Lian Jye Su
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Lian Jye Su In The News
CNN (2023-03-16)
“Coding is like learning how to drive — as long as the beginner gets some guidance, anyone can code,” said Lian Jye Su, an analyst at ABI Research. “AI can be a good teacher.”
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A3 Association for Advancing Automation (2023-02-20)
“The situation is quite dire,” says Lian Jye Su, research director at market analyst firm ABI Research, noting that the problem isn’t confined to North American manufacturing.
“China also faces similar issues in keeping its factory workers. One report stated that more than 60% of Chinese manufacturing workers were born between 1975-1985 and that very few young adults are interested in manufacturing jobs due to higher salary expectations and education levels.”
If demographics are a guide, then the labor crisis isn’t going away anytime soon.
“The manufacturing sector will always be expected to produce goods in a highly competitive, time-sensitive, cost-effective, and safe manner. Coupled with the ever-declining birth rate, the labor shortage in manufacturing will likely remain, and automation is the only way out,” says Su.
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CNN (2023-02-16)
“The tone of the responses is unexpected but not surprising,” Lian Jye, a research director at ABI Research, told CNN. “The model does not have contextual understanding, so it merely generated the responses with the highest probability [of it being relevant]. The responses are unfiltered and unregulated, so they may end up being offensive and inappropriate.”
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Venture Beat (2023-02-15)
ABI Research, a global technology intelligence firm, recently forecast that the edge ML enablement market will exceed $5 billion by 2027. While the market is still in a “nascent stage,” according to Lian Jye Su, research director at ABI Research, companies looking to ease the challenges of edge ML applications are turning to a variety of platforms, tools and solutions to boost an end-to-end MLops workflow.
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Technology for You (2023-02-10)
For the past three years, business leaders and organizations have faced an unyielding procession of challenges. As we usher in 2023, many of those challenges persist, and new ones are emerging. Yet, as unwavering as the challenges have been, technology and innovation have proven to be just as resilient. In its new whitepaper, 37 Technology Stats You Need to Know for 2023, global technology intelligence firm ABI Research has identified and highlighted the most impactful forecasts that illuminate the direction in which digital transformation is truly heading.
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CNN (2023-02-09)
Lian Jye Su, a research director at tech intelligence firm ABI Research, believes consumers and businesses would be happy to embrace a new way to search as long as “it is intuitive, removes more friction, and offers the path of least resistance — akin to the success of smart home voice assistants, like Alexa and Google Assistant.”
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IT Pro Today (2023-01-04)
A confluence of many factors – powerful computing in small form factors, edge computing, the integration of IT and operational technology (OT), 5G, and even the COVID-19 pandemic – has buoyed the adoption of artificial intelligence in a variety of industries. Valued at $93.5 billion in 2021, research firm Market View Research predicts the global adoption of AI will grow at an astounding 38% compounded annual growth rate until 2030.
So where does AI go from here? The experts shared six AI predictions for 2023.
Related: 5 Ways to Prevent AI Bias
1. Generative AI will continue to garner attention, said Mike Krause, AI solutions director at Beyond Limits, an enterprise AI software firm. Generative models, like the digital image generator DALL-E, analyze data and interpolate to create something brand new.
But generative AI models are not just good at creating digital images like DALL-E does. They are being used to discover new materials for battery design, carbon capture, and loads of other innovations, Krause said, who predicts that generative models will reach new heights in 2023. For example, expect developments in the healthcare space for vaccine modeling, drug discovery, and even personalized medicine supported by training data generated from electronic medical records, Krause said.
2. AI will become less of a black box, said Lee Howells, head of artificial intelligence at professional services firm PA Consulting. Howell predicts 2023 will see more organizations voluntarily publicizing their AI principles and outlining their processes.
“There will be greater use of ‘explainable AI’ over black box models in areas that directly affect individuals,” Howell said. “Organizations with published AI principles and demonstrably ethical use of AI and data will see greater acceptance by the public of the use of their data.”
“As more and more AI [systems] are being deployed across various sectors, regulators are keen to ensure that all AI models are behaving the way they should, free from any bias and discrimination,” noted Lian Jye Su, AI and ML research director at ABI Research. He argued that while explainable AI will make the process more transparent, it requires several market developments to happen, including a supportive model development and deployment infrastructure that can show the relationship between the inputs and outputs and processing layers, the introduction of AI models that are explainable by default, and clear regulatory guidelines and principles.
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Assembly (2022-12-13)
“Third-party programming software is designed to be agnostic to robotics hardware, meaning it can be used on most, if not all, industrial robots [marketed] by major brands,” says Lian Jye Su, robotics research director at technology intelligence firm ABI Research Inc. “Traditional robot software tends to very low level and requires high technical skills.
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CNN (2022-12-05)
Still, Lian Jye Su, a research director at market research firm ABI Research, warns the chatbot is operating “without a contextual understanding of the language.”
“It is very easy for the model to give plausible-sounding but incorrect or nonsensical answers,” he said. “It guessed when it was supposed to clarify and sometimes responded to harmful instructions or exhibited biased behavior. It also lacks regional and country-specific understanding.”
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Robotics and Automation News (2022-11-29)
Lian Jye Su, industrial, collaborative, and commercial robotics research director at ABI Research, says: “No doubt the market is affected by a series of headwinds, including high-interest rates, the recent withdrawal of major solution providers from the last mile delivery sector, and the lack of scalability in highly fragmented markets, such as agriculture and construction.
“But labor shortages, the focus on workplace safety, and rising costs have led companies to deploy robotics automation across various sectors.”
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Techgoondu (2022-11-17)
ABI Research, a global technology intelligence firm, said this was a huge development because it significantly boosts AI inference capabilities in phones.
