COVID-19 helped the development of AI: the main from the report of Stanford on the development of technology

Modern artificial intelligence

There are two directions for the development of AI:

  • solution of problems,
    associated with the approach of specialized AI systems to human capabilities, and their integration, which is implemented by human nature.
  • creation of artificial intelligence, representing the integration of already created AI systems into a single system capable of solving the problems of humanity.

But at the moment in the field of artificialintelligence, there is an involvement of many subject areas, which are more of a practical relation to AI, rather than fundamental. Many approaches have been tried, but not a single research group has yet approached the emergence of artificial intelligence. Below are just some of the most famous developments in the field of AI.

Artificial Intelligence Applications

  • Algorithmic trading

Algorithmic trading involvesthe use of sophisticated artificial intelligence systems to make trading decisions at a speed exceeding the speed at which the human body is capable.

This allows you to make millions of trades per day without any human intervention. Automated trading systems are commonly used by large institutional investors.

  • Market research and data mining

Several large financial institutions have investedfunds in the development of AI to use it in their investment practice. The developments of BlackRock 'AI, Aladdin, are used both internally and for the company's clients, assisting in making investment decisions.

A wide range of functionality of thissystems include natural language processing for reading text such as news, broker reports and social media feeds. The system then evaluates the sentiment in the mentioned companies and assigns a rating to them.

Banks like UBS and Deutsche Bank usean AI system called Sqreem (Sequential Quantum Reduction and Extraction Model) that can process data to develop consumer profiles and match them to the products they are most likely to want.

Goldman Sachs uses Kensho, a platformmarket analytics that combines statistical computing with big data and natural language processing. His machine learning systems use data on the Internet and assess correlations between world events and their impact on the prices of financial assets.

The information extracted by the AI ​​system from the live news feed is used in making investment decisions.

  • Personal finance management

There are products that use AI tohelping people manage their personal finances. For example, Digit is an artificial intelligence-powered app that automatically helps consumers optimize their spending and savings based on their personal habits and goals.

The app can analyze factors such as monthly income, current balance and spending habits, then make its own decisions and transfer money to a separate savings account.

Wallet.AI, a San Francisco-based start-up, is creating agents that analyze the data a consumer generates when interacting with smartphones and social media to inform the consumer about their spending.

  • Financial portfolio management

Automated advisor assistants becomeincreasingly used in the investment management industry. Automated systems provide financial advice and advice on portfolio management with minimal human intervention.

This class of financial advisors works forbased on algorithms designed to automatically develop a financial portfolio in accordance with investment goals and risk appetite of clients. He can adjust real-time changes in the market and calibrate the portfolio according to the client's wishes.

  • Underwriting

Online lender Upstart analyzes a hugeconsumer data and uses machine learning algorithms to build credit risk models that predict the likelihood of default.

Their technology will be licensed to banks so they can use it to evaluate their processes.

  • Warfare

The use of AI is an important trend in the creation of advanced battlefield and weapons control systems.

AI makes it possible to ensure optimal andadaptive to threats selection of a combination of sensors and means of destruction, to coordinate their joint functioning, to detect and identify threats, to assess the enemy's intentions.

AI plays a significant role in the implementation oftactical augmented reality systems. For example, AI makes it possible to provide classification and semantic segmentation of images, localization and identification of mobile objects for effective target designation.

  • Special services

British intelligence services will fightRussian fake news using artificial intelligence that will recognize the activity of the "troll factory". According to the UK Government Communications Center, artificial intelligence will fight fakes by checking data with reliable sources, detecting image and video manipulation and blocking suspicious bots.

  • Heavy industry

Robots have become ubiquitous in many industriesindustry and are often engaged in work that is considered hazardous to humans. Robots have proven effective in workplaces involving repetitive, routine tasks that can lead to errors or accidents due to decreased concentration over time.

Robots are also widely used in jobs that people may find humiliating.

In 2014, China, Japan, the United States,The Republic of Korea and Germany together accounted for 70% of global robot sales. In the automotive industry, a sector with a particularly high degree of automation, Japan had the highest density of industrial robots in the world: 1,414 robots per 10,000 employees.

  • The medicine

Artificial neural networks, such as Concept Processing technology in EMR software, are used as clinical decision systems for medical diagnostics.

