Artificial Intelligence | Information Ninja

02/18/2019

#AIChat

Cupcakes and cocktails.

This is a summary of #AIChat (a 30 minute Twitter chat on artificial intelligence). Where my guest(s) cut through the artificial intelligence noise.

On February 12, 2019, my guests? Kerry Harrison (@copywriterkerry) and Richard Norton (@ericbratislava) from @wearetinygiant (https://www.tinygiant.io/) The topic? #AI #cupcakes #alcohol #augmentedcreativity

*** Mistakes are mine. ***

Here’s Q1 for @ericbratislava and @copywriterkerry

I love your #AI and #cupcakes idea (https://t.co/fZ2ZfBZd4e) . Q1) How does this demonstrate the potential of #AI and #humans working together? #AIChat pic.twitter.com/qDpI9wLOa8

— Nick Tang (@nickhtang) February 12, 2019

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The neural network came up with recipes we'd never have considered before. The human brought all her experience in cake making to dial up and down the ingredients to make them taste amazing.

— Kerryharrison (@copywriterkerry) February 12, 2019

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A1: Our AI cupcake project https://t.co/SY1OwYHgjl was all about human-AI collaboration. The neural network generated 80 recipes, which were weird and wonderful. We then collaborated with a cake expert to make them a reality.

— Kerryharrison (@copywriterkerry) February 12, 2019

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A1 Interesting as we are now seeing the surge of #AI vending machines although most are #ML not AI but everything from custom cupcakes to dentistry is being vending machine tested globally🌐🤔 #AIChat

— BrainBlender🤔🌐 (@BrainBlenderTec) February 12, 2019

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What a sweet fusion! 🧁 Thanks for introducing us to this. Looking forward to hearing more about how you augmented traditional recipe development with AI. #AIChat

— Adlib Software (@adlibsoftware) February 12, 2019

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As you continue to discuss Q1, we’re going to switch to #AI and #cocktails! Based on this article: https://t.co/HA6WaL53Hi #AIChat

— Nick Tang (@nickhtang) February 12, 2019

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Here’s Q2 for Eric (@ericbratislava) and Kerry (@copywriterkerry) from @wearetinygiant (https://t.co/n5q3Y7uz4J) Q2) How did the bartender feel when he was following the #AI recipe? #AIChat

— Nick Tang (@nickhtang) February 12, 2019

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#AIChat A2: TBH he was a little nervous. He was concerned the AI would replace him and take his job. But after a while playing with the AI-generated recipes, he realised that he could bring his experience and creativity to the mix. And he could create something very different.

— Kerryharrison (@copywriterkerry) February 12, 2019

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#AIChat For example, one of the AI-generated recipes had ice cream in it. Normally ice cream is put on the top of drinks (Coke float) but the mixologist decided to blend it in with the other ingredients. And it tasted delicious!

— Kerryharrison (@copywriterkerry) February 12, 2019

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A2 Therein is the issue as now you can have a bot bartender that makes the recipe identical every time but using #AI can vary to personal preference 🌐🤔 #AIChat

— BrainBlender🤔🌐 (@BrainBlenderTec) February 12, 2019

https://platform.twitter.com/widgets.js

Tagged alcohol, Artificial Intelligence, cocktails, Cupcakes

01/22/2019

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#AIChat, Artificial Intelligence

What’s a Digital Twin? (#AIChat – Jan 10/19)

My guest? @RobTiffany. The topic? The value of digital twins to model machines, processes and businesses. Mistakes are mine. Not Rob’s. P.S. The goal of #AIChat? To help you cut through the artificial intelligence noise.

** 10 min until #AIChat. Join me from 2PM ET to 2:30PM ET My guest? @RobTiffany. The topic? The value of digital twins to model machines, processes and #business P.S. This is a 30 minute #AIChat. P.P.S. A S/O to @vfiorese_ for suggesting @RobTiffany as an #AIChat guest. ** pic.twitter.com/TtsZHNs5RJ

— Nick Tang (@nickhtang) January 10, 2019

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Twitter Universe.

Welcome @RobTiffany!

It’s a 30 minute #AIChat.

Let’s hit the ground running.