“One real benefit is the ability to perform on-device natural language preference inference, enabling real-time on-device speech-to-text and text-to-speech across multiple languages,” said Lian Jye Su, research director for AI and machine learning at ABI Research.
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CNN (2022-11-07)
Although the update would be seemingly minor, experts say it may signal broader changes are coming and could require extensive artificial intelligence training. Lian Jye Su, a research director at ABI Research, said having two trigger words allows the system to more accurately recognize requests, so the move to one word would lean on a more advanced AI system.
“During the recognition phase, the system compares the voice command to the user-trained model,” Su said. “‘Siri’ is much shorter than ‘Hey Siri,’ giving the system potentially less comparison points and higher error rate in an echo-y, large room and noisy environments,” such as in the car or when wind is present.
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CNN (2022-09-17)
“With Twitter and Apple now also enabling this feature, it is clear that this is a trend that many mobile users demand from these platforms,” said Lian Jye Su, research director at market research firm ABI Research. “Since the barrier to switching messaging platforms is near zero, rich and user-friendly features have become a critical competitive advantage.”
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The Washington Post (2022-08-05)
Amazon hasn’t had much success with household robots, but the iRobot acquisition and the company’s strong market reputation provide a “massive foothold in the consumer robot market” that could help Amazon replicate the success of its Echo line of smart speakers, said Lian Jye Su, a robotics industry analyst for ABI Research.
Su said it also illustrates the shortcomings of consumer robotics vendors like iRobot, which struggled to expand beyond a niche product and was in a “race-to-the-bottom” competition with Korean and Chinese manufacturers offering cheaper versions of a robotic vacuum.
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The Business Times (2022-08-04)
“It feels like the early days of the buy now, pay later market, where the absence of regulations and market supervision led to bullish sentiments,” said Su Lian Jye, research director at ABI Research.
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Loss Prevention Magazine (2022-07-26)
Lian Jye Su, principal analyst for artificial intelligence at ABI Research, a global technology market advisory, described some real-world use cases for face recognition in retail.
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Robotics and Automation News (2022-07-22)
Lian Jye Su, industrial, commercial, and collaborative robotics research director at ABI Research, says: “More precisely, businesses are looking for robotics solutions that are mobile, can navigate through obstacles in unstructured environments, and work alongside human employees without much supervision and control.”
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Industrial Automation (2022-07-14)
The investment market worldwide was relatively muted in 2020, as fewer deals were concluded due to the COVID-19 pandemic. However, the current labour shortage induced by COVID-19 and the ongoing supply chain crunch are leading more businesses to look for ways to automate labour-intensive, repetitive, and hazardous tasks. "More precisely, businesses are looking for robotics solutions that are mobile, can navigate through obstacles in unstructured environments, and work alongside human employees without much supervision and control," said Lian Jye Su, Industrial, Commercial, and Collaborative Robotics Research Director at ABI Research.
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The Boston Globe (2022-06-23)
Lian Jye Su, research director for AI and robotics at ABI Research, said fully autonomous robots like Proteus are more expensive up front. But he added that they’re cheaper to deploy because “you don’t need to design a specific environment for the robot to work in.” For instance, warehouse operators won’t need to erect physical barriers to separate people from robots. Nor will they have to set up radio beacons or barcodes to help the robots find their way.
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CIO (2022-06-17)
Enterprises looking to get started have plenty of options, says Lian Jye Su, principal analyst at global technology intelligence firm ABI Research. “Public cloud players such as Alibaba, Amazon, Google, and IBM offer researchers services to remotely run quantum programs and experiments,” Su says. Developers can now build quantum applications using IBM’s Qiskit, Google’s Cirq, Amazon Braket, and others, which are “open-source libraries designed for optimization of quantum circuits for quantum-classical or quantum-only applications, including machine learning,” Su said. “All these services are available online.”
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CIO World Asia (2022-06-13)
In recent years, the industry has witnessed the migration of Machine Learning (ML) closer to the data source to create a better user experience and enhance privacy. To ease the challenges in design and development and accelerate adoption, many companies are offering development platforms, tools, libraries, and solutions for edge ML applications. As the adoption of these edge ML enablement platforms and solutions continue to grow, ABI Research, a global technology intelligence firm, is forecasting the edge ML enablement market to exceed US$5 billion by 2027.
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Security Brief Asia (2022-03-18)
Since the emergence of big data, the attention on legitimate and transparent data collection, management and analytics is now greater than ever.
To better protect the welfare of their citizens, guarantee national security and safeguard their sovereignty and competitiveness, governments around the world have introduced privacy laws and data protection regulations.
However, in its new whitepaper, 'Data Governance: Definitions, Challenges, and a Universal Framework' global technology intelligence firm ABI Research argues that the current laws and regulations do not go far enough.
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The Boston Globe (2021-12-29)
Lian Jye Su, a Singapore-based robotics analyst for the US firm ABI Research, said that indoor drones presently comprise no more than 2 percent of the overall drone market. “But with the right solution like Cleo Robotics and Corvus Robotics,” Su added, “the market can potentially double or triple to 5 percent in the next five years.”
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The Business Times (2021-12-20)
Su Lian Jye, principal analyst at ABI Research, noted Tencent has also been expanding its WeChat Pay ecosystem in South-east Asia, although the international growth may have been slowed down by the pandemic and China's tech crackdown. "But the development should resume once the borders reopen and travel restrictions ease up," he said.
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Lifewire (2021-10-07)
"Most, if not all, AI nowadays are still focused on a single task," he told Lifewire in an email interview.
"Therefore, the estimate is that we will need one or two new generations of hardware and software before technological singularity is within reach. Even when the technology is mature, we also need to assume that the developer(s) of AI is given complete authority over its creation without any check and balance and a built-in 'kill' switch or fail-safe mechanism."
