Tag Archives: Big Data Analytics

How 5G Will Change Our Lives + Future!

At Dell Technologies World 2019, Harvard professor Jonathan Zittrain moderated a high-powered panel that discussed how 5G will change our lives and future.

If you are interested in 5G technology, and its impact on our future, check out the full video of their discussion!

 

How 5G Will Change Our Lives + Future!

Despite a shaky start, thanks to the HUAWEI Trump ban, 5G is the future. A large part of Dell Technologies World 2019 was dedicated to the topic of 5G and its impact on consumers and businesses worldwide.

One of the key guru sessions that Dell sponsored was this discussion on how 5G will change our lives and future. Check it out!

This 5G guru session was moderated by Jonathan Zittrain, the George Bemis Professor of International Law at Harvard Law School. He is also a professor at the Harvard Kennedy School, Professor of Computer Science at the Harvard School of Engineering and Applied Sciences.

Joining him on this high-powered panel on 5G’s impact on our lives and future were :

  • Caroline Chan, Vice President of the Intel Data Center Group, and General Manager of the Intel Network Business Incubator Division
  • Eliza McNitt, writer and director, a 2018 Emmy Awards Finalist and winner of the VR Grand Prize at The Venice Film Festival.
  • John Ellis, Founder and Managing Director of Ellis & Associates. Formerly the global technologist and head of the Ford Developer Program, he is an author, futurist and expert on big data.

 

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The Human-Machine Partnership by Erik Brynjolfsson + Rana el Kaliouby

At the Dell Technologies World 2019, we were lucky enough to snag a seat at the talk by MIT Professor Erik Brynjolfsson; and MIT alumni and Affectiva CEO, Rana el Kaliouby, on human-machine partnership.

We managed to record the incredibly insightful session for everyone who could not make it for this exclusive guru session. This is a video you must not miss!

 

The DTW 2019 Guru Sessions

One of the best reasons to attend Dell Technologies World 2019 are the guru sessions. If you are lucky enough to reserve a seat, you will have the opportunity to listen to some of the world’s most brilliant thinkers and doers.

 

The Human-Machine Partnership

The talk on human-machine partnership by Professor Brynjolfsson and Ms. Rana was the first of several guru sessions at Dell Technologies World 2019.

Entitled “How Emerging Technologies & Human Machine Partnerships Will Transform the Economy“, it focused on how technology changed human society, and what the burgeoning efforts in artificial intelligence will mean for humanity.

Here are the key points from their guru session on the human-machine partnership :

Erik Brynjolfsson (00:05 to 22:05) on the Human-Machine Partnership

  • You cannot replace old technologies with new technologies, without rethinking the organisation or institution.
  • We are now undergoing a triple revolution
    – a rebalancing of mind and machine through Big Data and Artificial Intelligence
    – a shift from products to (digital) platforms
    – a shift from the core to crowd-based decision making
  • Shifting to data-driven decision-making based on Big Data results in higher productivity and greater profitability.
  • Since 2015, computers can now recognise objects better than humans, thanks to rapid advances in machine learning.
  • Even machine-based speech recognition has become as accurate as humans from 2017 onwards.
  • While new AI capabilities are opening up new possibilities in many fields, they are also drastically reducing or eliminating the need for humans.
  • Unlike platforms of the past, the new digital networks leverage “two-sided networks“. In many cases, one network is used to subsidise the other network, or make it free-to-use.
  • Shifting to crowd-based decision-making introduces diversity in the ways of thinking, gaining new perspectives and breakthroughs in problem-solving.
  • Digital innovations have greatly expanded the economy, but it doesn’t mean that everyone will benefit. In fact, there has been a great decoupling between the productivity and median income of the American worker in the past few decades.

