future – THE MIGHTY DATA

They invited me to write National AI Strategy. So I proposed to …

Have you ever thought about how artificial intelligence would really be at most useful for your country? I was “forced” to do so by fate. Therefore, let me briefly depict what I think should be the key invest areas in AI court; How to bring artificial intelligence even to rural areas? But first of all, how to make world-class AI here, ideally in local language?

Sometimes you dip into things you even don’t know how. This was the case also one day when a strange email landed in my mailbox. Don’t take me wrong, I really have experienced a lot of bizarre pieces in email communication. But this one was really strange. It was an invitation from the National Artificial Intelligence Forum that they would like me to join the team of experts assembled to create the National Strategy for Artificial Intelligence (AI) for our country.

At first, I wondered if this was not a joke from one of my friends. But since April 1 has been already pretty quite away, I started to seriously consider that someone really means it. “Why me?” I asked myself. After all, strategic documents of this kind are not my daily job and I don’t know much about national AI programs of other countries either. However, the authors of the email seemed to anticipate my embarrassment and they left nothing to chance. In the invitation, they explained that the expert team will combine 1] academic environment, 2] representatives of domestic AI research companies, and 3] business representatives who already use real AI technologies today. I quickly realized that I owed my invitation to the third group. So I exhaled in relief … and confirmed my participation.

If I decide to devout my time into something, I try to make it at least of some quality. Therefore, immediately after accepting the invitation, I started studying the AI strategies of other countries. However, I was not looking for ready-made measures that could be “borrowed”. Rather I tried to dive mainly into parts where those papers discussed ways of assessing the country’s initial situation. For I realized that for country strategy, I was just about to participate, it will not help to “invite” the measures chosen by US or China. Thus sooner that I took part in any round of measures brainstorming, I had crystallized the key AI assumptions in my head. These were (euclidean) premises I decided to defend as the starting point of group work. I am sure there could be a lot of “meditation” on the topic of AI maturity, but I tried to put my postulates into as few points as possible:

The country for which we are going to prepare an AI strategy is not one of the current AI leaders, nor even the leaders in AI research. Therefore, at least to start, we will have to build upon already existing foreign solutions. (it does not rule out research focus as such into the future, I just mean that we do not have enough of our national research to draw from there)
Although AI is a wide spread buzz-word, what it really means and how it can be used in business, is known only to limited communities of people, mostly associated in university cities. Even in mid-sized cities that do not have a university or in the countryside, no one (including a local pastor, bartender or mayor) has a clue about what true nature of artificial intelligence is and what its applications are. In other words, AI awareness is very unevenly geographically distributed across the country.
Most countries have a very specific language environment. If a relatively few people speak English in given country, recently available, foreign (NLP and other AI) solutions will not work well. If the implementation of AI in a country were to be based on English solutions, it would be very risky both in terms of quality of solutions and due to (possible) resistance by end-users. (If you are to understand a conceptually difficult thing, it is not very helpful if it is also primarily described in a foreign language that you do not speak)
The whole world runs primarily on open-source AI solutions. Even the most advanced companies publish (on GitHub) their libraries for AI solutions.
Let’s think for a moment. How to maximize the effect of AI on local companies in the country? I admit, this is also a bit of a personal belief dilemma, because any answer to this question can be suppressed with phrase “who knows, how it really will be”. Nevertheless, I personally believe that AI will reach its maxim, when even ordinary, small businessmen will embrace it.
I came to the previous conclusion after also considering the fact that large, multinational companies will take care of the implementation of AI in their local subsidiaries. Large (abroad reaching) local companies will be pushed by competition from those other countries. The only group (in the first stage) that will not be guided to this are the national medium and small entrepreneurs. That is why, in my opinion, these should also be the focus areas of the national implementation strategy.
For SME companies, in addition to the language barrier, the “technological abyss” will also be important. Cloud environment is an inevitable prerequisite for most AI solutions design & maintenance today. However, it might be both costly and secondly unrealistic for a small business, as they cannot sustain their own full FTE Data Engineer and have no way to borrow a shared one either.

Enough of preparation, I police myself, and plunged into discussions about the initial strategy proposals. As it turned out later, the above three groups did not necessarily have a balanced representation in the expert team. The Task Force had to, therefore, often choke through proposals that ignored even several above mentioned premises simultaneously. Nonetheless, we ferociously adhered to the golden rule of brainstorming: every well-formulated idea would be included in the long list of possible measures. (knowing that we would have to subject those to more scrutiny later). Sometimes it was really painful for people in practice to withstand the tirades and their teeth were often clenched. After listening to all perspectives, I decided to nominate following draft proposal for the National AI strategy:

1] Create a hosted cloud solution at universities or one of the state institutions (based on a model like Amazon Web Services), as an extension on top of any of the commercially viable cloud alternatives. Using the central hosting/management of this repository, offer a ready-made, all-inclusive symbolically priced packages for AI solutions, which for end-users (and institutions) also include maintenance realized through experts paid by that central cloud provider. Simply turn-key cloud environments.