True Concerns About AI
The real danger of AI is its ability to divide humans, Su said. AI already has been used to seed discrimination and spread hatred through deepfake videos, he noted.
And, Su said, AI has helped "social media giants create echo chambers through personalized recommendation engines, and foreign powers alter political landscapes and polarize societies through highly effective targeted advertising."
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Mobile ID World (2021-09-22)
ABI Research is forecasting major growth in the audio chipset market. The firm’s latest report predicts that tech manufacturers will ship more than 2 billion devices with a chipset designed solely for ambient sound or natural language processing in the leadup to 2026.
ABI Predicts Edge Sound Applications Will Drive Audio Chipset Market
According to ABI Research, much of that growth can be attributed to recent advancements in audio chipset design. As it stands, many of the top voice assistants (including Siri, Google Assistant, and Amazon Alexa) operate in the cloud, and cannot run without an internet connection. That limits the performance of those systems in certain situations, and makes voice technology less appealing in industries that have privacy or security concerns.
Dedicated audio chipsets, on the other hand, enable voice and sound processing at the edge. That means that the systems will still work while offline, and that they can be integrated into the design of the device itself to provide a higher level of security.
That transition to the edge audio environment is already underway in the consumer sector. Apple revealed that Siri would have some offline utility earlier this year, while Google is reportedly developing a new Tensor System-on-Chip (SoC) to enhance its face and speech recognition capabilities. The first Tensor Processing Unit debuted all the way back in 2016.
In the meantime, ABI expects ambient sound processing technology to be popular in industrial and manufacturing facilities. Sensors can analyze the sounds of machines to watch for signs of early wear and tear, giving operators the chance to carry out predictive maintenance and fix their equipment before a machine breaks down entirely.
“NLP and ambient sound processing will follow the same cloud-to-edge evolutionary path as machine vision,” said ABI Machine Learning and AI Principal Analyst Lian Jye Su. “At the moment, most of the implementations focus on simple tasks, such as wake word detection, scene recognition, and voice biometrics. However, moving forward, AI-enabled devices will feature more complex audio and voice processing applications.”
ABI noted that many chip manufacturers are forming partnerships to improve their technology. For example, Syntiant and Renesas are working together to build a processor that supports both computer vision and voice applications, while Qualcomm has allied with the language processing start-ups Audio Analytics and Hugging Face. The tech giant has also released chipsets designed for use in smart audio devices.
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The Business Times (2021-09-14)
But as competition heats up and players in South-east Asia amass more firepower, Grab must continue to “invest heavily in research and development”, said Su Lian Jye, a principal analyst at global tech market advisory firm ABI Research.
He added that these investments should go towards emerging technology such as artifical intelligence and last-mile delivery. Grab can also look to continuously improve its user experience and optimise its existing operation. “That’s the best way to differentiate itself from its regional peers”, he said.
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Fortune Magazine (2021-09-02)
“ByteDance’s entire business is based on recommendation systems,” says Lian Jye Su, Principal Analyst at global tech market advisory firm ABI Research, referring to TikTok’s Beijing-based parent company.
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Fortune (2021-05-20)
“In order to stay successful and relevant, the CEOs of tech vendors need to dedicate a lot of energy to maintain[ing] good relationship with the government,” says Lian Jye Su, principal analyst at ABI Research in Singapore. “Not all CEOs want to dedicate their time and energy on this task or have the right skillset to do so.”
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Tech Target (2021-05-05)
"The prospect for both jobs is very rosy," said Lian Jye Su, who, as a principal analyst at ABI Research, is responsible for orchestrating research relating to robotics, artificial intelligence and machine learning.
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Computer Weekly (2021-04-14)
Lian Jye Su, artificial intelligence and machine learning principal analyst at tech market advisory firm ABI Research, said: “Microsoft has attempted to develop its own conversational AI in the past through Cortana. The company also acquired conversational AI startup Semantic Machines in 2018. However, all these have yet to allow Microsoft to replicate the success of Amazon, Google and Apple in the consumer space, and IBM in the enterprise space, and to compete directly with them.”
According to Jye Su, the Nuance acquisition demonstrates the value of conversational AI in its future roadmap.
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E Commerce Times (2021-04-13)
Lian Jye Su, artificial intelligence and machine learning principal analyst at ABI Research, explained in a statement that Microsoft has attempted to bolster its own conversational AI both through in-house development, with Cortana, and through acquisition, by buying Semantic Machines in 2018.
"However, all these have yet to allow Microsoft to replicate the success of Amazon, Google, and Apple in the consumer space and IBM in the enterprise space," he asserted.
Su added that Microsoft is also feeling the threat from the conversational AI capabilities demonstrated by AI players in China, such as Alibaba, Baidu, iFlyTek, Mobvoi, Zhuiyi, and Unisound.
"The acquisition of Nuance Communications will elevate Microsoft's capabilities and allow Microsoft to develop both consumer and enterprise-focused conversational AI solutions," he said.
He added that the move by Microsoft also acknowledges the importance of conversational AI and natural language processing capabilities to the future of AI.
"This announcement validates the
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Information Age (2021-04-13)
Voice recognition tech will be key to Microsoft’s growth plans, according to ABI research and artificial intelligence and machine learning principal analyst Jye Su.
“This is a recognition from Microsoft on the value of conversational artificial intelligence in its future roadmap,” Su said.
“The acquisition of Nuance Communications will elevate Microsoft’s capabilities and allow Microsoft to develop both consumer and enterprise-focused conversational artificial intelligence solutions.”
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The Business Times (2021-04-13)
Profitability is "critical" for Grab to become sustainable and to withstand challenges from newcomers to the market, noted Su Lian Jye, principal analyst at global tech market advisory firm ABI research.