Rana el Kaliouby (22:08 to 45:05) on the Human-Machine Partnership

  • Human communication is mostly conveyed indirectly – 93% is non-verbal. Half of that are facial expression and gestures, the other half is vocal intonation.
  • Affectiva has the world’s largest emotion repository, with 5 billion frames of 8 million faces from 87 countries.
  • Facial expressions are largely universal, but there is a need diversity of their data to avoid bias in their models. For example, there are gender differences that vary by culture.
  • They use computer vision, machine learning and deep learning to create an Emotional AI model that learns from all those facial expressions to accurately determine a person’s emotions.
  • Emotional artificial intelligence has many real-world or potential uses
    – detecting dangerous driving, allowing for proactive measures to be taken
    – personalising the ride in a future robot-taxi or autonomous car
    – the creation of more engaging and effective social robots in retail and hospitality industries
    – help autistic children understand how facial expressions correspond to emotions, and learn social cues.

 

Erik Brynjolfsson + Rana el Kaliouby

Professor Erik Brynjolfsson holds many hats. He is currently :

  • Professor at the MIT Sloan School of Management,
  • Director of the MIT Initiative on the Digital Economy,
  • Director of the MIT Center for Digital Business, and
  • Research Associate at the National Bureau of Economic Research

Rana el Kaliouby was formerly a computer scientist at MIT, helping to form their Autism & Communication Technology Initiative. She currently serves as CEO of Affectiva, a spin-off from MIT’s Media Lab that focuses on emotion recognition technology.

 

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2019 ASEANDSE | ASEAN Data Science Explorers Launched!

SAP and the ASEAN Foundation just announced that application for the 2019 ASEANDSE | ASEAN Data Science Explorers programme is now open! Here are the full details!

 

What Is ASEANDSE | ASEAN Data Science Explorers?

The ASEANDSE (ASEAN Data Science Explorers) programme is a joint collaboration between SAP and the ASEAN Foundation. It aims to promote and galvanise the use of data science amongst ASEAN tertiary students.

It aims to do this through two key activities – a series of enablement sessions, and a data analytics competition. Since its introduction in 2017, ASEANDSE has empowered over 5,000 youths from 287 higher education institutions in the ASEAN region.

 

The 2019 ASEANDSE Programme

The 2019 ASEANDSE programme will be carried out from February to October 2019. It starts with enablement sessions that are designed to improve the data analytics skills and knowledge of both students and lecturers at local institutions of higher learning across the ASEAN region.

These enablement sessions will be followed by a national, and then regional, data analytics competition. At these competitions, student teams of two will present their data-driven proposals using the SAP Analytics Cloud service.

Their ASEANDSE competition proposals must tackle issues affecting their country or ASEAN in general, according to these UN Sustainable Development Goals :

  • Good health and well-being
  • Quality education
  • Gender equality
  • Decent work and economic growth
  • Industry, innovation and infrastructure
  • Sustainable cities and communities

One team from each ASEAN member state will be crowned as the national finalist before advancing to the 2019 ASEANDSE regional finals, which will be held in Bangkok on 16 October 2019.

There, the 10 national finalists will be given the opportunity to present their winning ideas to a panel of judges made up of distinguished representatives from the ASEAN Foundation, SAP and various government officials and selected NGO organisations.

 

Where To Join The 2019 ASEANDSE Programme

The 2019 ASEANDSE programme is now open for registration, until 10 May 2019. Here are the eligibility requirements :

  1. Nationals of ASEAN member countries (ie. Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam)
  2. Full-time tertiary students currently pursuing their Diploma or Undergraduate studies in one of the tertiary institutions in Southeast Asia.
  3. Above the age of 16 as at the start of the Contest Period. Participants under the age of 18 must obtain parental consent. The consent form is available upon registration.

If you meet those requirements, you can register here!

 

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Learn How Expedia Finds The Best Flights In Just 3 Seconds!

Expedia is the world’s largest travel company, and you might be wondering – how on earth do they scan through quadrillions of flight plans every day, to deliver the best possible flight in mere seconds? Let’s find out!

 

Learn How Expedia Finds The Best Flights In Just 3 Seconds!

You may be familiar with how easy it is to book a flight on Expedia. Just key in your flight requirements and in mere seconds, Expedia delivers the best flight options for you. But that simplicity is back by serious data science.

Gabriel Garcia, who doubles as Expedia’s Global Head of Mobile Apps Marketing, and their APAC Head of Marketing, flew into town to give us a look at how Expedia performs its magic. And this is magic of the scientific sort.

