Top 10 Artificial Intelligence Technologies To Look For In 2019

Top 10 Artificial Intelligence Technologies To Look For In 2019

As we all know the world, in general, is vast increasing in terms of technology, and Artificial Intelligence is not excluded. There has been extensive progress in 2018.

I want to believe that personally, you have noticed all kinds of subtle uses of Artificial Intelligence Technology (AI). For example the transcription of your voice mails, the Gmail response prompter, automatic voice calls, and self-driving cars on the roads of Utah.

In this article, we want to consider Top 10 Artificial Intelligence Technologies To Look For In 2019.

1.Reinforcement learning:

Reinforcement learning

The most common form of machine learning is supervised and unsupervised learning. Reinforcement learning is different from these two forms of learning. The use of it is presently very limited. AlphaGo and some robots use it. But many companies and industries are experimenting with it in 2019 and will explore the use of it.

it is a structure that uses experience-driven sequential decision-making. This method communicates with the environment to learn and move towards a goal that rewards the actions taken.

2.Ethics in AI:

Ethics in AI:

In 2018 there have been many tremendous presentations on intelligent systems being designed in a manner that imitates individual, community and society’s ethical values.

Ethics in AI is only going to increase in 2019. IEEE global initiative on ethics of autonomous and intelligent systems, make it clear that policy or standards will be built on legal accountability, transparency, policies, embedding values into AI applications and governance frameworks.

3.Quantum Computing:

Quantum Computing

quantum computing would just be pushing a little in the right direction towards building better quantum computing devices in 2019. Although it would be a small increment. There will be a huge focal point in the area of AI.

Quantum computers use quantum physics to compute calculations faster than any supercomputer today. We are well aware of how computers use bits and bytes. However, unlike a regular computer, quantum computers use qubits (Quantum bits) to store information.

In 2019 a lot will be a focus on the challenges. Such as maintaining the coherence of the qubits or removing the unnecessary and noisy computations. Solving almost the unsolvable problems like climate change, the presence of Earth-like planets in the galaxy or our body’s ability to destroy cancer.

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4. Convergence of AI and other emerging technologies:

 Convergence of AI and other emerging technologies

2019 would see more examples of the convergence of AI with IoT and AI with Blockchain. In fact, self-driving cars is not a practical possibility without IoT working closely with AI. The sensors used by a car to collect real-time data is enabled by the Internet of Things (IoT) and the programs used for decision-making is powered by AI models.

Deep learning AI algorithms then take action as well as make decisions using this data. But the challenges with these cars is the ability to communicate with each other so that traffic as a whole is optimized.

There is a challenge too in terms of  Blockchain and AI too. Blockchain has challenges such as security and scalability and AI suffers from privacy and trust issues which  will be definitely looked upon in 2019

5. Facial recognition:

Facial recognition

Facial recognition has received a lot of negative results recently. However, this technology would continue to grow in 2019.

Facial recognition is a form of artificial intelligence application that helps in identifying a person using their digital image or patterns of their facial features. 2019 would see an increase in the usage of this technology with higher accuracy and reliability.

6. Biased data:

Biased data

This topic is becoming increasingly important as machine learning models are being used for decision-making such as hiring, mortgage loans, prisoners released from parole or the type of social service benefits.

Amazon is reported to have scrapped internal hiring tool that increased bias against hiring women. Some of these biases are conscious while some are unconscious due to data that is used for training. This will be taken care of in 2019.

7. Neural networks:

Neural networks

To put it briefly, neural networks or artificial neural networks imitate the human brain. They store all data in a digital format — sensory, text or time and use it to classify and group the information.

However, there is a huge demand for improvement in neural networks such as order fulfillment, prediction of the stock market, and diagnosis of medical problems or even to compose music!

The current neural network technologies will be improved upon in 2019. This would enhance AI to become more sophisticated as better training methods and network architectures are developed.

8. Socio-economic models:

Socio-economic models

There has been a lot of discrepancies when it comes to Socio-economic models. Everyone is contemplating “would AI take away our jobs?” and the answer, in a nutshell, is “it depends”. But even if it does the interesting part is that it would also enable newer jobs with different skillsets.

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It will drive new skills and new jobs, for high-touch jobs such as customer service representatives, teachers, caregivers etc. In 2019.

9. Deep learning:

Deep learning

Deep learning is the most popular form of AI algorithms, it is also the technology behind self-driving cars, voice control as well as image recognition. There is a range of voice-enabled applications that use natural language processing algorithms.

But there is a challenge when the number of dimensions of data increases. However, in 2019 there is a deep interest in deep learning algorithms that can solve even tougher problems such as interpreting technology infrastructure issues

10. Privacy and Policy:


The introduction of GDPR was a much-talked topic in 2018. 2019 would see further privacy and policy conversations. This is important in order to protect our privacy and ensure organizations approach data privacy earnestly.

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