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The Boston Globe (2021-04-13)
Microsoft’s success with Nuance is by no means assured, said Lian Jye Su, principal analyst at ABI Research. He pointed to IBM’s Watson Health initiative, which has also tried to apply AI technologies to health care. Earlier this year, The Wall Street Journal reported that IBM is considering a sale of the business, which generates annual revenue of $1 billion, but no profits.
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Computer Weekly (2021-04-13)
Commenting on the acquisition, Lian Jye Su, artificial intelligence and machine learning principal analyst at tech market advisory firm ABI Research, said: “This is a recognition from Microsoft on the value of conversational AI in its future roadmap. Microsoft has attempted to develop its own conversational AI in the past through Cortana. The company also acquired conversational AI startup Semantic Machines in 2018.
“However, all these have yet to allow Microsoft to replicate the success of Amazon, Google and Apple in the consumer space and IBM in the enterprise space, and to compete directly with them. Microsoft is also feeling the threat from the conversational AI capabilities demonstrated by AI players in China, such as Alibaba, Baidu, iFlyTek, Mobvoi, Zhuiyi and Unisound. The acquisition of Nuance Communications will elevate Microsoft’s capabilities and allow Microsoft to develop both consumer and enterprise-focused conversational AI solutions.”
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Smart Cities World (2021-04-07)
A report by ABI says such devices will feature deep learning models to automate and augment decision-making in applications such as intelligent traffic management.
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iHLS - Israel's Homeland Security (2021-04-05)
Security Cameras with artificial intelligence will be the smart city norm. The global installed base of smart cameras with an Artificial Intelligence (AI) chipset (a set of electronic components in an integrated circuit designed to work together) will reach over 350 million in 2025. This is the forecast of the global tech market advisory firm ABI Research. Over 65% of cameras shipped in 2025 are expected to come with at least one AI chipset. These cameras will feature deep learning (DL) models to automate and augment decision making in applications such as intelligent traffic management, autonomous assets, pedestrian flow monitoring and management, physical and perimeter security, and preventive threat detection.
Aside from low latency, data privacy concerns have also driven the adoption of AI at the edge as information can be processed without being sent to the cloud.
At the moment, most of the workloads are performed by either DL models hosted in the cloud, offered by video analytics vendors such as SenseTime, Ipsotek, icentana, and Sentry AI, or DL inference in smart cameras and network video recorders, such as HikVision and Dahua.
Two technology trends will likely further catalyze the deployment of DL-based machine vision. “The first one is edge computing. Instead of deploying specific DL models on smart cameras that are multiple times more expensive than legacy cameras, city and county governments can host DL models on gateways and on-premise servers. This allows data to be processed and stored at the edge, providing faster response time than relying on cloud infrastructure. The second is 5G. Communication service providers will be able to offer dedicated network resources to host microservices, six nines reliability service assurance, seamless device connectivity, and onboarding to support DL-based machine vision in the smart city,” explains Lian Jye Su, Principal Analyst at ABI Research.
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Biometric Update (2021-04-05)
Tech market advisory firm, ABI Research predicts that inclusion of AI chipsets in security cameras in smart cities will become the norm, reaching over 350 million in 2025. Featuring deep learning, these cameras will apply to areas around society, expanding on current CCTV practices. Abi suggests that data privacy concerns have also driven the take-up of AI at the edge, mainly because information can be processed without being sent to or stored on the cloud.
Israeli chip-developer Hailo have designed a deep learning processor that makes integrating the chip into edge devices easier for its customers. The expansion of facial recognition use being a key market driver for Hailo, leveraging accelerated AI will also prove applicable in other biometrics for products in smart cities.
“..Moving forward, the technology vendors that are successful in the smart city are those which will be able to demonstrate transparent and explainable DL models and those who show willingness to embrace open and common standards and ethical frameworks,” says Lian Jye Su, Principal Analyst of AI & Machine Learning at ABI Research.
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Wall Street Journal (2021-02-25)
Today, the best applications for AI are built around specific, often repetitive tasks, says Lian Jye Su, principal analyst at ABI Research, a global tech market advisory firm. The applications allow businesses to leverage big data and develop systems that can make decisions based on patterns and trends within a dataset, improving their algorithms as new data arrives.
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Computer Weekly (2021-01-18)
The challenges facing many enterprises involve a lack of the right people to manage data and advanced tools for analytics, says Lian Jye Su, principal analyst for ABI Research.
“The rapid advancement of data acquisition, storage architecture and analytics tools means enterprises are playing catch-up,” says Su. “Many lack predictive analytics, dashboards and visualisation tools and skilled people to run them, and this is a serious challenge.”
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Nikkei Asian Review (2021-01-14)
Su Lian Jye, principal analyst at technology analysis company ABI Research, said he has not observed an exodus from WhatsApp in Singapore.
"I think the prevailing attitudes that make WhatsApp sticky in Singapore are in the strength of WhatsApp's branding, the ease of use and simplicity," he said. "In the West, privacy and personal data protection are the main concerns. People are actively seeking out tools and solutions that prioritize these aspects."
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The Business Times (2020-12-18)
Bank Jago's focus on small and medium enterprises is firmly aligned with Gojek's corporate strategies, said Su Lian Jye, principal analyst at ABI research, adding: "This is a win for Gojek in the long run."
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Tech HQ (2020-12-04)
“Qualcomm’s addition of a large AI accelerator and TinyML to its next-generation 5G mobile platform is a game-changer for 5G mobile devices,” said Lian Jye Su, the principal analyst at tech market advisory firm, ABI Research.
“As more users switch to 5G mobile devices in 2021, embedded AI will be a critical success factor for enhanced user experience.”
