Who are the “godfathers of AI”?

If you follow latest news about Artificial Intelligence, you will frequently read quotes from the so-called ” Godfathers of AI”. In this post I collected and summarized the 10 most shared stories that made direct references to these godfathers.

The most frequently mentioned AI leaders were:

  1. Geoffrey Hinton
  2. Noam Chomsky
  3. John McCarthy
  4. Marvin Minsky
  5. Allen Newell
  6. Ray Kurzweil
  7. Andew Ng
  8. Yann LeCun

The most frequently mentioned topics were:

  1. Human brain
  2. University of Toronto
  3. Deep learning
  4. Ethics
  5. Google
  6. Neural network
  7. Stanford University
  8. Carnegie Mellon University
  9. Large dataset
  10. Facebook

 

The ” Father of Artificial Intelligence” Says Singularity is 30 years away (futurism.com) – February, 2018

Topics: artificial life, Ray Kurzweil, artificial intelligence, Kurzweil, global warming, world government, chemical evolution, human brains

  • It is that long-awaited point in time — likely, a point in our very near future — when advances in artificial intelligence lead to the creation of a machine (a technological form of life?)
  • Schmidhuber says it “is just 30 years away, if the trend doesn’t break, and there will be rather cheap computational devices that have as many connections as your brain but are much faster,” he said.
  • Of course, the development that he is referring to is the development of these artificial superintelligences, a thing that Schmidhuber says “is something that transcends humankind and life itself.”

AI Spotlight: Meet Professor Geoffrey Hinton, Godfather of AI (techstartups.com) –  December, 2017

Topics: Artificial Intelligence, machine learning, neural networks, deep learning, experimental psychology, data compression, pioneering work, graduate students

  • He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by Christopher Longuet-Higgins.
  • Professor Hinton is currently the leading a government-backed research facility in Toronto who wants to create a partially automated factory that would mass-produce transplantable stem cells into disease-fighting cells using Artificial Intelligence (AI).
  • He and his two graduate students, Alex Krizhevsky and Ilya Sutskever, were hired by Google to develop Android voice search.

‘Godfather’ of deep learning is reimagining AI – Phys.org (phys.org)

Topics: University of Toronto, Toronto, New York University, Wired magazine, Google, Nicholas, Gary Marcus, large datasets

  • Hinton, a University Professor Emeritus at the University of Toronto, recently released two new papers that promise to improve the way machines understand the world through images or video – a technology with applications ranging from self-driving cars to making medical diagnoses.
  • ” This is a much more robust way to detect objects than what we have at present,” Hinton, who is also a fellow at Google‘s AI research arm, said today at a tech conference in Toronto.
  • With his new research, there’s little doubt Hinton is doing his part to move the AI ball forward – even if it draws on ideas he’s been contemplating for the past 40 years.

Noam Chomsky: Where Artificial Intelligence Went Wrong (theatlantic.com) – December, 2017

Topics: practical applications, unified theory, theoretical framework, biological system, cognitive system, information processing, statistical models, systems biology

  • The success of fields like personalized medicine and other offshoots of the sequencing revolution and the systems-biology approach hinge upon our ability to deal with what Chomsky called ” masses of unanalyzed data” —placing biology in the center of a debate similar to the one taking place in psychology and artificial intelligence since the 1960s.
  • One of the points he made was that AI and robotics got to the point where you could actually do things that were useful, so it turned to the practical applications and somewhat, maybe not abandoned, but put to the side, the more fundamental scientific questions, just caught up in the success of the technology and achieving specific goals.
  • Well, if success is defined as getting a fair approximation to a mass of chaotic unanalyzed data, then it’s way better to do it this way than to do it the way the physicists do, you know, no thought experiments about frictionless planes and so on and so forth.
  • One way to do it is okay I’ll get my statistical priors, if you like, there’s a high probability that tomorrow’s weather here will be the same as it was yesterday in Cleveland, so I’ll stick that in, and where the sun is will have some effect, so I’ll stick that in, and you get a bunch of assumptions like that, you run the experiment, you look at it over and over again, you correct it by Bayesian methods, you get better priors.
  • A very different approach, which I think is the right approach, is to try to see if you can understand what the fundamental principles are that deal with the core properties, and recognize that in the actual usage, there’s going to be a thousand other variables intervening—kind of like what’s happening outside the window, and you’ll sort of tack those on later on if you want better approximations, that’s a different approach.

The Godfather of AI Was Almost a Carpenter – Bloomberg (bloomberg.com) – December, 2017

Topics: artificial intelligence, Google, Emeritus Professor, University of Toronto, Geoffrey Hinton, Chief Scientific Adviser, preeminent expert, Vector Institute

  • He is an Engineering Fellow at Google, managing Brain Team Toronto, the Chief Scientific Adviser of the Vector Institute, and Emeritus Professor at the University of Toronto.
  • His name is Geoffrey Hinton, and this Bloomberg 50 profile of him takes a peek into the life of the world’s preeminent expert in artificial intelligence.

The godfather of artificial intelligence is a Torontonian (torontolife.com) – September, 2017

Topics: Google, Apple, Facebook, Uber, health care, neural networks, Toronto, government funding

  • He’s in charge of the Vector Institute, a U of T–affiliated organization that will apply AI to a range of fields, including finance, construction and health care.
  • Vector’s existence is the reason Google and Uber have created AI labs in Toronto—the institute only accepted international funding if its investors set up shop north of the border.

