Artificial Intelligence technology can support mechanical, simple, repetitive and uncreative labor scenarios. In modern factories, industrial robots and robotic arms, combined with AI algorithms that have a higher level of "intelligence," can lead to higher productivity and production quality.
2. Creating new species in the digital economy era
From the perspective of current technology and technical ethics, it is still too early to say "brain-like intelligence", but AI, combined with cloud computing, IoT, VR/AR and other technologies, can indeed liberate and reconfigure the factors of production, and give rise to a variety of business and social creation. The ability to create "new species (in terms of products, services or types of businesses)". Behind the birth of the translation machine is a significant increase in the level of machine translation.
3. Pushing the Limits of Human Ability
With the proliferation of computers, computation, storage, and algorithms are gradually surpassing the limits of human ability in terms of global cognition, high concurrency, deep logic, and complex and accurate memories, providing entirely new levels of productivity. In addition, AI can be tasked with pushing the limits of human capabilities in some highly dangerous and complex production environments. For example, the use of AI in the translation of satellite remote sensing imagery can reduce the months required by traditional solutions to a few hours.
4. Activating data to innovate business and commercial processes
Over the past 20 years, Chinese enterprises have experienced widespread informatization and e-enablement, which has resulted in the deposition of a large amount of high-value data, which can be "activated" by AI to find new business value points, business processes, or customer needs, and help enterprises make better decisions than they do today manually. These data can be "activated" by AI to find new business value points, business processes, or customer needs, and help organizations make better business services and business processes than they do today. For example, Robotic Process Automation (RPA) tools can help organizations reduce operational costs in ****enjoyment services by 30-50%.
5. Breaking through stereotypes and discovering underlying logic and connections
Artificial Intelligence (AI) has powerful mathematical capabilities and sufficient computational speed to far exceed human computational capacity, and can handle millions of scenarios at once, which can break through the traditional "old expert" mindset and make hidden and fragmented problems visible. This ability is able to break through the traditional thinking of "old experts" and make implicit and fragmented problems explicit, and generate new knowledge. As a result, AI can help companies accurately match user needs or business requirements, and find the underlying logic and inner connections that would otherwise be undiscoverable due to the limitations of human labor and the human brain.
6. Provide new human-machine or service interaction modes
At present, AI has very strong capabilities in the fields of machine vision (image and video recognition), natural language understanding, and speech recognition, which means that a machine can have "visual, auditory, and linguistic/semantic comprehension capabilities" similar to those of humans. ". New, large and lucrative adjacent markets for HCI are opening up with new opportunities for growth and expansion, particularly in the automotive and healthcare sectors, and AI will be the new starting point for revolutionizing HCI.
7. Assisting Human Intelligent Decision Making
Artificial Intelligence can provide enterprises with intelligent decision making that is different from and more valuable than traditional Decision Support Systems, Knowledge-Assisted Decision Making Systems, or Expert Systems, and help enterprises build Decision Support Systems (i.e., Decision Support Systems, DSS, an important area of research in Artificial Intelligence), providing Decision makers to provide an environment for analyzing problems, building models, simulating the decision-making process and programs, calling on a variety of information resources and analytical tools to help decision makers improve the level and quality of decision-making.