Qualcomm says the new Snapdragon features a completely re-engineered AI Engine, the Hexagon 780. The chipmaker believes this redesign will help software developers working on Snapdragon 888-powered devices to make improvements in a number of areas including live-motion tracking of objects (to assist autofocus in video and photography, for instance); automatically adjusting audio to account for the device’s surrounding ambient environment; improving augmented reality filters in AR-capable apps. The AI computational performance is said to be so remarkable that Qualcomm says that the Snapdragon 888’s AI processing can erase a recorded character from a video scene and insert someone else instead – in real-time.
“With the AI capabilities of Snapdragon 888, OEMs can pack more and more AI enhancements into various applications in their mobile device, including beautification, edge detection, depth sensing and low-light noise reduction in the camera, more secure facial and fingerprint unlock in biometric identification, more fluid gaming performance and smarter app recommendations and battery optimization,” noted ABI’s Lian.
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Nikkei Asian Review (2020-11-12)
Su Lian Jye, principal analyst at technology analysis firm ABI Research, told Nikkei Asia that incumbent carriers in highly digitalized countries like Japan also have had to fend off new challengers. "In Japan, NTT Docomo, KDDI and SoftBank are challenged by Rakuten, a fourth telecommunications company that has no legacy infrastructure and is fully leveraging virtualization and cloud technology for its network equipment," he said.
Su said, however, that virtual telecommunications companies pose a bigger threat to Singtel than they do elsewhere because of Singapore's tiny domestic market. Whereas operators in countries like Japan and South Korea serve much larger populations, Singtel has to fight to maintain its hold in a small home turf with many players.
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Loss Prevention Magazine (2020-11-10)
“It is a rarity that you’ll be able to just load on the software and leverage system infrastructure as is,” said Bartol. Retailers need to consider whether to deploy the entire system on premise or leverage cloud computing, added Lian Jye Su. “Leveraging cloud computing will result in better flexibility and scalability in terms of cost,” he said.
Cost it out. “Some love it, and others have looked at it and said, ‘No way, I can’t afford it,’” said one longtime LP executive. Lian Jye Su noted that deploying AI technology requires a lot of spending on AI hardware, which may not be ideal for retailers that are on tight budget. A potential option is an “as-a-service” model, where a retailer is charged a subscription fee associated with continuing usage of the system, he said.
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Robotics Industries Association (2020-11-10)
When compared to main industrial and cobot adopters in electronics, automotive and mechanical manufacturing, the pharmaceutical manufacturing industry is a “niche and mature industry,” says Lian Jye Su, Principal Analyst at global tech market advisory firm, ABI Research.
At its healthcare research hub on the Texas Medical Center campus, ABB is experimenting with a mobile version of its YuMi cobot. Credit: ABB “The industry has been controlled by few major pharmaceutical firms with a very established supply chain and global footprint. This means that even when the demands for pharmaceuticals skyrockets due to Covid-19, there is no spike in new pharmaceutical factories, as compared to the massive ramp up in PPE manufacturing such as mask, protective shield and rubber gloves.”
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Nikkei Asian Review (2020-10-03)
History may repeat itself, said Su Lian Jye, principal analyst at ABI Research. Su said the deployment of 4G in the region can serve as a reference point for how the 5G race may pan out.
"With the lack of both enterprise and consumer-facing applications, telcos in Southeast Asia will generally wait for the use cases to mature in other big markets before bringing them to their local markets," he said.
Singapore was the first ASEAN market to launch 4G networks in 2011, followed by the Philippines in 2012, Malaysia and Thailand in 2013, Cambodia and Indonesia in 2014, Myanmar in 2016 and Vietnam in 2017.
"If a telco has a relatively mature 4G network, this means the investment in 4G has already been recouped and the telco may be ready for the next upgrade, compared with a telco that just recently rolled out its 4G network," Su said.
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EET Asia (2020-08-19)
Despite the current pandemic-related downturn, the demand for edge AI chips will grow to outstrip demand for cloud AI chips for the first time in 2025, according to a new report from ABI Research.
Demand for Edge AI chips is on hold due to current pandemic
Demand for edge AI chips in sectors such as industrial is paused due to the pandemic, but will rebound in 2022, says the report
By 2025, the edge AI chip market will reach $12.2bn in revenue, whereas cloud AI chip revenues will reach $11.9bn in the same time frame.
While most AI training and inference workloads are handled in the cloud today, ABI Research predicts that growth in the edge AI chipset market will be driven by increasing demands for low latency and data privacy plus the availability of low-cost ultra-low-power chips designed specifically for this application. AI training and inference will be processed in gateways and all types of edge devices, right down to sensor nodes in the next five years.
“By integrating an AI chipset designed to perform high-speed inference and quantized federated learning or collaborative learning models, edge AI brings task automation and augmentation to device and sensor levels across various sectors,” said Lian Jye Su, principal analyst at ABI Research. “So much that it will grow and surpass the cloud AI chipset market in 2025.”
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EE News Europe (2020-08-11)
"As enterprises start to look for AI solutions in the areas of image and object recognition, autonomous material handling, predictive maintenance, and human-machine interface for end devices, they need to resolve concerns around data privacy, power efficiency, low latency, and strong on-device computing performance," explains Lian Jye Su, Principal Analyst at ABI Research.
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Tech Target (2020-07-28)
5G is the first cellular technology generation that enterprise use cases will play a larger role in than consumer use cases. Learn more from ABI Research's 5G Technology Summit.
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Tech Target (2020-06-10)
However, machine learning and natural language processing, or NLP, another member of the AI technology family, enable chatbots to be more interactive and more productive. These newer chatbots better respond to user's needs and converse increasingly more like real humans. "Digital assistants such as Siri, Google Assistant and Alexa, are based on machine learning algorithms, and this technology may find its ways in new customer service and engagement platforms that replace traditional chatbots," said Lian Jye Su, a principal analyst at ABI Research.
