Why are artificial intelligence developers becoming a valuable resource in the IT industry?

Google's California office, home to the company's main AI department . Photo The New York Times

Silicon Valley companies are willing to spend huge amounts of money to attract rare specialists. If you  believe the  information of The New York Times, then the last couple of years, artificial intelligence developers have been very popular. It is such a rare resource that organizations are willing to pay big bucks and share shares on the stock exchange to attract employees with even little experience in the field.

Interest in technology computer engineering education

Google, Apple, Uber, Microsoft - these and other giants of Silicon Valley have been recruiting artificial intelligence specialists over the past few years. Some companies need them to  improve smartphone functionality , while others hope to use them to create safe, self-driving cars. And everyone is ready to invest a lot of money, even in not very experienced workers.

A typical AI developer who works for large companies makes between $ 300,000 and $ 500,000 a year. This number includes not only experienced university graduates, but also self-taught ones with a minimum of experience.

Companies often offer a share of shares to famous people in the industry, which is sometimes valued at several million dollars. A prime example is Anthony Lewandowski, who has worked at Google since 2007 and moved to Uber in 2016. During his time at an Internet search engine company, he earned more than $ 120 million.

Anthony Lewandowski. Photo WIred

According to Microsoft managers, the salary for the development of artificial intelligence is constantly growing. There are several reasons for this, the first of which is the competition of automakers with Silicon Valley for some experts in the field of self-driving transport.

Giants like Facebook or Google spend a lot of money on finding specialists in a rare field, because they are sure that only they will solve their problems. Mark Zuckerberg's companies, for example, need artificial intelligence specialists to develop algorithms for searching for offensive content on social networks.

Another reason: artificial intelligence developers are a very rare resource. According to The New York Times, there are only about 10,000 workers in the world who are capable of solving complex problems in the field. Therefore, tech companies are willing to spend a lot of money to attract as many workers as possible.

Lack of staff

Three years ago there was no such need - in 2014, Google invested about $ 650 million in its artificial intelligence laboratory, 50 people worked there. In 2016, the department grew to 400 employees and a budget of $ 138 million in salaries alone. That is, one employee accounts for about 345 thousand dollars a year.

Google CEO Sundar Pichai talks about the AI ​​technology built into the company's gadgets. Photo by Reuters

Companies are not only looking for specialists among young graduates, but also attract experienced scientists from prestigious US universities. Google once offered University of Washington academic Luke Zettlemoyer a salary of $ 180,000 a year to join the company.

This is three times more than he received at an educational institution. Google and Facebook have also  launched  training programs for aspiring artificial intelligence developers. This is how companies "grow" new and loyal employees.

The resources of the United States as a supplier of specialists are limited, so the giants of Silicon Valley are looking for promising workers around the world. The New York Times learned that companies have a strong interest in China and France, but the country of origin plays a minor role. Now only skills are valued in workers, even the most minimal ones.

Databases: we do not allow the loss of key assets

Information has become the most important resource in the post-industrial era. Much data becomes an attractive target for criminals. Cybercriminals hack information systems, send spam with spyware, organize targeted phishing attacks, and use contacts with unscrupulous users. The cost of information on the black market depends on many factors: relevance, volume, regional and industry specificity, liquidity of a particular record for committing a particular crime, and finally, simply on the subjective feelings of “sellers” and “buyers”.

Corporate information is often hunted not by lone hackers, but by organized criminal groups. By breaking into information systems, they try to take over large databases. They prefer to sell the stolen goods in bulk, and they often act on order. For example, a group neutralized in China stole more than 11 million records. A batch of 300 thousand records was sold for more than $ 30 thousand, and 1 million records for $ 121 thousand. Thus, one record in a large repository was estimated at $ 0.10 - $ 0.12.

