Do you need developers in the future?

    It's time for entertaining stories. To begin with, I propose to stock up on cookies and a large mug of heating fluid. Have you got everything? I present to you an interview with Dmitry Zavalishin, founder of the DZ Systems group of companies, and Alexander Lozhechkin, head of the Microsoft Strategic Technology Department in Central and Eastern Europe. In it you will learn how Microsoft has become today, how we compete with Amazon, and the most interesting thing that will happen to programmers if artificial intelligence enslaves the world. Under the cut you will find its textual decryption.



    Digital Transformation Series


    Technology articles:

    1. Start .
    2. Blockchain in the bank .
    3. We teach the machine to understand human genes .
    4. Machine learning and chocolates .
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    A series of interviews with Dmitry Zavalishin on the DZ Online channel :

    1. Alexander Lozhechkin from Microsoft: Do you need developers in the future?
    2. Alexey Kostarev from Vera Robot: How to replace HR-a with a robot?
    3. Fedor Ovchinnikov from Dodo Pizza: How to replace the restaurant director with a robot?
    4. Andrei Golub from ELSE Corp Srl: How do I stop spending a ton of time shopping?

    Who is the interview with?


    Dmitry Zavalishin is a Russian programmer, author of the OS Phantom concept, organizer and member of the program committee of the OS Day conference, founder of the DZ Systems group of companies. In 1990-2000, he took an active part in the creation of the Russian Internet segments (Relcom) and Fidonet, in particular, ensured the transparent interaction of these networks. In 2000-2004, he was responsible for the design, development and development of the Yandex company portal, created the Yandex.Guru service (hereinafter - Yandex.Market). Read more on the Wiki .

    Alexander Lozhechkin - Head of Strategic Technology at Microsoft Central and Eastern Europe, Member of the Board of Directors. In his free time he has a personal blog on Medium., in which he reflects on various topics, ranging from evaluating the work of employees, and ending with philosophical discussions about delightful mediocrity.

    Interview


    We are used to the fact that Microsoft is a technologically highly closed global monster, which, in general, is quite tough on technology synergies and seeks to completely drag people who started using them into its picture. It seems that this is not so today and Microsoft has changed quite a bit. Alexander, tell me about this, please.

    I have been working at Microsoft for 14 years, and have seen many stages of the transformation of the company. Indeed, for some time it was rather closed and focused on its technologies, but this has changed a long time ago. We love non-Microsoft technologies and understand that a world built on the technologies of one company will never exist.



    Therefore, it will not be the one who makes the technology that can capture the whole world, but the one who can best integrate with the technologies of other companies, manufacturers, and communities will benefit. We long ago set ourselves the goal of becoming a company that is most open and integrates best with other technologies. Open source, java, anything, everything works for us, we are trying to develop these areas.

    If you look at the structure of Microsoft products, you can see that the company has always been, conditionally, at the bottom of the stack: operating systems, compilers, DBMS tools, in other words, the tools that lie with the programmer. And the topic of digital transformation, conditionally, is at the other end of this scale. It is more business-related and concerns the ability to apply a set of IT tools to real business. Why are you there? And in what format are you there?

    Microsoft is truly a platform company. We do and continue to do so many products that, as you said, are at the bottom of the stack - these are our cloud technologies, compilers, database programming languages.

    In addition, we make products based on these products for productivity, for example, Office. Although one could argue here, is Office a product or a platform? Because you can expand it to infinity. Plus, we have a large line of business solutions - Dynamics. In principle, all parts of the stack are closed, but the digital transformation, it seems to me, can work at any of these levels.

    Here I would recall a rather characteristic attribute of all Microsoft products and technologies - this is their availability. Microsoft was not the company that invented PCs, but Microsoft made PCs appear on every desktop. You can scold Microsoft for this, you can not consider Microsoft technologies perfect, but the fact that they were able to spread around the world is a fact.