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Tech Target (2020-05-19)
Lian Jye Su, a principal analyst with ABI Research, identified two broad areas where organizations can use AI for financial gain.
Lian Jye SuLian Jye Su
"When it comes to revenue generation, I think it involves legitimate and appropriate monetization of existing internal or user data, or commercialization of internal AI practices and software," he said.
Organizations that commercialize internal AI practices and software "can choose to make their own internal AI-enabled products available to their clients or potential customers via licensing or via open source," Su said. He pointed to global manufacturer Foxconn, explaining that it developed its industrial AI platform with other partners and now offers it for sale through a spinoff entity.
Most organizations, however, aren't large enough to easily scale an AI-enabled product and roll it out for external sales, Su acknowledged.
"In the early stage [of AI use in business], I believe it is mostly about productivity gains and cost savings," rather than driving revenue with new AI products, Su said. But, he added, organizations that have learned to use AI to make their own internal processes faster, smoother and more reliable will also see revenue gains: Getting to market faster, after all, confers an advantage.
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TechTarget (2020-04-28)
"AI is very important to the enterprise in two main ways, namely automation and augmentation. Automation allows companies to scale their operation without the need to add more headcounts, while augmentation increases productivity and optimizes internal resources," said Lian Jye Su, a principal analyst at ABI Research.
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Robotics Business Review (2020-04-21)
y Lian Jye Su, ABI Research | April 20, 2020
The worldwide outbreak of COVID-19 has kept consumers at home in recent weeks and turned the retail industry upside-down. Public health awareness has motivated shoppers (primarily of food and essentials) to keep their outings brief and contact-free. Once our daily lives and routines re-enter a state of normalcy, the effects of the pandemic could precipitate a greater demand for retail stores with no workers, but to date, the unmanned store has not caught on.
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New Straits Times (2020-04-11)
The global market for such machines -- known as telepresence robots -- could rise by 20 to 35 percent this year because of Covid-19, and could hit US$400 million, according to Lian Jye Su, tech analyst at ABI Research.
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Industry Week (2020-03-17)
As a recent ABI report shows, the market is steadily embracing AI’s potential. Specifically, the total installed base of AI-enabled devices in industrial manufacturing is expected to reach 15.4 million in 2024. As such, the demands for the deployment of AI in manufacturing have led to the emergence of startups that work on AI algorithms to increase and optimize production processes in the manufacturing setting other than machine vision-based solutions. These AI algorithms can discover patterns, recognize conditions, and provide early warnings and explanations on current operation status and abnormalities. ABI Research, a global tech market advisory firm, finds SparkCognition and Sight Machine to be the leaders in industrial AI focusing on production process optimization.
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Modern Materials Handling (2020-03-03)
According to a recent analysis by global tech market advisory firm ABI Research, total shipments for machine vision sensors and cameras will reach 16.9 million by 2025, creating an installed base of 94 million machine vision systems in industrial manufacturing. Of that installed base, 11% will be deep learning-based.
Machine vision systems are a staple in production lines for barcode reading, quality control, and inventory management. “These solutions often have long replacement cycles and are less prone to disruption. Due to the increasing demands for automation, machine vision is finding its way into new applications,” said Lian Jye Su, Principal Analyst at ABI Research. “Robotics, for example, is a new growth area for machine vision: Collaborative robots rely on machine vision for guidance and object classification, while mobile robots rely on machine vision for SLAM and safety.”
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Nikkei Asian Review (2020-02-19)
Su Lian Jye, principal analyst at technology analysis company ABI Research, told the Nikkei Asian Review that current trends in the global auto industry are in line with the government's policy direction.
"With big markets like China, the U.S. and India all committed to EVs, it will drive car manufacturers to speed up their innovation and expand their revenue streams," he said.
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Fortune (2020-02-11)
“I think what the government has been doing right now, such as restricting the use of masks and keeping a calm tone, is a plus. That’s something they’ve learned through SARS that over communication is better than no communication at all,” said Lian Jye Su, principal analyst at Singapore-based ABI Research.
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Information Week (2020-01-27)
ABI Principal Analyst Lian Jye Su said in his experience, most executives have some sort of ideas around the basics of machine learning and the "garbage in, garbage out" principle, but most of them believe machine learning models are black boxes and that machine learning requires massive amounts of data.
"I would argue that this is mainly due to the prevalence of convolutional neural networks that require large amounts of data and somehow work better with extra numbers of convolutional layers, and I believe such perceptions will slowly disappear once other machine learning algorithms become more popular," said Su.
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Nikkei Asian Review (2020-01-22)
Su Lian Jye, principal analyst at technology analysis specialist ABI Research, praised the city-state's approach in garnering support from countries and businesses for its AI governance agenda, but warned that it would take time to bear fruit.
Noting that AI powerhouses such as the U.S. and China are pursuing different paths for the technology, Su said a small country like Singapore may have difficulty helping others find common ground.
"Without help and influence from the private sector, the Singapore government will find it rather difficult to lead and shape global AI discourse," Su said.
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Fortune (2020-01-20)
“China still depends heavily on Western technology,” says Lian Jye Su, principal analyst at ABI Research in Singapore. “That explains the sense of urgency from Beijing to accelerate China’s R&D into these sectors.”
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Nikkei Asian Review (2020-01-15)
One problem for many retailers is that they lack the resources to invest in AI, said Su Lian Jye, Principal Analyst at technology analysis firm ABI Research. "Cost is definitely a key hurdle."
With margins for brick-and-mortar retailers getting squeezed by online retailers, heavy investment in AI solutions can be a hard pill to swallow, particularly when return on investment is not that obvious, Su explained.
Su estimates that it may take another five to 10 years before AI greater traction among retailers in Southeast Asia. "Self-checkout counters which are very prevalent in countries like Australia and the U.S. only made their way into Singapore a good five years later."