Computer science vs engineering

It is understandable that up-to-date payment information is always highly valued. Using the stolen cardholder data, criminals can make a clone card and withdraw money from the account. In September, the payment details of millions of visitors were stolen from the American fast food chain Sonic. Most of the accounts for sale cost between $ 25 and $ 50. The price is influenced by a number of factors: payment system (American Express, Visa, MasterCard, etc.), card level (Classic, Standard, Signature, Platinum, etc.), whether the card is debit or credit, the issuing bank.

In recent years, cybercriminals have targeted social networks and web services, which have accumulated huge amounts of user information. At the end of August, a serious incident occurred on Instagram: as a result of a hack, about 6 million entries were stolen, including data from celebrity accounts. Cybercriminals uploaded information from millions of accounts to the specially created DoxaGram website and offered everyone to buy it for bitcoins - at the rate of $ 10 per search result. And at the end of May, an unknown person was selling on the Internet a database of 100 thousand users of the social network VKontakte, who were allegedly engaged in the distribution of extremist materials. The “product” was valued at 100 thousand rubles, that is, 1 ruble for 1 entry.

One of the most liquid records is insurance data. MFI Soft has systematized the range of advertisements for sale on the Internet sites of databases of Russian insurance companies. 34 unique databases with a total volume of records of more than 5.6 million have been discovered. Experts call the actions of insiders the main reason for the leakage of such information storages. At the same time, the size of the base does not correlate with the price indicator. As a rule, small databases, but containing fairly fresh and complete information, are valued higher than huge archives. Therefore, the cost of one record in a small or medium-sized database can reach 10 rubles, while in large databases the cost can drop to 0.001 rubles per record.

Medical information is also in strong demand on the black market. The range of prices is large here. A single entry can be worth a few cents, but in some cases the cost is thousands of dollars. For example, in the spring, hackers stole the personal cards and photographs of 25,000 patients, including national and foreign celebrities, from the system of the Lithuanian plastic surgery clinic and put them up for sale on the darknet. The price for one entry was from 50 to 2000 euros. In addition, the entire stolen base could be purchased for 344 thousand euros. The direct and indirect losses of companies affected by confidential information leaks can be many times higher than the amounts that hackers ask for on the black market. Based on a 2016 Ponemon Institute study commissioned by IBM. the average cost per stolen or lost recording was $ 141. Compared to the previous year, the average cost of one violation, although it decreased by 10%, is still an impressive $ 3.62 million. After the leak, the company loses on average 5% on the exchange, and the customer churn can reach 7%. The number of such leaks in the world in 2016 increased by about a third, the amount of compromised information increased by more than eight times. The share of high-tech companies accounted for nearly three quarters of all compromised data in the world - about 2.3 billion records, of which 87% were personal data (PD) of citizens. and customer churn can reach 7%. The number of such leaks in the world in 2016 increased by about a third, the amount of compromised information increased by more than eight times. The share of high-tech companies accounted for nearly three quarters of all compromised data in the world - about 2.3 billion records, of which 87% were personal data (PD) of citizens. and customer churn can reach 7%. The number of such leaks in the world in 2016 increased by about a third, the amount of compromised information increased by more than eight times. The share of high-tech companies accounted for nearly three quarters of all compromised data in the world - about 2.3 billion records, of which 87% were personal data (PD) of citizens.