    Now we are trying to do the same with artificial intelligence technologies, which very often stand behind decisions in digital transformation. Our goal is not so much to make them the most perfect (although we are also trying to do this), our goal is the democratization of AI, the democratization of information technology. We want to make the cloud available to any company on the market, to make artificial intelligence and ML technologies available to any company. This will allow companies to transform very quickly.

    And what does this mean in practice? Roughly speaking, if we are considering a developer who has set himself the task of providing the IT component of some new or traditional business, why would he come to Microsoft today? And what would you recommend him to consider first? What building blocks and which bricks could he use? (Offhand)

    At our place, I would first of all start with cloud technologies, since this is now what truly changes the world around. Here, I like to use this analogy with the famous quote that God made people, and Mr. Colt made them equal. I shift it to business: God created companies, and cloud technologies make them equal. Thanks to cloud technology, the capabilities of computers that were previously available only to large companies are becoming available to any company, whether it be a small startup or a company in a small or medium business. Today, you don’t need to build mastab data centers, invest huge resources in their support, and so on, in the cloud you can easily use the latest technologies, the latest ML algorithms, the same AI.



    Therefore, to your question about bricks, I would recommend using cloud technology. It is worth noting that our approach here is not that we dictate some of our own rules, what the cloud should be like; we give companies the opportunity to choose a stack suitable for them. You can use our cloud technologies in public clouds, that is, in our data centers, or you can, with a high degree of symmetry, build a similar infrastructure in your data center. But, in any case, it all revolves around the clouds, and then ML and AI technologies arise, such as the Cognitive Toolkit.

    That is, these are some software components that a developer can use. And if he deploys his application in the Microsoft cloud, then are these components ready for him?

    Yes, absolutely right. And here the use of technologies of other companies is not canceled in any way. For example, the same TensorFlow works great on virtual machines in the Microsoft Azure cloud. There are no restrictions and there are a large number of applications of third-party services. And this is probably the key attribute of what Microsoft has now become. We do not impose a choice, we provide it for everyone.

    How do you compete with Amazon? Indeed, the Amazonian cloud is quite solid. It seems to me that he was almost the first in this market. But appeared a very long time ago, at least. You still came a little later. Do you have price competition? Functional competition? What distinguishes you from the most powerful competitor?

    I would probably consider this issue a little more broadly and start with what we mean by cloud technologies. For example, the same hosting providers call themselves cloud providers, and this is probably true. There are several players - Microsoft, Amazon, and Google, who are present all over the world, and there are a large number of slightly smaller scale hosting companies that also, in general, offer cloud technologies may not be as developed, not so serious, not so big the number of implementations and stuff, but anyway, it's cloud technology.

    And if we consider this market more broadly, it turns out that, firstly, one player has no dominant position, and the market is very fragmented. And secondly, the market is growing very, very fast, so whoever the leader of this market today, no matter what definition we use, is not the fact that this will happen further, because the market grows significantly every year. For us, the main thing here is to grow at a faster pace as the market grows. Returning to your question, what is our difference ...



    Differentiation with Amazon - we try to keep up, firstly. And if any new technologies appear there, we try to implement them at home. We try to offer something that our main competitors do not have, and here, again, I would not forget not only about Amazon, but also about Google, and about everyone else.

    That is, the ML components for you are such a distinctive advantage?

    Initially, in general, Amazon arose as a service for providing virtual machines. Infrastructure as a Service (IaaS) is where they started, plus storage. We installed it on the Platform as a Service (PaaS) from the very beginning. That is, we did not offer just basic virtual machines, but some services built on top. And still, this is a very big focus for us.

    We later Amazon entered the market of basic infrastructure, virtual machines appeared a bit later, but now this can be said to be comparable. This is precisely the area in which we are trying to keep up and, perhaps in some ways, get ahead. Our main focus is PaaS and AI as one of the components.

    And here I, maybe not so much from the point of view of a Microsoft employee, but from the point of view of a person who is interested in the topic, noted how interesting the competition is now moving from software to iron.