Here’s Q1) Can you define what’s a digital twin? #AIChat

— Nick Tang (@nickhtang) January 10, 2019

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A1: In it’s simplest form, a digital twin is a digital representation of a physical object. This could be a machine, a person, or even a process. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A1.1: For some history, digital twins were originally created by NASA to have high-fidelity models of spacecraft for design and troubleshooting. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A1 follow-up. Is there such a thing as a wrong #digital #twin #AIChat?

— Nick Tang (@nickhtang) January 10, 2019

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A1.2 A digital twin can be wrong and therefore deliver bad results if it’s properties or attributes don’t match the physical object precisely. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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Q 1.3 Can a digital twin be more observable than the object it represents and does that make it less than a twin? #aichat

— spara (@spara) January 10, 2019

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A1.3: Digital twins tell the story of the machine #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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Still in use. DART https://t.co/n6IdVbRUg7 #aichat

— spara (@spara) January 10, 2019

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A1.4: Since a #DigitalTwin can carry more measured and calculated data than the physical object, I think it makes it a super twin. In a well-functioning system, the twins will drive all your operations. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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It does, but it makes it seem that the digital twin is the system controller. #aichat

— spara (@spara) January 10, 2019

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Here’s Q2 for @RobTiffany (it’ll help you with his definition of #digital twin in Q1)

How does a digital twin link to model machines, processes and business? #AIChat

— Nick Tang (@nickhtang) January 10, 2019

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A2: For starters, I believe that #digitaltwins should be at the heart of any #IoT system since you can’t understand the telemetry #data being collected without modeling the schema or shape of the object producing the data to provide context. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A2.1: When physical machines and people are connected to an #IoT system via a #digital thread of near real-time data, the digital twin is brought to life. You can see the latest state of the physical object as well as its history by viewing the digital twins. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A2.2: Beyond being a mirror of physical objects, digital twins can also carry rules, KPIs and #Analytics with them that are triggered when new #data arrives. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A2.3: The #DigitalTwin can map measure values to sensors from a physical object but it can also contain virtual or calculated values that are derived dynamically. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A digital twin does a great job of properly organizing the data relevant to a physical object which makes it easier for advanced analytics, #MachineLearning, and #DeepLearning to do their thing. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A2.4: The more #data your #DigitalTwins accumulate, the better the results will be from #AI. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

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A2.5: Classes of machines that are the same as each other can be improved when the #digitaltwin of one machine solves a problem that can be shared across a fleet. #aichat

— Rob Tiffany 🇺🇸 (@RobTiffany) January 10, 2019

https://platform.twitter.com/widgets.js

Tagged Artificial Intelligence

01/22/2019

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#AIChat, Artificial Intelligence

No. #AI won’t take over a journalist’s job: #AIChat summary: Jan 11/19

#AIChat is a Twitter Chat where my guest(s) cut through the artificial intelligence.

#AIChat session with @the_claus and Professor @NeilMaiden

Talking about @inject_en

Mistakes are mine.

Q1) How does @inject_eu work? #AIChat

— Nick Tang (@nickhtang) January 11, 2019

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A1 So, INJECT is a new digital tool to support journalists to write more original journalism, more quickly than now. It combines NLP, information retrieval, entity extraction and recommender tech to present journalists with content to inspire new angles on stories #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1 followup: Does someone sort through the information INJECT gathers to make sure that there’s no bias in the article? #AIChat

— Nick Tang (@nickhtang) January 11, 2019

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A1. The team maintains an editorial board to manipulate news creatively from different better researched sources #AIChat. But creative ideas can come from all sources, so more sources are better…

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1 followup: It is hard to find journalistic content without ANY bias. Since we are all (still) humans, everything we write is based on our upbringing etc

— Claus Hesseling (@the_claus) January 11, 2019

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INJECT could help journalists to overcome their own biases – in helping the to see "opposing" things #AIchat

