Insights shared at Symposium on Innovation and Technology

The tremendous growth in data, particularly privately held data by large businesses, is the reason for, and key to, the expansion and success in the use of artificial intelligence (AI) in business, according to speakers at the 13th Oct afternoon session of the Symposium on Innovation and Technology, under the theme ‘AI Empowerment – Grow without Limits’, held during the 38th HKTDC Hong Kong Electronics Fair (Autumn Edition).

Transforming business through AI

Microsoft uses AI for a wide range of purposes, from helping people with visual impairments and hearing disabilities to preventing the extinction of rare species and growing better crops, according to Winnie Chu, Cloud and Enterprise Business Group Lead of Microsoft Hong Kong. Microsoft believes AI will help humans do more to be more successful and improve capability. Chu said: “We are surrounded by data, but we need to leverage this data.”

“Microsoft is leveraging technology and putting it into applications to make work more efficient,” Chu said. For example, Microsoft has incorporated an AI-powered presentation translator in PowerPoint that allows users to save hours and can translate slides into 60 languages. Microsoft also combines machine learning (ML) and natural language processing (NLP) to provide examples to improve writing, while Microsoft Word understands the user’s language and suggests more appropriate words and expressions.

Some other examples of Microsoft’s AI breakthroughs include object recognition (96% human parity), speech recognition (96% human parity), machine translation (69.9% human parity), and machine reading comprehension (88.5% human parity).

Chu gave examples of industries leveraging Microsoft AI. Container-shipping giant OOCL uses it to predict schedules and cost needs, saving $10m per year in operational costs. In the healthcare field, Inner Eye in the United Kingdom uses 3D imaging to find the exact location of tumours, allowing precise radiotherapy. In the property market, Ricacorp in Hong Kong uses AI for the benefit of both buyers and sellers, helping buyers identify the best flat for their specific needs, and helping sellers decide the best price and time to achieve their most desired outcome.

Chu explained: “So how can your organization leverage AI to get more customers and work faster?” To help companies develop the technical know-how, Microsoft has a free Certification program, covering Data Science, AI and Big Data. “Microsoft’s goal is to enable all companies to do their own AI projects. University professors love this well-structured program.” The program is also tailored for people with disabilities.

Chu explained the reasons for the success of Microsoft’s social chatbot Xiaolce, which has become one of the most famous celebrities in China. Whereas other chatbots digest information and respond, Xiaolce interacts as in a normal phone conversation between friends on the phone. “Xiaolce has empathy,” Chu continued. It can predict what the person will say next and respond more quickly than the usual chatbots, making the conversation more natural. “This is important in the business world because social chatbots can enhance the online experience and bring in more revenue.”

“Microsoft is committed to providing a responsible AI platform to help our clients do more business,” Chu concluded.

Human-AI collaboration

“The possible applications of AI are almost limitless,” said MeiKei Ieong, Chief Technology Officer of the Hong Kong Applied Science and Technology Research Institute (ASTRI), adding that Hong Kong was at the forefront in many areas. For example, the Hong Kong University of Science and Technology (HKUST) and University of Hong Kong (HKU) are frequent winners of the ImageNet Challenge, in which software programs compete to correctly classify and detect objects and scenes. A breakthrough in 2012 in solving the challenges presented in the contest was considered to be the beginning of the deep-learning (DL) revolution.

AI competitiveness depends on talent, which in most cases comes from universities, and computational power for machine learning and inferences, said Ieong. The top three barriers for leaders in adopting AI are the need to attract, acquire and develop the right AI talent, competition from other investment priorities for resources, and security concerns about AI adoption. The top three barriers for passive users are limited or lack of general technology capability, lack of leadership and lack of opportunities.

Ieong described a few examples of projects with ASTRI acting as an AI partner for Hong Kong business:

1. NLP technology that understands colloquial Cantonese mixed with English, which can be used from conducting big data applications on social media analytics to helping teachers correct common mistakes in primary students’ writing.
2. An AI robot-financial adviser.
3. A surface inspection system that can detect faulty glass lenses and other surfaces, replacing labor and completing the job much faster.
4. AI Chinese optical character recognition (OCR), eliminating the need to manually enter vast amounts of data for banks and financial services companies.
5. An intelligent industry robot used for random bin-picking.
6. Optical sensing technology, used to detect driver fatigue and distraction for use in self-driving cars.

Regarding the impact of AI, Ieong referred to two job reports: one by Oxford, which concluded that up to 47% of current jobs were at risk from automation, and one by the OECD, which concluded the number was only 9%. He listed possible reasons for the huge discrepancy:

1. Adopting new technology is normally a slow process (though in China it is much faster).
2. Workers can adjust to changing technology by retraining and retooling to do other tasks.
3. Technology change generates more jobs, though this has resulted in a shortage of AI and data specialists.

Mr Ieong identified a number of things that can be done to develop the talent needed to support AI in Hong Kong:

• Training young people.
• Attracting skilled immigrants.
• Retraining people whose jobs are replaced by AI.

