Top 10 emerging future Technology Trends for 2020

With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. In the past year alone, the integration of multiple emerging technologies has sped up; the threshold of AI development continued lowering, and industrial intelligence led the dawn of the fourth industrial revolution.

Following these stones deeply buried in the soil of science and technology in 2019, we can blueprint the outlook of what’s to come in 2020, where science and technology will still be a quintessential function of society and the key to our understanding of the future.

Today, we are releasing our forecast of the 10 major scientific and technological trends in 2020.

AI technology will be industrialized with large-scale production

The increasingly mature AI technology and all types of associated business solutions are rapidly entering the stage of “industrialization.” With the continuous investment global technology giants pumped into AI technology, there will be many factories of AI models and data emerging in 2020, facilitating AI technology and associated commercial solutions on a large scale to update industries.

2020 will be a crucial year for the large-scale execution of AI chips

In recent years, AI chips have gradually reached a usable state, and 2020 will be a critical year for the large-scale implementation of AI chips. AI chips on the edge will be more low-cost, specialized, and seamlessly integrated into downstream solutions. In the future, more and more device-based CPU chips will integrate deep learning framework as the core to their designs. In addition to chips, AI will redefine the computer architecture and support AI training and inference as a new idea of heterogeneous design architecture.

Deep learning technology will penetrate the industry and be applied on a large scale

Deep learning is the most important and effective technology in the field of artificial intelligence. At the core of open-sourced deep learning platforms is the deep learning framework, which greatly lowers the development threshold of AI technology, and effectively improves the quality and efficiency of AI applications.

Blockchain technology will be incorporated into more scenarios in a more realistic manner

With the in-depth integration of blockchain technology with AI, big data, IoT, and edge computing, the problems concerning the online and offline mapping of data and assets will be solved one by one. Solutions such as data authorization, data use, data circulation and exchange built around blockchain will play a huge role among people from all walks of life. For example, in e-commerce, blockchain can ensure the authenticity of the whole process data of goods; in supply chain, it can ensure the openness and transparency of the whole process data, as well as the safe exchange between enterprises; in government affairs, it can achieve the opening of government data, the realization of electronic certificates and so on.

The Internet of Things (IoT) will breakthrough in three directions: boundary, dimension, and scenario

With the development of 5G and edge computing, computing power will not be limited to cloud computing centers, expanding to everything and building a distributed computing platform. At the same time, the insight into time and space, the two most important dimensions of the physical world, will become the basic capabilities of the new-generation IoT platforms. This will promote the integration of IoT with more scenarios such as energy, power, industry, logistics, medical treatment, and intelligent city, and create greater value.

AutoML, automatic machine learning, will greatly lower the threshold of machine learning

AutoML will be able to integrate the iterative process in traditional machine learning and build an automatic process. Researchers only need to input meta-knowledge (such as convolution operations, problem descriptions, etc.), the algorithm can automatically select the appropriate data, optimize the model structure and configuration, train the model, and deploy it on different devices. The rapid development of AutoML will greatly lower the threshold of machine learning and increase the popularity of AI applications.

Multimodal deep semantic understanding will become more mature and widely used

Multimodal deep semantic understanding takes the information of different models such as voice, image, and text as input, and integrates perception and cognition technologies to achieve a multi-dimensional deep understanding of information. With the rapid development and large-scale application of computing vision, speech, natural language understanding, and knowledge graph, multimodal deep semantic understanding is gradually mature, which leads to a broader application scenario. Combined with AI chips, it will be widely used smart home, finance, security, education, healthcare, and other industries.

Natural language processing technology will be deeply integrated with knowledge, and computing platforms for general natural language understanding will be widely used

With the emergence and development of pre-training large-scale language model, the technology of general natural language understanding has been greatly improved. Semantic representation pre-training technology based on massive text data will be deeply integrated with domain knowledge to continuously improve the effectiveness of natural language processing tasks such as automatic question answering, emotional analysis, reading comprehension, reasoning, information extraction, etc. The general natural language understanding the computing platform, which integrates large-scale computing power, rich domain data, pre-training model, and improved R&D tools, will be gradually improved and widely used in the internet, healthcare, legal, financial and other fields.

Intelligent transportation will accelerate its implementation in various scenes such as parks and cities

The development of autonomous vehicles is becoming more rational, and the market will be more confident in the development of intelligent driving in the next few years. In 2020, more autonomous vehicles will be applied to different scenarios such as logistics, public transport, geofenced areas, and so on. At the same time, V2X (vehicle to everything) technology is ready for large-scale deployment and application, which makes vehicles and roads form a wide range of connections, further promoting the realization of Intelligent Vehicle Infrastructure Cooperative Systems (IVICS), and accelerating the implementation of intelligent transportation in parks, cities, expressways and other scenarios.

Quantum computing will usher in a new round of explosive growth, injecting new vitality into AI and cloud computing

With the successful demonstration of quantum hegemony, quantum computing will usher in a new round of explosive growth in 2020. In terms of quantum hardware, the performance of programmable medium-sized noisy quantum devices will be further improved and have the ability of error correction. Quantum algorithms with certain practical value will be able to run on them, and the application of quantum artificial intelligence will be greatly developed. In terms of quantum software, high-quality quantum computing platforms and software will emerge and be deeply integrated with AI and cloud computing technologies. In addition, with the emergence of the quantum computing industry chain, quantum computing will surely garner more attention in more application fields. More and more industry giants have invested in R&D resources for strategic layout, which has the opportunity to bring a new face to the future AI and cloud computing fields.

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