    Microsoft recently introduced a project that was once a Microsoft Research project on the use of programmable matrices for ML algorithms. It has already been deployed at many of our data centers. This is a thing that can greatly accelerate typical ML algorithms. And the example that we showed not so long ago is when we translated “War and Peace” on the stage from Russian into English, and it turned out that if we use the same algorithms on basic virtual machines, this, relatively speaking, takes a day . When used in programming matrices, it takes already seconds or minutes. That is, there is an increase of hundreds of times, and it seems to me (again from my private point of view I’m looking) that the competition will go further to where different providers of cloud services will compete in providing something unique,

    That is, roughly speaking, this means that the cogs that you provide have these subsystems available for software. At the same time, do I understand correctly, maybe we will bury too deeply now, but it’s really very interesting. Roughly speaking, if we take a standard neural network, which is a set of layers, then part of the layers physically degenerates into the hardware components that AI computes?

    Yes, absolutely right. And due to this, a dramatic increase in productivity is obtained.

    Not surprising. This, of course, is a very serious application.

    This is the first moment by which we try to differentiate ourselves, and the second moment is what I already said: we initially have hybrid clouds. We are not talking only about public clouds, like our competitors, we are talking about the fact that the clouds should be either in private data centers, or with a hosting provider, or in our data centers, and we try to maintain a very high degree symmetries between what is available in public clouds and what the customer can deploy.

    And in FPGA can deploy?

    No, here in FPGA they cannot. Naturally, there will never be full symmetry, but at least we try to ensure the highest possible degree of symmetry, and this is exactly what a product like Azure Stack aims for - this is when you deploy an infrastructure in your data center that allows you to practically without rewriting, without changes, without adaptation, deploy a large number of applications both in the public cloud and in your own data center.

    And of course they can be integrated software?

    Yes, they are integrated, and it turns out that the public cloud can be such an extension of the private. When you store something at your place, let’s say you cannot give away some data to the public cloud. And the second cloud is needed in order to very quickly increase and scale loads.

    In this case, quite often there is such a fairly obvious topic as public and private sharding. That is, roughly speaking, we want to store the data of this user publicly or in this country, and the data of this - either non-public, or simply in another country. Is there any support for this?

    There are technologies that allow you to do these things, and we also have many partnership solutions, for example, from start-ups. One of the options for implementing this is when the data that you don’t want to give is replaced with some conditional hashtags and, accordingly, only these hashtags are transferred to the public cloud; then there are technologies that allow you to simply mirror some data, that is, separate them by identifier and separate them by public and private repositories.

    This begs a rather obvious picture when the cloud would offer a conditional interface to the database into which you can embed a predicate that describes, in fact, where this data goes. But this probably does not exist.

    Yes, this is not basic functionality, but it is something that can really be implemented, and this is just one of the goals of creating hybrid clouds - this is when the possibilities are separated, for example, according to the degree of sensitivity of data to movements.

    I also want to ask about the ML technologies that you offer. Indeed, if I correctly understand the current situation in this market, then it looks something like this: there is a fairly wide range of developments, and, essentially, the success of a particular team that makes a real solution based on ML solutions lies in choosing the right compose these developments. And the spectrum is quite large. Perhaps if they turn to your technology, then this spectrum is somehow narrowing? Or is it not narrowing? Or is it possible in this place to link solutions from Microsoft with solutions from other vendors?

    Yes, we just have a set of ready-made blocks. If you want to deploy TensorFlow from Google on Azure - please do it, it's all possible, it all works. Here our approach is the same as it was once with a PC, our task is to make it accessible to everyone, that is, we are democratizing artificial intelligence technologies. As often happens, nobody canceled the Pareto law - the problem is solved with the help of 20% of efforts. And we are trying to provide technologies that even people who are not super-specialists in AI technologies could use.



    Here I have an example of our customer, this is a company that bakes bread. They had a very big problem: bread is a product that needs to be consumed fresh, and they copied a lot of bread. Since the worst thing that any commercial company can have is unmet demand, they always brought with a margin, and then disposed of up to 20%, because it was stale, and these were direct losses.

