The 11th of May 1997 IBMs supercomputer Deep Blue beat the current world champion, Garry Kasparov, in chess. IBM Research released a little re-cap of the event and what has happened over the years up until today and Watson, that was launched to fame in similar manner, by winning Jeopardy in 2011.
Deep Blue actually lost the first game in 1996 with 4-2 in favor of Garry Kasparov, but in the re-match in 1997, Deep Blue won.
Since publishing the post on what languages Watson supports and how much Watson actually cost, those posts have generated outstanding most visits on this blog. Since Watson is constantly updated I thought it was time to update those posts since the Watson language post is from Dec 2015 and the Watson price / cost post is from August 2016.
I will in this post just point out some major updates and differences, the complete tables of languages and prices etc are in the respective original post.
New, discontinued and merged Watson APIs
Today there are 13 APIs available with a lot of merging happening. Well, there is actually 14 listed today, but Tradeoff Analytics is already discontinued, so 13 is the correct amount. Just recently a few APIs have either merged or been discontinued. Dialog is now only available through Conversation (no more XML horror), Alchemy is fully integrated and all the visual / image APIs are merged to one. I like this change even though it is kind of the opposite of what IBM told us a year ago when the stated there would be 50 APIs released. To be honest it is a lot easier to work with 14 then 50, so great to see this merge happening. This might naturally lead to the notion that you pay for more features per API than you actually need, but overall IBM has lowered the price, so that is not currently a risk. I only found one service where the things had changed in a negative way, and then it was only the free option for Language Translation, it has decreased from 1.000.000 free characters to 250.000.
Update: What does Watson cost?
Below are some notable changes to the Watson pricing.
Natural Language Understanding: Compared to Alchemy Language, the entry level has decreased from $0.007 to $0.003 per call, which is a significant decrease in price. Secondly, customized models have decreased from $3500 to $800 so also a price decrease. Otherwise very similar structure.
Conversation: Price decrease as well, from $0.0089 per call to $0.0025 per call.
Language Translation: Primarily a 75% decrease in free translations from 1.000.000 to 250.000. The only service that is updated in a negative way.
Visual Recognition: More than 50% reduction in price for Custom Classifier Training per image. This is great since that is a key feature in Visual Recognition that no one else is offering. IBM also removed the fee for storing the custom model.
Discovery News: Is the old Alchemy News. Fee model is integrated into the Discovery service instead as prior in the Alchemy Language service.
Discovery: A new search engine service, so updated the table with the pricing for this service.
Unfortunately not so many updates as one would have hoped for during the 1.5 years that have passed since my initial post on the topic, still there are some changes. First the documentation is now a lot better and most services have a “supported language” section available, not all, but most. I assume the merging of some services has enforced some structuring of both the APIs as well as the documentation, which is very notable in the Natural Language Understanding documentation. Prior it was scattered all over and documented in so many places it was hard to keep track, now it is all displayed in a nice table (which is included in my post as well). Outside of that, there are just a few languages added to the APIs.
In the table, I have tried my best to provide accurate links as well, so it is easier to find updates on the languages and to read more if needed.
Is Chef Watson included in IBMs new Watson Ad product? Chef Watson is the most publicly talked about Watson use-case, after Jeopardy I assume. Chef Watson takes a scientific approach to cooking and creates dishes that on a molecular level as well as cognitive level should fit together, it creates some pretty interesting recipes, but yet mostly tastes really good (yes, I have tasted dishes made by Chef Watson), but where did Chef Watson go?
Can I buy Chef Watson? Can I use an API all consume the brilliance of Chef Watson? Or was it just a gimmick to be used as marketing for IBM?
Well, none of the above it seems, even though the API example might be close, and naturally, marketing plays a part as well, but no, none seems fully correct.
Nonetheless, Chef Watson is still available for us all to play with at IBMChefWatson.com.
Is Chef Watson commercially available?