— Claus Hesseling (@the_claus) January 11, 2019

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A1 The heart of INJECT is a set of creative search algorithms that operationalize expertise of experienced journalists in strategies. User choices to explore, for example numbers and evidence, or human angles, or comedy, invoke different creative search algorithms #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1. Unlike robot-journalism and other #AI uses, INJECT does not seek to replace any key element of a journalist’s work. Instead, it uses different technologies to enhance/empower journalists operating in less and less time, and fewer resources. Journalists control the AI #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1 Our INJECT team are currently designing new algorithms to manipulate the creative news index (now over 10million articles) to discover new, evolving, breaking and under-reported angles on topics. These new features should be available by the summer #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1 In background, 24/7, INJECT generates creative indexes of news stories. Using RSS, it reads and makes sense of about 15000 stories published each day from 300+ titles in 6 languages, and builds a rich index from which to generate creative guidance for journalists #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A1 Furthermore, to support hyper-local and specialist journalism, INJECT’s algorithms can read and make sense of local news and other types of archive, so that INJECT’s creativity support can exploit these information assets #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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Many journalists are afraid of algorithms and #AI – but INJECT's mission is to create AI tools that support journalists #AIchat

— Claus Hesseling (@the_claus) January 11, 2019

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As we’re talking Q1, here’s Q2 for Professor @NeilMaiden and @the_claus How does @inject_eu help journalists and their newsrooms? #AIChat

— Nick Tang (@nickhtang) January 11, 2019

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A2: #AIChat. INJECT is different from other search engines. Engines like Google look to return the best-fit that you asked for. INJECT takes what you ask for, and gives you something a little different. Many people struggle with idea, at first. I think of it as ‘Googlisation’

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2 Journalists also use INJECT in unpredicted by creative ways. For example some freelancers use it to prepare for interviewing people, others to discover new stories and outlines to pitch to editors #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2) NYT or WaPo have great archives – and if you use it right it can be a goldmine. But smaller news outlets often don't have to resources to do that. INJECT could provide help here #AIchat

— Claus Hesseling (@the_claus) January 11, 2019

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A2 #AIChat By ‘smart’ archive, we mean that we attach machine-readable semantics to published articles. We can extract content, tag it with inferred meanings, and manipulate these INJECT inferences in the tool’s reasoning engines

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2 #AIChat. Yes, Claus raises a key issue. Many media organisations are seeking to make smarter use of their #news archives, and journalists also want to be inspired by what they themselves have written before

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2. Our studies with INJECT reveal that INJECT works better to support more original feature articles. So our recent focus has been to support news and media businesses focused on quality #journalism. #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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Follow up Q in response to A2: It's great that you are surfacing smaller publications!! Given the problems we've had with fake news lately, how do you ensure the news (source) is credible? #AIchat

— Mia Dand (@MiaD) January 11, 2019

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A2 #AIChat. Mia – we have chosen a set of over 300 publication titles in many countries across 3 languages, to reduce the risk of bias, echo chambers etc. But this approach is not foolproof. So INJECT seeks to empower journalists to avoid ill-researched sources

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2: Adding to that: Even big new organisations get things wrong. So far there is no AI to solve this #AIchat

— Claus Hesseling (@the_claus) January 11, 2019

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A2: Plus: With INJECT also smaller publications can make us of AI and machine learning. With our tool they can turn their "dumb" archive into "smart" archive #AIChat

— Claus Hesseling (@the_claus) January 11, 2019

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A2 Our studies of INJECT newsrooms have shown that its use improved the novelty of articles written by journalists over a period of months. Journalists generated not only new angles but also new content and new forms of content #AIChat

— Neil Maiden (@NeilMaiden) January 11, 2019

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A2) and an essential one to keep in mind. Even with the AI software, it’s still up to the reporter to make sense of it all. In order to create a well balanced article. #AIChat

— Nick Tang (@nickhtang) January 11, 2019

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Well-said @nickhtang I am a big fan of quality journalism and any technology that helps surface content from the smaller publications that get overshadowed by the big outlets…!!! #AIchat

— Mia Dand (@MiaD) January 11, 2019

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#AIChat One wider observation is that journalists seek more original news stories. This requires #creative thinking of different forms. In this sense INJECT is different for uses of machine learning tools in news

— Neil Maiden (@NeilMaiden) January 11, 2019

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#AIChat Thanks to Nick and Mia. You can find out more about our INJECT project and product at https://t.co/AmHC0aW6Zx

— Neil Maiden (@NeilMaiden) January 11, 2019

https://platform.twitter.com/widgets.js

Tagged Artificial Intelligence, Journalism

01/22/2019

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#AIChat, Artificial Intelligence

Welcome to 2019. Is it Time to Tax the Artificial Intelligence and Robots Who Take our Jobs?