    To solve this problem, we applied Azure ML - this is a product in which, literally, you can leave the data with the mouse, test the model, then he learns to calculate this model himself, and then we check this model on the control sample, see what this model is about I learned. In other words, this is such a product that it is very easy to use and anyone can teach it, well, the programmer will certainly master it within one day.
    For example, no one on the customer’s team was an ML specialist, or the Deep Neural Network. There were just ordinary techies who started using this tool a week later. And they managed to halve the losses simply because they learned how to correctly calculate how much bread should be brought to each bakery every day based on previous data.

    Now you say terrible things, really! Horrible! Indeed, pay attention, a new elite of programmers has already begun to take shape. A very clear wave occurred: there are programmers who own the ML theme, and there are programmers who have not yet crawled. I often hear discussions on this topic. For example, when the first cars appeared, and everyone had horses, those who controlled the horse became useless to anyone, and drivers appeared. And now you say that Microsoft brought in this place a robot-steering for the car before people learned how to control them with their hands.

    This is a good analogy, very beautiful. But what's the big deal? This is wonderful!



    Well, how many people in this place will lose their job I think ...

    There has just recently been a discussion on this subject in which I participated. My point of view on this score is quite radical, but I believe that even if robots can replace people in some professions, this will not lead to any dramatic consequences. I call this the time of the new antiquity, as I did in ancient Greece. True, thanks to the not very ethical use of slave labor, the citizens of the Greek poles got the opportunity not to do heavy work from morning till night, but got the opportunity to engage in art, philosophy, and self-knowledge. Why not expect the same from robots now?

    That is, thanks to Microsoft, we will all enter an era when we will drink wine sitting at a table with fruits, and next to the wall computers controlled by artificial intelligence will steer factories, create wine for us and grow fruit for us?

    I was rightly objected to such an analogy that we can all turn out to be a society like in Ancient Greece, engage in art and philosophy, or, in fact, a corrupted society of Nero in Ancient Rome. Therefore, it depends only on us, and it will be interesting to understand what kind of society we have: one that can become a society of new antiquity, or it will be a society of the new depraved system of Patricia.

    As always, with any tool, the effect depends on those people who use it. This is clear. But let's get back to the topic of using the tools that Microsoft now has in real life. We started with the fact that there are several cases of digital transformation, in which Microsoft participated, and they showed good results.

    Thank you for what you just said, because the separate interest of the “bread” case lies precisely in the fact that it turned out to be possible without significant immersion of the people who made the product into the technologies themselves. On the one hand, I have a little concern with this, but on the other hand, where to go: this ax already exists, now the question is who will take it in hand. It is valuable that the technology has been commoditized or something, has become generally so widely used, probably this is not possible everywhere. But the effect is 50% serious! It is from a business point of view of a really large scale. Is there anything else on this subject?


    Yes, we have many cases. And so, just as I was preparing for this interview, I was trying to pick up cases that would not represent some huge companies with enormous resources, because everyone understands that a company of the size of a large bank or a large production can afford a lot. And in this sense, they, as examples, are of little interest to us, but it is compact small businesses that are not able to invest heavily in this.

    Another example that I really like is the Russian startup Sarafan, which used ML technology for image recognition, and at the same time they came up with a very cool business model of how this can be monetized. For example, they allow you to open Instagram of some celebrity where beautiful models of clothes are presented on it, and with the help of ML technology they understand which brand and what kind of model is on the photo. Immediately they allow you to go to the store’s website, where exactly these sneakers or this blouse can be bought, and even at a discount.

    A very cool monetization model for this startup, because they get money as a commission from those orders that really happened. I really like this case, because this is an example of how we directly transfer ML technologies to money.

    I want to note that here everything is limited only by imagination: how else can you apply ML. Again, not being high-level specialists, you can write an application that will recognize photos and identify clothing brands on them.

    And what exactly is the developer's work in this place? It may seem that it all comes down to running a tool in the Microsoft cloud, clicking with the mouse, and she did everything for you, but this, of course, is not true.

