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Next-Gen Enterprise | Artificial Intelligence

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AI applications
311
Adoption of AI is becoming a common phenomenon across the industry. Companies are in different stages of AI maturity and depending on the level of adoption they are seeing varying levels of impact. While there is lot of excitement in the rapid...
Digital transformation
78
Rohan Khadabadi writes on why digital transformation is key and how enterprises should have an evolving hybrid cloud strategy powered by digital levers like AI, Big Data and Blockchain. Read more.
Machine Learning
50

Nov 03, 2020

Myths About Machine Learning

Mohita Singhal Technical Manager

Artificial Intelligence, Machine Learning, Deep Learning are the most prominent technologies, used in different products and applications we use in our everyday life. Artificial Intelligence is the intelligence exhibited in machines, unlike the...
Part I - Why Your Chatbot Will Never Work
276

Oct 08, 2020

Part I - Why Your Chatbot Will Never Work

Dennis Helms Solution Architect, ERX Enterprise Cloud

How many IT or business unit executives out there have read an article in your favorite business technology periodical that stated, “If you don’t embrace the AI wave now, you will be drowned by your competition”?  It’s ok, no one can see you
THE FUTURE OF AVIATION
181
The aviation industry experts are expecting a U-shaped recovery of the industry, which translates into a prolonged and stretched, slow paced rebound. However, the initial symptoms of recovery in the commercial aspects might begin to surface only by...
AI and Machine Learning in Financial Services
854
Needless to say, in this post-COVID-19 world the way businesses and clients interact with each other has irreversibly changed. We have seen banks and other financial institutions leveraging technologies like AI, Machine Learning and Intelligent...
Leveraging Big data and AI in Life sciences
168

Jul 17, 2020

Leveraging Big data and AI in Life sciences

Shyam S Senior Associate, Digital & Analytics

Cost-effective mass production coupled with cutting edge manufacturing and quality control can make the output of the entire life science industry reach out to an ever-increasing consumer base. This complements the decision-making process of...
NextGen Laboratories
93
As the world continues to grapple with the COVID-19 crisis, pharmaceutical research laboratories have become the center of attention. Companies, including startups, are leaving no stones unturned to harness advanced technologies to arrest the crisis...
Accelerating Implementation of Augmented Intelligence
112
Even though digital transformation and digital-first business have been the buzzwords for over a decade now, these have only been realized to its optimum extent in the last few months. This has given rise to the inevitable "humans vs machines"...
AI applications
311
Adoption of AI is becoming a common phenomenon across the industry. Companies are in different stages of AI maturity and depending on the level of adoption they are seeing varying levels of impact. While there is lot of excitement in the rapid...
Open Innovation
1,776
All too much as already been said about the drastic impact Covid-19 has had on the world. Within a matter of weeks, Covid-19 or the coronavirus has become a household names. So far it has spread across more than 140 countries and infected over 800,...
Chronic Disease Management process
988
Chronic Disease Management (CDM) is an integrated care approach to manage chronic disease or condition that is persistent or otherwise long-lasting in its effects. As care delivery continues to evolve from reactive disease treatment to proactive,...
Digital transformation
78
Rohan Khadabadi writes on why digital transformation is key and how enterprises should have an evolving hybrid cloud strategy powered by digital levers like AI, Big Data and Blockchain. Read more.
AI
1,888
Manufacturing is an area where the incorporation of different parts of AI is taking place. AI encompasses a range of technologies that are learned over time, as they are exposed to more data. AI has brought a new dimension which helps analyze data,...
AI Innovation
706
Digitization, Internet of things, connected humans, connected machines, and connected world are all generating large volumes of data at an unprecedented scale. IDC predicts that by 2025, there will be 175 zettabytes of data and continue growing at...
RPA
829

May 18, 2020

Application of RPA, AI, ML in Post trade Ecosystem

Muralitharan K Business Manager, HCL Technologies, Malaysia, SDN, BHD.

Advancement in technologies like Robotics process automation (RPA), Machine Learning (ML), Artificial Intelligence (AI) offers various products and services to reduce the manual intervention and improving operational inefficiencies in the middle and...
processes
150
Is iRPA (Intelligent Robotic Process Automation) now advanced enough to automate the back office? In this blog, Stuart Jameson covers the 5 key enablers to AI/ML that must be in place to leverage intelligent process automation opportunities – and...
AI
2,526
The Utility industry is shifting from a highly traditional, regulation-driven marketplace to an advanced technology-driven environment. For Infrastructure optimization and supply-demand balance, use of the smart devices has increased exponentially...

UnBox.ai, Art of testing AI applications
Jayachandran Kizhakootramachandran - Associate Vice President | December 17, 2020
311 Views

Adoption of AI is becoming a common phenomenon across the industry. Companies are in different stages of AI maturity and depending on the level of adoption they are seeing varying levels of impact. While there is lot of excitement in the rapid adoption of AI, many companies may be oblivious of some of the inherent risks regarding AI models. Stakeholders are increasingly consuming insights from AI applications (less critical to mission critical) for decision making and it can have larger implications, unless it is managed well. History is privy to instances when things have gone wrong and the 2008 financial crisis is a case in point.


Digital Transformation & the Merits of an Evolving Hybrid Cloud Strategy
Rohan Khadabadi - Senior Area Sales Manager | December 8, 2020
78 Views

Rohan Khadabadi writes on why digital transformation is key and how enterprises should have an evolving hybrid cloud strategy powered by digital levers like AI, Big Data and Blockchain. Read more.


Myths About Machine Learning
Mohita Singhal - Technical Manager | November 3, 2020
50 Views

Artificial Intelligence, Machine Learning, Deep Learning are the most prominent technologies, used in different products and applications we use in our everyday life. Artificial Intelligence is the intelligence exhibited in machines, unlike the natural intelligence displayed by humans. Machine Learning is a subset of artificial intelligence and it is the technique to learn from data without using complex set of different rules. It is the study of computer algorithms that improve automatically with experience. Training is done on the sample data to build mathematical model for making predictions on unseen data. Deep Learning is part of machine learning methods based on artificial neural networks, inspired by our brain's own network of neurons, uses multiple layers of neurons to extract higher level features. These technologies are used everywhere whether it is Google Search Engine for information extraction; Voice Assistants like Apple Siri, Google Home or Amazon Alexa for making voice calls, send messages, play music, control devices, set timer and other actions based on the command; self-driving cars or autonomous vehicles capable of sensing the environment and moving safely by making an extensive use of deep learning and AI; product recommendation on Ecommerce platforms by applying various machine learning techniques; movie recommendations on Netflix; fraud detection in banking and finance, Cybersecurity, facial recognition in Facebook. Deep learning is applied in various fields like computer vision, speech recognition, natural language processing, machine translation, medical image analysis. These technologies are used in various industry verticals such as healthcare, automotive, business, manufacturing etc. However, there are certain misconceptions about machine learning that come in the human mind, which we would like to highlight.