This is the first unofficial #AIChat for 2019.

#AIChat is a Twitter chat that helps you demystify artificial intelligence.

This topic?

Started by @JBarbosaPR.

Should #AI and #robots pay taxes? Mistakes are mine. Not @JBarbosaPR

There has to be a clear intent to make #AI & #Robots pay taxes . Beware, To the masses its a farfetched idea, but the implications of NOT addressing it are unnerving. #society #jobs #taxes #AI #unemployment #disruption @MiaD @nickhtang pic.twitter.com/5TlZuV3B1z

— Jan Barbosa 🐝 (@JBarbosaPR) January 3, 2019

we don’t tax the tools we use to make products,
and AI and Robots are just tools, nothing too tax,
the product that is sold is what should be taxed.

— Stanley Waite (@stanleywaite1) January 3, 2019

Taxing robots is crazy and impractical. Should we tax washing machines? How about software? Can you even define the robots that would be taxed?

— Peter Harris (@2peterharris) January 3, 2019

Well #robotics / #AI could wipe out entire departments and make many blue collar jobs obsolete. How many could be trained ? I gave training overseas to a dept changing from paper to digital and a few people just quit their jobs the first day as jobs dry up who pay the tax?

— Jan Barbosa 🐝 (@JBarbosaPR) January 3, 2019

Noting there is a problem is not the same thing as having a good solution. It may be that technology will affect jobs, but taxing robots is not the answer. Software will displace more people than robotic machines, by far.

— Peter Harris (@2peterharris) January 3, 2019

Feel #AI is seen more as a cost cutting tool than a job empowering tool. Already soaring GNP is not representative of economic state of a country as workplace is doing more with less workers and far less salaries.

— Jan Barbosa 🐝 (@JBarbosaPR) January 3, 2019

Cost reduction and productivity improvement are the same thing… In any case, if you propose taxing robots, you first need to define robot, which I submit will be a hard thing to do.

— Peter Harris (@2peterharris) January 3, 2019

Agree, and I get its not in the mind of #techs to implant taxes / use of tech politics. But same for #CRISPR , #AI use, or Job Cutting #tech it will finally rest in the hands of politicians / society / economist to decide possibly never the techs. Great idea for #AICHAT 🤔

— Jan Barbosa 🐝 (@JBarbosaPR) January 3, 2019

Most of it rests in the hands of the developer as they can hold or launch a disruption which usually is far ahead of what Gov is ready for🌐🤔 #AIChat

— BrainBlender🤔🌐 (@BrainBlenderTec) January 3, 2019

Value creation that is not done by human beings needs to pay for the viable marketplace of consumers, who cannot consume if value creation is done by robots. Only in totally insane world do you have robots created to buy stuff they have no idea why there were programmed to buy.

— CityVP Manjit (@CityVP) January 4, 2019

Corporations have Personhood , yet their personhood allows far more flexibility than ours. In a globalized world corporate personhood can move freely between states and achieve perks as tax benefits than humans cant. Then why not #AI / robots fall under same rules ? #ethics #AI

— Jan Barbosa 🐝 (@JBarbosaPR) January 4, 2019

I don’t believe that corporations are people but if you can get 5 votes to swing your way on the Supreme Court – all bets are off. The 1% are not robots, they are living flesh and blood people who need robots to squeeze the next bit of green juice from their plutocratic economy.

— CityVP Manjit (@CityVP) January 5, 2019

Thank you for raising an important, largely overlooked issue: “Why we should start taxing the robots that are taking human jobs (How #automation helps tax avoidance)” via @TC_Africa https://t.co/Z7xmAWNw5D #4IR #AI #Robotics

— Glen Gilmore 🚀 #MWC19 (@GlenGilmore) January 4, 2019

i fully disagree with the idea of taxing the robots…
there has been no problem for decades with the robots that have been used in the car industry, workers have all found new jobs to do and cars became cheaper or better for the same price, more sales generated more tax gained.