    Yes, it’s good that it’s not so simple. I still consider myself a programmer and still know how to write code, so I still hope that in that beautiful society of the future that we have just described (hi ​​to Orwell "1984"), programmers will still find work. And not everyone will sit and drink wine, and write philosophical books. So, the programmer, of course, needs to understand how this framework works.

    It turns out very interesting here: as soon as we start working with artificial intelligence (AI) technologies, we are more and more transferred as programmers from the design time during runtime, because we are creating something already alive (which you need to not just create and let into life). When we bring it to life, it still does not know how, and it needs to be taught. This moment of model training, it seems to me, brings the profession to the programmer even closer to the profession of the Creator or parents.

    Parents ... Yes, I also had a feeling of closeness of what is happening with the child: when you gave birth to him, everything only begins. This is a good parallel. Perhaps this is relevant to all the works related to ML: is the programmer's task the task of choosing the optimal tool from the possible options and preparing a training sample for it?

    Yes.

    This is where the main work and, apparently, the inevitable Agile also takes place. At this moment, the development work does not end, and we overestimate the quality of recognition. How is this part of life generally arranged? But we can’t constantly monitor and evaluate the quality of each recognition. What is going on in this phase? Is it sampling, or are there any tools that can somehow figure out how much this recognition was high-quality or low-quality?

    Yes, absolutely right. And in this regard, for us, as programmers, everything is very good, because now we can’t just write a product and give it to the customer, we can receive money from the customer all the time. I hope our audience understands a sense of humor! Indeed, the same models that are created there must be constantly trained, constantly monitored. And here it is the programmer’s task to correctly configure KPI and the feedback form, that is, how we will evaluate, say, the same recognition quality. And here there is just a ton of options! You can, for example, make two models that will compete with each other, well, or many models that will compete with each other. Or you can compete with a man, why not? I mean, when we do something using algorithms,

    But this sampling in this case, you can’t check every sample.

    Yes, there are no universal methods. Here, again, our task is to provide a tool, and how they will be used, we are no longer trying to determine this.

    But these same tools, can they just use FPGA technologies? Or is it just a new technology?

    FPGA is still a new technology. It can be tested, we are gradually deploying it to all data centers, but this, let’s say, is more likely tomorrow’s business.

    But is it built into these ML components?

    Yes, it is all transparent, after it is deployed, it will be imperceptible, just suddenly the same algorithms will work 1000 times faster. And this is all really the future, which will be very interesting to see.

    In private cloud, you don’t give away FPGA topics in order to retain some part of your competitive advantage? Or is it simply complicated enough and not yet sufficiently framed as an alienable technology?

    I think that it is too early to comment on this, you need to see how it works. This is still a new technology, and here you need to control how it works so as not to release a not very high-quality product on the market. It is difficult to make plans for the future, no one knows what will happen tomorrow. Well, who knew that graphic chipsets would be so popular, not in order to calculate 3D graphics, but in order to mine bitcoins? Therefore, the development of this technology is also difficult to predict. It seems to me that very interesting things opened up there, and if we add quantum computers there as well ... And Microsoft is very much involved in quantum computers, and we have a large laboratory at the Bohr Institute in Copenhagen.

    It would seem that ML should fall well on just quantum computers. A little bit from these heavens we will return to the earth and remain in the theme of hardware.

    Of course, it’s very unexpected to talk with Microsoft about the hardware, but it’s interesting. The topic of the transition from Intel-based processors to ARM within the clouds, it somehow started to take off, and then it seemed like it was a bit quiet. And there was talk that Windows will migrate to ARM, what about this? Moving, not moving?


    Windows works fine on Snapdragon, runs on ARM. Already there are devices on which all this works. And the cool thing is that the translator is built in there, so win32 applications can work, unlike the first attempts by Windows to run on ARM, where only applications written on the new Windows platform could work.

    Binary translator?

    Yes, a binary translator, that is, now all familiar applications can work on ARM, so here we have new distances. We have not yet disclosed all the details, but what they promise now and what comes from secret laboratories are computers that will not need to be charged.

    Why?

