A Great Simian or just a Monkey

artificial intelligence

How to make a cognitive movie trailer

Cognitive platforms can improve almost every process available. In cooperation with 20th Century Fox, IBM Watson created a movie trailer for the horror movie Morgon. The trailer was created in 24h and by that reducing the production time from weeks to hours. What do you think of the result?

This is the Watson created trailer for Morgan (incl. some comments)

The “classic” trailer is found a bit further down in the post.

So how was this possible and what steps was involved?

First of all, it is important to make it clear that a cognitive solution is almost never acting alone, it is acting in partnership with humans where each part is providing parts that will elevate the other.

The thing that made this project interesting is that there was no existing “ground truth”. This means that there was no right or wrong, no previous training or “how to”, so Watson had to act on it’s own and produce something on its own for the first time. To stitch it all together, IBM provided an internal IBM Research filmmaker to the project for the actual film-cutting.

Watson needed to do a couple of things to make the trailer a reality.

First, as with us humans, they needed to teach Watson what a trailer is and specifically a horror movie trailer. Since no “ground truth” existed, Watson needed to learn what a horror trailer is, so the team pushed 100 horror movie trailers through Watson and while doing that also helped him understand a few things in the trailers. The team used the following.

  1. Learn what a horror movie trailer is
    Needed to understand what was in the trailers and sense the emotion involved. This by both looking at and listening to each trailer and being trained by experts in how a horror trailer is constructed:

    – Visual analytics to identify people, objects, scenery and based on that identify emotions within each scene.
    – Audio analytics to identify tone of voice of the characters as well as the vibe of the soundtrack and sounds during each trailer.

  2. Watch the Morgan movie
    Now that Watson has learned what a horror movie trailer is, it was time to watch the movie that Watson should make a trailer based on. So he leaned back and watched the full Morgan movie.

After watching the movie Watson identified 10 different moments that would be worth including in the trailer. Interestingly Watson chose moments of the movie that other trailers did not include, now compare to the “classic” trailer below.

What is really cool is that this is a “creative project”. In creative projects, you rarely know what to expect as outcome until you see the result. To put Watson to the test on such a creative task is very very interesting.

Creating a movie trailer is usually a very labor-intensive project that involves many manual steps. It usually takes many days or even months to create.

It took Watson 24 hours to create this trailer for the movie Morgan. Reducing the production time from weeks to hours.

This is a great example of an isolated task that can act as a great example where it is beneficial to make a process cognitive, even though this project is pushing the limits given that it is a creative project.

Photo credit: 20th Century Fox

cognitive pre-requisits

Tell me what I do not know!

Artificial Intelligence will be a huge part of our daily lives and in our businesses from now on, but what we see today is not always Artificial Intelligence or my preferred term, Augmented Intelligence. It is just re-packed machine learning with a conversational interface. AI and cognitive are not only algorithms it is so much more. Many high-end AI / Cognitive products today are not mainly algorithm, that goes for Google DeedMind as well as IBM Watson.

Without further rambling, I thought I would state my position on the topic. It is actually pretty simple. A product, service or process that will be an AI-enabled or cognitive shall have one single pre-requisite in my opinion.

An AI, cognitive product or process should tell us things we do not already know. If not, it is not AI or Cognitive!

If it does not meet that “general” term, it is not AI or Cognitive, period! AI and cognitive per se is to think, learn and reason etc, but to provide value in a business and to assist us, we need to guide our software in a way that they provide information, solutions and data that we could not generate ourselves with resources at hand.

The future of software in the enterprise is about elevating both us as humans, and our business. Efficiency and speed is fantastic, but that is nothing new, it is what we have today!

I think that in 5 years most processes and things we do in a company will be elevated by cognitive elements. AI and Cognitive will be everywhere.

Photo: From a morning walk last week in my new hometown.

Augmented Intelligence instead of Artificial Intelligence

Artificial Intelligence is a term that, for me, only causes confusion and also builds up caution towards new tech. It indicates that AI will replicate our intelligence and some are even afraid of AI taking over our jobs etc. It is a term that stunts the development and our progress to more successful companies. A term that much better describes what it is about is Augmented Intelligence.

Augmented Intelligence is actually what it is all about. Augmented send the notion of evolving and increasing our existing knowledge. The intelligence that systems will assist us with is not artificial, it is real and elevated. It is systems that are taught by humans and then elevated to assist and scale human expertise to help businesses and applications to assist people with well-defined tasks and help them make more informed decisions.

This heavily connects to the fact that collaboration between human and computer is a very important part of becoming a successful business in the future. This collaboration is about systems helping humans and humans helping systems.