“We are seeing an increase in the number of leaks and the volume of compromised data of high-tech companies, for which information, including customer information, is, as a rule, a key asset, therefore any leak turns out to be very sensitive for business,” said Sergey Khairuk, analyst of InfoWatch Group. - In 2016, the data of hundreds of millions of users of such popular resources as Facebook, Foursquare, GitHub, iCloud, LinkedIn, MySpace, Snapchat, Telegram, Tumblr and Twitter were stolen. Hackers successfully attacked the largest mail services - Gmail, Hotmail, Yahoo, Mail.ru, stole data from clients of telecommunications companies, including Deutsche Telekom, Three UK, Verizon and other operators. Compromise of more than 95% of data in the field of high technologies in 2016 was caused by 31 "mega-leaks" with damage to more than 10 million records each. In the structure of leaks, the volume of citizens affected by personal data has grown significantly, while the shares of payment information, trade secrets and know-how have decreased. Despite an increase in the number of leaks caused by an outside intruder, leaks within high-tech companies are also very dangerous. Thus, the number of leaks due to the fault of an external attacker in the field of high technologies increased by almost 15% over the year, while the change in the distribution of damage depending on the impact vector is minimal. In 2016, the number of cases of deliberate information leaks increased in high-tech organizations, as well as the proportion of qualified leaks associated with fraud or abuse of access rights. Despite an increase in the number of leaks caused by an external intruder, leaks within high-tech companies are also very dangerous. Thus, the number of leaks due to the fault of an external attacker in the field of high technologies increased by almost 15% over the year, while the change in the distribution of damage depending on the impact vector is minimal. In 2016, high-tech organizations saw an increase in the number of cases of intentional information leaks, as well as the proportion of qualified leaks associated with fraud or abuse of access rights. Despite an increase in the number of leaks caused by an external intruder, leaks within high-tech companies are also very dangerous. Thus, the number of leaks due to the fault of an external attacker in the field of high technologies increased by almost 15% over the year, while the change in the distribution of damage depending on the impact vector is minimal. In 2016, high-tech organizations saw an increase in the number of cases of intentional information leaks, as well as the proportion of qualified leaks associated with fraud or abuse of access rights. while the change in the distribution of damage depending on the impact vector is minimal. In 2016, high-tech organizations saw an increase in the number of cases of intentional information leaks, as well as the proportion of qualified leaks associated with fraud or abuse of access rights. while the change in the distribution of damage depending on the impact vector is minimal. In 2016, high-tech organizations saw an increase in the number of cases of intentional information leaks, as well as the proportion of qualified leaks associated with fraud or abuse of access rights.  

It is difficult for the supermind to communicate with people - they simply do not keep up with it

Introduction

Machines have already surpassed humans in many areas, but the general level of human intellectual development is incomparably higher. But the day is not far off when machines will become superintelligent.

The Fritz program plays chess significantly stronger than the leading grandmasters, but it cannot be called superintelligent, since it is superior to humans in only one narrow area.

Nick Bostrom believes that superintelligence is an intellect that is many times superior to the most outstanding people in mental development, scientific and technical activities, worldly wisdom and the development of social skills.

The book provides a variety of information about the history of artificial intelligence and the current state of affairs. The author ponders whether the superintelligence will be helpful or destructive, friendly or hostile.

Reading this book is very difficult: scientific vocabulary, examples from physics, mathematics, economics and nanotechnology, along with numerous tables and diagrams, do not allow the reader to relax for a minute. The author himself admits that he tried to make the book easier to read, but he failed. He also warns that not all information is reliable and has scientific confirmation. At the same time, the book is of interest to those who are not indifferent to the future of humanity and who are interested in modern technologies computerquestions.

The past and present of artificial intelligence

After the appearance of the first computers in the 1940s, scientists started talking about the imminent emergence of the superintelligence. The predictions did not come true, but modern futurists, like their predecessors, believe that superintelligent machines will be created in the near future.

History of artificial intelligence

1642-1940s - the zero generation - the simplest mechanical computers.

1940–1955 - first generation - vacuum tube computers.

1955-1965 - second generation - computers on transistors.

1965-1980 - the third generation - computers on integrated circuits.

1980–… - fourth generation - computers on huge integrated circuits.

The fifth generation, focused on distributed computing, was never created; it was to become the basis for devices capable of imitating thinking.

In the summer of 1956, a group of scientists came to the first symposium on artificial intelligence at Dartmouth College in the United States. It was this event that became the starting point for research in the field of artificial intelligence, and many of the participants in that symposium gained worldwide fame. At first, they created only small systems, each of which in the laboratory could do something previously inaccessible to machine intelligence.

One of the earliest systems, The Logical Theorist, succeeded in proving theorems, one of which was more elegant than the original.

In the mid-1970s, the fashion for artificial intelligence passed. Sponsors refused to finance projects to create artificial intelligence, because they considered this direction unpromising.

