Alibaba Version 10 Technological Trends 2020: AI, IoT and 5G Developing Rapidly

Alibaba Version 10 Technological Trends 2020: AI, IoT and 5G Developing Rapidly

What are the 2020 tech trends like? Alibaba DAMO Academy, a global research initiative initiated by Alibaba Group, has released a report on the latest technology trends that have huge potential this year.

Most of these trends are familiar to the tech industry. Where at this time we live in an era with rapid technological growth. Jeff Zhang, Head of Alibaba DAMO Academy and President of Alibaba Cloud Intelligence, put special emphasis on the new generation of IT technology marked by breakthroughs in cloud computing, artificial intelligence, blockchain, data intelligence and 5G. The technology is expected to accelerate the digital economy.

DAMO Academy itself was founded on October 11, 2017, which is dedicated to exploring new things through science and technology research. Delivering even better progress for humanity is the main driving factor for this research company initiated by Jack Ma.

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There are 10 2020 technology trends released by Alibaba DAMO Academy. His name is also a prediction, it cannot be a benchmark for whether it will actually materialize. Some may actually become a trend, some may not. Sometimes the business interests of the parent company also have a role. Here are 10 predictions of technology trends this year according to Alibaba DAMO Academy:

IoT supports digital transformation

IOT Internet of Things (IoT) has been known for several years. In 2020, 5G technology, IoT devices, cloud computing, and edge computing are believed to accelerate the integration of information systems, communication systems and industrial sector control systems.

Through Industrial IoT, manufacturing companies can take advantage of machine automation technology, factory logistics, and production scheduling. This is a way to realize the C2B smart manufacturing business model (consumer to business smart manufacturing).

In addition, interconnected or integrated industrial systems can adjust and coordinate the overall production capabilities of vendors, from upstream to downstream. Ultimately, this will significantly increase the productivity and profitability of producers. For producers with production goods that are worth hundreds of trillions, if productivity has increased by 5-10{7ae9dcebd9dd004c164f5ac83492ab0da83c9658891ee56b8436678e90c11220}, it means that there is an additional trillions of profit.

Large-scale collaboration between machines

Traditional single intelligence cannot meet the real-time demands and decisions of large-scale smart devices. Now, the development of collaborative sensing technology from IoT and 5G will realize collaboration between multiple agents – machines that work together with each other and compete with each other to complete targets.

The combined intelligence generated from the cooperation of various sectors will further strengthen the value of the intelligence system. Where the large-scale intelligent traffic light delivery will realize dynamic adjustment and display real-time calculations. Meanwhile the robots in the warehouse will work together to complete the sorting of cargo more efficiently. Manufacturers can also use self-driving cars and UAV drones which can see the overall traffic conditions on the road, making delivery more efficient.

AI becomes cognitive intelligence

AI Cognitive Artificial Intelligence (AI) has reached or exceeded the human limit in the areas of perceptual intelligence such as speech to text, NLP (natural language processing), video comprehension, etc .; however in areas of cognitive intelligence that require external knowledge, logical reasoning, or domain migration, AI is still in its early stages of development.

Cognitive intelligence will draw ideas from cognitive psychology, brain science, and human social history, combined with techniques such as cross-domain knowledge graphing, causality inference, and continuous learning to build effective mechanisms for stable acquisition and expression of knowledge.

Blockchain applications will be adopted en masse

BaaS (Blockchain-as-a-Service) will further reduce the barriers to entry for enterprise blockchain applications. Various hardware chips embedded with core algorithms are used on the edge, cloud and specially designed for the emerging blockchain, which allow assets in the physical world to be placed into assets on the blockchain, further extending the boundaries of the Internet of Value and realizing “interconnection”. multi-chain ”.

In the future, a large number of innovative blockchain application scenarios with multi-dimensional collaboration across various industries and ecosystems will emerge, and large-scale production-grade blockchain applications with more than 10 million DAI (Daily Active Items) will be massively adopted.

In-Memory-Computing Technology

In Memory Computing In the Von Neumann architecture, memory and the processor are separate and the computation requires data to keep moving. With the rapid development of data-driven AI algorithms over the last few years, it has finally come to a point where hardware becomes a bottleneck in the exploration of more advanced algorithms.

However, unlike Von Neumann, in the Processing-in-Memory (PIM) architecture, the memory and processor are fused together and computation is carried out where data is stored with minimal data movement. Thus, computational parallelism and power efficiency can be significantly improved. We believe innovation in the PIM architecture is the ticket to the next generation of AI.

Modular design

Traditional models of chip design cannot efficiently respond to the rapidly evolving, reproducible and customized needs of chip production. The open source SoC chip design based on RISC-V, a high-level hardware description language, and IP-based modular chip design methods have accelerated the development of agile design methods and the open source chip ecosystem.

In addition, the modular design method based on chiplets (chipmakers) uses advanced packaging methods to pack chiplets that have different functions together, which can quickly adapt and ship the chips that have passed specific selection by different applications.

The critical period before large-scale quantum computing

In 2019, the race to achieve “Quantum Supremacy” returns to focus on quantum computing. In his demonstration, using superconducting circuits, increased the overall confidence in superconducting quantum computing for the realization of large-scale quantum computers.

In 2020, the field of quantum computing will receive increased investment, accompanied by increased competition. This is also expected to experience acceleration in industrialization and gradual formation of ecosystems.

In the coming years, the next milestone will be the realization of fault-tolerant quantum computing and the demonstration of quantum advantages in dealing with real problems. Starting from a big challenge to existing knowledge today. Quantum computing is entering a critical period.

New materials in semiconductor devices

Under the pressure of Moore’s Law and the enormous demand for computational and storage power, it was difficult for the classical Si-based transistors (system of units) to sustain the continuous development of the semiconductor industry. As of now, major semiconductor manufacturers still don’t have clear answers and options for chips beyond 3nm.

The new materials will create new logic, storage, and interconnection devices through new physical mechanisms, driving continuous innovation in the semiconductor industry. For example, topological insulators, two-dimensional superconducting materials, etc .; which can achieve conveyance without losing electrons and spins which can form the basis for high-performance logic and new interconnection devices; while new magnetic materials and new resistive switching materials can realize high performance magnetic Memories such as SOT-MRAM and resistive memory.

AI technology protects data privacy

AI Privacy data The cost of compliance required by the latest laws and regulations on data protection related to data transfer is higher than before. Hence, there is increasing interest in using AI technology to protect data privacy.

In essence, it is to allow data users to perform computational functions of input data from different data providers while maintaining that data as privacy. AI technologies like this promise that they can solve the data silo problem and the problem of lack of trust in current data sharing practices.

Cloud becomes the center of IT technology innovation

With the continuous development of cloud computing technology, the cloud has grown far beyond the scope of IT infrastructure, and has gradually become the center of all IT technology innovation. The cloud has close relationships with almost all IT technologies, including new chips, new databases, self-driving adaptive networks, big data, AI, IoT, blockchain, quantum computing and more. Meanwhile, the cloud continues to innovate with new technologies, such as serverless computing, cloud software architecture, integrated software design, and intelligent automated operation. Cloud computing is redefining every aspect of IT, making new IT technologies more accessible to the public. The cloud has become the backbone of the entire digital economy.