He pointed out that cities such as Paris and San Francisco provide free coding universities and even free housing for students, and work with companies to supply tech workers.

Ieong concluded his presentation stating: “AI will take over a lot of tasks, but will free humans to adopt more value-added, personalized and analytical roles,” adding that a massive amount of tech talent is needed to implement AI in industry.

Journey to AI and rise of platform-centric business architecture

Who are the leading industry disruptors? IBM sought the answer to this question by surveying 12,000 CEOs, including 1,200 in China, and found that 74% said the main disruptors were their peers that had moved to platform-centric business models; start-ups were not the problem. And 70% said they were using data more in their business.

David Chow, Partner and General Manager of IBM Hong Kong’s Global Business Services, provided these numbers in a talk on platform-centric business architecture. Mr Chow emphasized the importance of data for the success of AI. He pointed out that despite the fantastic amount of data on the Internet, 80% of all data is held by large corporations and is not available on the Internet, but that only two percent of this 80% is harvested using AI.

Chow asked, “How can companies use AI to take advantage of their own data, outside data and procured data?” He explained that AI capabilities included natural language processing, reasoning, processing text, audio and visual data, and providing data insights and computer architecture.

AI can provide business growth, an enhanced customer experience, decision support, talent engagement, and process and system transformation, he explained.

Regarding employment, for example, IBM has about 300,000 employees globally and uses AI to compare candidates over time both to help recruiters identify candidates most likely to succeed in a position and to examine each employee’s digital footprint to help them become more effective.

Chow described IBM’s cognitive customer care platform. Since chatbots may not interest some users anymore, IBM was looking for ways to help consumers more effectively. It launched two new bots in collaboration with Hang Seng Bank, called Dori and Haro. HARO can understand and process Cantonese and a mixture of Cantonese and English, and is used to handle general customer inquiries, engaging in interactive dialog to help them manage their personal finances. DORI can search for credit card merchant discounts and online store offers.

IBM conducted a case study with leading insurers in Hong Kong to develop a 24 hour assistant that can help agents with the questions their customers are asking them. The assistant has a tone analyzer that understands the person’s tone, style and emotional state, so that IBM can develop a personality profile and give a tailored customer experience. “Now we can use data to provide better products and services,” Chow said.

IBM’s cognitive-capture solutions help organizations identify and classify documents, analyze content and context, and extract and flag documents for review, including forms, trade transactions and even letters, Chow explained.

In the healthcare field, about 700,000 scientific articles are published each year, Mr Chow pointed out. IBM helps medical specialists identify the latest information in their field of interest to help improve institutional knowledge and best practices.

“AI is helping make life better at work and at home,” Mr Chow concluded.

AI in networking and security

“By 2020, insights-driven businesses will steal US$1.2 trillion per annum from their less-informed peers,” predicted Garrick Ng, Chief Technology Officer of Cisco Hong Kong, Macau and Taiwan. Ng explained why ML is emerging now:

1. Lower storage costs.
2. Much higher central processing unit (CPU) speed, which allows more to be done.
3. Algorithm maturity and efficiency.

Ng also explained the difference between AI, ML and DL. DL is a subset of ML, which in turn is a subset of AI. While AI is a technique that allows computers to mimic human behavior, ML gives computers the ability to learn from data. This is the present focus, since it is the recent explosive increase in data that allows machines to learn. But the neural network in DL is a powerful and diverse tool used at Cisco.

Cisco is involved in cognitive collaboration, applying it in the form of bots and virtual assistants, computer vision (CV), and audio and visual technology.

In CV, computing ability allows the computer to be trained to do tasks better and faster than humans can. “But we will not see Terminator-type capability in robots,” he said. “CV can be used to do only very specific tasks that can’t be transferred to other functions.”

He showed an example of how CV can be used in a video conference to count people, adjust the temperature, identify and zoom in on the active speaker, and connect names to faces to make work more productive. In another example, Cisco’s Webex assistant uses speech recognition to allow voice control and natural language understanding, which permits dialog management and question-and-answer sessions, as well as room booking and temperature adjustment through voice commands. “These changes won’t transform life,” Ng said, “but they will make small improvements.”

Another AI function is noise detection in meetings. AI can detect and classify non-human noises, and transform the noise data or mute it.

Cyber-security is being improved through AI, said Ng. Cisco blocks 20 billion threats per day. By looking at initial data packets and the sequence of packet lengths and times, Sisco can map the entire internet in a three-dimensional flow, ‚identifying the good guys and the bad guys‘.

Cisco provides predictive analysis for network outages, explained Ng. On one network with 57,000 devices and 60 platforms, Cisco can predict an outage 15 hours before it happens and provide a preventive fix within one hour. “ML can give these precise predictions thanks to massive data,” Ng explained. “In the ML universe, data is king, even more important than algorithms. Whoever has the best data will have the best system.”

“The main benefits of AI and ML,” concluded Ng, “will be intelligent infrastructure and improved business efficiency.”