Artificial intelligence has emerged since the 1980s, and many startups, governments, and large corporations have begun deploying artificial intelligence systems to handle tasks previously performed by human experts. Compared to traditional programming languages, these systems are mostly based on behavioral rules and then form "memory". Artificial intelligence systems can handle more computationally intensive tasks such as machine learning, planning and scheduling, and natural language processing. In today's big data generation, many people believe that artificial intelligence has completely subverted the technology industry. Lei Feng.com has done a lot of related research and reports.
However, in the process of the development of artificial intelligence, its core elements have not changed much. For example, NASA's Space Shuttle program, launched in the late 1980s and 1990s, resulted in the successful commercialization of the entire industry chain, including unmanned aerial vehicles, space telescopes, space stations, and Planetary detectors, etc. Even some technologies are used in the ERP industry and e-commerce, customer relationship management and advertising marketing applications. In recent years, artificial intelligence technology has been widely used in many other industries, including:
Life Sciences: Artificial intelligence can learn clinical trial data, then match the patient to the most appropriate treatment, or find the best doctor.
Network security systems: Artificial intelligence can predict the potential dangers of a corporate network (at least telling companies where to buy insurance).
IoT system: Based on RFID tags, artificial intelligence can react to changes in asset positions and predict and analyze certain scenarios to prevent crime.
In the above several fields, Lei Feng also has a number of related articles detailing the role of artificial intelligence in these areas. In addition, many people's daily interactions and familiar systems also use artificial intelligence technology. For example, Apple's Siri and Amazon's Alexa can listen to our voice commands. Amazon can intelligently recommend products. Netflix can push programs according to user preferences. Cars and driverless systems, able to play chess and Go computers, and so on.
There are still many use cases for artificial intelligence. In fact, in the nearly four decades of the development of artificial intelligence, there have been five core elements supporting the entire industry and connecting various technology nodes. Artificial intelligence applications absorb massive amounts of data, react to the surrounding environment, improve fitness through learning, achieve better performance, and synchronize service systems and users.
First, strengthen the absorption of data
Artificial intelligence systems based on data hardening need to interact with massive amounts of data, and they typically get billions of orders of information at high speed. For artificial intelligence systems, real-time absorption of data is one of their must-have skills, in addition to the need to obtain uninterrupted streaming data (mostly small data modules, such as IoT sensor evaluation) and bulk data (some Big data modules, such as historical data tables in the system database).
Second, adaptability
With machine learning technology, adaptive applications can be self-optimized. Over time, they analyze the results of the work process and then learn how to do it better. Machine learning workflows require data scientists to model choices, which involves a complete set of iterative processes, including feature engineering, algorithm selection, and parameter tuning. The developer then deploys the machine learning model inside the application and imports new data, which classifies the data and analyzes the behavior in terms of classification. Finally, these applications that deploy machine learning "review" their processing results and re-train them with the resulting data.
Third, the reactivity
Modern artificial intelligence systems can make changes in real time according to the surrounding environment. Traditional applications are more based on batch mode—you schedule applications to perform tasks, they run, then store the results, and finally close the program. Artificial intelligence applications constantly monitor their input (usually from a variety of streaming media data platforms) and then perform operations based on actual conditions. Artificial intelligence programs automatically call programs, rules, and behaviors, and then make their own decisions. Simply put, the artificial intelligence system will always be in operation and then react based on different inputs.
Fourth, forward-looking
Many artificial intelligence systems are not only reactive, they can plan for the future and implement the best action plan. In fact, system planning, game planning, and even language analysis systems require a forward-looking solution. These systems must have the ability to switch input data at any time depending on the scenario (case). For example, artificial intelligence will obtain weather forecast data in time to analyze whether it will delay shipping or shipping shipments from China. Once delivery delays, will it affect the US manufacturing schedule, and whether it needs to re-optimize production. plan.
Five, concurrency
Artificial intelligence systems, like traditional applications, must support simultaneous processing of multiple users or multiple systems. By developing distributed systems in the operating system and database worlds, artificial intelligence systems need to constantly ensure the implementation of the four-factor principle (ACID) of traditional database transactions: atomicity, consistency, isolation (IsolaTIon), and Durability.
to sum up
With the improvement of software and hardware technology, on the one hand, the amount of business data is increasing. On the other hand, the improvement of system performance helps to greatly reduce the response time. For modern artificial intelligence systems, the correct construction system can help enterprises rapidly expand technology. infrastructure. Of course, whether it is an individual or a business, the above five characteristics have played a pillar role in the development of artificial intelligence in the past four decades, and it is also the focus of all artificial intelligence systems. Lei Feng.com will continue to pay attention to the important role of artificial intelligence in all walks of life. For details, please pay attention to the corresponding public number or sub-section.
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