The True Father of Artificial Intelligence – OpenMind (bbvaopenmind.com) – September, 2016

Topics: Caltech, Marvin Minsky, Stanford university, California Institute of Technology, machine intelligence, artificial intelligence, personal computer, Ibm

  • However, McCarthy is enshrined as the father of artificial intelligence not only for managing to open the field and turn it into a new area of research, but also for continuing to provide evidence for its development for half a century.
  • “The speed and memory capacity of today’s computers may be insufficient to stimulate many of the more complex functions of the human brain, but the main obstacle is not the lack of capacity of the machines, but our inability to write programs that take full advantage of what we have,” he came to enunciate in those years.
  • However, despite his efforts, this system did not help McCarthy to achieve his true objective: that a computer would pass the Turing test, according to which a human asks questions through a computer screen, and if he cannot decide whether it’s another human or a machine that is responding, this is definitively intelligent.
  • Near the end of the research stage of his career, in 1978, McCarthy had to give up on his purist idea of ​​artificial intelligence: “To succeed, artificial intelligence needs 1.7 Einsteins, two Maxwells five Faradays and the funding of 0.3 Manhattan Projects,” he resignedly recognized.

Marvin Minsky, “father of artificial intelligence,” dies at 88 (news.mit.edu) – January, 2016

Topics: MIT Media Lab, Marvin Minsky, Harvard University, Seymour Papert, pioneering work, Artificial Intelligence, Princeton University, Nicholas Negroponte

  • Minsky joined the faculty of MIT’s Department of Electrical Engineering and Computer Science in 1958, and co-founded the artificial intelligence Laboratory (now the Computer Science and Artificial Intelligence Laboratory) the following year.
  • Minsky received the world’s top honors for his pioneering work and mentoring role in the field of artificial intelligence, including the A.M. Turing Award — the highest honor in computer science — in 1969.
  • Faculty Achievement Award; the Computer Pioneer Award from IEEE Computer Society; the Benjamin franklin Medal; and, in 2014, the Dan david Foundation Prize for the Future of Time Dimension titled “Artificial Intelligence: The Digital Mind,” and the BBVA Group’s BBVA Foundation Frontiers of Knowledge Lifetime Achievement Award.

Welcome to the AI Conspiracy: The ‘Canadian Mafia’ Behind Tech’s Latest Craze (recode.net) – July, 2015

Topics: big data, computer scientists, machine learning, deep learning, speech recognition, neural network, core technology, tech companies

  • In 2013, Hinton was hired as a distinguished researcher at Google, where he works on its expanding deep learning division; LeCun was tapped to lead Facebook’s AI efforts later that year; and last week, Ibm announced it was working with Bengio, a professor at the University of Montreal, to infuse Watson, its super-computer, with deep learning.
  • Fruits of their efforts are already starting to appear in front of consumers, with deep learning woven into products like the new Google Photos app and in the facial recognition technology infused in Facebook’s new app, Moments.
  • In 2012, the Google “Brain” team — a unit born in Google x with the audacious aim to build the largest artificial neural network, an AI brain — released a seminal finding: They sat the brain in front of millions of Youtube videos and, without input on feline features, it began spotting them.
  • The main reason it has been taking off in the last few years is scale,” said Andrew Ng, the scientist who launched the Google Brain team (called the deep learning team) and currently runs a similar team at Chinese search giant Baidu.
  • “There may or may not be products that come out of this for the next two or three or four or five years,” LeCun told Re/code.

How a Toronto professor’s research revolutionized artificial intelligence (thestar.com) – April, 2015

Topics: big data, Seymour Papert, speech recognition, computer vision, machine learning, DARPA, based systems, Silicon Valley

  • Hinton now spends three-quarters of his time at Google and the rest at U of T. Machine learning theories he always knew would work are not only being validated but are finding their way into applications used by millions.
  • He arrived that summer for what he describes as a trial run — he was hesitant to leave Toronto, where he has lived with his family for most of the past quarter-century — and the short-term stint didn’t have any other obvious job title.
  • The man who designed it claimed it would eventually be able to read and write, and the story said it would be the “first device to think as the human brainPerceptron will make mistakes at first, but will grow wiser as it gains experience.”
  • Ask anyone in machine learning what kept neural network research alive and they will probably mention one or all of these three names: Geoffrey Hinton, fellow Canadian Yoshua Bengio and Yann LeCun, of Facebook and New York University.
  • “It’s good to have some people considering the ethics and implications of this sort of thing, but it’s not something I’m worried about any time in the next, say, 40 years,” says Google senior fellow Jeff Dean.

 

John McCarthy: Computer scientist known as the father of AI (independent.co.uk) – November, 2011

Topics: Silicon Valley, Artificial Intelligence, Marvin Minsky, California Institute of Technology, Stanford, cloud computing, Steve Jobs, computer scientist

  • John McCarthy, an American computer scientist pioneer and inventor, was known as the father of Artificial Intelligence (AI) after playing a seminal role in defining the field devoted to the development of intelligent machines.
  • In 1958 he created the Lisp computer language, which became the standard AI programming language and continues to be used today, not only in robotics and other scientific applications but in a plethora of internet-based services, from credit-card fraud detection to airline scheduling; it also paved the way for voice recognition technology, including Siri, the personal assistant application on the latest iphone 4s.
  • Described as ” focused on the future,” McCarthy was ” always inventing, inventing, inventing,” and in the 1960s he conceived the idea of computer time-sharing or networking, which allowed users to share data by linking to a central computer; it ultimately lowered the cost of using computers.