The new golden age of artificial intelligence can be considered the early 1980s, when Japan launched a major project to create fifth-generation computers. The project was funded by the government in conjunction with commercial structures, and its goal was to create a high-performance machine that thinks like a person and can work with large databases. Many countries have followed Japan's example and resumed work on artificial intelligence. The developers tried to create the so-called expert systems - programs that process significant databases designed to partially replace a person in various fields of activity. Hundreds of such systems were created, the codes for which were manually written by thousands of programmers. However, after a few years it became obvious that to develop, controlling and updating expert systems is difficult and expensive. Thus, the project to create fifth generation computers ceased to exist by the end of the 1980s.

Since the 1990s, methods of neural systems and genetic algorithms, based on modeling the human brain, began to develop.

In what areas is artificial intelligence superior to humans

By now, machine intelligence has already outstripped humans in many activities. Previously, people naively believed that in order to become a strong chess player, you need to have developed abstract thinking, be a strong strategist, be able to create cunning flexible plans and try to "read" the opponent's thoughts. It turned out that the strongest chess player can be defeated by a program with a special algorithm connected to a powerful processor. However, such artificial intelligence is limited only to the game of chess.

Checkers. In 1994, the CHINOOK program was able to defeat the reigning world champion. This was the first time that the program actually became the world champion in intellectual games.

Chess. In 1997, the Deep Blue program won a match against world champion Garry Kasparov, who confessed that he had noticed glimpses of real intelligence and superhuman ingenuity in the machine.

Scrabble. In 2002, the program defeated the strongest players.

Today, these achievements are no longer surprising. As John McCartney (the American scientist who first used the term "artificial intelligence") remarked: "As soon as artificial intelligence begins to function, people stop considering it artificial intelligence."

Internet in the 90s? How it was? Part 1: Gopher

I am starting to publish a series of reviews devoted to Internet protocols, common and not very common in the nineties of the twentieth century. This is done primarily in order to identify alternative methods of communication within the global web in the light of endless leaks of corporate and private information. Without any kind of blockchains and domains of the Onion zone. Simply put, without the modern mythology of planned obsolescence.

And the first Internet protocol of the nineties with which we will begin our acquaintance will be Gopher. He was chosen due to the fact that a rather negative reputation has developed around him in narrow computer circles. Namely as a non-functional and useless protocol. But this is only because the authors of such statements have never delved into the settings and configuration of this product.

The Gopher standard and viewer (browser) were developed at the University of Minnesota in 1991 as part of a program to enable easy document sharing over the Internet. Between people, institutions and even countries. Gopher's popularity increased when the Veronica and Jughead search engines were developed. The protocol itself was named after the gopher, the mascot of the University of Minnesota football team.

But in February 1993, the aforementioned institution decided to start charging licensing fees for Gopher servers. What caused a reasonable panic among the owners of these services. At the same time, CERN gave up the rights to the WWW standard, which stopped the popularization of Gopher. It wasn't until 2000 that the University of Minnesota re-licensed the development under the GNU General Public License. But as you can imagine, precious time was lost.

Electrical engineering vs computer engineering

Nevertheless, this protocol today may be of interest not only to corporate developers, but also simply to lovers of closed data exchange. Outside the ubiquitous Google, Microsoft and Yandex bots.

The first thing that strikes you about Gopher is its minimalistic requirements and dimensions. The server archive takes some 290 kb, and the WSgopher client 368 kb, respectively. The second thing that pleases me is full cross-platform functionality. There are servers and browsers for absolutely any operating system from Dos and Unix to MacOS and Windows. For example, for the review we used Motsognir for Winodws 9x, which works great even in XP. Available for download like other solutions from this page: http://www.jumpjet.info/Offbeat-Internet/Gopher/Servers/OS/specific.htm

The third and not unimportant feature of the protocol is the simplicity of server configuration. If in WWW we are used to endless configuration files with many modules connected, then with Gopher things are easier. There are only two configuration files. One directly owned by the server developers, but designed according to protocol standards. The full description of which, in the case of Motsognir, is in the manuals.pdf file, inside the archive. The second gophermap file is created if desired by the owner in the public (shared) directory with files. It manages not only the listing of catalogs, but also their design. It's kind of a mixture of a modern .htaccess file with the usual html tags of a different standard. Examples of gophermap file settings can be found on the Internet.