2] Localize some of the most wanted Udemy / Udacity / Cloudera / … artificial intelligence courses and basic Machine Learning and Deep Learning skills. Purchase a mass license for such localized courses for 100,000 residents in a given country and grant access to these courses for a symbolic amount (e.g. 5 EUR / person).

3] Create a moderate national community for Opensource solutions in the AI area. Collect and localize into national language information on new AI modules and their reviews by foreign experts. Create conditions for Slovak (research) teams to actively participate in the development of individual branches of these solutions.

4] Select 5-6 most important industries in SME segment of companies. Recruit at least one relevant large business per each area to provide local, anonymized data. Organize Hackathons with the participation of international teams, with aim to develop specific solutions for AI use in the industry and based directly on local data. Set conditions for participation in Hackathons so that the developed solutions can be freely picked-up and implemented in any company registered in the country and operating in selected industry.

5] After the implementation of Hackathons, for each industry recruit at least 4 volunteers from within already existing companies to be become pioneer beneficiaries of AI. In those pioneers Central AI agency, via means of a state grants, implements ready AI solutions (from Hackathons). In case of higher interest of the volunteers for pioneer status, a lottery with oversight a notary will be drawn to decide whom the grant ought to be awarded. Participation in the grant is subject to the approval of the company elaborated about in measure 6, see below.

6] Realize roadshows in the regions and district towns where AI and its concrete, ready-to-use solutions (acquired through Hackathon) will be presented. Representatives of pioneering companies with AI implemented under Measure 5 will be presenting at the meetings. instantly available, plug-and-play solution, free of charge and even in local language. If measures 4 + 5 + 6 are overly successful, repeat this procedure for other sectors.

What do you say? Does that make sense to you, or would you suggest something completely different? Well, I will not bore you with which my actions had gained enough “support” for the final draft of the National Strategy. Some passed, others did not survive the fight and prioritization. But that’s not the point of this blog, anyway. In the sense of his unfinished blog title, I wanted to give you some food for thought: What are the inputs for AI strategy in your country where you live? Would you suggest similar solutions for you homeland or do you have much better ideas? How to bring artificial intelligence to the rural village habitat? But first-mostly: How to build world-class AI and (preferably even) in the local language? So that ordinary John and Ann can take benefit of it important process as well.

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AI SUPERPOWERS : Book for those WHO THINK about OUR FUTURE

A few weeks back, I came across the book AI SUPERPOWERS by Chinese author KAI-FU LEE. I think it’s about 250 pages that anyone, who works in the field of data analytics should read (or at least think about it). It’s one of those books that are best when you read them yourself. Therefore, I will try to keep my review a reasonable balance between teasing and the feeling that you already know all what the book should tell you.

AI SUPERPOWERS offers many points to think about. I personally counted at least 20 (!) thoughts that I realized that I haven’t thought about yet. However, before outlining some of them, we should explain who the author is. Kai-Fu Lee is a Taiwanese man who worked for 35 years in the field of artificial intelligence. He started voice analytics for Apple, set up a Microsoft research center in Asia and, as CEO of Google of China faced the dilemma of establishing Google in a country that does not necessary celebrate its existence. He also manages venture capital funds to develop AI solutions. Kai-Fu Lee is a rare combination of experience with state-of-the-art AI approaches from Silicon Valley and a typical Asian “cautious overview” that does not accept simplifications as well as does not need adhere to cult of America is Great. He praises where he sees real mastery and pinpoints hardly pretending and unwarranted stereotypes.

The reason, I think you should read this book by yourself, is that among official lines of the text you will likely find your own inspirations (as it was with me). The book is a busy tree where everyone can choose “how much they sit” on each branch. However, in essence the book is a cocktail of three complementary streams (some of which you would not expect to appear judging by the very book title) :

The first stream (most in line with the name of the book) describes developments in the field of artificial intelligence. It contrasts how diverse the paths to the sophisticated analytics were for the US and China. Taiwan and Hong Kong Hong Kong have a bond with China, but their relationship is not, ehm, optimal. (I have a colleague from Hong Kong who narrates often about it in detail.) So, Kai-fu Lee’s position is not a pink ode on the Chinese model. Quite the contrary, it offers a very balanced view of where China stands in AI area and where lags behind US. As he had experienced both environments, his comparison is a valuable counterweight to the general propaganda both for and against China.