"Here we are talking about AI that requires a lot more technical know-how and good quality data. Hence I am a bit more conservative," he added.
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CNN Business (2020-01-10)
"As demonstrated by Neon, we are still very far from a commercially ready AGI solution," principal analyst Lian Jye Su of ABI Research said. "The best AI nowadays are narrow [ones] that performs singular tasks very well, such as the camera AI in our smartphones, the defect inspection camera AI on an assembly line, and the facial recognition AI in payment terminals."
According to Su, we should "always question the intention and financial rationale behind attempts to make artificial general intelligence a reality."
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Nikkei Asian Review (2020-01-02)
According to global technology analysis company ABI Research, full-scale automated retail stores worldwide will grow exponentially from fewer than 500 this year to more than 44,000 by 2023.
Still, for Singapore at least, unmanned stores may take a while longer to catch on.
"Such a business model is not viable yet, at least for the near term," said Su Lian Jye, principal analyst at ABI Research, adding that for the concept to really catch on in Singapore, major retailers would have to get behind it.
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AV Network (2019-12-18)
In its new whitepaper, 54 Technology Trends to Watch in 2020, ABI Research’s analysts have identified 35 trends that will shape the technology market and 19 others that, although attracting huge amounts of speculation and commentary, look less likely to move the needle over the next twelve month. "After a tumultuous 2019 that was beset by many challenges, both integral to technology markets and derived from global market dynamics, 2020 looks set to be equally challenging,” said Stuart Carlaw, chief research officer at ABI Research. “Knowing what won’t happen in technology in the next year is important for end users, implementors, and vendors to properly place their investments or focus their strategies.”
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EE Times (2019-12-11)
“Some AI use cases are much more mature, such as predictive maintenance and machine vision, as they can rely on rule-based AI in the case of predictive maintenance, or benefit from the advancements in other sectors in the case of machine vision. Other, more advanced use cases still require many trials and much R&D,” said Lian Jye Su, principal analyst at ABI Research.
Su said that leading industrial machine and robot vendors have in fact been implementing rule-based AI for some time. While these systems generate and collect large amounts of data, they are kept proprietary and are governed by stringent protocols to ensure the highest levels of accuracy and precision. This means industrial manufacturing has been slower to implement data-driven AI solutions than sectors such as finance and enterprise software. “The industrial manufacturing sector has missed out on the boom of data-driven AI that has transformed many other industries,” he said.
One particularly big challenge manufacturing companies face is building and training in-house data science teams for AI implementation. “I believe any highly skilled AI talent will more likely choose to work for major cloud AI vendors than for a manufacturer,” said Su. “Already, there has been an AI talent war going on in the industry, and any manufacturer who is trying to get into the war will only be on the losing end.”
The shortage of AI and data science talent is effectively shaping the industry as manufacturing companies instead rely on partnerships with cloud service providers and with some of the growing number of pure-play AI startups to develop their AI capabilities (see sidebar). System integrators, chipset and industrial server manufacturers, and connectivity service providers complete the picture.
U.S. versus China?
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Financial Times (2019-12-04)
That in turn is leading to increased take-up of artificial intelligence: according to tech market advisory firm ABI Research, the number of AI-enabled devices in industrial manufacturing will reach 15.4m in 2024.
Machines with worn-out parts that are no longer made do not have to be cast aside: replacements can be made with 3D printing. Since AI can help predict wear and tear, these replacements can be ready in good time. Lian Jye Su, principal analyst at ABI Research, points out that “DIY enthusiasts” can take this one step further and use the technology to improve their old machines — a process of optimisation that AI readily lends itself to.
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Smart Energy International (2019-11-07)
The US has reclaimed the number one position in terms of investing in artificial intelligence (AI) technologies in 2018, following losing the spot to China in 2017, according to ABI Research.
Lian Jye Su, a principal analyst with ABI Research, said: “The United States is reaping the rewards from its diversified AI investment strategy. Top AI startups in the United States come from various sectors, including self-driving cars, industrial manufacturing, robotics process automation, data analytics, and cybersecurity. All these startups research on and invest in cutting edge deep learning technologies in their solutions, democratizing AI for enterprises and end consumers.”
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The Drum (2019-10-31)
Lian Jye Su, principal analyst at ABI Research said: “The United States is reaping the rewards from its diversified AI investment strategy. Top AI startups in the United States come from various sectors, including self-driving cars, industrial manufacturing, robotics process automation, data analytics, and cybersecurity. All these startups research on and invest in cutting edge deep learning technologies in their solutions, democratizing AI for enterprises and end consumers.
"There is no doubt that Chinese AI investment is feeling the pinch of reality, but China is still undeniably the largest single market for AI implementation. Favorable policies and flexible regulations in China, backed by a government willing to invest and deploy innovative technologies at scale, will certainly amplify AI adoption in the region. While the United States may be leading in investment in AI research and development, in the longer term, China will be able to capitalize on those technologies and bring them to the masses."
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TechRepublic (2019-10-31)
US-based industrial manufacturers are slightly ahead of their Chinese counterparts in integrating artificial intelligence (AI) capabilities into their operations, even though both countries have a near-equal number of installed bases of AI-enabled devices, according to global tech market advisory firm ABI Research.
Both countries are incentivized to develop approaches that encourage AI adoption in industrial manufacturing, but "the US has managed to achieve more momentum," according to Lian Jye Su, principal analyst. This is due to "acute challenges in manpower and rising cost of materials. So they need to adopt AI to make sure they can overcome these challenges."
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Environment & Energy Leader (2019-10-04)
The industrial sector in the US, driven by high labor costs and the quick time-to-market, has been pushing to enhance production efficiency and lower operation costs, leading to an increase in the use of industrial artificial intelligence (AI) applications, according to a new report from ABI Research.