At the same time, the most important myth discovered among Russian-speaking commentators was the allegedly static nature of the protocol. Although this is not the case. After all, the Gopher server supports the inclusion of not only GGI, but even PHP. That is, de facto, the protocol implements dynamic content, despite the ascetic appearance of the basic configuration. Moreover, if desired, the server can be configured in such a way that access to the service will be carried out only through accounts exported from Telnet for UNIX or Linux. Simply put, it is possible to password-protect directories and the server itself.

For developers, the task is also simplified due to the fact that Gopher is open source. So, if you wish, you can edit it in your own way. This protocol functions as standard through the 70th port. And it also allows you to prescribe the specialization of files for viewing by external applications of users.

All in all, I have a very good impression of setting up and configuring the Gopher client / server. And its flexibility and cross-platform allows you to use it in conjunction with other alternative solutions. For example, to provide direct access to files uploaded via FTP with separation of rights by account, as well as read correspondence in conjunction with UseNet and other protocols. But more on that in the following reviews.

How to meet an IT specialist: 5 non-invented stories

Before, every mother wanted to see her daughter as the wife of an officer. Now the 21st century is the age of technology. Many girls want to come home and say, “Hurray! I am meeting with an IT specialist! " Five girls told the SoftTeco journalist about their experience of meeting and developing relationships with a programmer. 

Where can you meet a programmer?

Katya (the programmer's wife) : My husband and I met in a place that has nothing to do with his work. But fully reflecting my interests - I'm a book blogger. It happened at a book presentation at Gallery Y. In those years, she was on Independence Square. I can definitely say that there is no universal way of how and where you can meet a programmer. They are very versatile people, which means they can be found everywhere. 

Lera (the programmer's wife) : My future husband and I worked (and still work) in the same company - SoftTeco. A colleague invited me to eat pizza with them. I met the guys, among whom was my husband. In general, people spend more than 50% of their time at work, so finding your soul mate there is most realistic. Plus, during responsible work processes you see a person "in action" and you can appreciate his character. Qualities such as reliability, resistance to stress and the ability to compromise are very important in family life :). You can also meet at IT-meetups, at IT-courses, in a general company of friends (if you have techie friends), and even in a cafe. The main thing is that you are an interesting and developed person and that you have something to talk about.

What types of engineers are there

Lina (the programmer's wife) : My husband wrote to me on VKontakte and offered to take a picture. As you might guess, he didn't have a camera :). So that programmers can go to the trick to meet with you. I think that you can get acquainted on the "programmer" platform a la GitHub. Find the mail of a programmer who has many stars on the project and write. 

Vika (programmer's wife): I met my husband on Tinder. From my own experience, I can say that foreign programmers love this platform. My husband has a brother and friends - programmers. And they're all on Tinder. 

Masha (programmer's girlfriend) : I made acquaintances with programmers in very different places - from the queue at the bakery to the bar. Programmers are ordinary guys who spend their time in the most ordinary places and do not put salary numbers at the top of their judgments about themselves and other people. I think there are no universal locations for IT dating. 

How to charm a programmer?

Katya: Everything is individual. Someone likes homemade cutlets and football, while others like Chopin and Italian coffee. I think that men, and we are talking about them, always like warm-hearted girls, interesting and smart interlocutors, not dummies.

Lera : Everything works the same as for ordinary men. But given that programmers are people of intellectual work, they like smart girls.  

Lina : My husband loves to talk about his work. For 2 years of relationship, I have learned 3 words from his professional vocabulary: release, donate and reject. I don't understand anything else. I think the key to a successful relationship is to say “Yes, I think you did the right thing” to all stories about work. 