Here are some key points from from his presentation and Q&A session with us :

  • The Expedia mobile app was downloaded more than 250 million times by Q4 2017.
  • Expedia gets about 30 billion searches per year, or about 82 million searches per day.
  • More than 50% of the traffic on Expedia is from mobile devices.
  • 1 in 3 bookings are made using mobile devices.
  • Expedia uses data science and machine learning to make sure every search delivers the best possible options, out of the billions of possibilities.
  • In particular, they use the Best Fare Search (BFS) algorithm to narrow down millions of possibilities for every search to the 1000 most relevant options… in just 3 seconds.
  • They have hundreds of data scientists and analysts who develop new analytical and predictive algorithms.
  • They have also migrated to an agile development process, with weekly incremental changes, instead of quarterly updates. This allows them to test new ideas and adapt to changes much faster.

 

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Exclusive Tour Of SAP Leonardo Center Singapore

On 8 May 2018, SAP SE (NYSE: SAP) announced the establishment of the SAP Leonardo Center Singapore, to help their customers, partners, and foster faster innovation throughout the broader ecosystem of universities and start-ups across the Asia Pacific and Japan (APJ) region.

Join us for an exclusive look at the new SAP Leonardo Center Singapore, including a tour of the digital innovations that SAP Leonardo offers enterprises and businesses.

 

SAP Leonardo Center Singapore

SAP Leonardo Centers are interconnected hubs that serve as points of contact for companies and startups interested in SAP Leonardo. They are part showcase, and part collaborative centers. Their real-world examples of digital innovation using SAP Leonardo serve as inspiration for SAP customers and partners. They also offer a place for businesses and startups to experiment and innovate, jointly or in collaborative efforts.

Leonardo Center Singapore expands SAP’s presence in the APJ region, which already boasts three SAP Innovation Centers and four SAP Labs. It will be the fifth in the global network of SAP Leonardo Centers, serving a “front-end” to assist SAP customers in transforming their businesses with SAP Leonardo and Design Thinking.

SAP Leonardo brings together the Internet of Things (IoT), Machine Learning, Blockchain technology, Big Data Analytics and Data Intelligence on the SAP Cloud Platform. It also applies SAP’s technological capabilities and deep knowledge of 25 industries to deliver the promise of Intelligent Enterprise.

“The SAP Leonardo Center in Singapore will showcase the art of the possible in digital innovation and help our customers scale quickly, easily and effectively,” said Scott Russell, President, SAP APJ. “Together with our customers and partners, we aim to leverage the SAP Leonardo Center Singapore as a think tank to drive purpose-led innovation that will ultimately improve the lives of one billion people and deliver the Intelligent Enterprise for over 70,000 customers in APJ by 2022. The SAP Leonardo Center in Singapore will play a key role in realizing our growth strategy and drive customer success in the new Intelligence era.”

 

Collaborative Hub

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The SAP Leonardo Center Singapore aims to foster a collaborative environment for businesses, start-ups, small and medium-sized enterprises to experiment and innovate.

It will also serve as a hub for SAP’s broader digital technology ecosystem including universities, startups, tech communities and accelerators.

Through the SAP University Alliances program, SAP APJ helps to educate 1.7 million students in educational institutions across the region. SAP APJ has also established 13 labs in APJ with plans to open more in the future.

 

Tour Of SAP Leonardo Center Singapore

Thorsten Vieth, Director of Industry Innovation at SAP South East Asia, took us on a tour of SAP Leonardo Center Singapore. SAP created various booths to showcase real world examples of SAP Leonardo at work.

They include traffic management of an entire city, how a smart stadium manages crowds, predictive maintenance of smart trains, and ensuring safety of drivers and passengers in smart buses.

They also showed how machine learning can be used to simplify the maintenance of home appliances with IoT capability, while providing a transparent and secure service record using blockchain technology. Such capabilities not only improve the customer experience, they also reduce costs for businesses.

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An Immersive Experience With IBM Watson

IBM Watson is a cognitive intelligent system that uses natural language processing and machine learning to reveal insights from large amount of unstructured data. You may remember it for winning the quiz show Jeopardy in 2011.