    Thanks to ARM, these will be ordinary laptops that we use in our lives with all the applications we are used to, but in which the power consumption will be so low that we can leave charging at home and this will be guaranteed to be enough for a full day without any restrictions. In general, we work with ARM from the client’s point of view, I don’t know about the cloud yet, but the fact that Windows works fine on ARM is no longer news.

    But did you know that the Elbrus processor has binary x86 translation to native Elbrus, and on this binary broadcast Windows starts, which in binary translates to the Elbrus command system and, without knowing about it, works on Elbrus?

    Yes, here, I recall a joke about two new Russians. One of the other asks:
    - Do you speak German?
    - Yes, of course.
    “But it's English.”
    - You see, I also know English.

    So now I will say that windows also works on Elbrus.

    No, is there something else interesting? If you had a binary broadcast of ARM in x86, and then all of this could be put on Elbrus and see how all this pyramid would be tormented in order to translate all this.

    Of course, this is also a very interesting topic. For a long time I was very impressed with what the development was done: a virtual x86 is launched on a java-script, in which Linux is launched directly in a browser in a virtual machine running on java-script, and it works in your browser window. It was enchanting! In general, it is enchanting today! It seems that pretty soon the questions on what it is done on, what it works on, will cease to be relevant, because it will be possible to launch anything on anything. But, thanks, in fact, this is a very interesting topic, especially considering that it supports win32 applications ... in general, there is value in it. Although you are not the first in this place, the same Apple twice made a jump from processor to processor, supporting previous applications with binary translation, but it is impressive!


    In general, it seems to me that win32 will live for a very long time. So far, as you know, not a single banking transaction (I heard such a fact) has passed the Cobol code. Although how many years have passed. It seems to me that win32 is so widespread that even if Microsoft really wanted to ... It would still be left to live for a very long time. This is a world built on win32 and it is wonderful!

    Yes, the legacy topic is wide enough, and it is really, in part, good that there are such virtualization tools that allow the solution made to somehow wrap up, that it costs and works. But still, back to digital transformation.

    Although, of course, it’s very interesting to talk with you about the essence of what is happening inside the computer, because I myself am very interested in this. But come on, tell me some other examples about what is happening now interesting?


    There are many examples and, indeed, it is very cool how information technologies are changing the world around us now. Going here to this studio (I’m revealing a little secret in front of the audience), we went to car sharing. Car sharing is an example of how IT has transformed our typical industry. This service is completely impossible without mobile communications, without mobile applications, without a mobile phone - smartphone.

    We have similar examples in other industries. The same DoDo Pizza. This is not a company that bakes pizza, this is an IT company that suddenly for some reason began to bake pizza.

    By the way, Ovchinnikov ( ed. Fedor Ovchinnikov, founders of the pizzeria chain Dodo Pizza) formulates it differently. He says that “we, in general, are businessmen who are engaged in pizza, but we are simply engaged in proxies through the systems that control this process. After all, I nevertheless very clearly asked him: “How do you feel: nevertheless, roughly speaking, an IT person who somehow succeeds in business, or a businessman who knows IT well?” And his answer was - the second. Still, in this place understanding of the key business is very significant.

    I’m constantly comprehending what the guests say and how exactly this coupling is arranged by digital transformation with IT. Where is the fine line between software and businesses themselves? She essentially is not, and ownership of what is happening in business is critical!


    Yes, and here, I completely agree with the definition that Tigran ( ed.Tigran Khudaverdyan - CEO of Yandex. Taxi ") in your program. It was surprising that we use the same definition internally. Which companies do we consider IT-shy, which are not IT-shy, that is, software and non-software? If most of the added value is created using software, then this is a software company. And so, it can be represented by a bank, it can be represented by a pizzeria, by anyone. But if software is a way of creating added value, then this is a software company. Therefore, Uber, Airbnb are all software companies.

    Returning to some more examples that can be reasoned about, I really like the example of the company, a native of Microsoft, Vlad Martynov, whom everyone knows most as the head of Yota Devices.

    The creator of YotaPhone?