The initial and most interesting question must be: Can a company pay for access to Chef Watson and integrate capabilities in their business applications?
The answer seems to NO. Have been involved in discussions where companies (large global ones) have tried to acquire access, but been denied by IBM. The reason given has been that the Chef Watson team has been focused on the Watson Ads initiative. Watson Ads?
What does Chef Watson has to do with Watson Ads……and more importantly, what is Watson Ads? Does IBM nowadays produce ads or ad-tech?
What is Watson Ads?
An example is Campell Soup that is an early advertiser using Watson Ads. If you visit a site with a Watson Ad from Campell you can start to chat and ask about recipes etc. Naturally, the answer will be recipes based on Campbells products. You can play with the ads on watsonads.com. As an ad product it is actually pretty cool and I hope many companies start to use this format instead of dumb banners etc, these are both in context and has a way higher level of engagement, which probably lead to better conversions.
Watson Ads seems to be a product brought to life by the Weather Company (acquired by IBM a while ago and a part of Watson). The product is an ad format that acts like a chatbot. The chatbot is listening to your questions and replies with contextual replies that suggest ways to consume the products of the company whose ad you are chatting with.
So, finally I have understood, what I believe is, the reason for the Chef Watson team being involved with the Watson Ad product.
I want Chef Watson APIs
I am not entirely sure that ad-tech is a great fit for IBM, I am not either entirely convinced that directing the Chef Watson team towards an ad product is the best use of those brilliant people, but now that the Watson Ad product is out there, they might go back to providing the capabilities of Chef Watson to others. Hopefully, the components of Chef Watson can be a part of the Watson APIs as the capabilities from Weather Company and the other Watson APIs that are already available. Would love to do some interesting things with a Chef Watson API.
I have wanted to share this for a while and it never seemed to be the right moment. Well, here it is! This started as a vision a while ago, originally based on an idea from my brother-in-arms Carl and together we brought it to this (Peter & Svante not to be forgotten as co-conspirators as well).
This is an IBM Watson-powered cognitive financial companion for your complex financial life.
The video walks you through a day in your life with your financial lifestyle companion.
Above, in the video, is your financial companion that wants to inject value in every transaction you make and improve your complex financial life.
The simple background is that our personal financial lives are complex and scattered all over the place, the customer experience is usually really bad and we are constantly ripped off by fees / bad advice. Today with cognitive platforms like IBM Watson and more intuitive user experience through chatbots and other methods, we can actually improve our financial lives with products like this one. One important thing is to actually empower the users and not only capitalize on them.
It is powered by IBM Watson APIs and a lot of nice mojo from our team.
Yesterday I wrote a lengthy ramble on what we need to change with the internet today. Much was about how we and others use our personal data to mislead us (propaganda, fake news, alternative facts, behavioral analysis and psychometrics), but then I realized that I have actually written about this before, more than a year ago. In the below post “Transparency is the future”.
At that time none of what I wrote yesterday was public knowledge (that does not mean it did not happen), but AI, cognitive and psychographic profiling (e.g. Personality Insight with Big 5 / OCEAN, sentiment etc) was starting to be seen as important. I then realized a big challenge in all the data that is available and what actually could happen if we did not think things through. The key takeaways are:
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.
We and everyone else in the segment need to be fully transparent about the following:
How we store the data
How we keep it safe
That personal information is not shared and are truly personal
Provide info on the reasoning on the answers provided
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.
Well, we did not think things through and now we have, misleading information and propaganda all over the place and our behavior online is constantly being profiled and then targeted…….but what is really sad is that we could have prevented it.
It is all our fault, we cannot blame anyone else!
… unfortunately, we did not decide to guard our personal data or to be transparent in what way the data is used!
It is all our fault, we cannot blame anyone else!
Photo: Kallbadhuset in Helsingborg (no I do not dip voluntarily in Swedish waters, too bloody cold), taken during a dog walk an early morning in March 2017.
