MobiDev, a US-based software engineering company with development centers in Ukraine, has compiled customers’ requests and needs in the area of AI and came with the list of AI trends that matter for Business in 2021.
According to 2020’s McKinsey Global Survey on artificial intelligence (AI), in 2020 more than 50% of companies have adopted AI in at least one business unit or function, so we witness the emergence of new AI trends. Lockdowns resulted in a massive surge of online activity and an intensive AI adoption in business, education, administration, social interaction, etc.
1. AI for Security & Surveillance
AI techniques have already been applied to face recognition, voice identification, and video analysis. These techniques form the best combo for surveillance. So, in 2021, we can foresee the intensive exploitation of AI in video surveillance.
AI in video surveillance can detect suspicious activity by focusing on abnormal behavior patterns, not faces. Such AI-driven video solutions could be also useful for logistics, retail, and manufacturing. Another niche that provides promising perspectives for the AI application is voice recognition. Technologies related to voice recognition are able to determine the identity. By identity, we mean the age of a person, gender, and emotional state. One of the most crucial technologies for security is biometric face recognition.
2. AI in real-time video processing
The challenge for processing real-time video streams is handling data pipelines. To implement an AI-based approach in live video processing, we need a pre-trained neural network model, a cloud infrastructure, and a software layer for applying user scenarios. Processes parallelization is achieved through file splitting or using a pipeline approach. This pipeline architecture is the best choice since it doesn’t decrease a model’s accuracy and allows for use of an AI algorithm to process video in real-time without any complexities.
3. Generative AI for content creation & chatbots
At the heart of the text generation stands Natural Language Processing (NLP). Combining NLP and AI tools allows the creation of chatbots. According to Business Insider, the chatbot market is expected to reach USD 9.4 billion in 2024, so let’s emphasize the ways businesses benefit from AI-driven chatbots implementation.
Another example is NLP text generation that can be used in business applications. An NLP-based Question Generation system presented in the video below is used in a secure authentication process.
4. AI-driven QA and inspection
Companies started to invest both computational and financial resources to develop сomputer vision systems at a faster rate. Automated inspection in manufacturing implies the analysis of products in terms of their compliance with quality standards. The methodology is also applied to equipment monitoring.
A few use cases of AI inspection are detecting defects of products on the assembly line, identifying defects of mechanical and car body parts, baggage screening and aircraft maintenance, inspections of nuclear power stations.
5. Game-changing AI breakthroughs in healthcare
Scientists use AI models and computer vision algorithms in the fight against COVID-19, including areas like pandemic detection, vaccine development, drug discovery, thermal screening, facial recognition with masks, and analyzing CT scans. Also, AI helps to develop vaccines by identifying crucial components that make them efficient. AI-driven solutions may be applied as an efficient tool in The Internet of Medical Things and for handling confidentiality issues specific to the healthcare industry.
6. No-code AI platforms in at least three areas
Adoption of the no-code AI platform simplifies the task because it reduces the entry barrier. The advantages are fast implementation, the lower cost of development, and ease of use. No-code AI platforms are in demand in healthcare, the financial sector, and marketing — though produced solutions couldn’t be highly customized.
7. Diversity in AI
According to NYU’s research, 80% of professors involved in AI development are men, and only 10% of researchers who work with Artificial Intelligence at Google are women. The number of female graduates of AI Ph.D. programs and computer science faculties has remained at a low level for a long time. But the need for diversity in AI should influence this situation, which is one of the emerging trends. Moreover, women in AI can make big decisions influencing the development and implementation of AI systems.
Trends show that the future of Artificial Intelligence is promising because AI solutions are becoming commonplace. Autonomous cars, robots and sensors for predictive analysis in manufacturing, virtual assistants in healthcare, NLP for reports in media, virtual educational tutors, AI assistants, and chatbots that can replace humans in customer service — all these AI-powered solutions are moving forward with huge steps.
More detailed information about the impact of AI trends on business in 2021 can be found at: MobiDev