From automated parking techniques to anti-fraud options, this worldwide AI skilled is reworking a number of industries with revolutionary machine-learning purposes whereas mentoring the subsequent technology of tech expertise
As synthetic intelligence continues to rework industries worldwide, Central Asian companies are more and more adopting AI-powered automation to remain aggressive within the world market. In accordance with an IDC report, AI may contribute as much as $19.9 trillion to the worldwide economic system by 2030, accounting for 3.5% of the world’s GDP (elpais.com). One worldwide skilled making use of these applied sciences is Abylaikhan Azamatov, who has carried out AI options throughout Japan, UAE, Russia, and Kazakhstan. His pc imaginative and prescient and machine studying work has improved enterprise processes throughout a number of sectors.
From developer to AI innovator
Azamatov’s journey into synthetic intelligence started with a stable basis in data expertise. After graduating with honors from the Worldwide Info Know-how College, he explored revolutionary tasks, together with “Robotai,” a robotic system designed to reap apples effectively. Azamatov rapidly transitioned into software program improvement, working as a Backend Python Developer in Moscow, the place he built-in machine studying fashions into server techniques.
These early tasks gave Azamatov invaluable insights into how AI options might be successfully carried out inside current infrastructures. He quickly acknowledged that probably the most highly effective purposes weren’t essentially probably the most advanced however those who solved actual enterprise issues effectively.
This sensible strategy to expertise led Azamatov to specialise in monetary expertise, the place he developed credit score scoring fashions for Financial institution Middle Credit score, certainly one of Kazakhstan’s main monetary establishments, and anti-fraud techniques for Kaspi Financial institution, Kazakhstan’s main digital financial institution. His anti-fraud system for monitoring authorized entity operations decreased fraud ranges by 25%, demonstrating the tangible impression of his work.
Pioneering pc imaginative and prescient options
Azamatov’s experience really grew to become outstanding throughout his time at Parqour, the place he developed an automatic parking system that elevated car recognition velocity by 30%. The answer, which mixed YOLO (You Solely Look As soon as, a real-time object detection algorithm) for detection and a customized CNN (Convolutional Neural Community) for recognition, was efficiently carried out in over 50 services.
The parking automation undertaking needed to overcome important challenges, together with excessive climate circumstances and variable lighting that would have an effect on recognition accuracy. Regardless of these obstacles, the system maintained excessive efficiency ranges, resulting in shows earlier than authorities officers for implementing revolutionary parking options in main city areas.
At ARK in Moscow, Azamatov continued advancing pc imaginative and prescient purposes by automating merchandising processes, which improved forecasting accuracy by 15% and decreased picture evaluation processing time by 20%. These achievements demonstrated his skill to optimize advanced algorithms for sensible enterprise purposes.
Worldwide expertise and experience
Azamatov’s technical prowess is complemented by intensive worldwide expertise. Working as an ML Engineer at Nexus Fronttech in Japan, he participated in additional than 10 outsourcing tasks, reaching as much as 95% mannequin accuracy enhancements. This expertise gave him invaluable insights into optimizing fashions for units with restricted sources.
“Working in different countries taught me how to adapt solutions to varying market requirements and cultural contexts,” Azamatov notes. “The technical challenges might be similar, but implementation approaches need to be customized based on local business environments.”
His work prolonged to the UAE, the place he served as an AI advisor for KPI, serving to launch a market startup by optimizing enterprise processes and technological infrastructure. As an AI Engineer for Latoken, a cryptocurrency trade, he developed AI options to guard the platform from automated bots, considerably enhancing safety measures.
Regional Variations in Technical Infrastructure
Based mostly on his cross-market expertise, Azamatov describes how technical approaches for AI implementation various dramatically throughout the 4 areas the place he labored. In some rising markets, he encountered restricted web stability that compelled his groups to deploy native servers and carry out calculations on-site, decreasing dependency on cloud options. His tasks typically used NVIDIA GTX as a substitute of costlier RTX fashions, requiring cautious worth balancing towards efficiency in server configurations.
Azamatov discovered that the Center East introduced a stark distinction with its sturdy community infrastructure, enabling hybrid architectures that mixed native processing with cloud storage and analytics with out bandwidth limitations.
“Clients could afford high-performance servers with GPU acceleration or specialized NVIDIA Jetson modules,” he notes, which allowed his groups to implement extra advanced and resource-intensive fashions with out compromises.
Throughout his time in Japan, Azamatov noticed that the technological panorama demanded extraordinarily excessive information high quality requirements and accuracy necessities. His tasks there emphasised meticulous high quality management, superior mannequin implementation, and deep integration with IoT techniques to realize superior automation and reliability. In the meantime, in his UAE tasks, Azamatov prioritized cloud-based, scalable options that would combine with authorities registries for fast information processing and high-level automation.
Monetary Applied sciences: From Conventional Banking to Cryptocurrency
Azamatov’s expertise in each conventional banking and cryptocurrency sectors revealed contrasts in technological approaches. For his anti-fraud system at Kaspi Financial institution, he labored inside a monolithic or classical microservices structure constrained by strict regulatory necessities and obligatory auditing.
Azamatov’s banking tasks operated inside a extremely regulated atmosphere, requiring strict KYC and AML compliance. They have been developed utilizing conservative expertise stacks, together with Java, .NET, and established SQL databases.
Against this, his safety implementation for the Latoken cryptocurrency trade employed a versatile microservice structure with frequent updates and blockchain integration. “Development followed agile methodology with short testing cycles and rapid implementation of changes,” Azamatov factors out. Whereas regulatory processes have been much less formalized, they maintained excessive transparency necessities and safety for blockchain operations. His expertise stack relied closely on open-source parts, microservices in Golang and Python, and superior blockchain applied sciences.
Present tasks and future imaginative and prescient
Azamatov has intensive expertise as a Chief Language Fashions Professional at Freedom Finance Financial institution, the place he developed a Telegram bot based mostly on GPT that gives suggestions to purchasers. The bot integrates with the financial institution’s super-application, which incorporates brokerage companies and third-party companies.
“The future of artificial intelligence isn’t just about implementing cutting-edge technologies,” Azamatov emphasizes. “It’s about creating solutions that address our specific economic and social needs while developing local talent to compete globally.”
Academic contribution and social impression
Azamatov has shared his experience by educating at a web based programming faculty the place greater than 100 college students accomplished programs. He’s additionally participated in initiatives supporting youngsters from low-income households by organizing academic packages in IT and programming.
“My mission is to advance the field of artificial intelligence by nurturing a new generation of technical specialists and fostering innovative approaches to problem-solving,” says Azamatov. “I believe we can drive technological progress through education, supporting talented engineers, and promoting forward-thinking methodologies in AI development.”
His cross-market expertise has supplied him with distinctive insights into world greatest practices whereas demonstrating the significance of adapting options to particular enterprise environments and technological contexts.
