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Comparing five artificial intelligence development languages, which one is better?
Comparing five artificial intelligence development languages, which one is better?
Artificial intelligence in our country has developed strongly in recent years, and we have achieved good results in many fields such as face recognition and medicine. But in addition to higher requirements for hardware such as GPUs, the development capabilities of programmers are also increasing day by day. How to choose a suitable development language is also a top priority.
Artificial intelligence can be seen everywhere in our lives. This is mainly because it faces changing needs in different environments and scenarios through single or composite Solutions and algorithms can help us solve problems.
In the past few years, different friends around me have been talking about #artificial intelligence#. We are all software developers, and we also feel that the change in development language has enabled artificial intelligence to move forward.
The rise of artificial intelligence has also placed higher requirements on programmers, and the demand has also increased significantly. In the early days, I remember that when I was a similar artificial intelligence engineer, I could earn about 30K in Beijing. When facing personnel recruitment, they spoke some artificial intelligence development languages. This may be the reason why the editor has not read books for a long time. He just pretended to be calm and felt his own shortcomings at the same time.
Let’s talk about the characteristics of commonly used artificial intelligence program development languages.
Python
Python was released in 1991. If it weren’t for the artificial intelligence in the past few years, I’m afraid it would still have to wait a while before it would become the more popular development language it is now. Now 59% of artificial intelligence software development engineers are using this development language. Instead of choosing C, which has the best performance in the world. I think there are several reasons:
- Simple and easy to use, conducive to dissemination
- Phthoe is positioned as an artificial intelligence development language
- A large number of algorithm libraries
- Easy to develop, improve development speed and save development costs.
- Perfectly combined with JAVA, with JAVA as a big help behind, everything goes smoothly
LISP
LISP is the best language behind Fortan, but because It was developed for artificial intelligence in 1958. It has fallen behind slightly after iterations of modern technology. LISP has some minor flaws, and is mostly used for logical operations. But it is an early positioning of artificial intelligence, so it should have a place.
R Language
R language was released later than LISP in 1995. It is actually another upgrade to the S language. Mainly used to generate statistical systems and data analysis systems, R language has relatively high operating efficiency, making it a king within a certain date. It has good support for Gmodels, RODBC, OneR, and Tm. The combination of multiple solutions can solve complex problems.
C
As for the C language, the first time I came into contact with it was a strange demand from a customer, who asked for it to be decompressed and used. System plug-ins are not allowed to be installed. At that time, I decisively chose C. If we talk about processing speed, C is definitely the strongest among the strong in terms of performance. Especially for artificial intelligence, higher running speed is required. However, because C has relatively few related class libraries and its syntax is complex, it is not used by some small companies, and the cost is too high. But he has strong support for OPENCV and other aspects.
JAVA
JAVA is a development language that evolves with the times. Early open source ideas promoted the generation of a large number of open source frameworks. Rather than writing JAVA language, it is better to say that I am growing up after learning various frameworks and understanding the ideas of the masters. But for AI, JAVA has some shortcomings. It dares to use VM virtual technology, which has become a shortcoming in processing speed that is difficult to deal with.
Summary
For artificial intelligence projects, the above list is the best 5 development languages. It can only help you have a reference when choosing a development language based on your own situation. In fact, once you know one language, it is easy to learn other languages.
I also hope that the artificial intelligence in the motherland can develop very well and make our motherland a real technological power. Let the beautiful country also learn what respect means.
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