As a side note, augmented intelligence also fits much better as term in the landscape of cognitive. Artificial Intelligence is one part of cognitive, but many tend to mix cognitive with Artificial Intelligence. If we replace Artificial Intelligence with Augmented Intelligence, it is much easier and more relevant…..at least for me.


ai chatbots and cognitive platforms

Cognitive Platforms are the future, not Bots and AI

Wherever you turn, whatever magazine you read, you see Bots, more Bots. Most of them sprinkled with Artificial Intelligence. In my view, this is a flawed and wrong assumption. The future is a platform that makes processes cognitive. A cognitive platform that will enable processes to think, learn, reason, solve problems and communicate in the expected domain and in the expected language. Bots and Artificial Intelligence are part of this platform.

The future is cognitive platforms!

Just a bot is just plain stupid, it does what you tell it to do, it is very much like traditional programming, the program does what it is programmed to do, nothing more, nothing less. It is a fun interface and an innovative communicative interaction. To escape the risk of endless loops and repeating the same stupid standard answer over and over again, we sprinkle some artificial intelligence on the poor Bot. Now we have a Bot that understands what you are saying to it and also can reply with a bit more elaborative answer then the basic standardized sentences. Does that mean that the Bot will actually assist us in our daily life and improve our performance as humans?

The above is true to a certain degree, in some cases, it will improve our lives, but mainly in the way of speed to information, the Bot will not tell us things we could not find out in other ways, it will just find it fast and deliver it to us. Such Bots are already here and have been for decades. Bots are simply put another type of interface.

The sprinkled AI is mainly about language and algorithms, a subset of the real meaning of AI. Languages in the sense that the Bot will understand you, classify what you intend to communicate and also often do this in several languages. A flaw today is that we often confuse machine learning and algorithms with the true meaning AI. It cannot be AI when most of the time it is a formula created in a spreadsheet that we then put to work on extensive amounts of data to help us to provide insight and conclusions to the user or the company. That is just machine learning. This is often done in very impressive ways (Spotifys Discover Weekly is a good example here), I have personally built companies mainly based on machine learning, so I am not in any way negative to the practice. It is just that it often (not in the Spotify case, just to be clear, they use machine learning) is described as AI and that it is the overall future of tech and in that I disagree. Why? Well, let’s start by looking at what AI is according to Wikipedia

Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

So, according to Wikipedia all is fine, cognitive and AI is the same, but that is not the way it is translated into today’s tech-world. Most describe AI as a combination of Machine Learning, Natural Language Processing and Algorithms. With this in mind, I prefer the “cognitive” term instead of AI. The AI term is in many ways already destroyed by those who claim to do AI, but mainly does Machine Learning and NLP based on structured data.

Lets not forget that 80% of todays information today is unstructured, not even possible to interpret for most systems today.

Today 80% of the information we have at hand is unstructured, that means that very few computers can work with that data in a valuable way. To be able to understand millions of medical journals or law books from all over the world the computer need to be able to learn, reason etc as well as to learn the domain specific language. You cannot apply an algorithm from a spreadsheet to accomplish this, a software that is very close to a human brain is needed. A cognitive platform learns, communicates and does problem-solving.

The Cognitive Doctor vs the Human Doctor (example)

Over the years we have done tremendous research on cancer. We also have a huge amount of medical journals on cancer patients. Let’s play the role of the doctor. You think you have read a lot about cancer, and this specific version of cancer. You have also been in practice for 20+ years so you have seen your fair share of cancer patients passing by as well as written a lot of research papers on the topic, which would classify you as a very knowledgeable and experienced doctor within the field.

A patient walks in with the diagnoses of cancer, the specific cancer type that you are experienced in. You look at the journal and talk to the patient. Given the research reports you have done over the years, as well as the one you have read from others in combination with your experience in the field you come to the conclusion that a specific type of treatment would be the best way to progress. Hopefully, the patient gets well and all is good.

Now, if the doctors working process would be cognitive the cognitive parts of the process would read ALL available research, ALL available medical journals. This in combination with getting all the data and info about the person incl. historical sickness and traumas etc that the patient might have. Again, let’s not forget that most of this data is actually unstructured and not even readable to most computers today. The cognitive process looks at all data (structured and unstructured) and swiftly replies to the Human Doctor with three alternatives (including the info these recommendations are based upon) for treatments for the patient, including a ranking on which alternative might be most suitable for this patient.

Now, the truth is that no doctor in the world can keep all information inside his / her head, the truth is that most of us tend to do what we have seen previous success with. What a cognitive enabled process now have given us is three alternatives for the Human Doctor to consider. It is still the Human Doctors decision, but the help presented might give new angles and new info that the Human Doctor actually had not considered. The decision is still the doctors, the decision is now only based on a more trustworthy base of data and information. Still presented to the patient by its doctor without even knowing that a computer actually helped a lot in providing the best treatment for you.