What are the best machine learning blogs?

While building Frase‘s RSS feed reader, I had to follow blogs and publishers to test our feed monitoring platform. Being interested in AI, I started off by creating a list of machine learning blogs. I thought this list would be a good starting point for anyone trying to monitor news and insights from knowledgable AI-related sources. Most of them have RSS support and I plan on periodically updating this list.

Specialized Publishers

Non-profit Organizations

Academic Research and University-related

Startups

Large Companies

List was last updated: May, 16th 2018

Do robo-writers actually exist?

”Is Frase going to take my job?” – this is what writers frequently ask me while I am giving them a demo of the Frase Research Assistant. My answer is always the same: Frase doesn’t intend to replace the writer, but rather automate research tasks so you can focus on the creative aspects of content creation.

The closest Wikipedia entry for “robo-writer” is automated journalism:

”Also known as algorithmic journalism or robot journalism, where news articles are generated by computer programs. Through artificial intelligence (AI) software, stories are produced automatically by machines rather than human reporters. These programs interpret, organize, and present data in human-readable ways.”

Over the last five years, many stories have emerged about mysterious robo-writing projects, mostly in the context of how AI will radically disrupt journalism. Besides journalism, there is evidence about robo-writing being used in different contexts, from advertising copy to financial reporting. As I mentioned before, I I am personally in favor of robo-writing when automation can help writers become more creative and insightful.

The most shared stories on robo-writing:

For this post I’ve collected 12 of the most shared articles on the subject (ordered by published date), and then had Frase summarize them for me:

Robot Writing, AI, and Marketing: It’s the End of the World as We Know It (skyword.com) – January, 2018

Topics: big data, content marketing, lead generation, marketing automation, data mining, information architecture, internet of things, digital marketing

  • The definition of AI has merged and melded since the early days of sci-fi, so let’s clear this up: When we talk about AI today, we’re generally talking about “narrow AI,” or algorithms that are set up to do a very specific task, like trade a stock or make a widget.
  • Now, I’m here in Pittsburgh and there are self-driving Ubers everywhere on the road, so in a few years we employed a lot of folks, gave them a great livelihood and then all of those Uber drivers may potentially lose that livelihood.
  • If your job consists of a lot of repetitive marketing tasks like these, then you may want to consider how to evolve your role and skill set, as it will become more cost-effective and productive to have AI handle these types of activities.
  • “Truthfully,” he says, “I believe that where these jobs and these professions are going to shift to with the impact of AI is actually to the creation aspect; that’s where humans thankfully will still have a role.
  • AI does have a role in taking away a lot of the time that we spend looking at analytics and processing and crunching the data—all of that should be fulfilled by AI to free us up to do truly creative work.”

Coca-Cola chooses AI over brains to generate latest adverts (thedrum.com) – April, 2017

Topics: digital marketing, social media, Content creation, creative agencies, Coca cola, Adweek, Mobile World Congress, software algorithms

  • Coca-Cola is ditching flesh and blood creatives in favour of software algorithms in an experiment to see whether AI bots have what it takes to beat their human masters.
  • Mariano Bosaz, Coca-Cola’s global senior digital director, is spearheading the move as part of wider efforts to push the bounds of technology to see what they are capable of.
  • Bosaz added: “I don’t know if we can do it 100 percent with robots yet—maybe one day—but bots is the first expression of where that is going.”

Can Artificial Intelligence Replace The Content Writer? (digitalagencynetwork.com) – August, 2017

Topics: content marketing, customer experience, structured data, augmented reality, natural language processing, Gartner, data processing, artificial intelligence

  • While less likely to be automated, these areas are not exempt—roles such as data collection and data processing, once revered for their level of required expertise, are now 64% and 67% likely to be automated, respectively.
  • This can be seen in the above example: the second extract, written by Wordsmith, is more matter-of-fact and event-driven than its human counterpart (and the overuse of ‘season’ at the end particularly gets to me).
  • With the information already at hand, writers will have more time to focus on how articles are structured, how argument or opinion is built to leave the best impact on the reader.
  • Analyst giant Forrester have claimed that 16% of jobs in the U.S. will be lost to artificial intelligence by 2025.

Can robots truly be creative and use their imagination? (theguardian.com) – February, 2017

Topics: neuroscientist, research associate, professor emeritus, University of California, associate professor, machine learning, University of oxford, Artificial intelligence research

  • I’ve been working on writing novels computationally for well over 10 years now and I’m still trying it, although I believe that within the next two to three years I will have broken its back and will produce 100,000-word novels in half an hour or so, novels that I think most people would consider to be creative.
  • We are used to machines being used as tools that do not have a high level of cognitive ability, so it’s difficult for people to think of them as being able to exhibit truly creative behaviour.
  • Another problem is that it is difficult to automate the combination of ideas from many different sources that forms the source of much of human creativity: you might find inspiration from an interview with a neuroscientist in designing a new office layout.