On 22 June 2017, IBM invited us to participate in an exclusive demonstration of Watson’s capabilities. They also showed us how Watson allows even non-techies mine large amounts of abstract data for pertinent information.

For a similar demonstration of artificial intelligence and big data analytics capability, check out our recent article – The AWS Masterclass on Artificial Intelligence by Olivier Klein.

 

An Immersive Experience With IBM Watson

In development for over 12 years, IBM Watson is understandably far complex than when it debut in Jeopardy. It is powered by 50 underlying cognitive technologies, including natural language processing, machine learning and deep learning.

This particular session was conducted by Zainal Azman Shaari and Cheok Swin Voon from IBM’s Eco-system Development team, and is limited to the functions of IBM Watson Conversation and its natural language understanding (NLU) capabilities.

A Monash University team of final year students then showed what they accomplished with IBM Watson in just a few weeks, despite not having any programming abilities. Specifically, they showed how they can mine Twitter to not just determine how often people were talking about a fast food brand, they also used IBM Watson to determine whether the tweets were positive or negative in nature.

For a similar demonstration of artificial intelligence and big data analytics capability, check out our recent article – The AWS Masterclass on Artificial Intelligence by Olivier Klein.

Next Page > The IBM Watson Q&A Part 1/2

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The IBM Watson Q&A Part 1/2

  1. What is IBM Watson?
  • IBM Watson is a cognitive intelligent system that uses natural language processing and machine learning to reveal insights from large amount of unstructured data. It has the capability to tackle tough problems in every industry from healthcare to finance.
  • Through understanding the data it learns from human input, it is not only able to improve its response accuracy but also understand trends that can then be utilised to generate business insights.
  • Watson is powered by 50 underlying cognitive technologies – including natural language processing, machine learning and deep learningto provide capabilities that span language, speech, vision and data insights.

 

  1. Can you tell us about Watson’s history? Who are the brains behind its inception?
  • IBM has been researching, developing and investing in AI technology for more than 50 years. The rise of big data (2.5 billion gigabytes of data are created every single day) and the world’s need to make sense of it all – is what ultimately led IBM researchers to develop Watson.
  • When IBM Watson won the historic Jeopardy! exhibition on TV in 2011, it was a watershed moment. And since then we’ve only accelerated our innovation, advancing and scaling the Watson platform and applying it to many industries, including healthcare, finance, commerce, education, security and IoT. We’ve engaged thousands of scientists and engineers from IBM Research and Development, and partnered with our clients, academics, external experts and even our competitors, to explore all topics around AI.

  • IBM Research is today the largest industrial research organization in the world, with twelve labs on six continents, and the company invests $6 billion on R&D.
  • The labs are viewed as one of IBM’s greatest assets and a vital part of defining the future. In August 2016, we celebrated the 30th anniversary of the Almaden research lab. Today, Almaden’s research community focuses on solving problems across areas as diverse as nanomedicine, services science, atomic scale storage, food safety and medical image analytics.

 

  1. What are some of IBM Watson’s accomplishments in the real world today?
  • Since its debut, Watson solutions are now being built, used and deployed around the world and across industries, including healthcare, financial services, travel and retail. Since 2015, IBM has seen a 400 percent increase in Watson app creation on Bluemix, an increase of over tenfold over the last year.
  • Watson has played a role in supporting more than 200 million patients through healthcare systems in the U.S., China, Japan, Thailand and India, collaborating with doctors, helping improve treatment recommendations and helping deliver more efficient care.
  • Watson is also available to more than 200 million consumers to answer their questions, find what they need and make recommendations with greater personalization.
  • At the same time, Watson is tackling dozens of meaningful business and societal challenges, helping reduce building emissions, reducing hiring cycles and finding ways for cities to save more water and other resources. In education, half a million students can choose their courses to master a subject with Watson and we’re also helping teachers address each student’s unique needs.

 

  1. With the interaction between IBM Watson and regular users becoming increasingly more complex and utilize more of the user’s personal information, is there a potential risk for loss of privacy for users in an unfortunate incident?
  • While Watson is indeed able to process more forms of information, we have also ensured that we have developed safety measures within Watson as well as continue to work with our industry partners all to ensure that the data that Watson has access to is not accessible by any unauthorized third-parties.

