Introduction:
The new crown epidemic has accelerated the digitalization of society. The blockade of the offline environment has led to a surge in online activities. has adopted artificial intelligence in business, education, administration, and social .
According to the 2020 McKinsey Global Artificial Intelligence (AI) survey, in 2020, more than 50% of companies have adopted artificial intelligence in at least one business department or functional department. We have witnessed the new The emergence of artificial intelligence trends. Enterprises apply artificial intelligence tools to create more value, increase revenue and customer loyalty. Companies with high deployment rates of artificial intelligence will invest at least 20% of their earnings before interest and taxes (EBIT) in artificial intelligence.
The degree of artificial intelligence application varies from industry to industry. According to the data mentioned in the McKinsey Global Artificial Intelligence Survey, we can find four leading industries: high-tech, telecommunications, automobiles, and assembly.
Most companies apply artificial intelligence to service operations, service or product design, advertising, and sales. In terms of investment, the field of drug discovery and development has received the most funds: in 2020, the total assets will exceed 13.8 billion U.S. dollars, an increase of 4.5 times over the previous year.
In the next few years, artificial intelligence will be used to simplify operations and increase efficiency. Companies should try to benefit from the commercial applications of artificial intelligence by improving IT infrastructure and data management. But not every AI model deployed can be helpful to the company and suitable for performance monitoring. We will focus on the following major AI technology trends.
Trend 1: AI for security and surveillance
artificial intelligence technology has been applied to face recognition, voice recognition and video analysis, These technologies constitute the best combination of security monitoring. Therefore, we can foresee the massive use of artificial intelligence in video surveillance in the next few years.
Artificial intelligence is conducive to the flexible setting of the safety system. In the past, engineers spent a lot of time configuring the system because it was activated when a certain number of pixels on the screen changed, resulting in many false alarms. These false alarms are mostly caused by fallen leaves or running animals. The artificial intelligence security system can identify objects more accurately, which contributes to more flexible settings.
video surveillance The artificial intelligence in can detect suspicious activities by focusing on abnormal behavior patterns instead of faces. This ability can create safer public and private spaces by identifying potential threats. This AI-driven video solution may also help logistics, retail, and manufacturing.
Another technology that provides prospects for artificial intelligence applications is speech recognition. speech recognition-related technologies can determine identity. Identity refers to a person's age, gender, and emotional state. A feature suitable for security and surveillance is the built-in anti-spoofing model that can detect synthesized and recorded speech. One of the most critical security technologies of
is biometric face recognition. Different malicious applications of try to deceive the security system by providing fake photos instead of real images. In order to prevent this situation, people are currently developing and using a variety of anti-spoofing technologies on a large scale.
Trend 2: Artificial intelligence in real-time video processing
The challenge of processing real-time video streams is processing data pipelines. The engineer's goal is to ensure accuracy and minimize the delay of video processing, and artificial intelligence solutions can help achieve this goal.
In order to implement AI-based methods in real-time video processing, we need a pre-trained neural network model, a cloud infrastructure, and a software layer for application user scenarios.Processing speed is critical for real-time streaming, so all these components should be tightly integrated. For faster processing, we can parallelize the process or improve the algorithm. Process parallelization is achieved through file splitting or using pipeline methods. This pipeline architecture is the best choice because it does not reduce the accuracy of the model and allows the use of AI algorithms to process video in real time.
Modern real-time stream processing is inseparable from the application of background removal and blurring. Epidemic prevention and control have contributed to the emergence and popularization of new trends in video conferencing, and the demand for these tools has increased. The technical trend of real-time video processing will be actively developed. According to GlobeNewswire, the global video conferencing market is expected to grow from US$9.2 billion in 2021 to US$22.5 billion in 2026.
Trend 3: Generative artificial intelligence for content creation and chatbots
Modern AI models can generate very high-quality text, audio and images, almost non-composite The exact data cannot be distinguished. The rapid development of natural language processing (NLP) has led to the emergence of language models, which can be combined with NLP and AI tools to create chatbots. According to Business Insider, the chatbot market is expected to reach $9.4 billion in 2024.
chatbots try to understand people’s intentions, not just execute standard commands. Companies working in different fields use artificial intelligence-driven chatbots to provide human-level communication for their customers or users. The application of chatbots is widely used in the following business areas: healthcare, banking, marketing, tourism and hotels .
Artificial intelligence-driven chatbots help automate management tasks.For example, in the field of healthcare, they reduced physical labor. Here, chat bots help schedule appointments, send reminders related to medication, and provide patients with answers to questions. In other areas, chatbots have been introduced to deliver targeted information, increase customer engagement and support, and provide users with personalized services.
Trend 4: AI-driven QA and inspection
Computer Vision The most compelling branch is artificial intelligence inspection. Due to the application of deep learning models to improve accuracy and performance, this direction has been booming in recent years. Companies began to invest in computing and financial resources to develop computer vision systems at a faster rate.
Automated inspection in manufacturing means analyzing whether the product meets quality standards. This method is also suitable for equipment monitoring.
These are several use cases of AI inspection: detecting product defects on the assembly line, identifying defects in machinery and body parts, baggage inspection and aircraft maintenance, and nuclear power plant inspection.
Trend 5: No-code AI platforms in at least three areas
No-code AI platforms help small companies use powerful technologies that were previously only applied to large companies. It takes time, expense and relevant experience to develop an AI model from scratch. The code-free artificial intelligence platform helps small businesses simplify their tasks because it lowers the barriers to entry. Its advantages are:
1. Fast implementation: saves time up to 90% compared with writing code, processing data and debugging from scratch;
2. Lower development cost: eliminates enterprises through automation Requirements for large data science teams;
3. Easy to use: drag and drop function simplifies software development,No coding is required to create applications.
Although the resulting solutions cannot be highly customized, no-code AI platforms are required in the healthcare, financial sector, and marketing sectors. Enterprise-sized companies and medium-sized enterprises use code-free platforms to develop software solutions for image classification, recognition of gestures and sounds, and object detection.
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