The second line is the author’s personal account of how (thanks to the cancer he managed to overcome) he changed his view on the direction in which artificial intelligence should go. The story of a seriously ill man, who at stair to possible end of his life completely alters way of thinking, is almost a cliché in our culture. But if you manage to be stay less cynical and you will close your eyes on this emotional aspect of the story and focus in reading this section rather on his conclusions, it becomes an inspirational reading.

The third stream of the book was a bit of a surprise to me. But a pleasant one. Being tricked by the title of the book, I did not expect author to try to extrapolate AI trends and describe what awaits us. The focus of this last part is similar to (for me the hilarious) SuperIntelligence book, so very inspiring read. However, as AI SUPERPOWERS came out later, it is already looking at some future aspects of AI richer, with result of the first experiments (eg. with UBI) and, hence, in more specific narrative.

However, in order not to just scratch the surface of this masterpiece, let me offer you few specific inspirational ideas that this book has brought to me. I believe they might be the right “teaser” to actually read the whole book:

Copy-cat China. The book clearly and detail depicts that China has reached its peak in economic significance by copying foreign products. Therefore, author bluntly admits that in industrial production and design of material things, China is certainly not a ruling world power, but rather an “embarrassing copier”. However, the development of online services, AI and data analytics has gone through completely different story. As a result, the latest Chinese advancements in AI and digital services are a still bit in shade of “copy-cat sticker” of the past. But book clearly explains that it would foolish and outright dangerous for the external world to keep perception China in this mental illusion.

From cash directly to App-pay. In some parts of Africa, they have long lagged behind in building a fixed line network, so many areas have been cut off from the world. However, suddenly, with the advent of mobile networks, they could skip the landline stage and get access (to internet) directly via mobile network. A similar episode took place in China in the area of payments. In China, credit cards have never properly settled as a form of payment. And when e-commerce was launched, the market has jumped directly on in-app payments like We-chat or Alibaba.

4 AI development forces. Like any effort, even the development of artificial intelligence has its own factors that can accelerate or hinder it. In the case of AI, the following 4 dimensions seem to be relevant: a) Computing power in the form of HW, b) sufficient human talent, c) volume and quality of data you have for training AI, d) business underpinnings for implementing developed solutions. At the same time, the extent to which these 4 factors are fulfilled by a particular country predetermines what role that country should take in applying the AI. I also used this knowledge to prepare an AI strategy for Slovakia, which construction of I had the honor to participate in.

The status of your phone’s battery. When predicting phenomena, you should use all the available inputs and be aware of whether you are not limiting the possibilities of AI by your very own prejudices. The book gives some great examples on this subject, most of which I liked how the usual state of your mobile battery is related to your discipline of paying off financial obligations. My regular readers know I’m a strong promoter of Feature engineering and data riddles, so I really enjoyed this part.

Probably this much, Your Honor. In many areas, AI will serve as a human counselor. Medicine is often discussed, but Justice is more of the Taboo so far. Artificial intelligence can also be helpful in this sensitive area without machines deciding on us. There are already systems that search within historical court records to detect false testimonies of witnesses, contrasting the information given in previous legal litigation. Moreover, AI can provide inputs to calibrate the severity of penalties for the same criminal acts (using scatter-plots between particular aggravating/attenuating circumstances and the length of the sentence periods to see if the proposed sentence is too strict or moderate).

Autonomous car(t)s. The discussion of self-propelled vehicles is primarily zooming on autonomous cars. However, there are much simpler implementations that are both not as dangerous and show much more of immediate, mass-use potential. These include shopping carts, for example. They could be programmed to follow you (and stop whenever you turn to fetch something) or even set themselves the fastest route through supermarket, depending on where your shopping lists items are located in store.

Hold on, I’m sending you a drone. The second implementation of self-propelled vehicles, which is simpler than cars, are flying things. No, this is not hype about drones, but really there is more space in the air and lower chance of collisions than on the road. We might not realize it, but the planes were equipped with autopilots sooner than cars. We also have pilot-less attack aircraft, but not unmanned tanks or warships. Therefore, one of the nearest ways of AI use will be unmanned rescue units that will be able to extinguish fire or rescue people even in the exposed terrain, without compromising the lives of the helicopter or aircraft crew.