— Stanley Waite (@stanleywaite1) January 4, 2019

What Jan is proposing isn’t all that far-fetched. Appliances like washing machines are already taxed and so are software, services, etc. We will need to rethink the tax code to accommodate this new category of “robot service providers”.

— Mia Dand (@MiaD) January 3, 2019

Then what you are likely proposing is something more like a broad tax on capital assets, including software. Remember, a machine tool is just another automated worker. But, taxing sources of productivity enhancement is generally bad economics..

— Peter Harris (@2peterharris) January 3, 2019

Our current tax code isn’t adequate to cover the variety of form factors that robots/AI may take in future. Will need input from tech, law makers, accountants, AI ethicists etc. to come up with a solid taxation model. Either way, good discussion! Thanks all!

— Mia Dand (@MiaD) January 3, 2019

This article is discusses the problems that are not solved with taxing robot / AI owners. It is about more than the universal income. https://t.co/xRm9qpECRy

— Kevin K. Conroy (@KevinKConroy) January 3, 2019

Tagged Artificial Intelligence

11/01/2018

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#AIChat, Artificial Intelligence

#AIChat Summary -> Wed. Oct 24th, 2018

#AIChat is a 60 minute Twitter chat on artificial intelligence (AI).

Where my guest cuts through the AI noise.

To give you actionable advice you can use at work.

Today’s guest? Tricia Howard. Tricia is the best when it comes to #cybersecurity. She works as @Optiv. And you can read her cybersecurity articles on her website: https://triciakickssaas.com/. Or from her Twitter account (@TriciakicksSass)

The topic? AI and cybersecurity.

Here’s question Q1) How is #AI being used in #cybersecurity? #AIChat pic.twitter.com/d5ijfrpyLZ

— Nick Tang (@nickhtang) October 24, 2018

A1 – There are two sides to this, the whitehat side and the blackhat side. From the good side, there is everything from cognitive search engines, ahem, @IBMWatson, all the way to zero-day #malware protection. One of the most practical applications is the #UEBA factor. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A1 (2) Being able to recognize anomalies in user behaviour which kicks off an automated workflow.The most exciting to me personally is the automated data lake. Data is only as good as what you use it for. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A1 (3) When we talk #BigData someone has to be there to ingest and make sense of all of it to bring out real business use cases. #AI can do that, and at a fraction of the time it would take for humans to analyze. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A 1: AI and Machine Learning are being combined to provide insights that humans can’t catch in devices – anomalies, speed up detection, and other subtle, notable patterns that could indicate a breach of security. #AIChat

— US Cybersecurity Mag (@USCyberMag) October 24, 2018

A1 – suppose your system admin’s master password was #hacked. #AI will detect that the credentials were used from Pakistan – but your admin 👩‍💼 lives in Miami. It will trigger a big red flag and sound the alarm bells.

— Avrohom Gottheil (@avrohomg) October 24, 2018

We agree with @USCyberMag!

“As with any new technology, there will be failures”

— Proven Data (@Proven_Data) October 24, 2018

While you’re all discussing Q1 for @TriciaKicksSaaS, let’s start on Q2. What are the challenges of using #AI in #cybersecurity? #AIChat pic.twitter.com/MNXDxAoE0d

— Nick Tang (@nickhtang) October 24, 2018

A2: This is where I was talking about the two sides of #AI. With every great innovation there can be a negative application. From the “bad” point of view – there are so many “hacker toolkits” that automate attacks at a relatively low cost.
#AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A2 (2): It is much more expensive to defend against these attacks than it is to deploy them (most of the time.) There’s still a lot of negative stigma around #AI as well which can be a challenge. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A2 (3): There are still lots of places for improvement for #AI in #security. It’s not a catch-all. There needs to be specific applications for the AI to be used in order for it to be effective… at least until we get truly cognitive ‘beings.” #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A2 The challenge for using #AI in #Cybersecurity is that #technology changes rapidly, and the threat actors are extremely advanced. We have to continue to innovate to stay ahead of the game. #aichat