With political powers, dictators raising, cyber-threats intensively increasing and nation sponsored propaganda machines and troll agencies always present, we need to improve several things with the Internet of today. We need to take back control over our personal data, stop misleading information and become more transparent.
It has been quite here on the blog for a while, there are several reasons for that, but one of the more important ones are that I have been struggling with what is happening with the Internet of today. The last several years, disinformation, propaganda and fake news / alternative facts have almost entirely taken over the flow of news and important information about the society we live in and the world in general. When you start to investigate this you realize how perfected the system is and how much impact it really has.
This is not about Brexit, Cambridge Analytica, Trump, Bannon, Sverigedemokraterna or Robert Mercer. They are just using the tools available at hand to reach their goals. It is how several components work together.
The System I am referring to here is much more than Trump and Russian (or US for that matter) propaganda and / or nation-wide hacking, it is more about how we consume information today and how the companies providing this information does not have any incitement to prevent this from happening, the opposite actually. The more times we click on these links the more money they make.
Facebook and Google make a living of presenting information they think we want, now that organizations, countries, brands, politicians and individuals have found ways to use this information to manipulate us, it is has become a flawed system.
Revenue makes this system tick
I will use Facebook as an example, but this is not isolated to Facebook in any way.
Facebook is an ad-tech company. Their business model is to provide tools for advertisers to put the advertising company’s information on the screens of a very targetted audience and charge money for that service.
User targeting. The success of Facebooks ad-tech is in two major parts. The first is the amount of personal data we have given to Facebook (does not matter how much you change your settings, they still will get to you) and the second thing is how they utilize that information to let advertisers target you based on interest, location, gender, age, civil status, your friends, what is in your photos, where your photos are taken, where you have been etc etc. An additional scary thing is that most have also given Facebook access to other personal data like browsing history etc, that is why you see travel ads on Facebook an hour after you search for your next vacation destination with Safari or Chrome, that info is added to your info used for targeting.
News targeting. This is what most people do not think about. We hear about filter bubbles and most of us have realized that the news we get is in some way personalized to fit my interest and behavior. Facebook wants us to interact as much as possible with content on the platform, so they push news to our feed that they think we want instead of showing a constant feed of lunch-pictures, which we do not interact with as much as we do with news-posts. That is why you see news articles more often even though just one friend has liked that post and 10 of your friends have more recently posted a picture of their newly ingested lunch.
Conversion. The conversion rate that Facebook provide in most of their metrics is actually astonishing and the reason for that is naturally no 2 above, but to further increase this conversion they are mixing no 2 and no 3 to elevate their revenue.
Since advertiser can impact what information that is put in front of the users, a bad spiral has been created (and that is why Mark Zuckerberg constantly denies that Facebook had any impact on the US election).
The scary part – Conversion
When it gets really scary is when this data is used to profile us and put information in front of us that we actually do not agree with, but when in the way it is presented we lean towards agreeing and by this changing our mindset. This can happen since behavioural analysis is done on us and information is then presented in a way to shift our mindset. This method is perfected and originally from Cambridge University (no affiliation to Cambridge Analytica though).
It is today easy to plant disinformation, propaganda or simply false news. This also creates nationalism and authoritarianism.
This is the system that Cambridge Analytica has been utilizing when they helped Trump get elected. They did social profiling on almost every US citizen that can vote and personalized their feed to shift their beliefs (and if it did not work re-iterated until it did, on individual basis) in favor of Donald Trump. Cambridge Analytica is a company rarely seen in public, but a brief background is that it is funded by billionaire Robert Mercer from one of the most successful hedge funds in the world, Renaissance Technologies (before becoming co-CEO of this hedge fund he worked at IBM Research on computational linguistics). Cambridge Analytica also has senior Trump advisor Stephen Bannon on the Board of Directors. The CEO is Alexander Nix and it has a UK version of it as well with the name of SCL Group. SCL Group did the same thing for Brexit. Below is a video of Alexander Nix presenting what they did for Ted Cruz in the primaries, before they joined forces with Trump, it still describes what they do pretty well.