Is this pure fiction? Actually not! 

What is the future then? It is cognitive platforms!

For me, the success in this space lies in how well a company makes its processes cognitive. Cognitive will never be a specific product (like a Smart Bot) it will be integrated into existing (or new) business processes. Damn, that sounds boring, but let’s be honest here, most companies have defined ways of working aka processes. Most of these processes can be vastly improved by making them cognitive. To be clear, it is not new processes it is about making existing processes cognitive and by that more efficient, more valuable and more productive.

To be able to do this a process needs to be able to access different cognitive functions and consume them where appropriate. I could be to read, learn and understand a law book (and solve legal obstacles) or thousands of medical journals (like the cancer doctor example above) or it could be to find certain objects in millions of images or to analyze incoming communication, voice or e-mail, to be able to give a better customer experience, it could also be to give a quick, accurate  and personal (tone, personality) reply (in the right language) to a customer that interacts with the company.

This is only provided by a cognitive platform and not by a bot or AI (as positioned today by tech companies), but both are important parts of the cognitive platform.

PS I think I will break down this rant rambling post in a few more specific posts on the topics of cognitive platform, cognitive process etc Stay tuned DS

Photo from the movie Big Hero 6 by Disney

cognitive transparency

Transparency is the future

Transparency will be the key to success in the era of artificial intelligence and cognitive. With all new technology also comes new challenges. In the artificial intelligence and cognitive area of technology one main challenge is how to manage privacy and integrity.

Currently artificial intelligence and cognitive products are the new hot and trendy topic and also it seems to be the new hot area for new startups.

Disclaimer: The company I have co-founded, Monies, is one of those. Our goal is to unify your financial life and bring meaning and consciousness to your financial life. By that we are naturally in the needles eye of this post and transparency will be one of a few keys to our success.

Since these systems and technologies are a lot about emotions and to learn about how we as humans work and to learn, reason and have a conversation based on the input you provide, it is essential that we trust the technology and that we know 100% that the info is secure, not shared and private only to me. Already at this stage there are a lot of risk and many will fail.

In my opinion we will also need to be really assured that my data is not mixed with other persons or organizations data. This is important since most of the AI / cognitive platforms are….platforms. This means that all data goes into “one” place and not on your own dedicated instance or server. Most platforms, Facebook, Google, Amazon or IBM are physically based in huge data centers and all data is physically stored in the same environment as other individuals or organizations data. For these organizations to be able to build the necessary trust that our data is secure and private to us or our organization, transparency will be of outmost importance to establish this trust.

If we push the topic it is the same as when you share information with another human, you need to feel that you trust that individual prior to sharing sensitive information. Since these technologies replicates a lot of the behavior we have as humans. Would you share your private info if you knew that the other person immediately shared that info with the rest of his company or even other companies that they are also doing business with, would not think so.

Even though machines replicate a lot of our behavior today, some things are hard to establish, like trust. Enter the revenge of transparency. Transparency have long be pushed down in the value-chain in favor of capitalizing on our private data, companies like Facebook, Google and others that have as a business-model to re-sell your data to companies that want to reach you with their message. Their business model is to sell your data, you are the product.

This will not compute in the era of AI and cognitive. We will, in my opinion, be much more restricted in what we share about ourselves if we do not feel safe and secure.

Ai and cognitive as technologies are already here to stay so this is not a post against these technologies, the opposite, I believe strongly in them, even so much that I have started a company in the segment.

We and everyone else in the segment need to be fully transparent about the following:

  1. How we store the data
  2. How we keep it safe
  3. That personal information is not shared and truly personal
  4. Provide info on the reasoning on the answers provided
  5. Provide evidence that backs the answers that are provided

Only then can a artificial intelligence and cognitive technologies really become as successful as they are expected to become.

I will end this post with a quote rom Rob High, IBM Fellow and CTO of IBM Watson, in a Mashable article on the topic recently.

They’re subject to the human condition — that is, all of the forms of expression that we leverage to communicate our thoughts, ideas and knowledge, and all of the experiences that we’re exposed to that shapes those thoughts — cognitive systems don’t behave like other deterministic (mathematically modeled) computing systems. They are subject to the same ambiguities, nuances, subtleties and lack of universal truth that we as humans are subject to. They, like other human experts, are only really held up as an expert when we develop trust in them. Cognitive systems, like other human experts, have to establish that trust by being transparent about why they believe what they believe — answer what they answer. And in doing so, they will reveal whether they are acting nefariously or not.

Photo: The top photo is taken from a train entering Stockholm a rainy winter day in December. I thought the wet window could symbolize some transparency.

Powered by WordPress & Theme by Anders Norén