O2O, the key to platform success. Online-To-Offline (O2O) is a concept where you start a service in the online environment but at its end there is material fulfillment in the physical world. Examples of such services are E-commerce, Uber or Booking.com. Markets that offer o2o products are more tangible to people than pure virtual services (self-learning courses, online software business). People feel the physical dimension of such a service. Therefore, we are also more willing to pay for such a service (such as pizza delivery), while services such as online tax advice are only slowly collecting their enthusiasts.

What is different this time? Past industrial revolutions are often used as an example of how mankind has dealt with the harsh changes in the labor market. Thus, the optimists say that even AI will not be a disaster for jobs (by the way, a few words why Kai-Fu Lee is not so optimistic on this note). This book brings one interesting twist to this issue, the Deskilling paradigm. When attentively reading the history, we find out that the jobs, that sprung after the industrial revolution, required of workers shallower knowledge of the matter then their alternatives before revolution (weaver vs. weaving mill operator, mathematician vs. man with a calculator, …). This phenomenon is called Deskilling. The important question remains whether we are ready to admit such a development for healthcare professionals or teachers. To put in one sentence: In the AI Industrial Revolution, the vocations at stake are those where the credibility of the profession is linked to the human factor.

Bigger surveillance, not weaker one. Due to the accumulation of data and some other factors, AI services have a greater tendency towards monopoly than in other economy sectors. (anybody, Google?) It is, thus, important that the AI industries are subject to stronger rather than the weaker (antitrust) regulation than traditional industries. However, the states are lagging behind both in legislation as well as competency to steer them. There is no clear idea how to regulate services such as Facebook and public authority, at the same time, lack educated employees to supervise them first place. It feels almost like if there was no one with medical education in Health Care Supervision Office.

If you are interested in any of the topics, I encourage you to read the entire book. It’s really worth it. If you’re still wondering if it’s a good (time) investment, check out the Kai-Fu Lee’s video, where he talks about some parts of this book.

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5+1 interesting AI videos

After reviews of some AI related books caught quite a interest from TheMightyData.com community, I decided it to elaborate on these points a bit and point you to yet another insights. To prevent turning you into bookworms, I decided to pick a bit more engaging media this time and I would like to inspire you to see some good AI related video speeches. Enjoy!

How AI can save our humanity | Kai-Fu Lee

If you work in AI community name of Kai-Fu-Lee might not be unknown to you, as he stood behind boost of AI in Apple (and few other platforms). What is more, his view on AI is rather encouraging. In his life (and attached video) he strives to point our areas, where people can succeed even after AI fully kicks in. Is it hope worthy following? Well, that conclusion I leave up to you to make after seeing this great video.

A brain in a supercomputer | Henry Markram

There are at least 2 things fascinating about this video. The first one that it was filmed 8 years (!) ago. That depicts how far away the Oxford guys have been in the respective topic already back then. Even 10 years later down the road, some research teams are not at verge of the same understanding of matter. The second fascinating aspect of the video is that in less than 16 minutes, it walks the spectator from basics of Neuroscience up to expert insight on Neural Simulations. And that is certainly worth your 16 minutes.

The Truth Behind Artificial Intelligence | Andrew Zeitler

Andrew was only (hard to believe) 17 years old when he delivered this speech. And if you pardon his young enthusiasm (here and there bordering with affect) he will introduce you to load of interesting thoughts on what are the next milestones for General AI, as well as how will General AI most likely behave, when it comes. For those educated in matter, some parts of the speech might be, I admit, a bit sluggish. However, have You pumped into applause any hall of that size when you were 17?

Where AI is today and where it’s going. | Richard Socher

Richard Socher is professor at Stanford Computer Science Department, mainly focusing on Deep Learning. And he is awesome in clearly and humorously explaining what progress there has been achieved in neural networks lately, as well as stating where AI still drags its feet (as you will see sometime literally). For those facing master or PhD thesis this might be good short list of highly desired topics. If you out of school and happen to already work in AI area, maybe an inspiration to educate more about some areas of AI, you did not cross upon yet. But even if you are lightly interested in AI topics, Richard is a great entertainer, so its worth seeing the video just for fun sake.

Music and Art Generation using Machine Learning | Curtis Hawthorne

Creativity is one of the often cited to be “last fortress of human superiority”. Machines cannot be creative, so at least here we are safe to assume human dominance for longer time, right? Well, to assess to what extent that is really true, I suggest you see this video by Curtis Hawthorne, who reports on how far (they in Google) machines got so far.Next time you hear this soothing self-defense of humans, you already will have an educated arguments to discuss.

The final bonus+1 track id nobody else but Nick Bolstrom, the author of the book SuperIntelligence. In his video he describes basic principles of his book. So if you have not read my review of this fascinating piece of reading take a try with the author himself to motivate you to read it.

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