Responsibilities of an AI Engineer's:
1.Convert the machine learning models into application program interfaces (APIs) so that other applications can use it.
2. Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what result they gain from the model.
3. Build date ingestion and data transformation infrastructure.
4. Automate infrastructure that the data science team uses.
5. Perform statistical analysis and tune the result so that the organization can make better - informed decisions.
6. Set up and manage AI development and product infrastructure.
7. Be a good team Player.
The Emerging technology in Artificial Intelligence :
Emerging technology in artificial intelligence are:-
1. AI - enhanced Analytics Solutions :
i) This category helps to organise the customer, journey and experience.ii) This system can understand the customer learn, performances, predict next best action/solution, and surface insights.
iii) This is a top priority area for the contact centre as AI enhanced analytic solutions can deliver new and stronger business benefits.
2. Deep learning (DL) :
i) DL is a type of machine learning algorithm that has the ability to generate better Predictions/insights, scale up with large data sets, and reduce the effort to build the model.
ii) In the contact centre DL is used in conversational system (speech recording NLG, NLU, etc), speech analytics, and other areas.
3. Natural language generation NLG :
i) NLG is a part of the Tech stack in conversation systems.
ii) NLG used advanced AI algorithm to generate speech from text.
iii) NLG used to generate speech in Alexa, in virtual assistant and in a natural language IVR.
iv) NLG is used as a part of the Smart Care conversational and platform that Powers lVR and chatbot channels.
4. Speech Analytics:
i) Speech analytics used AI technology to recognize speech, convert speech into text, and perform analytics on the text data set.
ii) This technology is used in many contact centers to improve customer interactions, and agent performance.
5. AI for cyber - security applications :
i) Artificial Intelligence and machine learning technology is increasingly finding it way into cyber security system for both corporate system and home security.
ii) AI and machine learning Technology can be employed to help identify thetas, including variant of earlier threats.
iii) AI powered cyber security tools can collection data form a company's transactional systems, communication networks digital activity and websites, as well as from external public source, and utilize AI algorithm to recognize patterns and identify threatening activity.
iv) In home security system is integrated with consumer video cameras and intruder alarm system integrated with a voice assistant.
6. AI/ml for IoT :
1. The internet of things has been a fast growing area in recent years.
2. The use of AI/ml is increasingly interwined with IoT.
3. AI, machine learning and deep learning are being employed to make IoT devices and services is smarter and more secure.
4. In an industrial setting IoT networks through out a manufacturing plant can collect operational and performance data.
5. It is then analysed by AI systems to improve production system performance, boost efficiency and predict when machines will require maintenance.
7. AI and machine learning in hyper automation :
1. Hyper automation is the idea that think within an organisation that can be automated should be automated.
2. AI and machine learning are key components and major drivers of hyper automation.
3. To be successful hyper automation initiatives cannot rely on static packet software.
4. Automated business processes must be able to adapt to changing circumstances and respond to unaccepted situations.
5. That's where AI machine learning models and deep learning techniques come in.
6. Learning algorithms and models allows the system to automatically improve over time and respond to changing business processes and requirements.
8. Virtual agents :
1. Virtual agents a have become a valuable tools and instructional designers.
2. A virtual agent is a computer application that interacts with humans.
3. Web and mobile applications provide chatbots and their customer service agents to interact with humans to answer their queries.
4. Google Assistant helps to to organize meetings, and Alexia from Amazon helps to make your shopping easily.
5. A virtual assistant also acts like a language assistant which picks cues from your choice and performance.
6. Virtual agents act as - software - as a service to.
0 Comments