What News-Writing Bots Mean for the Future of Journalism (wired.com) – February, 2017

Topics: BuzzFeed, Usa today, Fox News, Washington Post, Twitter, news articles, Megyn Kelly, Los Angeles Times

  • “Republicans retained control of the House and lost only a handful of seats from their commanding majority,” the article read, “a stunning reversal of fortune after many GOP leaders feared double-digit losses.” The dispatch came with the clarity and verve for which Post reporters are known, with one key difference: It was generated by Heliograf, a bot that made its debut on the Post’s website last year and marked the most sophisticated use of artificial intelligence in journalism to date.
  • It works like this: Editors create narrative templates for the stories, including key phrases that account for a variety of potential outcomes (from “Republicans retained control of the House” to “Democrats regained control of the House”), and then they hook Heliograf up to any source of structured data—in the case of the election, the data clearinghouse VoteSmart.org.
  • There may not be a wide audience for stories about the race for the Iowa 4th, but there is some audience, and, with local news outlets floundering, the Post can tap it.
  • “If we took someone like Dan Balz, who’s been covering politics for the Post for more than 30 years, and had him write a story that a template could write, that’s a crime,” Gilbert says.

 

New AI Can Write and Rewrite Its Own Code to Increase Its Intelligence. (futurism.com) – February, 2017

Topics: machine learning, deep learning, Google, program synthesis, MIT Technology Review, learning algorithms, large companies, mathematical framework

  • A company has developed a type of technology that allows a machine to effectively learn from fewer examples and refine its knowledge as further examples are provided.
  • For example, an AI system is fed data about how the sky is usually blue, which allows it to later recognize the sky in a series of images.
  • This form of probabilistic programming — a code that uses probabilities instead of specific variables — requires fewer examples to make a determination, such as, for example, that the sky is blue with patches of white clouds.

 

Automated content: Can algorithms write your content for you? (futurecontent.co) – September, 2016

Topics: online content, data science, Fast Company, Steve Jobs, Yahoo, business intelligence, Microsoft, Medill School of Journalism

  • French spent years scanning portions of two Susann books, Valley of the Dolls and Once Is Not Enough, into Hal’s databanks, and deconstructing the writer’s style into 100 different parameters which Hal then turned into the final prose.
  • Joseph Medill was an editor and journalist in the purest sense, and he created a publishing legacy both familial—three of his grandchildren went on to run newspapers—and professional, through the Medill School of Journalism (MSJ).
  • We know more about what readers read than ever before, but we also know how they interact with articles, what they look at next and what their responses mean.
  • Add to this vast improvements in other technology like facial recognition is it’s not beyond the realms of possibility that an AI will be able to pull in all these different data sets and create a story from scratch with all the nuances of a seasoned writer.

 

Artificial Intelligences Are Writing Poetry For A New Online Literary Magazine (popsci.com)

Topics: postmodern, artificial intelligence, human beings, average person, traditional sense, curation, common sense, good poetry

  • The project’s name is itself an apt title for the work done by humans for the site: the implementation of an artificial intelligence designed to write, and the curation of what it has written.
  • ” You can talk about what the creator was trained on, or how the creator works, but not the creator’s intent— maybe the algorithm writer’s intent, but it’s a step removed, which is more fun for the reader, I think.”
  • Still, reading an excerpt from ” Gimble” in a poem titled ” Madness,” makes one wonder how detached we can be from a machine’s ability to synthesize what reads as a believable abstraction on such an emotional and human subject:
  • i am all the world and the day that is the same and a day i had been

 

Google’s AI has read enough romance novels to write its own (thenextweb.com) – May, 2016

Topics: Google, final round, software engineer, annual event, Buzzfeed, Japan, deep learning, National Novel Writing Month

  • In an effort to make its apps more conversational, Google fed its AI engine a whopping 2,865 romance novels so it can improve its understanding of language.
  • After going through the massive trove of novels, the engine was tasked with writing sentences of its own based on what it had learned.
  • Given the rapid pace of development in the fields of AI and deep learning, it seems like the day isn’t far off when our next read will come not from a library shelf, but from a computer that tailors a custom book to your exact specifications.

 

Will Robots That Can Write Steal Your Creative Job? | Observer (observer.com) – April, 2016

Topics: machine learning, analytical tools, virtual world, artificial intelligence, blog post, Google, Ibm, computer program

  • In a way, it felt like going to see any other indie rock band, but I got the sense that the computer doesn’t have much sense for when a song should come to an end.
  • When I saw Narrative Science’s Kristian Hammond on a SXSW panel, he described how his company has built software that can turn piles of data into texts that can be read and digested by human brains.
  • For example, you might rely on some expert’s framework to devise a stock market portfolio for yourself, but you can’t call that expert up every night to ask how your picks are performing in light of his or her system.
  • Sometimes referred to as the economic singularity, it posits that soon so much more work will get done, and done better, by machines that hardly any people will be needed at all.

 

Japanese AI Writes Novel, Passes First Round for Literary … (digitaltrends.com) – March, 2016

Topics: Japan, artificial intelligence, press conference, writing process, award committee, Matsubara, literary award, human creativity

  • Yet, now that a Japanese AI program has co-authored a short-form novel that passed the first round of screening for a national literary prize, it seems that no occupation is safe.
  • One of the team’s two submissions to the competition made it past the first round of screening, despite a blind reading policy that prevents judges from knowing whether an AI was involved in the writing process.
  • But there are still some problems [to overcome] to win the prize, such as character descriptions,” said Satoshi Hase, a Japanese science fiction novelist who was part of the press conference surrounding the award.

