Artificial intelligence is shaping in different directions every day. It’s spanning into platforms, tools, and applications. AI is the new bride for major tech giants attracting huge spendings in the form of investment.
At the same time, this technology is becoming more affordable by the day and growing in its uses. AI is now a special interest in trading, asset management, healthcare, manufacturing, automobile, sales, marketing, and so on.
Considering AI opportunities that lie ahead of us, here are some of the valued expectations:
Business Communications Using AI
AI for Video and Voice Calls
With the use of AI for business communications, human interaction between clients and customer service or sales representatives will experience new capabilities.
AI-enabled communications will positively reflect on call center performance, customer satisfaction, and generated revenue.
Voice and video contents can be analyzed in real time allowing enterprise users to get interpretations to even non-verbal cues.
For this, image and speech recognition and analysis algorithms will be on the front row. Data queries will be faster to reply, there will be increased efficiency and productivity, business communication will be more sophisticated.
AI Smart Features for Meetings
AI-driven features are essential for better convenience in business meetings. They are good tools for increasing productivity and user experience.The use of AI will make video and call conversations even productive than in-person meetings.
Practical use of such AI smart features includes speech-to-text transcription for:
- Making meeting notes
- Highlighting the key points
- Recording tasks
- Setting up meetings with a help of a virtual assistant
- Identifying participants of a meeting and providing relative information about them.
Artificial Intelligence for Healthcare
Healthcare solutions are becoming more effective with the use of AI. This is made possible by training machines to learn and carry out clinical and administrative duties. With human supervision, AI will help to achieve precision medical services.
Diagnostics by using images, robot-surgeons, digital consultations, personal medical experience, health predictions and monitoring with the use of wearable devices, etc. are possible industrial applications of AI in healthcare.
People will trust AI more in health matters, and the technology will help human professionals to make the best decisions. Medical data reports analyzed by AI and intelligent tools will be the instruments for more progress in healthcare.
The Union of AI and IoT
The use of Machine learning and Big data will be a smooth facilitator for the Internet of Things. The connections and communications between billions of devices will make real-time data more available to enterprise systems for analysis by AI.
Streaming data collected by IoT will become more effective. It will also be easier to class algorithms based on the data types they can accept, their similarities in structure, and the fraction of processed data with time data records. Metadata and logic execution by IoT devices will be useful in Machine learning and the training of other forms of AI.
AI will also help in outlier detection, to run root cause analysis and predictive maintenance of IoT devices. Advanced ML models built on neural networks will enhance running on Edge. These ML models will be more compatible with structured data such as video frames, speech synthesis, time-series generated by microphones, cameras, and sensors.
Automation of DevOps through AIOps
The automation of DevOps through AIOps will become mainstream and change the management of IT infrastructure. It will make the root cause analysis faster hence solving a task with taking a shorter time interval.
IT operations will move from reactive to being more predictive. This is a piece of great news for cloud vendors as they are benefactors.
There are tons of data sets harvested from operating systems, hardware, application and server software. These generated data sets are essential for searching, indexing, and analytics. They can be summed and compared for correlation and similar patterns by application of Machine learning models.
Open Source AI and Neural Network Interoperability
The ease of using AI is on the rise with the introduction of open source AI solutions by Tech giants such as Google, Apple, Tesla, and NVIDIA.
Open source in AI is becoming even more promising because more companies are interested in sharing knowledge and make AI stacks available. This will be the next step of AI evolution and will create empowerment for a better AI community with wider support.
Selecting the best frameworks for neural networks is a big challenge. This is due to the fact that once you select and train a specific AI model, it is difficult to change the framework of that AI to use another tool.AI adoption rate will boost with enhanced interoperability among neural networks. Click To Tweet
AWS, Facebook and Microsoft have already built an open ecosystem for interchangeable AI models called ONNX – Open Neural Network Exchange.
Microsoft Cognitive Toolkit, Caffe2, Apache MXNet, and PyTorch are all supporting the Open Neural Network Exchange. Developers can easily train models in frameworks supported by ONNX and get ideas into production faster.
More AI-Enabled Chips
For AI to make an instant inference especially in large data types like object detection and facial recognition, it must execute algorithms with great speed. In order for AI to perform complex computational analysis, it needs specific processors to enhance the CPU. This is because the training speed of an AI model is somewhat not dependent on even the most sophisticated CPU.
Leading chip manufacturers are working on special chips with high execution speed for AI applications. The design and nature of these chips are specific for use cases tied to speech recognition, computer vision, natural language processing and more.
More investments in custom chips based on ASIC and FPGA are expected from tech giants such as Google, Amazon, Microsoft, and Facebook. Special chips will be manufactured for operating modern workloads based on AI and high-performance computing. A fraction of these chips will also empower next-generation databases to hasten predictive analytics and query processing.
The insight into what is expected from AI as listed above is a result of considering all the AI trends and industry reports until 2018.
We will see more applications in areas of autonomous transports, automatic text and art generation, computer vision etc. Smartphones will also acquire more complex behaviors with AI voice assistance, optical character recognition, and more.
With so many opportunities, AI specialist are getting listed among the most highly demanded and payed professionals today.
Velvetech is consistent in AI solutions provision and creation of tech innovations. Reach out to us for consultations today.