The evil ecosystem
This ecosystem is several parts that feed off each other.
The Platforms (Facebook etc)
The Impactors (I think I just made up that word). The ones that want to impact us
The users, that would be you and I
The platforms want revenue, the impactors want to impact us, the users want news and relevant information.
As you see in the ecosystem section above the last part is flawed, since we are not getting information and news that is relevant, but information others (the impactors) want us to consume and be impacted from. This is a major flaw on the internet today. It impact us all in a very very bad way.
As most things in business, Facebook (again, they are just the easy to use example here) is revenue driven and they want us to see and potentially interact with as many ads as possible and that makes us vulnerable for misleading information that creates a world made of powerful people where we, the internet users are the enabler for this happening, this without our own intent and knowing.
We need to stop misleading information and take control over our personal data.
Why this rambling? I have for some time tried to get my mind around this and since I have been quite heavily into cognitive computing and AI the last years a lot of thoughts have crossed my mind. With my background it might have been logic to work more intensively with large corporations on how to target their audience in a better way with behavioral targeting (using cognitive solutions), but my conclusion is that it is not ethical to use social, behavioral profiling and cognitive computing to do this.
I have at least 10 posts on this topic in draft mode, but have not published since it only paints a negative picture of the current world and some are almost doomsday prophecies. Just imagine the post I have on “Cognitive Warfare”, interesting, but also a bit scary, will keep it in draft for a while longer.
We need to tackle the problem with personal data and misleading information first.
When the users are safe and the information is not misleading and transparent, first after that we can use cognitive to interact with users the right way as a business.
What is Watson Beat? It is a cognitive technology that makes original music inspired by songs you play for 15-20s. Sounds bananas I know, but this could really be a game changer since Watson Beat creates music completely without bias and trends.
UPDATE: As gdf pointed out in the comments, Watson Beat is now open sourced. So if you want to play around with Watson beat, just go to the Watson Beat github page.
Most Watson services are built to learn and from that reason and suggest solutions to our questions, that is not the case with Watson Beat. Watson Beat is “inspired” by the music we play for him and then he creates a new song based on that inspiration. Since Watson is not taught by being played thousands of songs as he was with movie-trailers when he created the Morgan trailer, but being taught “music” (what pitch is etc) he will create songs without sounding like everything else and therefore actually contribute to potentially new genres or new trends in music. I think we all remember those years when everything that was released sounded like it was produced by Timbaland (and mostly was)?
“Watson Beat is not constrained by normal human biases, and those biases can actually get in our way,” says Rob High CTO IBM Watson.
You can often hear slight traces of the original song, but that is not always the case. Here is the Set from Soundcloud.
I first noted that Watson Beat was in the making when I stumbled upon the IBM Research Soundcloud account and found a set that was named Watson Beat. At that time I tried to find more information, but it was a dead end for me, I just found out it was an IBM Research project that might be released.
Just recently I found this Facebook Live video with the two individuals that build Watson Beat at IBM Research. In the video, Janani Mukundan, a machine learning researcher at the IBM Austin Lab and musician Richard Daskas, say that the app hopefully will be released by the end of 2016 and, more importantly, it will be released as Open Source.
I think it is a very interesting project and looking forward to play with the app when it is released.
Since Watson is a cloud service, security and data privacy are important. This paper on Watson, Watson Developer Cloud, Bluemix and Softlayer is a great overview that should bring some clarity and comfort on the topic. Watson Developer Cloud Services Security Overview
One of the biggest challenges with the cognitive era and for enterprises to adopt this shift is in my opinion, two things. The first is the gap between the tech and the business, which leads to the constant question “How do we start?”. The second one is that most companies selling this tech have a salesforce that is used to sell other things and have not had time to adapt to selling cloud-based cognitive solutions to their customers.
