The year 2018 already witnessed a major surge in platforms, tools as well as application-based AI or Machine learning. This increase in the use of technology has a huge impact on several aspects, such as healthcare, manufacturing, pharmacy, automobile as well as agro-industry.
So, what will you expect in the current year? More advancement of ML and AI-related technologies in 2019 and beyond. Organizations like Amazon, Apple, Google, Facebook, etc are investing in the latest research on AI.
With this, AI is here for you with its brand new advancement. And thereby, gets closer to the consumers with the passage of time.
Therefore, let’s delve into the latest AI trends that you can go for in 2019.
Astounding Features that you Should Look for
The following are the best trends of AI that are worth chasing for. So, let’s take a look into these.
Increase in AI Activated Chips
AI depends on specially built processors that work with the CPU. The fastest and advanced CPU might not enhance the training speed of the AI model.
While integrating, the model requires surplus hardware to carry out complicated mathematical calculations to optimize certain tasks like detection of the object as well as face recognition.
In 2019, reputed chip producing corporates like Intel, NVIDIA, AMD, ARM, etc will transfer specially built chips that enhance the execution of applications powered by AI.
These chips are meant for particular purposes, cases, and scenarios pertaining to computer vision, voice recognition, as well as natural language processing.
Upcoming applications coming from healthcare and automobile domain will depend on these chips in order to provide a high-quality experience to the end-users.
2019 is the year where reputed corporates like Amazon, Google, Microsoft, etc will enhance the investments in the custom chips. And, these are on the basis of the application-oriented integrated circuits as well as field-programmable gate arrays.
These chips will now be used in order to perform modern workloads on the basis of AI and high-performance computing (HFC).
Some of the chips will also help the upcoming generation databases to enhance the processing of query and forecasting analytics.
An Amalgamation of AI and IoT at the Edge
Industrial IoT is at the peak for artificial intelligence that can carry out several functions like outlier detection, analysis of root cause, as well as maintenance of the equipment.
Advanced versions of ML models work on the deep neural networks that will be enhanced to make it compatible with an edge.
They are helpful in dealing with speech synthesis, video frames, time-series data powered by gadgets like microphones, cameras, and many more.
Therefore, IoT is ready to become the largest driver of AI in the grooming enterprise. Edge gadgets are built integrating specially built AI chips on the basis of FPGA and ASIC.
Interoperability Among Neural Networks Becomes the Focal Point
One of the biggest challenges in creating a neural network model is to select the correct framework. Therefore, it is in the hand of data scientists and developers.
They need to choose the correct tool from myriads of choices comprising of Caffe2, PyTorch, Apache MXNet, Microsoft Cognitive Toolkit, TensorFlow and many more.
When the model works on a particular framework, it becomes really cumbersome to port that one to another framework.
The deficiency of interoperability among several neural networks is damaging the usage of AI. To counteract this challenge, AWS, Microsoft, Facebook is working on a joint venture to create Open Neural Network Exchange(ONXX).
It is therefore viable to reuse the trained neural networks throughout several frameworks.
The year of 2019 will see ONXX as one of the remarkable technology in this industry. Beginning from researchers to the edge device manufacturers, each and every player of the eco-system will depend on ONXX as a generalized runtime for the purpose of inferencing.
Automatic Machine Learning is Gaining Grounds
One trend that is going to modify the image of the ML-based solution is the implementation of AutoML. This will help the business analysts as well as the developers to build the machine learning models.
Moreover, this will also take into account the complicated scenarios without carrying out the arduous process of training ML models.
While handling AutoML platform, business analysts are concentrating on problems of business instead of getting bemused in the workflow.
Therefore, AutoML is the best fit among cognitive APIs and custom ML platforms. It comes with a proper form of customization without compelling the programmers to perform the outright workflow.
Cognitive APIs implies black boxes. However, AutoML is available with the same sort of flexibility with the slight modification of custom data as well as portability.
AI Automate DevOps Using AIOps
You can use modern gadgets and infrastructure in order to produce log data with the intent of indexing, searching as well as for analytics.
The enormous data sets come from hardware, Operating Systems, as well as server software. They are segregated and correlated to get through proper insights as well as patterns.
You can implement Machine learning to data sets. But IT operations undergo a huge change from being reactive to predictive.
The Applications of ML and AI in IT operations and DevOps comes with intelligence. Therefore, you can implement this in several corporates.
This will helps the ops team to carry out concise and perfect analysis of root cause.
AIOps will reach unparalleled success in 2019. The public cloud vendors and enterprise will be going to take advantage of the unique blend of AI and DevOps.
Logistics Becomes Increasingly Efficient
We are entering into a whole new world where it is feasible to cover 20,000 sq ft distribution center with the help of skeleton crew.
Kiva Systems in collaboration with Amazon Robotics implements a combination of AI and advanced robotics comes with big-box retailers with unparallel solutions of logistics.
Warehouse of the future will undergo a huge change. They will be designed in order to accommodate human packers. Moreover, they will build efficient robots that will work round the clock.
Therefore, you don’t require lighting to view what they are performing.
Creation of Content Using AI
Different brands are using AI technology to build meaningful content.
There are certain organizations that come with a SaaS platform. It permits publishers to change written content into a video one using AI video production.
Publishers are striving for hours to make content for their websites using social media. Within a fraction of seconds, you can help the publishers to create awesome videos using certain tools.
Also, other organizations are implementing natural language generation in order to build news stories on the basis of earnings data.
Therefore, this current year will see a lot of media companies adopting the natural language and video creating technologies.
Peer-to-Peer Networks Creating Transparency
Machine Learning is a special kind of Artificial Intelligence and organizations.
Using this, Facebook is constantly implementing a statistical model to help the machines to take firm decisions about the content that will show up next.
To make the model function properly, they need an enormous amount of data and proper computing ability.
With the increase in peer to peer networks, similar to the cryptocurrencies, the small scale enterprises have the power to run advanced AIs by leveraging the cumulative power of personal PCs.
The Demand of Data Scientists Exceeds the Demand for Engineers
As per the latest report, the growing demand for data scientists is increasing at a tremendous rate. Do you know the reason behind this?
With the help of Machine Learning, AI implements probability to detect the proper answer or decision to any given problem.
With the increase of data in the machine learning domain, the platforms will become more viable to carry out certain predictions.
AI to Overpower IT Strategy in the Near Future
We are entering into a far-fletched advanced. Here, peer-to-peer network of computers has the ability to resolve the most challenging tasks within minutes.
AI has a tremendous impact on preventing certain health problems through the accumulation of human molecular data.
Therefore, follow this informative guide to know the latest features of AI and how this will impact the modern civilization in this year of 2019. So, stay focussed and go through the trends mentioned in the blog that will ultimately pave the path of exuberance.