 

This News-Writing Bot Is Now Free for Everyone | WIRED (wired.com) – October, 2015

Topics: Yahoo, news stories, beta version, structured data, mail merge, total sales, Associated Press, similar technology

  • Today Automated Insights has launched a beta version of its new free service based on Wordsmith, the technology it uses to generate stories for companies like the AP.
  • There are many rules—known as branches—that you can set, such as the ability to use one set of words when a variable happens to be greater than a certain number and a different set when it happens to be lower than that number.
  • You could create a template that will generate the text ” sales increased in quarter two” if the number in the spreadsheet cell containing the quarter’s total sales was bigger than the cell for quarter one.
 

How is NLP impacting content marketing?

Business leaders are starting to research more about technical topics like natural language processing and machine learning. In this post, we summarized the top 10 results on Google (as of May, 14th, 2018)  for the query “how is NLP impacting content marketing?”.  As a quick spoiler, these were the topics that got mentioned in at least 50% of the articles: unstructured data, business intelligence, search engine optimization, sentiment analysis, neural networks, chatbots, customer experience, automated content creation, digital transformation.

How can NLP technology be used for marketing (econsultancy.com)

Topics: business intelligence, unstructured data, structured data, search engine optimization, sentiment analysis, mobile apps, machine learning, scalability

  • The holy grail of NLP has been to convert ‘unstructured data‘ (text and multimedia) into structured data and we are inching closer towards that goal with advances in NLP and multimedia indexing technology.
  • Social prospecting solutions require NLP capabilities that can sift out passing mentions of a brand, and focus on those where this is an intent to purchase.
  • State of the art NLP systems can mine social media for such expressions of interest and return social handles of people matching the customer’s criteria.
  • The interaction of these two leads to compelling solutions, for example in leveraging socially trending topics (or brands) to promote customer content matching those topics or brands.

What Does Natural Language Processing Mean for Writers (portent.com)

Topics: natural language, machine learning, Natural Language Processing, neural networks, Artificial Intelligence, word processor, chatbot, language model

  • It’s not news that there are things computers are really good at that humans are bad at, and some things humans are really good at that computers can’t seem to manage.
  • Google made a splash in 2015 when the neural networks they’d trained on millions of images were able to generate pictures from images of random noise, something they called neural net “dreams.” And in 2016, they announced Project Magenta, which uses Google Brain to “create compelling art and music.”
  • “[Google’s algorithm] Hummingbird can find some patterns that can give it important clues as to what a text is about,” says Matthew, “but it can’t understand it the way a human can understand it.
  • Language takes root best in our “procedural memory,” which is the unconscious memory bank of culturally learned behaviors, rather than in our “declarative memory,” which is where you keep the things you’ve deliberately worked to “memorize.” Children can pick up other languages more easily than adults because they’re tapping into their procedural memory.
  • We can go into the idea that robots are going to take over the world and they just need to learn to speak first, and that’s kind of cool for a movie.

What do linguists make of AI and natural language processing? (econsultancy.com)

Topics: target language, natural language, machine translation, natural language processing, statistical machine translation, translation process, language professionals, foreign languages

  • One might assume that professional linguists would feel a constant need to stay updated on any impact such technology may have on their future careers.
  • — there is an apparent lack of understanding of the connection between AI, NLP, and advanced machine translation such as statistical machine translation (SMT) or neural machine translation (NMT).
  • Once the usage and purpose of statistical and neural machine translation are understood, most linguists start to think about how it could support them in their work instead of ignoring it as a threat to their livelihood.
  • It’s difficult to say how many linguists would admit to using SMTs for their translation projects, as despite improvements in the technology, its acceptance amongst clients is still low.

Can Artificial Intelligence Replace The Content Writer? (digitalagencynetwork.com)

Topics: content marketing, customer experience, structured data, augmented reality, natural language processing, Gartner, data processing, artificial intelligence

  • While less likely to be automated, these areas are not exempt—roles such as data collection and data processing, once revered for their level of required expertise, are now 64% and 67% likely to be automated, respectively.
  • This can be seen in the above example: the second extract, written by Wordsmith, is more matter-of-fact and event-driven than its human counterpart (and the overuse of ‘season’ at the end particularly gets to me).
  • With the information already at hand, writers will have more time to focus on how articles are structured, how argument or opinion is built to leave the best impact on the reader.

Artificial Intelligence for Content Marketing and Content Creation (techemergence.com)

Topics: content marketing, best practices, healthcare industry, content creation, search engines, Google, customer service, deep learning

  • With improvements in AI technology, newer NLP platforms can augment human researchers by creating multi-page summarized articles for even open-domain questions like ‘what is the future of AI technology going to look like?’ or ‘How is AI affecting the healthcare industry?’
  • Summarizing content through the use of NLP can be either “extractive” (where the system distills text into just the most relevant parts, cutting out the rest) or “abstractive” (which is machine learning based, and involves AI coming up with it’s own “wording” for summarizing a given text).
  • As opposed to what Google does in summarizing fact based questions, more advanced contextual summarizing would involve condensing information from the top 50 search results, finding meaningful relationships between these results and then extracting the most appropriate sentences from within those relationships.
  • Essentially, the platform offers a word processor that can learn from things that you write and can research contextual topics in the background and give you links for the topic etc.