— Avrohom Gottheil (@avrohomg) October 24, 2018

A2: Challenges could stem from turning over all tasks to automation. #AI still requires some level of human interaction. It’s not a complete replacement, especially when critical data & PII etc are at stake in #cybersecurity. #aichat

— Adlib Software (@adlibsoftware) October 24, 2018

Yep. there always needs to be oversight. Take a light bulb for example: it’s pretty self-sustainable, does its job, etc…until it burns out and needs to be changed. We improve the life of them and optimize them, but they still have to be changed when they’re burnt out. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

As you’re talking about Q2, here’s Q3 for @TriciaKicksSaaS: Do you think #AI will replace humans in #cybersecurity? #AIChat pic.twitter.com/EkSQZsVesB

— Nick Tang (@nickhtang) October 24, 2018

A3: Aha! One of the negative stigmas! I’ve actually written about this (not specific to security) and the answer is no. They will augment humans but not replace them. We will just get more sophisticated – more analytical roles rather than basic blocking and tackling. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A3 (2): True #AI is set it and forget it – and some of this is still rudimentary. We still need people tuning the software until it truly is learning on its own. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A3 (3): Aside from that, as we’ve said here today, there still needs to be oversight and coaching to get the machine to do the intended job. We don’t want to hinder it persay, but we need to be sure we’re keeping an eye on where it’s going to stay relevant. #AIchat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

Along the line wont the capabilities/ problems ahead allow for solely #ai intervention ??? In times when #ai could write its code / modify ( still proto ) just imagine capabilities used as exploitation tool ??? #CyberSecurityAwarenessMonth #CyberSec #cyberattacks #aichat

— Jan Barbosa 🐝 (@JBarbosaPR) October 24, 2018

I wouldn’t say solely #AI, but yes machines will be battling each other. It’s happening now.The bad peeps are using a code to figure out how to get in and the humans are catching up. When the machine becomes truly cognitive there will be AI battles. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A3: The #futureofwork will likely be augmented by #AI, not obliterated because of it. Teams can focus on strategy while #AI focuses on the automated, mundane tasks. #AIchat

— Adlib Software (@adlibsoftware) October 24, 2018

#AI systems yield a large number of false positives. You eventually need the help of human experts to find evidence of security breaches and make critical decisions. Till we attain #singularity 😂

— Archonsec (@archonsec) October 24, 2018

A3) As we have talked about extensively today, #AI has a wide margin for error, and therefore will never fully replace humans. Even when AI is perfected, we simply will have a different set of responsibilities and capabilities. #AIChat

— US Cybersecurity Mag (@USCyberMag) October 24, 2018

A3. Certainly not. #AI will only add up to human resources rather than replacing them for #cybersecurity

AI will be an enabler rather than a replacement for humans when it comes to cyber security.#AIChat

— Moin Shaikh (@moingshaikh) October 24, 2018

Last 10 mins of #AIChat with @TriciaKicksSaaS Talking #AI and #cybersecurity. Here’s the last question! Q4) What are the solutions for the #CISO looking to use #AI and #humans in #cybersecurity? #AIChat pic.twitter.com/HxJ9iJMycX

— Nick Tang (@nickhtang) October 24, 2018

A4: Threat Intelligence is your friend. Using #AI to pull from worldwide feeds with a simple search will be able to seriously beef up your security strategy. Any sort of #NGOA is killer too. The hackers are acting fast, so we need to be responding fast. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

A4 (2): Being able to orchestrate and automate workflows and policies will assist with that. Ways that can augment your human team (especially with the talent shortage) is where you want to be looking to implement #AI into your security strategy. #AIChat

— Tricia A. Howard🦄🎭 (@TriciaKicksSaaS) October 24, 2018

I think the responsibility of a #CISO in regards to #AI and #ML is the same as current Cybersecurity practices. Enforce good practices that shrink the attack surface and set you up for success. AI is just another tool to help modernize and achieve that goal. #AIChat

— US Cybersecurity Mag (@USCyberMag) October 24, 2018

A4: Most of what we’ve discussed on #aichat today has centered on a unified approach between humans and #AI versus a silo approach. One cannot exist without the other.