 

  1. It was mentioned that IBM Watson understands natural languages. What does this mean and what languages does it support?
  • IBM Watson is able to understand sentences spoken by people by analysing the words used as well as the context of the sentence in order to accurately interpret sentences.
  • Currently IBM Watson is able to understand and reply in nine different languages including German, Spanish, Korean, Japanese and English to name a few. We are also constantly updating Watson with additional languages to allow more people in the world to experience him.
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  1. Why is understanding natural human speech such a complex task for artificial intelligence systems to perform?
  • The primary difficulty when it comes to recognizing human speech is that natural speech is inherently filled with unstructured data, and this is the same across all forms of content written by humans for other humans.
  • The main difference is that normal structured data is governed by well-defined rules whereas speech is governed by rules of grammar, context and culture which is implicit, ambiguous and complex.
  • With a host of factors to consider and eliminate, recognizing speech can be both a time-consuming task as well as one that is open to a host of errors if not interpreted correctly.

 

  1. What is the systems implemented into Watson that allows him to easily comprehend human speech?
  • To facilitate IBM Watson to better tackle the challenge of understanding human speech, Watson is fitted with two different set of APIs that give it the ability to both comprehend and respond to human interactions: Natural Language Understanding (NLU) & Watson Conversation.
  • The Natural Language Understanding API allows Watson to analyze text to extract meta-data from content such as keywords, entities, sentiment, emotion, relations and many more.
  • Watson Conversation, on the other hand, functions as a visual dialog builder that helps create natural conversations for Watson that can be deployed on chatbots and other virtual agents.

Next Page > The IBM Watson Q&A Part 2/2

 

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The IBM Watson Q&A Part 2/2

  1. It was mentioned that Watson is capable of self-learning and improvements, can you explain more how this system works?
  • What makes Watson truly unique from pre-programmed AI is that Watson is capable of consistently learning from user input as well as correct itself to provide better answers to human queries.
  • Watson does this by undergoing a constant feedback loop with human input that involves correction of errors in order to determine the most appropriate answer that is based on the context of the question.

 

  1. What is the vision that IBM has for Watson and what is IBM currently doing to ensure that they can achieve this vision?
  • Our vision for IBM Watson is to develop it into a full-fledged platform that is capable of making a real impact in any industry it is applied in.
  • We are also focused on developing Watson as an Artificial Specific Intelligence, also known as narrow AI, that is specifically focused on relevant knowledge in its required field of expertise to ensure that they can respond in the same way professionals do.
  • We are currently actively working with professionals in the field as well as expanding the capabilities of Watson in order to ensure Watson is able to reach out to over 1 billion consumers by the end of 2017.

 

  1. Can you explain more about the term ‘machine learning’?
  • Machine learning can be defined as AI system that possesses the ability to learn without requiring constant programming.
  • Programs with machine learning systems are able to make use of most forms of new data it is exposed to develop and improve responses or solutions.
  • In future, AI systems will be able to understand more complex data while also delivering more accurate results compared to humans. This could allow future machines to be more autonomous while also handling challenging tasks that normal humans cannot do.

  1. In order to implement Watson, are developers required to pay a certain fee in order to utilize related assets and data?
  • No, interested developers who want to make use of the Watson platform to create their own cognitive apps or businesses can do so from the public Watson Developer Cloud and other platforms.
  • Our cloud platform represents the easiest way for potential developers to create their next-gen cognitive apps with a total of over 160 unique APIs and services in 179 countries.

 

  1. Does IBM foresee a drop in openings for jobs that Watson is able to perform given his increasing capabilities for complex tasks?
  • With every major advancement in technology, there will always be a change to the existing workforce where there will be new ways of working as well as new skills and jobs that will be in greater demand. This is the same case as well for cognitive computing.
  • Despite this, we believe that Watson and the field of cognitive computing will instead introduce a whole new level of collaboration between man and machine, and serve to expand human intelligence instead of replacing it.
  • We believe that by thoughtfully and purposefully combining the best qualities of both man and machine, we can understand our world better as well make better decisions that can lead to future innovations.