Vika: Programmers are shy and calm. They are attracted by modest, feminine and well-bred girls. They want to feel the female energy next to them, I'm not a kid-friend.

Masha : Many programmers have a rather monotonous job. Therefore, in their personal lives, they are looking for a breath of "fresh air". In my experience, many programmers enjoy hedonistic girls who fill their lives with unusual events, new emotions and lightness. There is a separate category of geek programmers who storm code and fantasy worlds. They are looking for girls who will be on the same wavelength with them, have a "technical" mindset and are ready to remember the names of all the heroes of some fantasy board game. 

And what is contraindicated to do?

Katya: Look for a programmer on purpose and he will like trying.

Lera: I would not focus on the level of income and would not try to single out programmers as a separate social class. A woman, first of all, must be self-sufficient. And thanks to this, she will meet a cool guy!

Lina: You can't underestimate his interests. It will be important for the programmer to watch the apple presentation if he is an iOS developer. Therefore, you should not be offended that you will not have a date on the 10th of September. 

Vika: You can't come on dates with a neckline and a short skirt. In my experience, programmers are more attracted to an elegant, discreet image. I know that programmers are afraid of mercantile girls and may specifically not post photos with material benefits. 

Masha: Often programmers are guys who, even from a young age, earn good money and have managed to get pretty tired of jokes about high salaries. Therefore, if they are determined to have a serious relationship, then they easily catch girls for manipulation and attempts to take control of their budget. You yourself understand how it all ends. 

AI and machine learning in medicine

Artificial intelligence (AI) will become one of the most important factors affecting the development of human society in the coming years. We put into this concept all areas of development of the sphere, including Machine Learning (ML), Generative Adversarial Networks (GAN), Gradient-boosted-tree models (GBM), deep reinforcement learning ( Deep Reinforcement Learning, DRL), etc.

Acting as a cloud provider, Cloud4Y has partnered with various healthcare organizations. It was always an interesting experience with new technical, legal, psychological difficulties that had to be overcome.

Business, technology, and healthcare are areas where AI is most in demand. Let's take a look at how AI / ML tools can influence the quality of healthcare delivery.

The idea of ​​using artificial intelligence in medicine dates back to 1972, when MYCIN was launched at Stanford University. It was a prototype AI program used to study the issue of blood poisoning. Early AI research continued mainly in American institutions (MIT-Tufts worked together, actively developed the technology at Stanford and Rutgers University. In the 1980s, Stanford University continued its work in the field of artificial intelligence as part of the project "Medical Experimental Computer Artificial Intelligence in medicine ”(SUMEX-AIM).

Thanks to the growth in computing power and the emergence of new artificial intelligence technologies, work in this direction has become much more active. News regularly appears about the next scientific discovery made with the help of neural networks and machine learning. What interesting things can you tell about the possibilities and prospects of AI in medicine today?

AI in radiology computers questions

Numerous medical imaging data is stored in abundance in small local systems. But what if you leverage deep learning by uploading data to the cloud and feeding it to AI? Machines and algorithms can efficiently interpret imaging data by identifying patterns and anomalies.

Most obvious use case: a radiologist / radiologist assistant, who is involved in identifying and localizing suspicious skin lesions, lesions, tumors, internal hemorrhages, brain lesions, etc. The computer works faster and more accurately, and therefore is able to give out specific data about the disease a few seconds after processing the information. Man cannot do that.

There is another point. Highly qualified specialists are expensive and in great demand. They are under serious pressure, literally bogged down in the streams of data that are pouring on them from all sides. If you believe  this article , such a specialist should issue a diagnosis every 3-4 seconds. Machine intelligence can improve the skills of the ordinary specialist, helping him to sort out difficult situations. Thus, reducing the number of false diagnoses and saving lives.

The identification of rare or difficult to diagnose diseases often depends on the experience of the doctor, as well as the degree of "neglect" of the disease. Simply put, until the sore gets out, it may not be recognized. By training a computer on large datasets containing raw images and many forms of pathologies associated with certain diseases, it is possible to improve the quality of diagnosis and the number of diseases identified. This idea is being developed by the startup AIDOC. 

