In 2018, we all experienced a dramatic emergence of the tools, platforms and applications based on Artificial Intelligence and Machine Learning. These technology tools not only transformed the internet and software industry, but it also had a massive impact on a wide range of verticals, including manufacturing, health, agriculture and automobile.
AI-related and ML technologies will continue to grow in 2019 and the coming years. Organizations such as IBM, Facebook and Google are investing a lot of money and time in development and research of AI techniques to offer benefits to the users.
Most of us wonder what transformation will AI bring in 2019. From the Gmail email response prompter to transcription of voicemails, automatic appointment calls, Alexa for smart homes and self-driving cars on the road, we had witnessed a lot in 2018. But the question is what changes are we going to experience in 2019 and 2020..
We shall discuss some of the fantastic Artificial Intelligence trends to watch. Following are the artificial intelligence trends to watch out in 2019:
1. Introduction of AI-enabled chips
The AI model requires additional hardware to solve complex mathematical problems to increase the speed of tasks, like facial recognition and object detection.
Chip manufacturers, including NVIDIA, ARM, Intel and Qualcomm will deliver specialized chips to enhance the speed of AI-based applications.
AI-enabled chips will be designed for particular use cases and scenarios related to natural language processing, speech recognition and computer vision. Industry-grade applications will soon depend on these chips to provide intelligence to consumers or end-users.
2. Facial Recognition
But, this technology will continue to grow in 2019. Facial recognition is an AI-based technique that is introduced to identify an individual using patterns of their facial features and their digital image.
2019 would witness an increased usage of facial recognition technology with high reliability and accuracy. For example, Facebook’s Deepface program is used for tagging friends and family in photos. Also, almost every smartphone now come up with a face lock.
From advertising to shipping experience, facial recognition will continue to be used for biometric identification. Due to non-invasive identification and ease of deployment, this AI technology trend will continue to rise.
Other use cases of Facial recognition include payment processing via security checks and law enforcement. The upcoming facial recognition techniques can also be used in the healthcare industry for clinical trials and medical diagnostics. Openwater, one of the portable medical imaging technologies, is breaking the boundaries that can read images from our brain.
3. The convergence of AI and IoT
For instance, the concept of self-driving cars would not have become practical without the combination of AI and IoT. IoT-enabled sensors collect real-time data and AI models power decision-making programs.
IoT is ready to become the significant driver of artificial intelligence in the enterprise. Edge devices will be equipped with AI-enabled chips based on ASICs and FPGAs.
4. Socio-economic models
While artificial intelligence will take away jobs where resources will be scarce, it will also bring newer jobs with multiple skillsets.
No matter what is the answer, the topic is under discussion by various governments and the World Economic Forum. It is because the rise of AI applications will have a risk of widening skills gap and can create polarized societies.
Though automation may eliminate the need for jobs, there will always be a demand for jobs like teachers, caregivers, customer service executives and more.
Redistributive programs will be the focus of attention for lawmakers in 2019.
5. Interoperability among neural networks
After a model is trained and assessed in a particular framework, it is difficult to port the trained model to another framework. It happens due to the lack of interoperability among neural network toolkits. To overcome this challenge, Facebook, Microsoft and AWS have partnered to develop Open Neural Network Exchange, that allows reusing trained neural network models across various frameworks. It will become a crucial technology for the industry in 2019.
6. Automating DevOps via AIOps
After machine learning models are applied to such data sets, IT operations can transform from being reactive to predictive. When the potential of Artificial Intelligence is applied to operations, it will reconstruct the way infrastructure is handled. The application of AI and ML in DevOps and IT operations will offer intelligence to companies. It will help the ops team conduct an accurate and precise root cause analysis.
It is the reason why AIOps will become a focus in 2019. The convergence of AI and DevOps will benefit both enterprises and public cloud vendors.
7. Automated Machine Learning Models
When using AutoML platform, business analysts can stay emphasized on the business problem rather than getting lost in the workflow and progress.
The platform can fit between custom ML platforms and cognitive APIs and deliver the right level of personalization without requiring developers to go through the complete workflow.
8. Deep Learning
However, deep learning is a technology behind self-driving cars, image recognition and voice control. With the emergence of both Google Home and Amazon’s Alexa, you may find a wide range of voice-based applications using natural language processing, an application of Deep Learning.
Therefore, we can witness increased interest in the next-generation of deep learning algorithms which can overcome complex problems, for example, interpretation of technology infrastructure issues.
9. The convergence of AI and Blockchain
As we all know that the blockchain deals with challenges like scalability while AI has trust and privacy issues, these two technologies can be combined to resolve these challenges.
Powering decentralized marketplaces, blockchain can help AI algorithms to become more trustworthy and transparent. For instance, Enigma is a startup that provides a secure data marketplace that users can subscribe and access via smart contracts.
10. Policy and Privacy
Most of us do not know how our digital information is being used over the internet. Facebook’s crisis over privacy has led to consciousness regarding the privacy of digital data.
From the AI trends mentioned above, it can be concluded that AI is not going to witness a decline any time soon. We will continue to see new AI trends with each passing year.