 

  1. What does IBM foresee will change in the landscape of cognitive computing?
  • We foresee that cognitive computing in the coming years will continue to make huge advancements in technology that will make our systems even smarter.
  • Through continuous human interactions, these systems will be able to learn at a much greater rate and continuously learn up to the point where they can fully run without human intervention.
  • As cognitive systems continue to be refined, we can also expect these systems to tackle an even broader range of tasks that even humans may not be able to do.
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  1. How has IBM globally performed financially in the past year of 2016?
  • 2016 was another solid year for IBM as we have achieved several milestones in the year.
  • Aside from working some of the world’s largest most well-known companies across industries, we have also invested into our capabilities such as cloud, analytics and cognitive that has now accounted for 41% of our total revenue.
  • We have also not lost sight of our goal of developing innovations in 2016 with over 8,000 patents registered in 2016 and we are currently leading in terms of U.S. patents earned for the 24th year in a row.

 

  1. What are some of the upcoming plans that IBM have in the year of 2017?
  • In the coming year, we are looking to continue our research into our field of expertise for designing and developing innovative new systems that can enhance our client’s business and help them succeed in their field.
  • We have some projects in Malaysia in the banking, manufacturing and healthcare industries.

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Mellanox Technologies Expands Presence In Malaysia

KUALA LUMPUR, April 12, 2017 – Mellanox Technologies, Ltd. (NASDAQ: MLNX) today unveiled its expansion plans for Malaysia. The announcement, which is in line with the country’s ambitions of becoming the leading Big Data Analytics (BDA) solutions hub in South East Asia, reiterated Mellanox’s commitment to Malaysia through its strategic investment roadmap.

 

Mellanox Technologies Expands Presence In Malaysia

“Malaysia’s investment in Big Data, data centers and the Cloud is impressive,” said Charlie Foo, Vice President and General Manager, Asia Pacific Japan, Mellanox Technologies. “With a year-over-year growth of more than 20 percent in the last five years, the field of digital data management is maturing rapidly. Mellanox’s investment in Malaysia looks to complement Malaysia’s advancing digital economy by providing intelligent 10, 25, 40, 50 and 100Gb/s interconnect solutions that serve today’s and future needs in Malaysia. This will enable organizations to be less concerned about today’s technological demands while concentrating on running their business, resulting in unparalleled operating efficiency for these organizations.”

Mellanox’s investment into Malaysia’s digital economy comes at a time when the country is ramping up its efforts to see its ICT roadmap to fruition. The country’s ICT custodian, Malaysia Digital Economy Corporation (MDEC), noted that MSC Malaysia — a national initiative designed to attract world-class technology companies to the country — reported a U.S. $3.88 billion in export sales in 2015, representing an 18 percent increase over 2014.

Today, the MSC Malaysia footprint has expanded to include 42 locations across the country, hosting more than 3,800 companies from more than 40 countries, employing more than 150,000 high-income knowledge workers, 85 percent which are Malaysians. This has propelled Malaysia to a top three ranking in AT Kearney’s Global Services Location Index since 2005, with only China and India ahead of Malaysia.

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Mellanox’s Open Ethernet switch family delivers the highest performance and port density with a complete chassis and fabric management solution, enabling converged data centers to operate at any scale while reducing operational costs and infrastructure complexity.

Mellanox InfiniBand solutions have already been chosen to accelerate large High Performance Computing (HPC) customers in Malaysia. HPC customers use super computers and parallel processing techniques for solving complex computational problems and performing research activities through computer modeling, simulation and analysis. These HPC customers span various industries including education, bioscience, governments, finance, media and entertainment, oil and gas, pharmaceutical and manufacturing.

The company is actively seeking partnerships and collaboration opportunities to support customers from different industries, primarily within Big Data, data centers and the Cloud.

 

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The IBM Watson Malaysia Summit 2017

KUALA LUMPUR, 23 March 2017: The cognitive era is here and organizations ought to seize the opportunity to leverage the game changing technologies for business growth and transformation.