    Yes, the creator of YotaPhone, but once he worked at Microsoft, and we are proud of such a graduate of our company. He has a very interesting startup called ICEBERG, which brings cloud technology and ML to the sport. Now they use it for hockey, mostly. But in general, this is a technology that can be applied to any sports. They take off the playing field at short intervals, watching the players: how they move, how many times they gave a pass to whom, how many times they scored. Next, look at statistics on past games (that is, collect a huge amount of information), put it in a black box, where some algorithms do something there, and give the results to the managers of sports clubs: which player is in better shape now, which is better against to put this opponent, what combination.

    They also bet on the following games.

    Here, by the way, about bets on the following games. We have long had Cortana (Cortana, for those who don’t know, is what works on Windows, it’s analogous to Siri, analogous to OK Google).

    Alice's analog?

    Yes, absolutely right. With Cortana, we have been predicting various sports events for a long time and correctly guessed 15 out of 16 matches of the last World Cup.

    That is, in general, "Back to the Future" you killed? Has the topic of this film become meaningless?

    In general, it has already become meaningless for many other reasons, we won’t go into politics ... Guessed, if I’m not mistaken, three out of five Eurovision finalists. In principle, the statistics work very well and, if combined with the startup that manages the teams, the prospects are really very interesting there. But here we must not forget that with these predictions we influence the system itself. Therefore, everything here will never be so simple, but the opportunities that open up are staggering.

    Here we are now hooked on a certain topic (again, we’ll get away from what we should talk about with you, but it’s painfully interesting!). In this sense, I even have such a mild syndrome. As the creator of Yandex.Market, I feel that I myself am a little to blame. The appearance of such services, in general, squeezed the margin out of Retail very strongly, and intensified competition, and in general, substantially made this Retail meaningless.

    Are we not afraid of the emergence of services that are able to analyze statistics and predict behavior. Well, for a second, another 10 years, and the behavior of mankind can be predicted. This is, generally speaking, terrible! Firstly, the competition in humanity itself will become very fierce, and secondly, it will make our lives meaningless. That is, tomorrow the computer will be able to predict about everything about you. Maybe it's time to stop? Can I turn it off? Or is it all scary, and we will go to some meta level?


    Well, I am an optimist, everyone is waiting for this time of new antiquity. But if you return to the Yandex.Market theme, I recently came across a very interesting quote from Bezos, the creator and leader of Amazon, in which she said that in the world of the Internet and in the world of services such as Amazon and Yandex.Market, the manufacturer needs much more pay attention to the creation of the product, not its distribution. He says that in the past, approximately 30% of the effort was spent on creating a product, and 70% on its promotion, sales, and so on. And in our world, thanks to Yandex.Market and Amazon, this has changed: 70% of the time and effort needs to be spent on creating a product and only 30% on its distribution. It seems to me that nothing bad has happened in this regard. Now those who do such a commodity service (sale) are forced to compete, but those

    I would not say that the products become the same, on the contrary, products appear on the market that were not there at all yesterday. And that's great! Previously, in order to produce, for example, a backpack, you had to be a big company, otherwise you had to be doomed to vegetate from the very beginning in a very small niche market. Now there is, for example, Kickstarter. The money for creating a product is received by crowdfunding, and with the help of Amazon and other services that allow you to distribute the product, you can (well, not instantly) with quite limited efforts to become an international company. This was not the case before.

    I’m ready to change the world that was yesterday, where retail-ers had a big margin, but no one could get into this retail, to the modern world where retail-ers had a small margin, but new sartups can be created that produce not only software that is easiest to distribute, but also including some tangible things.

    You know, I’m also an optimist and, in general, agree that if the wheel, fire and nuclear energy have not already killed mankind, then, probably, computers, in general, will do nothing wrong with us! Thanks a lot! Microsoft is a company that brings Artificial Intelligence to every table!

    Yes, absolutely right! And makes all companies equal regardless of size!



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    Do you need developers in the future?

    • 49.3% Yes, who else will drive the machines 72
    • 30.1% Yes, but not mancoder 44
    • 11.6% No, cars will take over the world 17
    • 8.9% I don't care 13

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