Since the 1990s, the term Big Data has been mentioned by people. Big data has developed rapidly and is affecting our lives more and more deeply. Artificial intelligence was found at the Dartmouth Summer Research Project on Artificial Intelligence in 1956. The concept and development goals of artificial intelligence have experienced several heartbreaks. But today, AlphaGo can beat human top players on the Go board.
Artificial intelligence is entering a rapid transition from theory to reality, which will greatly improve our quality of life. As an engine of big data, artificial intelligence is accelerating the implementation of deep data application services. In the era of massive connections in which the Internet of Everything data is exploding, we believe that companies that have mastered artificial intelligence and big data-related technologies will become the wave of the times.
The Birth of the Concept of Big Data
The concept of big data is not new, and it has been frequently mentioned in the 1990s. But the concept of big data has become hot again in recent years, because it was thrown out again in the EMC world 2011 conference on the theme of Cloud Meets Big Data led by EMC in May 2011. In May of the same year, McKinsey published a related research report, and the concept of big data became hot again. So what is big data? Big data has a lot of technologies and different directions, so different people can have different perspectives. For example, massive data calculations, difficult and complex data analysis, etc., these may be characteristics of big data.
What is Big Data?
So let’s introduce what big data is. There are two popular definitions of big data. The first is what Gartner said.
Big data requires a new processing mode in order to have stronger decision-making, insight, and process optimization capabilities to adapt to massive, high growth rate and diversification of information assets.
— Gartner
This concept expressed a very important meaning. Big data has now become an information asset. In the era of big data, we need new processing models to process these information assets. Because the original processing mode cannot deal with these data within the required time or accuracy requirements.
Another concept is summarized from the characteristics of big data. McKinsey summarized the four characteristics of big data with massive data scale, fast data flow, diverse data types, and low-value density. That is what we usually call the 4V characteristic of big data. IBM later added the fifth characteristic, and thus formed the definition of big data, which is the 5V characteristics of big data that is relatively common in the industry. Let’s take a look at what is called 5V characteristics one by one.
Volume
The first V is a large amount of data, so in the era of big data, the magnitude of the data to be processed is very large. Currently, this magnitude is usually used for data analytics and mining on the terabyte level.
Velocity
The second characteristic is called fast processing speed. It used to take weeks, months, or even longer to process the data to get the results, but now we need to get the results in a shorter time, such as minutes or even seconds.
Variety
The third characteristic is called multiple types of data. The data that we could process before was usually structured, that is, two-dimensional tables. But in the era of big data, more diverse data types need to be processed, there are structured, unstructured, and semi-structured data. These data must be processed separately or even mixed by big data technology.
Value
The fourth characteristic is called a low data value density. The amount of data is very large, but there is not much data that is valuable to us. These data are submerged in the vast ocean of data, so the value density of its data is relatively low, which means that I need to filter and mine in hundreds of millions of data, but I may only get dozens or hundreds of useful data.
Veracity
The fifth characteristic is relative to the fourth characteristic. What veracity said is that the value of commercial value is high or more real, that is, the value of the data that is mined is very high, whether it is directly decisive for our decision-making, insight, or process optimization. So it’s more straightforward.
These 5V characteristics of big data tell us that today’s big data refers not only to data but to data plus a series of processing techniques. We need to find and mine the part of data that is valuable to our work in a very short time from a large amount of data so that we can make decisions or optimize for the work. The whole process is called big data.
What is Artificial Intelligence?
Artificial intelligence is a new technical discipline that researches and develops theories, methods, technologies, and application systems for simulating the extension and expansion of human intelligence. The goal of artificial intelligence research is to let machines perform some complex tasks that require intelligent humans to complete. That is, we hope that the machine can replace us to solve some complicated tasks, not just repetitive mechanical activity but some that require human wisdom to participate in it.
So let’s see what artificial intelligence can do.
Image Recognition
Image recognition is now widely used in our lives. For example, the identity of a person can be identified based on photos or when a person’s face is captured with a camera. In many train stations in cities of China, you can swipe an ID card, the machine collects a face image of you with a camera, and then identify and verify your identity. Some building access control uses image recognition for identification, you no longer need an access card or a key. Other applications include advanced human-computer interaction, video surveillance, automatic indexing of images, and video database, among others.
Speech Recognition
Speech recognition provides a faster and more convenient way for us to interact with computers. When we speak to the computer, it can know what we are talking about and interact with us. This method is completely different from what we used to type on the keyboard. This way of interacting with the computer can bring us many extended applications. Virtual assistants like Siri, Google Assistant, Alexa can perform tasks or services for an individual based on commands or questions.
Self-Driving Car
Autonomous driving or self-driving car is also very popular in the field of artificial intelligence. Google’s Waymo has already started commercial self-driving car service called “Waymo One”. Chinese Internet companies also successfully tested autonomous driving on the Fourth Ring Road in Beijing. Now there are also some advanced cars with modules for autonomous driving.
With the emergence of 5G technology, I will believe that this technology will revolutionize the way we travel in the future. C-V2X, the Cellular V2X (vehicle-to-everything), is a communication technology using the same 5G network. It allows vehicles to communicate with each other wirelessly and also with other transport infrastructures such as traffic lights, roadside, etc.
Conclusion
Big data and artificial intelligence are two important branches of computer science today. In recent years, research in the fields of big data and artificial intelligence has never stopped. Big data is inextricably linked with artificial intelligence. First, the development of big data technology depends on artificial intelligence, because it uses many artificial intelligence theories and methods. Secondly, the development of artificial intelligence must also rely on big data technology; it requires tons of data for support. Technology innovation has just begun, and there are more new technologies that we need to keep learning.
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