What Challenges Does the Development of Strong AI Face?
Several companies have implemented new technologies to improve their products and services. These technologies have also allowed organizations to innovate in the market. They have changed not only the market but also the world as we see it. Artificial Intelligence (AI) and machine learning are also reshaping the world, but they have been facing limitations.
Organizations have been looking for skilled tech talent that can help them overcome development challenges. For that reason, employers’ job offers are now more attractive than ever.
AI has been applied in fields like web development and mobile development to allow systems to gather and analyze data. This is because data is today’s most valuable resource, and companies have realized what they can achieve with it.
Every technology indeed has to face challenges to its improvement. For that reason, here are some hurdles AI needs to overcome to achieve its greatest potential.
Lack of People Power
A few years ago, AI was considered something we only saw in movies. However, it’s no longer a fairytale. Thanks to tech professionals like Web Developers, Data Scientists and Software Engineers, it’s been possible.
At the same time, AI was not a big deal of money until companies realized what it could achieve. After realizing AI’s potential, major companies like Google and Facebook started to invest vast amounts of money on its improvement. These companies have been able to develop exceptional products like smart chatboxes and smartphones with facial recognition features.
Also, educational organizations like Springboard now offer courses where people can learn AI and machine learning skills. Nevertheless, as we are still in the middle of a tech transition, there is a lack of people power.
There are not enough tech professionals that can help companies unleash their AI-powered vision. Under those circumstances, the improvement of AI technologies has slowed down. Nonetheless, many companies are working together to find a solution that could remedy this situation.
Lack of Computing Power
Machine learning algorithms make numerous calculations within seconds. The same happens when AI is implemented. As a result, great processing power is required. As days pass, users keep generating more and more data. For that reason, organizations will need better devices that could help them process all that information.
In the same way, more complex algorithms are being used. They allow tech professionals to analyze data more efficiently. But, they will still be bottlenecks as companies require even more skilled tech pros.
On the other hand, the tech market is continually evolving. For example, years ago, holding a powerful CPU in your hand was unthinkable, but today it’s possible thanks to the evolution of the smartphone. Mobile Developers take advantage of portable CPUs to develop efficient applications. The next-generation of computing infrastructure will solve the computing issues we are facing these days.
AI indeed has huge potential. However, the majority of its implementations are specialized. As a result, today’s algorithms are only allowed to become better at just one task. In other words, one algorithm can only carry out one task. Smart cars that use AI to learn how to drive themselves learn only how to drive, becoming better and better at it.
In the same way, the machine learning algorithms used by Netflix, for example, learn what content you like to watch and make recommendations based on it. Nevertheless, these algorithms don’t carry other general tasks like setting specific content for specific schedules during the day.
Generalized AI that powers robots or systems to carry out tasks is still a dream. On the other hand, the future is promising as more companies keep investing in AI. For that reason, it will take just a little more time for AI to achieve its greatest potential.
AI algorithms need users’ input to learn from experience. No matter how good an algorithm is or how well the software is developed, a system is useless without input. With this in mind, it’s crucial to point out that most users are concerned about AI.
This is because AI algorithms use people’s information to improve. For that reason, users feel that their lives are being compromised. In the same way, AI makes predictions on things people don’t understand. As a result, they are uncomfortable using AI-powered products. Given these points, AI development has been slowed down by the lack of user trust.