The gap between tech and business
Traditionally companies selling software to the enterprises have a preset business proposition. An example is SAP for financial or Salesforce CRM for sales. If we go a bit more tech it can be a database to store things in or it can be an application server to have our apps running. With AI and cognitive computing, it is something else. We hear all these execs talk and talk about how great cognitive businesses, products and processes will be, but how do we convert these high-level talks to become concrete solutions that will evolve our business? I read a post on the Watson blog the other day and it contained a video of several execs from IBMs Watson unit that talked about how great cognitive business and cognitive computing are (IBM is an example, it could be Google, Facebook or Microsoft, but since I often post pro-IBM posts they can be the example in this post). Try to make something out of the video that you and I can convert into real-life adoption. Really hard, isn’t it?
Additional fun from the video:
The title of the video is “How IT and Watson are partnering in the Cognitive Era”. Ok, what does that even mean? The video does not give a single indication on how IT and Watson even partner, on what level or in what way?
A quote from the video “Adopting cognitive solutions is not as difficult as it sounds!” I agree, but the “how” or “why” is completely absent.
What the heck is Watson anyway? Is it a product, a suite, a platform, APIs, a human, a computer,? If it is supposed to be easy, like the video insinuates, it might be a good idea to make that crystal clear what Watson really is. If you have read some of my posts you hopefully know the answer though.
Number 3 in the list is a big challenge I would say. It needs to be very clear what Watson is for companies to grasp the potential of what they can do with cognitive solutions like Watson (I think it is the same with Googles products within this space). In Watsons case it gives each salesperson the right to interpret this to their benefit. This happens every day at IBM when sales uses the Watson terminology to push clients towards “their” Watson product (if in Analytics, you sell Watson Analytics, if in Cloud you sell Bluemix and the Watson APIs etc). From a short-term pipeline point of view it might be good, but for the customers I doubt it is good.
We need to bridge the gap between high-level executives like those in the video and the APIs, this so it becomes easier for companies to actually adopt and become more cognitive. If this does not happen I am afraid many companies will miss huge opportunities and the cognitive software providers will miss out on great revenues from their great software.
What happens today is that you get either the high-level exec buzzword-ish mumbo jumbo or the deep deep tech talks about how the tech actually work, usually only with one single API (or pre-packaged solution like Watson Virtual Assistant). That will not build great cognitive businesses.
A new salesman / women is required
Selling cognitive solutions requires a new type of salesperson. The classic software sales rep has a portfolio of boxes that is dressed up for each company it is presented to and wrapped in a nice business case, usually a business case that is applicable to many customers, not only one. The new type of salesperson needs to look at things differently, it is mainly about creating the value proposition together with the customer. Cognitive is not a product it is an enabler to make your business better and faster. It is up to us as sales and business developers to actually understand and apply these new technologies to our clients and customers. Why is this a problem? Simple, customers do not get the best solutions presented to them by their salesreps. They get pre-fabricated food, when they could get the two-star Guide Michelin dinner. They would probably pay less as well and get a solution that over-delivered on their expectations.
Why sell pre-fabricated frozen pizza when you can sell a personal dinner at a 2 star Guide Michelin restaurant?
Companies that sell cognitive computing APIs like Watson need to shift to a new salesforce. Another great thing is that this new salesforce will also think cloud-first and not old on-prem software. They will understand how these cognitive APIs exist in the cloud in a secure and compliance ready way. Most of your old salesreps will have a really hard time converting their old way of selling to selling APIs in the cloud (at least in the right way). I would say that the only way to trigger a shift of the old reps is to change how they are compensated and completely shift to cloud based incentives, otherwise they will stick to their old stuff (I sell what I know works).
This post is almost without a specific topic, just one thing I felt needed out of my system. Salesreps, get your act together and start to sell real value to your clients, they will appreciate it. Put in the extra work to build a case for your clients that match their needs and their business, they will value it and it will hopefully be a fruitful relationship for everyone involved.
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.
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.
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.