2021 development issues of innovative economy in the agricultural sector

 
 
“DEVELOPMENT ISSUES OF INNOVATIVE ECONOMY IN 
 
THE AGRICULTURAL SECTOR”
 
International scientific-practical conference on March 25-26, 2021. 
Web: 
http://conference.sbtsue.uz/uz
 
financial and operational accuracy in the market. 
Organizations are 2-3 times more likely to purchase pre-configured solutions based on promising 
technologies than to develop their own (the percentage depends on the specific solution). 
Almost all respondents (91%) consider SaaS applications to be a key factor contributing to the 
development of new technologies. 
Front: 
Middle/Back: 
Image recognition-used, among other things, to 
recognize customers in branches and send them 
specialized offers 
Fraud detection 
Chatbots and voice assistants 
AML & KYC 
Personalization of products and offers 
Credit ratings 
Biometrics 
Risk managemen 
Robot assistants 
Compliance 
 
Document processing 
AI in transport 
On April 28, 2020, it became known that scientists of the Far Eastern Federal University (FEFU), 
together with colleagues from the Moscow Institute of Physics and Technology (MIPT), are developing 
mathematical methods of convex optimization for the accelerated solution of a wide range of problems in 
economics, science, and many applied areas of human activity. The scientists reported their results in the 
book "Numerical Methods of Convex Optimization" published by Springer. 
According to the company, the algorithms are adaptive, that is, they recognize all the necessary 
parameters themselves during operation, and are economical, they require a relatively small amount of 
memory. It is advisable to use these algorithms, for example, for modeling traffic flows, combating traffic 
jams and optimizing freight transport routes, calculating tolls, ranking web pages, solving inverse problems 
when you need to understand the reasons that gave rise to some consequences. 
The scientist said that for the classical problem of solving a system of linear equations, modern 
algorithms are many times more efficient than traditional methods, the complexity of which is 
approximately equal to the cube of the number of variables. 
Based on the algorithms, you can create a way to process a "heavy" image so that it requires 10 times 
less space at the output than at the input, but retains 95 percent of the original properties. At the same time, 
such a picture can not be distinguished from the original one by eye. 
The scientist noted that optimization problems are directly related to life, that is, nature itself often 
speaks the language of mathematics, and in order to understand its structure, it is necessary to solve the 
optimization problem 
AI in logistics 
Over the years, the use of artificial intelligence in SCM supply chain management has increased 
significantly worldwide, driven by a higher demand for transparency and traceability of data, as well as the 
need to improve customer service. The leading industries in terms of AI adoption in SCM (as of early 2020) 
are telecommunications(26%), high technology (23%), healthcare (21%), professional services (19%), and 
travel, transportation, and logistics (18%). 
Despite the benefits of integrating AI, some organizations are unable to implement it due to the 
following issues: 
Limited availability of high-quality, consistent, and up-to-date (real-time) data 
Availability of supply chain data in different departments (for example, marketing, inventory, 
purchasing manager, and others have their own databases) 
Limited integration between systems and databases for accessing, cleaning, and analyzing data. 
Limited data management policies related to the extended supply chain 
Procurement experts believe that the recent supply chain disruptions caused by the COVID-19 
pandemic highlight more than ever the need to integrate AI into the supply chain to optimize performance. 
To avoid a critical supply chain failure, an organization needs to have a complete picture of the entire 
ecosystem; accurately predict supply and demand; and optimally plan logistics and delivery, among other 

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