Tag Archives: AI

The Art of Enabling the Disabled

Artificial Intelligence and Machine Learning (AI and ML) technologies have come a long way since its first inception. Who would have thought that we would have a working model of actual computer-based assistants that can do things like manage our schedules? Who would have thought that we could even use these assistants to manage our homes? These things can even be used to diagnose cancer patients, something impossible without doctors even five years ago.

Amazon Web Services (AWS) is at the forefront of AI and ML technology. As one of the world’s largest technology innovators, they would naturally be at an advantage to feed enough data to the technology and accelerate their development. Because they are also one of the largest technology firms any man has ever seen, they are also at an advantage in placing AI and ML in places and applications we may never have imagined.

Linguistics is one segment that has benefitted greatly from technologies today. Linguistics, if you think about it is also one of the most complex things that us humans can create and understand. The context of it and interpretation can be affected by plenty of things too. Linguistics is affected by area, culture, community, heritage, and even lineage.

For example, there are differences between French spoken in France and Canada. There are even subtle differences between French spoken in France and Monaco, or even Switzerland. The most common language of all, English has differences even in spelling and context in Britain, the Americas, and even Australia. English spoken today is also a distinct form of the language that was spoken 50 years ago.

The Pollexy Project

The progression of technology in linguistics have progressed through years and years of feeding all these data into it. That has allowed us to communicate with global communities with more ease than peeling an orange. AWS has taken it a little further than that though. They have gone beyond spoken or written languages. Through something called AWS DeepLens, they have developed translation algorithms to sign languages.

While that technology might sound like it is as simple as gesture controls, it is plenty more than that. Yes, it is technically gesture control and recognition. But it is way larger and more complex than just a solution for end-point devices. The trick is to teach the native algorithm to recognise all the available sign words and even alphabets. The AWS DeepLens Community projects so far has learnt to recognise most of the alphabets in the American Sign Language.

But technology also goes beyond just recognising alphabets to understanding proper words with the algorithm in Amazon Alexa. It is not just about communicating with your friends anymore. It is about using the platform as a home assistant tool, a customer service tool, a command center, and user defined PC experience that mimics voice control and command for us. Instead of using voice though, its all in the gestures.

Making Amazon Alexa respond to Sign Language using AI

The tool they use is called Amazon Transcribe. It works just like any transcribe apps you can find in the market. It supports up to 31 languages currently with more being added by time. It even supports ASL as a component to create text from sign language.

Simple communication is just the beginning for the technology though. AI and ML still has a long way to go even in the medical field. Just like the human race, the technology gets better everyday though. If you really think about it, the technology is not that new in the first place. We have embarked on the journey of having machine built and defined assistants since we started developing computers to help us with simple and complex mathematical problems.

It is just that simple mathematical problem solver has become something much bigger today. Who would have thought that we would let computers fly a commercial airplane? Who would have thought that cars can drive themselves today? Who would have thought that we could hire a private translator without spending any money or any time? You just have to look into your pocket.

Combining AI and Humans in the New Decade

*This article is a contributed article by Ravi Saraogi, Co-Founder and President of Uniphore, APAC *

2020 marks the transition into the great unknown. With the emergence of new possibilities and challenges ahead of us, successful organisations must be quick to identify and take advantage of opportunities through the power of emerging technologies. Specific to the customer service industry, brands that utilise Conversational Artificial Intelligence (AI) technologies will improve business operations and customer experiences.

It is estimated that about 70% of organizations will integrate AI to assist employee productivity by 2021[1] to meet the high demand of delivering faster, relevant and holistic services to today’s customers. More often than not, customers today are frustrated that broken customer service systems and poorly equipped agents don’t understand their requests. To fix this, businesses must move away from a siloed experience and approach service holistically.

Photo by mahdis mousavi on Unsplash

In terms of the adoption of the adoption of AI in Malaysian businesses, it was revealed that only 26% of companies in Malaysia have actually begun integrating AI into their operations, according to a survey that was conducted in 2018. The low adoption rate is attributed to two key barriers that are related to organizational culture on AI and limited employee skill sets2. Thus, the time is now to blend the capabilities of people and AI and better understand conversations in real-time for businesses to stay ahead of the race.

New Power to Customer Voice

With technological capabilities, it’s about time we start hearing what customers really want. Customers today are time poor, distracted and empowered by lots of products and services to choose from. Instant gratification is their modus operandi. With other factors like price point and product quality being at par, superior customer service remains challenging and is often a deal breaker. In a competitive landscape, customers demand a seamless experience when interacting with a brand.

That said, poor customer experiences are not difficult to resolve at all, more so today due to machine learning, AI and automation. This is because AI is now helping brands to truly listen to the voice of the customer and understand their needs in order to quickly resolve customer queries, deepen customer engagement, and deliver superior customer experience at scale.  

Making Headway with Conversational Service Automation

Minister of Communications and Multimedia, Gobind Singh Deo emphasises Malaysia’s potential in the development of AI in both public and private sectors, and the importance of ensuring the local government and industries capitalise on the opportunities at hand.[2]

The use of AI is becoming more prevalent in the customer service industry as conversations become more complex. There is a small window of opportunity for brands to deliver personalised customer service, particularly when your engagement happens across diverse channels. Being equipped with an understanding of context, sentiment, behaviour and real intent, and being able to act on such insights in real-time becomes even more crucial.

Photo by Joseph Pearson on Unsplash

Conversational Service Automation is about enabling front office automation in contact centres. Consider this scenario: A customer starts a conversation with a chatbot for quick self-service. The bot is able to provide some quick and valuable updates based on the customer’s previous interactions. If the conversation gets more complex, the voice bot politely hands the call to a human agent via a live transfer. The agent is assisted through real-time analytics and chat transcripts to be able to make the next best offer which the customer gladly accepts.

This automation backed by real-time analytics is continuously self-learning, enabling real-time listening of conversations across channels and then converting them into actionable insights. As a result, a win-win situation is created where businesses can reduce work pressure on call center agents, improve accuracy of information and greater customer satisfaction.

Getting Ahead of the Race with Voice and AI

We are in the midst of a customer experience transformation and conversational AI technology is leading this change. There is a positive acceptance from both businesses and customers to adopt newer conversational AI technologies. This is driven by the try-before-you-buy and pay-as-you-go models offered, which enterprises find appealing and less risky. Brands can take smaller bets, test-and-learn and then scale up.

Automation has successfully allowed computers to respond to contexts within queries, monitor customer behaviour and improve overall customer service. Moreover, contact centre agents can now receive real-time alerts and recommendations for upsell and cross-sell. The time is now for companies to leverage conversational AI to deliver a quantum leap in customer service, in an industry that is full of potential. It is good to note that brands that embrace conversational service automation will be the ones who stay ahead of the competition and thrive in the new decade.


[1] https://www.gartner.com/en/newsroom/press-releases/2019-01-24-gartner-predicts-70-percent-of-organizations-will-int
2 https://www.stuff.tv/my/news/malaysian-companies-needs-build-ai-culture-it-too-late-microsoft

[2] https://www.malaymail.com/news/malaysia/2019/09/12/gobind-malaysia-well-positioned-in-se-asia-for-ai-research-and-development/1789773