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5 Challenges Faced By The Artificial Intelligence Industry

Srikanth by Srikanth
November 15, 2020
in Artificial Intelligence
Reading Time: 4 mins read
5 Challenges Faced By The Artificial Intelligence Industry
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We know how the artificial intelligence field is growing which is also creating major changes in our lifestyles, day by day many things are getting better and with the help of this technology, we humans are getting more closer to the machines, the sci-fi movies that we used to watch with trill is going to become the reality soon and we are going to move in the robots era where every machine will able to understand us and our requirements. Apart from this, the major role will be played when they will be customized for the each one of us we will be bind without own device which not only solves some technical issues of our but also helps us to become the better human in nature. But also have to keep in mind that this can also be destructive if it is command by the destructive person.

Creating a machine that can understand the natural language and act naturally similar to human nature is tough but still everyone is working to make this sci-fi theories true which helps human beings to make their life easier then now, though the development we are seeing on the daily basis is worth appreciable as many of the challenges and failures are being faced by these technology developers and researchers but still they are getting together and solving this problem. some of the common challenges that are faced by the AI industry is listed as follows

1) Data should precise

For the better development of the machines, the data that are collected to do the predictions, as well as some calculations, should be precise and correct as it can affect the performance of the machine, not only that but noisy data can also create errors during computation and working.

Artificial intelligence is based on the more precise data will get you better output, here the quality of the data should be good so that there are fewer chances of getting false predictions and we know how much it is important to get the truthful output. So to have the exact outcome of your input it is necessary to collect proper data apart from this it is difficult to collect the precise data as it may vary from sources to sources.

2) Security is not maintained

The main challenge that currently the whole industry of artificial intelligence is facing security as we know that input will be given over the network only and there are more chances of the input violations through the network. So to avoid this many cybersecurity analysts are working on this and this is one of the challenges for them also.

For example, we know that smart cars would be in the market very soon and they are also using one of the forms of artificial intelligence and thus while giving the instruction to it, it will pass on the command over the network which can be hackable and modifiable so while doing this it can create any critical situation. so to avoid this type of the hackable security is the major concern for the artificial intelligence developers as well as industry

3) Technology is Algorithm-based

We know that Artificial intelligence is mainly based and work on the different types of algorithms so it becomes difficult to understand how the algorithm is working and only some of the human have the knowledge about the algorithms and calculations due to this some of the developers of the artificial intelligence also faces difficulty in developing.

As well as in selecting that what type of algorithms can be used for which task and this is only done by the experts as they have already gained some experience while developing, as they have to integrate more than one algorithm together for every specific task this increases the complexity of the programs which affects the computation speed over the network as it takes more time to execute the program.

4) Lack of human power

Artificial intelligence is a new field with some complexity so it becomes difficult to understand and learn the things over here, thus many people don’t prefer to learn Artificial intelligence and thus we have limited number of the knowledgeable people in this field due to this there is the lack of human resource over here.

Apart from this it takes time to learn the deep learning and Artificial intelligence concept and become expertise in them few of the people are experts in this field and we need more of them because artificial intelligence needs more experience for which algorithm should be used and from which techniques you can get more precise data that can be used for and which type of prediction should be done over here.

5) Less computation speed

Due to many algorithms used here together with the complexity of the programs increases and thus while getting the predictions or any type of output, the processing is done after the input is given over the network also takes time.

Thus the computation speed lacks apart from this many of the artificial intelligence applications need internet connectivity and due to less speed of the internet, the computation time also increases but after the 5G will available in the market the speed of the computation will increase and will result in speedy and accurate outputs.

All in all, artificial intelligence is still facing some of the issues which are listed above and the industry is still trying to solve this problem while researchers are researching about the new scopes that can be used for the artificial intelligence technology. Not only that, but we can also say that the new era will almost have artificial intelligence in all sectors and in new different ways.

Concluding, as we know all the technologies have its own pros and cons with the challenges in them, every industry has their own challenges and they try to overcome it similarly only even the artificial intelligence is also facing this problem and simultaneously finding the solutions for it.

Tags: AI NewsData privacy
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