— Adlib Software (@adlibsoftware) October 24, 2018

A4: AI/Automation should be used when knowing the problem you are trying to solve, which is a process. No point using AI on an inefficient process. That’s why you still do the hard work of modelling first (OODA works) before you implement. https://t.co/3P5igeDI6p #aichat

— Mark C Stafford (@StaffordCyber) October 24, 2018

How #AI Can Be Applied To #Cyberattacks https://t.co/ft2V0LdD1O by @d0znpp via @Forbes #CyberSecurity
Cc @Shirastweet @digitalcloudgal @TriciaKicksSaaS @TamaraMcCleary pic.twitter.com/Hil3UACTg3

— ipfconline (@ipfconline1) October 26, 2018

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Tagged Artificial Intelligence, Cybersecurity

09/13/2018

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#AIChat, Artificial Intelligence

Summary of #AIChat (Tuesday, May 1st, 2018)

#AIChat is a 60 minute monthly chat on artificial intelligence.

Where our guest(s) help you make sense of the artificial intelligence (AI) world.

To give you or your company ideas on how to use AI. At work. Or home.

This is a summary of #AIChat with @pchalasani, Chief Scientist @mediamath. Talking #AI #programmatic #marketing #ads #adtech

https://mobile.twitter.com/i/moments/991397829724667904

Tagged ads, adtech, Artificial Intelligence, marketing, programmatic

09/13/2018

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#AIChat, Artificial Intelligence

Summary of #AIChat on September 6th, 2018

#AIChat is a 60 minute monthly Twitter chat on artificial intelligence.

Where my guest(s) help you make sense of the artificial intelligence world.

To give you artificial intelligence ideas to use at work. Or at home.

September’s guests? Professors Yannakakis and Togelius. The experts in artificial intelligence and gaming.

When you click on the link, you’ll have a recap of the chat:

‪https://twitter.com/i/moments/1037711066300440576‬

Tagged Artificial Intelligence, gaming

07/06/2018

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#AIChat, 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:

https://mobile.twitter.com/i/moments/1014518481578967040

Tagged Artificial Intelligence, Medical

05/16/2018

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Artificial Intelligence

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

targeting your vendors or your servers. To get the movies and TV shows before they’re released and
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 (https://itspmagazine.com/from-the-newsroom/so-how-does-machine-learning-apply-to-cyber-security)

Ng, David, Ryan Faughnder and Paresh Dave. “Cyberattacks once again roil Hollywood but can anything be done about it?” http://www.latimes.com/business/hollywood/la-fi-ct-hacking-disney-netflix-20170523-story.html May 23rd, 2017

Oggel, Peter. “Mastering security to transform your media business.” (https://v-net.tv/2017/07/13/mastering-security-to-transform-your-media-business/), July 13, 2017

\Suciu, Peter. “OTT. The Challenges of Infrastructure: ‘Quality of Service’ not guaranteed.”TV Technology (http://www.tvtechnology.com/resources/0006/ott-the-challenges-of-infrastructure/281371), July 21, 2017

Thomas, Brian E. “Why AI is crucial to cyber security.” http://www.cio.com/article/3201147/cyber-attacks-espionage/why-ai-is-crucial-to-cyber-security.html June 16, 2017

Tribbey, Chris. “Deep Inside The Internet Backbone.” (http://www.broadcastingcable.com/news/technology/deep-inside-internet-backbone/167181#.WW-tYB0Xi00.twitter), July 17th, 2017

Vogel, Beth. “How Does Your Digital Transformation Effort Stack Up” https://blog.box.com/blog/how-does-your-digital-transformation-effort-stack/ May 3, 2017

Wong, Steve. “Hacking Hollywood: How Safe Is Your Data?” http://www.mesalliance.org/wp-content/uploads/2017/04/Hacking-Hollywood-How-Safe-Is-Your-Data-SW-04-24-2017.pdf

Tagged Artificial Intelligence, content

08/16/2017

2 Comments

Artificial Intelligence

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

*** A thank you to Mia Dand, CEO of @LH3.com 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?

By:

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?

Pros:

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.

Cons:

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.

Continue reading →

Tagged Artificial Intelligence, content, media and entertainment

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Tag Archives: Artificial Intelligence

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

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