Other medical tasks that could potentially be performed by artificial intelligence and are beginning to be developed include:

  • Computer interpretation of medicalimages. Such systems help scan digital images, for example from computed tomography, for typical manifestations and to highlight noticeable abnormalities such as possible diseases. A typical application is tumor detection.
  • Heart rate analysis
  • Project Watson is another use of AI in this area, a question / answer program designed to help oncologists
  • Assistant robots for elderly care
  • Processing medical records to provide more useful information
  • Creation of treatment plans
  • Identifying an increased risk of disease
  • Assistance with repetitive tasks, including medication management
  • Providing advice
  • Drug creation
  • Using humanoid dummies instead of patients for clinical education
  • Music

Although the evolution of music has always been affected by technology, artificial intelligence has made it possible, through scientific advances, to emulate, to some extent, a human-like composition.

Among notable early efforts, David Cope createdAI named Emily Howell, who managed to become famous in the field of Algorithmic Computer Music. The algorithm behind Emily Howell is registered as a US patent.

Other developments such as AIVA (ArtificialIntelligence Virtual Artist) focus on composing symphonies, mainly classical music for films. This development rose to prominence as the first virtual composer to be recognized by the music professional association.

Artificial Intelligences can even create music suitable for use in medical settings, Melomics uses computer music to relieve stress and pain.

China overtook the United States in scientific publications on artificial intelligence

China has the largest number of articles on AI in scientific journals, accounting for 22% of all publications per year in the world. Next comes the EU - 16.4%, and the third place is taken by the United States - 14.6%.

In terms of the number of AI patents, the United States is the leading power. However, the second and third places in this ranking according to the data for 2014 belong to South Korea and Japan.

AI is not only being developed in America,Europe and Asia. One of the largest events in the field of machine learning - the Deep Learning Indaba conference - was held in South Africa, where more than 500 developers from dozens of African countries came.

But, as noted by experts at Stanford, the United Statescontinue to lead in the volume of research produced jointly by scientific institutions and technology companies, and accordingly - in translating ideas into reality.

As a result, the United States and China made approximately the same contribution to the development of artificial intelligence, if analyzed according to different parameters, said Jack Clark, co-chairman of the AI ​​Index.

Investment in the AI ​​industry has grown by 40%.

The number of AI-related articles on arXiv (the largest free archive of publications of scientific articles and their preprints) has grown from about 5.5 thousand.

In 2015, up to almost 35 thousand in 2020.Scientific organizations all over the world are the first in terms of the total number of articles. In the second place in the United States is research carried out by commercial companies, and in Europe and China - research commissioned by the state.

The rapid development of the industry is not only talked aboutdata on the number of startups, articles and vacancies. The report cites the successes in the field of computer vision as an example. For 18 months, the time for training machines to recognize objects has decreased from an hour to four minutes.

Investments in startups declined

However, there are fewer developers and startups that have received investments. In 2017, investments were distributed between 4 thousand, and last year, less than a thousand companies received them.

This is due to the fact that the AI ​​industry itself has become more mature. Now small technology projects have begun to be eliminated, and large and stable companies are receiving funding in this area.

Investments are divided among themselves by the second - the dominant players in the market. In addition, due to the pandemic, investors were primarily interested in developments in the field of medicine, pharmaceuticals and biotechnology.

Investments in AI for medicine have grown

AI development for drug creation, includingamong those used in the treatment of covid-infected, vaccines, technologies for fighting cancer and other pharmaceutical and medical products received the largest volume of private investments in 2020 - more than $ 13.8 billion.

This is 4.5 times more than in 2019. They are followed in the list by developers of self-driving vehicles ($ 4.5 billion) and educational products with AI ($ 4.1 billion).

AI has become less likely to make mistakes

One example of AI progress is the GPT-3 language neural network model. It allows you to create large texts - it generates them based on 175 billion parameters.

You can see how she copes atan example of this experiment. The Gardian's editor commissioned GPT-3 to write a nearly 500-word column on "why humans shouldn't be afraid of artificial intelligence."

AI models have become more accurate and smarter. In January of this year, the Google Brain team's system was able to achieve 90.2% accuracy. For some simple tasks of visual recognition, the AI ​​accuracy can be 99%.

In a competition in the ImageNet competition for one task, where it was required to mark pictures by class, in 2012 the best algorithms made four mistakes out of 10 attempts, in 2020 - one.

The threat of unemployment due to the growth of the number of AI

With such a rapid development of algorithms,the question of the negative consequences of automation. It all depends on the region, MIT professor Eric Brinolfsson, one of the authors of the report, told Gizmodo.

I think that a lot of workers will be destroyedplaces and new ones will be created, but probably for other people and in other areas. Developing countries are likely to be the hardest hit, as they are most dependent on low-wage jobs.

Eric Brinolfsson, professor at the Massachusetts Institute of Technology

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