IBM Malaysia managing director Chong Chye Neo said Watson, IBM’s augmented intelligence (AI) technology, is already in use in more than 45 countries and across 20 different industries.

“Watson is represented by a diverse set of Watson services that span language, speech, vision, and data insights based on over 50 underlying technologies,” she said, adding that Watson now powers new consumer and enterprise services in the health care, financial services, retail and education markets.

“IBM’s Watson has been put to the test to diagnose cancer, detect autism, advance early childhood education, transform banking practices, improve farming practices and invent new recipes,” she added.

 

The Inaugural IBM Watson Malaysia Summit 2017

Chong was speaking at IBM’s inaugural Watson Malaysia Summit 2017 to over 300 customers and business partners from the banking, financial services, manufacturing, government, and healthcare industries. Attendees were also treated to live demonstrations on some of the innovative cognitive technologies currently deployed today in Malaysia as well globally by companies such as Silverlake Axis, Sunlife-I, MDT Innovations and Skymics.

She said that the concerns surrounding AI can be addressed by how businesses and society collaborate to address the sweeping avalanche of technologies driven by mobility, hyper-connectivity and the Internet of Things (IoT).

IDC predicts that by 2018, 75% of all consumers will interact with services based on cognitive computing on a regular basis.

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Chong further said that IBM is guided by three guiding tenets: purpose, transparency and skills, which are crucial to help people develop trust in an AI system. “For IBM, the purpose of AI will be to aid humans, not replace them. For most of our businesses and companies, it will not be a “man or machine” scenario, instead it will be a symbiotic relationship between the two. Our purpose is to augment and really be in service of what humans do.”

She added stakeholders must also be clear or transparent in building AI platforms, the industry domain, how they are trained, and what data was used in training. “With Watson, institutions can combine their decades of knowledge with industry data. These systems will be most effective when trained with domain knowledge in an industry context,” she added.

Skill is the third tenet in addition to purpose and transparency is skills. “AI platforms must be built with people in the industry, be they doctors, teachers, or underwriters. And companies must prepare to train human workers on how to use these tools to their advantage,” she concluded.

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SAP & IDC : The Future Of The Malaysian Internet Economy

On 24 November 2016, SAP and IDC hosted an exclusive briefing on the future of the Malaysian Internet economy. The timing is impeccable because the Malaysian government has declared that 2017 should be the “Year of the Internet Economy“.

Their analysis and opinions on how Malaysian businesses and entrepreneurs should chart their courses going into 2017 are invaluable for anyone who wants to stay relevant in the new age of the Internet economy. We all need to stay on top of the wave of new developments, or risk having it crash on us.

 

2017 – The Year Of The Internet Economy

In 2015, the Malaysian Internet economy contributed 17.8% to the GDP (Gross Domestic Product), just shy of the 18.2% target set for 2020. On the back of this rapid growth in importance, Prime Minister Datuk Seri Najib Tun Abdul Razak called on Malaysians to “embrace, adapt to changes and explore new areas of growth to accelerate the economy“.

SAP Malaysia is in full agreement of this view. In the past decade, the rate of adoption of new technologies has accelerated and technology is changing the rules of business with disruption becoming the norm. This will accelerate in 2017 and local businesses need to absorb, understand and adapt to these underpinning seismic shifts taking place, particularly with regards to Internet of Things and Big Data Analytics.

SAP Malaysia Managing Director Terrence Yong kicked off the session with his view on the Malaysian digital economy, and how IoT and big data analytics are changing the way we make, buy and sell products and services.

IDC Asia-Pacific Research Director Chin Jun Fwu then shared his findings on the adoption of the latest IoT and big data analytics here in Malaysia, before SAP (Southeast Asia) Head of Analytics Kathleen Muller touched on the impact of data analytics and the Internet of Things, particularly for SMEs (Small and Medium Enterprises).

Unfortunately, the current adoption of big data analytics and IoT in Malaysia is low. The key takeaway is that price is not really the issue, but rather inertia. Even if they are aware of what they must do to adapt to the changing world, there is resistance to learning new ways.

That will have to change, soon. Otherwise, even the most established businesses may lose out to their more nimble competitors.

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