AI is able to improve the quality of the work of medical institutions by automating the time-consuming and responsible part of the work of doctors. With the help of computer algorithms, you can also control the effectiveness of treatment and the quality of the operation performed, and predict the rate of recovery of the body.

Microsoft's InnerEye project is a good example of such technology. He suggests using ML techniques to segment and identify tumors using 3D X-rays. This can aid in accurate surgery planning, navigation and effective tumor contouring for radiation therapy planning.

AI in pathology

Pathological diagnosis includes examination of a tissue section under a microscope. Using Deep Learning to train an image recognition algorithm, combined with human experience, will provide more accurate diagnostics. Analyzing digital images at the pixel level can help detect lesions that the human eye can easily miss. And this will provide a more efficient diagnosis.

Such technology is being developed, for example, by Harvard Medical School. The algorithm uses speech and image recognition technology to recognize images with pathologies and trains computers to distinguish between cancers and non-cancers. Combining this algorithm with human work resulted in 99.5% accuracy. 

Machine Learning and Medical Science

Petabytes of data are generated in all kinds of medical facilities. This data, unfortunately, is usually randomly scattered and unstructured. This is by no means a reproach towards doctors. They have not so much to treat as to report on treatment. However, chaos greatly interferes with planning and global monitoring of the health of a particular country or the world as a whole.

An added complication is that, unlike standard business data, patient data does not lend itself well to simple statistical modeling and analytics. A powerful AI-powered cloud platform with access to medical databases is capable of efficiently analyzing mixed information (eg, blood pathology, genetic traits, X-rays, medical history). It is also (theoretically) capable of analyzing input data and revealing hidden patterns that are not visible due to an excessively large amount of medical information.

Interpretable AI models and distributed machine learning systems are great for these tasks. They will allow not only to effectively develop medical science, finding new patterns and racial / sex / age characteristics of people, but also to form more accurate data on the health status of the population in specific regions.

Surgical assistant robots

Already, many operations are carried out using computer vision and manipulators controlled by a surgeon. This is a significant part of the development of medical technologies, leveling the factor of human fatigue and increasing the efficiency of procedures. AI robots are great at helping conventional surgeons. For example:

Supervise the work of the doctor, acting as an insurance against inattention;

Improve visibility for the surgeon, remind him of the sequence of actions during the procedure;

Create accurate, minimally invasive tissue incisions;

Reducing the pain level for the patient through the selection of the optimal incision geometry and suture.

Speech therapist with computer vision. How does the Belarusian application CatZu follow your language?

This issue on the ITitov YouTube channel contains a lot of cats and useful information for adults and their children. The CatZu app is a smartphone speech therapist that stands out from other developments in its analytical mind and persistence.

Today, professional defectologist Antonina Sudilovskaya simply breaks TikTok with her articulation exercises. In her account, a virtual cat, which is the main character in the CatZu application, increasingly began to appear in the lead role. His popularity in the youth social. the network can easily be transferred to users of the mobile service. Also, the virtual cat has already been checked out in several preschool institutions. He bribes everyone with his charisma and lures them into his neural networks computer engineer majors.

The essence of the application is that the cat exercises together with its users. If you raise or lower your tongue incorrectly, do not smile enough or make your lips a duck poorly, then a mobile assistant with a computer vision system will not let you into a new level of the game.

“Our cat does not know how to talk, but it helps to motivate people to do articulatory gymnastics, because the procedure itself is boring. Today, some experts are already grateful that such an additional tool for work has appeared , ”notes the founder of the CatZu startup, Antonina Sudilovskaya.

The startup CatZu is about a year old, and now the team is starting a new stage - testing the product by everyone. We also plan to find investors for marketing research.

Where can you find this virtual speech therapist today, and what additional bonuses does the service offer? All the details are in the new release on the ITitov YouTube channel.