Can Neuro-Linguistic Programming really Influence Sales? (maximizer.com)

Topics: emotional responses, skill sets, empirical support, Virginia Satir, human psychology, desired outcomes, specific goals, basic concepts

  • Stephen Covey’s habit of “begin(ing) with the end in mind” applies, a clear vision of a path to a successful sale, looking for visual clues that monitor how successful your sales pitch is, or whether your attempts at conversation are working well or failing miserably.
  • While wholesale subscription to NLP principles like anchoring and reframing may be less than ideal, managers should be aware of some general concepts that could impact an individual’s performance and potential as a team member.
  • This works on both sides of marketing equations, where sales prospects are less wary of the dogma of high-pressure salespeople that immediately put them on edge, and sales pros are less likely to be intimidated by negative feedback and clients that are unimpressed by their products or services.

How NLP Systems Help Marketers | Centric Digital (centricdigital.com)

Topics: natural language processing, natural language, target audiences, actionable insights, digital communication, digital transformation, social media, computational linguistics

  • The ability to keep a finger on the pulse of consumers’ reactions to a product on social media is immensely valuable, since, in the words of Apiumhub, “It has the potential to turn all of Twitter or Facebook into one giant focus group.” Countless SaaS offerings accomplish this by scraping the text away from social or publishing platforms and providing actionable insights based on interpreting those statements.
  • In fact, countless components of a potential consumer journey can be mined with the same datafied approach, creating a thoroughly personalized marketing touch point and driving sales on the basis of an overall sense of each consumer’s style and preferences.
  • As previously stated, the simple Amazon tracking that occurs when someone views a product page is a one-size-fits-all operation: The ad engine isn’t quite sure whether the consumer bought the item or not, and so it surfaces an ad for that item repeatedly in the middle of almost every subsequent site they visit.
  • If marketing content could make meaningful use of expressed language from the user’s entire web journey, including search terms, social media posts and reviews written customers would receive information in their preferred medium.
  • For example, when the user searches for a “baggy sweater” with the intention of finding a sweater that fits loosely, and instead the search returns sweaters made of a bag-like material, or sweaters with tote bags depicted on them — this is not product marketing on par with a premium ecommerce shopping experience.

 

Artificial Intelligence–the Next Frontier In Content Marketing  (blog.marketo.com)

Topics: unstructured data, machine learning, natural language processing, neural networks, deep learning, marketing automation, natural language generation, seamless integration

  • With the ability to process an enormous amount of unstructured data and decipher natural language, AI is used to extract insights and make recommendations based on previously established criteria.
  • This capability allows marketers to fully leverage the power of personalization and marketing automation technologies to deliver targeted content to each prospect or customer and increase the ROI of their content marketing efforts.
  • You can use AI to identify trending topics by using algorithms to track conversations on the Internet, such as those occurring on social media and within published content, to help you stay ahead of the trends and create content that will lead the conversations.
  • Leveraging the AI features in your current tools will not only give you a great starting point to familiarize yourself with the technology, but you’ll also be able to take advantage of the seamless integration that’ll allow you to get up and running faster and more cost-efficiently.

Artificial Intelligence in digital marketing (besttechie.com)

Topics: big data, search engine optimization, social media marketing, content marketing, digital marketing, search queries, search engines, Whatsapp

  • One of the most popular and common words that are consistently used in the world of marketing is “segmentation.” There are plenty of people with a variety of needs and interests, and the companies need to categorize them as segments to increase their sales and retain their customers successfully.
  • There are plenty of benefits that are brought by AI in the world of digital marketing, but there are many challenges that are faced by the digital marketers due to the entrance of AI.
  • AI based marketing tools can assist the digital marketers in developing an effective marketing strategy, but the thing is that these tools can be easily available to all digital marketers, which forces the digital marketers to increase their skills and constantly be aware of new tools and services in an effort to stay on top of their game.
  • For now, the digital marketers should keep on learning the new digital marketing skills, and they should keep themselves updated with the recent updates on artificial intelligence to be competitive in the world of digital marketing.

Content Intelligence: Will AI-powered Content Marketing be a game changer? (martechadvisor.com)

Topics: email marketing, content management, user experience, marketing automation, Content Marketing, customer engagement, data management, individual users

  • -A better breakdown of audience data by using data management platforms like Lotame can tell a content marketer what type of reader is consuming their content, what the reader’s other category interests are, location, etc.
  • Like several other companies, Wayblazer leverages the Ibm Watson technology for the travel industry by focusing on the language recognition API to analyze triggers from a traveler’s search so that they are further be able to share personalized hotel recommendations.
  • Also gone are the days of waiting for the RJ to play your favorite track what with platforms like Spotify, (a world digital music service) using AI and deep learning to provide music recommendations to users based on their past listening preferences.
  • To answer the glaring question as to why content marketers are increasingly looking at AI to supplement their content marketing efforts, Mark Schmukler, CEO and Co-founder, Sagefrog says, “Personalization has a big effect on the success of content marketing and can be well-executed through artificial intelligence and marketing automation tools.
  • A marketing agency with expertise in content marketing and marketing automation can help marketers find the tools and tactics that together create the best possible user experience throughout a content marketing campaign.”

