wifi camera backs
  • smart phones on set
  • USB stick and
  • personal information on remote productions.

Keep in mind that not all your customers have the same content security needs.

The system must be flexible to work with customer’s needs without having to create a customized solution for each one.

And you’ll need an integrated analysis, a powerful user insights into what people are watching.

One solution?

You could use a premium security to protect your content, like white box cryptography. Or watermarking.

Or use an audience detection per view transaction company. That bridges the gap between the theatrical release and streaming services. For example, companies such as XCinex offers a per viewer ticketing model. Everyone in the room must have a ticket as if they’re going to a movie or concert. No ticket? No show.

But have you considered how artificial intelligence (AI) can help you?

By using

  • machine learning (ML) to analyze data to protect your IT systems. Machine learning can help you to identify the weak network elements or hosts where malware can exploit the weakness in the network. While scanning the network to identify and eliminate false positives and
  • behavior analytics. Instead of using a learned behavior approach (pre-learn or dynamic learning) over a period of time, AI can analyze network, application and user behavior to identify problems to prevent attacks.

Detecting threats to your servers is the main focus of AI and machine learning’s technology push.

Machine learning, advanced analytics and cutting edge technology will help companies track the data from their networks and Internet.

Big data will help you stay one step ahead of the hackers.

Before they can steal your content.

End Notes

Kadakia, Smit. “So, How Does Machine Learning Apply to Cyber Security?” ITSP Magazine (

Ng, David, Ryan Faughnder and Paresh Dave. “Cyberattacks once again roil Hollywood but can anything be done about it?” May 23rd, 2017

Oggel, Peter. “Mastering security to transform your media business.” (, July 13, 2017

\Suciu, Peter. “OTT. The Challenges of Infrastructure: ‘Quality of Service’ not guaranteed.”TV Technology (, July 21, 2017

Thomas, Brian E. “Why AI is crucial to cyber security.” June 16, 2017

Tribbey, Chris. “Deep Inside The Internet Backbone.” (, July 17th, 2017

Vogel, Beth. “How Does Your Digital Transformation Effort Stack Up” May 3, 2017

Wong, Steve. “Hacking Hollywood: How Safe Is Your Data?”




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Summary of #AIChat with @ConnektInc (Tuesday, April 24th, 2018)

On Twitter (@nickhtang), I have a monthly Twitter Chat devoted to talking about artificial intelligence.

For this month’s talk? My guest was Tripp Boyle, SVP @ConnektInc. We talked about artificial intelligence, television and voice assistants.

Q1) Why could TV be a catalyst for voice shopping?





Q2) What’s the role of AI?





Q3)Which types of TV programs have the biggest t-commerce potential?



Q4) Why are consumers still resisting from using a voice assistant to buy a product during or after a TV show?






In the News

I was interviewed by Cathy Hackl (Twitter: @CathyHackl) on my thoughts on artificial intelligence and how it could change reputation management and communications.

Here’s the link to her article:





Artificial Intelligence (AI) – Your Friend or Foe in the Entertainment Industry?

*** A thank you to Mia Dand, CEO of for editing this article. ***

Artificial intelligence (AI) is currently used in the entertainment industry. Combined with machine learning (ML) it can help networks and others get their content seen by the right people(1). It can also suggest to viewers what to watch next based on their interests. The key? Analyzing the metadata that’s used in the search optimization, ad targeting and recommendations.

How does machine learning help program AI?


  • Using natural language processing to analyze the dialogue in the TV show. To creates a series of themes
  • Analyzing the dialogue between actors helps it and AI examine the mood and personality traits of the main characters which allows consumers to find specific scenes and episodes
  • Gaining a deeper understanding of the video content. An example? The personality traits being displayed by an actor.

For example, Amazon uses AI to analyze scenes, objects and faces. It helps the company figure out what the viewers are clicking on.

When media and entertainment (M&E) businesses use ML, it helps them:

  • build logo and brand recognition and
  • determine how audiences are reacting to the content. The data can be used to market, personalize and stop consumers from switching to another service.

As AI starts using voice search in devices, the pay TV industry uses it to improve the viewer experience. An example? Food Network launching a search capability on Amazon voice enabled devices (Amazon Echo, Echo Dot, Amazon Tap, Amazon Fire TV). The viewer asks the devices about Food Network programs, schedules, recipes and more.

In the advertising world, AI can be used to personalize the content for the customer and advertiser. By using content intelligence, AI can examine what the viewers are watching and when and provides the advertiser a one to one marketing approach to the viewer.

Advertisers should consider AI as their partner that helps them analyze the data to find a fast solution (2). The pros and cons of using AI?


  • AI can be used for targeting and helping discover people to target the ads. It includes bidding efficiently for the ads and
  • AI can be used to build B2B sales leads.


  • AI can’t answer questions that have a broad answer. For example, it can’t recommend which social media platform to use for an advertising campaign (there’s no consistent measurement across these platforms)
  • AI can’t analyze data from consumer surveys or media consumption data. Media planners need to define the data before AI analyzes it and
  • AI can’t write long ads.

In the film industry, AI helps a movie studio figure out whether or not to make the film by analyzing the screenplay. Or determines the box office potential of a film before it’s released by using a neutral network algorithm to analyze 30 years worth data (box office revenues, film budgets, audience demographics and casting information).

Here are two examples where AI was used to write a short screenplay or scene:

  • an AI named Benjamin wrote the short film Sunspring by examining hundreds of movie scripts from the 80’s and 90’s. This is the first time an entire screenplay has been written by AI.
  • In the film “It’s No Game”, AI was used to write David Hasselhoff’s line. The machine learning algorithm learned to create long sentences based on learning rules from a corpus (composed of dialogue taken from several collections of films and television series) of writing. Another algorithm was used to create short sentences from the words.

AI can automatically create an edited clip that can be sent to another company or given to a human editor to create the final clip. For instance, IBM Watson selected the 10 most usable moments from the horror movie “Morgan.” The human editor created the movie trailer from the clips. This was done in 24 hours instead of taking 10-30 days using a human editor.

As machine learning continues to evolve, media companies can use the technology to create other types of content such as series and movie reviews (AI can find the data from different reviews to see what the critics or consumers are saying about it on social media or online).

AI should be seen as a partner.

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