Can automatic summarization improve your content curation strategy?

Something we think about a lot at Frase is summarization and its potential use cases in content marketing. There are two main approaches to summarization: extractive and abstractive summarization.

  • Extractive summarization: it works by selecting the most meaningful sentences in an article and arranging them in a comprehensive manner. This means the summary sentences are extracted from the article without any modifications.
  • Abstractive summarization: it works by paraphrasing its own version of the most important sentences in the article.

If you are like me, you already subscribe to newsletters from experts who let you monitor market trends without having to do the research by yourself. For example, I am subscribed to a newsletter about artificial intelligence curated by Rob May. If you think about it, most newsletters are a mix of personal commentary along with a list of curated contents. It is here where I find automatic article summarization to be relevant. I usually open these newsletters on my phone, and it is not convenient to open every article. Could summarization give me an overview of each article and help me consume this information more efficiently?

As an example, I’ve pasted below a few summaries for the search query “what is content curation?” — Frase summarized the top 5 Google results for that query. Would this make a decent newsletter if you were informing your audience about this topic? I believe the mix of personal/human commentary, along with automated summaries can be a good strategy for the busy marketer.

“What is content curation?”

5 AI-generated summaries from Frase:

Curate or Be Curated: The Coming Age of the Curation Economy (huffingtonpost.com)

Topics: social network, mobile devices, Linkedin, digital content, content creators, Yelp, Facebook, Google

  • A few facts to underline the trend: Eric Schmidt, the chairman of Google, has famously said: “Five exabytes of information have been created between the dawn of civilization and 2003, but that much information is now created every two days, and the pace is increasing.”
  • So, if you accept the facts behind Rosenbaum’s Law — that the creation of raw content is going to double every two years — then the nature of consumption is what is going to change on the web.
  • Much as the quality of a restaurant is created by the chef, the quality of the curated end-product is going to be made by the curator.
  • In the past few years, the growth in mobile devices along with the widening definition of content from contextualized data to raw data has opened the floodgates of participation.

The Busy Person’s Guide to Content Curation (blog.bufferapp.com)

Topics: social media marketing, Digg, Evernote, content marketing, Twitter, browser extension, social media, digital marketing

  • We’ve mentioned before that a possible rule of thumb for social media content is the 5-3-2 Rule: For every 10 posts, five of them should be content from others, three should be content from you, and two should be personal, non-work-related.
  • If curating content is something you’d love to try for your marketing efforts, you’re likely wondering about the one big hurdle: time.
  • Here are four tools to get you started, and you can check out more from the complete list: BuzzSumo Medium collections SlideShare In addition to these unique places, there are some common, popular sites that you can also use to sift through new stories.
  • The off-the-radar spots are often quite good; there’s content on those sites that your audience may not have seen before, which adds an immediate boost of credibility for you and a boost of value your readers.
  • We share the best stories we can find from our archives and from the web to our profiles on Twitter, Facebook, Google+, and Linkedin, and we curate a list of content suggestions that are offered fresh each day for folks to pick up and add to their buffers.

Content Curation in Marketing: The Definitive Guide (curata.com)

Topics: Search Engine Optimization, mobile apps, Lead Generation, content marketing, Linkedin, digital content, search engines, competitive intelligence

  • Curata’s definition of content curation is as follows: content curation is when an individual (or team) consistently finds, organizes, annotates, and shares relevant and high quality digital content on a specific topic for their target market.” At its best, curation is… a person, not simply a computer algorithm.
  • This guide is focused on the marketing side, but the majority of best practices covered are relevant for any use case, so let’s examine a few other possibilities: share content to inform, educate, and influence your prospects and customers, simultaneously strengthening your brand’s position as a go-to resource and industry thought leader.
  • If you’ve chosen your topic well, you should be able to find at least a dozen known and trusted sources by reviewing the content you consume via: trade publications, Twitter lists, specific Twitter users, industry blogs, LinkedIn Pulse or Scientific journals.
  • Email them less often—perhaps change from a daily to weekly list; segment your list by topic so the content is more relevant to them; pay more attention to the content you are curating—perhaps you are being too self-promotional; or be more consistent—you may be curating sporadically which makes you less trusted.

What is Content Curation and How Can You Use it For Your Small Business? (smallbiztrends.com)

Topics: online community, email marketing, content marketing, digital content, social media, Social media sites, mailing list, content curation

  • However, by publishing and sharing added value content, companies are able to get a leg up on the competition and provide marketing leads with far more than a ham-fisted, hard sell.
  • Yet by cherry-picking select pieces of juicy, existing content and re-sharing it in a format that is compatible with your company’s unique marketing strategy, you’ll be able to capitalize off the expertise of others in order to provide your own business with credibility as an industry thought leader.
  • You’ve got to get a good feel for what your consumers or followers want or need in terms of content and tinker with how to offer them value.

What is Content Curation? (blog.elink.io)

Topics: content marketing, digital content, digital marketing, content strategy, infographic, white papers, curation, case studies

  • “Curation is more than packaging – it is to help readers (discern) what is important in the world.” Maria Papova, Brainpicker. Here is elink’s definition: Content curation is adding your voice to a handpicked collection of content, from a variety of sources around a specific topic, that you publish and share.
  • Here’s an example of what that curated content piece would look like: 2) Collect Content Every marketing team has its set of expertise and areas of strength with the types of engaging content they produce.
  • Tell your customers why they should pay attention and care about the curated content you are sharing; this will help your audience get the most out of your curated content and view you as a thought-leader.
  • Although there are a number of ways you can curate content through your marketing channels, some of the most popular methods marketers use include curated newsletters, web content and through social media.

 

How is artificial intelligence transforming content creation?

The rate of digital content creation has exploded and artificial intelligence promises automation, personalization, and scale. Walter Frick at Harvard Business Review explained why AI can’t write articles yet in 2017, but also concluded that it can help us better write our own.

The following list features existing use cases where AI is leveraged to automate, assist or augment any step of the content creation process:

Newsroom automation

To deal with the growing volume of information and gain competitive advantage, the news industry has started to explore and invest in news automation.

  • Washington Post – “Heliograf is creating a new model for hyperlocal coverage,” said Jeremy Gilbert, The Post’s director of strategic initiatives. “In the past, it would not have been possible for The Post to staff more than a handful of the most significant games each week. Now, we’ll be able to cover any game that we have data for, giving the teams and fans near-instant coverage to read and share.”
  • Associated Press – The Associated Press uses Wordsmith to transform raw earnings data into thousands of publishable stories, covering hundreds more quarterly earnings stories than previous manual efforts.
  • ReutersReuters Tracer automates end-to-end news production using Twitter data. It is capable of detecting, classifying, annotating, and disseminating news in real time for Reuters journalists without manual intervention.

Advertising copy generation

As ad-tech companies develop a better understanding of audience preferences, they will aim to personalize advertising messaging as much as possible.

  • Saatchi Trained IBM Watson to Write Thousands of Ads for Toyota: Saatchi wrote 50 scripts based on location, behavioral insights and occupation data that explained the car’s features to set up a structure for the campaign. The scripts were then used to train Watson so it could whip up thousands of pieces of copy that sounded like they were written by humans.
  • Persado enables brands to engage each consumer across all channels with personalized emotional language. “Imagine having a data scientist and a copywriter for each person in your audience; you get the language that performs and the analytics explaining why, resulting in more business and unseen insights”.

Data-driven storytelling

Think telling a story out of an Excel spreadsheet.

Understanding and Producing Video

Video is among the fastest growing forms of content creation. Extracting meaning from videos and automatically creating new ones will be a growing opportunity.

  • Reelycomputer vision and deep learning specialized in transforming video into actionable data.
  • Wibbiz – automatically creates premium videos from text.

Robo-writing & Paraphrasing

Input a topic and an AI will craft a human-readable article for you. This is what a few startups are building to help writers scale their content production. Examples include Articoolo, AI Writer and WordAI.

SEO and keyword research

Search engines now analyze your website through the lense of AI algorithms, which means they understand the overall context and theme, not just keywords. New AI tools for keyword research help you expand the scope of your keyword research process.

  • Marketmuse – MarketMuse is an AI-powered research assistant that accelerates content creation and optimization so you can win in organic search.
  • Twinword – an AI-powered keyword research tool that uses smart filters to quickly narrow down your keywords.

Summarization

When you are doing research, it is easy to waste time browsing sources that are not relevant to you. Summarization helps you quickly skim articles and decide whether they are worth reading.

  • Agolo – Agolo uses artificial intelligence to create summaries from your information in real-time.
  • Salesforce’s has published ground-breaking research related to summarizing long-form text.

Image editing

What if AI could do all the image editing for us?

  • Object AI’s technology automatically detects the subject of the photo and makes photo editing intelligent.
  • Adobe’s prototype AI tools let you instantly edit photos and videos

Personal communication

One big area of content creation includes email. Can AI help us create better content personalized to our audience?

  • Crystal Knows – it understands the personality of your co-workers by analyzing their email language. It then helps you optimize your emails accordingly.

Voice recognition for note-taking

A lot of knowledge may get forgotten in conversations and meetings. Can AI help us turn voice into comprehensive text notes?

  • TetraTetra uses AI to take notes on phone calls, to help you focus, remember the details, and keep your team in sync.

Proofreading and grammar

AI models trained to make us better writers.

  • Atomic Reach’s editor provides real time, custom and predictive recommendations to create perfectly written content with your audience in mind every time.
  • Grammarly – Grammarly makes sure everything you type is clear, effective, and mistake-free.

Question Answering

Bots like Siri or Google Assistant are capable of answering fact-based questions, like “What is the capital of Spain?”. However, they often struggle to reply open-ended questions, like “Why is unemployment growing in Spain?”. In this situation, an AI would have to use multiple small snippets of evidence to make a combined judgement.

  • IBM proposes to navigate through knowledge sources like Wikipedia to search for the answer, prioritizing some documents in their search over others; and combining knowledge from different parts of the documents they read to reason out an answer.

Question Generation

Can computers ask intelligent questions?

  • Maluuba (Microsoft) – while there have been many advances in machine reading comprehension to develop models that can answer questions, Maluuba has been working to teach machines to ask informative questions.