The total installed base of AI-enabled devices in industrial manufacturing will show a compound annual growth rate of nearly 65% through 2024.
US manufacturers have been aggressive with the adoption of industrial AI solutions; this has given birth to pure-play AI players in the US and will keep the US as the global leader in industrial AI solutions for some time to come. Over time, however, China will catch up, as investments are poured into AI and related technologies, says Lian Jye Su, principal analyst at ABI Research.
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Nikkei Asian Review (2019-10-03)
History may repeat itself, said Su Lian Jye, principal analyst at ABI Research. Su said the deployment of 4G in the region can serve as a reference point for how the 5G race may pan out.
"With the lack of both enterprise and consumer-facing applications, telcos in Southeast Asia will generally wait for the use cases to mature in other big markets before bringing them to their local markets," he said.
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ThomasNet (2019-09-27)
The total number of AI-enabled devices in industrial manufacturing will reach 15.4 million by 2024, according to a new report by ABI Research, a global market advisory firm.
Artificial intelligence (AI) is sweeping the industrial manufacturing sector, its adoption and integration across manufacturing facilities spreading incredibly quickly. AI is revolutionizing a host of different processes, including generative design in product development, production forecasting in inventory management, and production processes like machine vision, defect inspection, production optimization, and predictive maintenance.
“AI in industrial manufacturing is a story of edge implementation,” says Lian Jye Su, Principal Analyst at ABI Research. “Since manufacturers are not comfortable having their data transferred to a public cloud, nearly all industrial AI training and inference workloads happen at the edge, namely on devices, gateways, and on-premise servers.”
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ECT News Network (2019-09-24)
To remove all bias from a law enforcement AI model, you need a bias-free historical data set, and all models must use the same data. Both those conditions are difficult to meet, said Lian Jye Su, principal AI analyst at ABI Research, a technology advisory company headquartered in Oyster Bay, New York.
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Nikkei Asian Review (2019-09-19)
SEPTEMBER 19, 2019 15:15 JST
The Zipster app developed by Singapore startup mobilityX lets commuters compare fares offered by ride-hailing services such as Grab and Go-Jek.
SINGAPORE -- Grab or Go-Jek, which is cheaper?
That is a question Toyota Motor-backed technology startup mobilityX hopes will drive commuters to its all-in-one transport app Zipster, launched in Singapore this week after five months of trials.
Founded by former Singapore civil servant Colin Lim, mobilityX says its app is Asia's first integrated mobility-as-a-service platform, enabling commuters to compare fares and travel times across a range of transport options, including taxis, ride-hailing services, buses, trains and e-scooters.
"We don't desire to play judge or jury," the 47-year-old Lim told the Nikkei Asian Review, adding that the app is neutral when comparing transport providers.
"It's not about saying public transport is better than ride-hailing," Lim said. "It really depends on consumers' needs at that point in time."
With more than 16,000 downloads already, Lim said the company wants to introduce a subscription-based model next year that will offer users a mix of travel options pegged to a specific price point, shaving up to 20% off the cost of each journey.
Equipped with its own digital payments system -- commuters can even buy travel insurance via the app -- Lim said he has no plans to turn Zipster into another "super app," preferring to focus on mobility and associated services.
"This is a new battleground, and is probably something that Grab and Go-Jek will happily engage in," said Su Lian Jye, principal analyst at ABI Research. "At this stage neither Grab nor Go-Jek will prefer to share their information with large conglomerates, or with each other. So a third-party platform like Zipster makes more sense."
While users are not yet able to book rides using Zipster, Lim said the company eventually wants to add booking and payment capabilities so that commuters can do everything within the app.
The danger in this, warned ABI Research's Su, is favoritism.
"Zipster is basically playing the role of Google and Baidu, who have in the past demonstrated preferential treatment for clients who offer large advertisement fees," he said, adding that there was an onus on regulators to ensure fair play
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EE Times (2019-09-10)
Two new reports from ABI Research detail the state of play for today’s AI chipset market. EETimes spoke to the reports’ author, Principal Analyst Lian Jye Su, to gain some insight into which companies and technologies are making inroads into this potentially lucrative market
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Tech News World (2019-08-20)
Still, the cloud AI chipset market has been expanding rapidly, and the industry is seeing the emergence of a wide range of use cases powered by various AI models, according to Lian Jye Su, principal analyst at ABI Research.
"To address the diversity in use cases, many developers and end-users need to identify their own balance of the cost of infrastructure, power budge, chipset flexibility and scalability, as well as developer ecosystem," he told TechNewsWorld.
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Forbes (2019-08-01)
"Unfortunately this is a very difficult one to answer," says Lian Jye Su, AI expert and Principal Analyst at ABI Research. "What we are looking for is a perfectly neutral law enforcement agency that is free of all biases and discriminations during its decision-making process. We may look to artificial intelligence to help, but we'd need to make sure the following two things happened: that such a system would be based on a completely bias-free historical dataset and that all AI models would be trained with the same data."
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Robotics and Automation News (2019-05-16)
Nearly 55 percent of total commercial robots shipped in 2024 will have at least one Robot Operating System package installed, according to ABI Research. Lian Jye Su, principal analyst at ABI Research, says: “The success of ROS is due to its wide range of interoperability and compatibility with other open-source projects. ROS 1.0 leverages Orocos for real-time communication and OpenCV for machine vision models.”
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Design News (2019-04-09)
As Lian Jye Su, a principal analyst at technology advisory firm ABI Research, has noted, typically the market for AI chips for the cloud has been dominated by Nvidia. But with this latest announcement Qualcomm joins a handful of new challengers in the space.
“Several other players, including established suppliers like Intel and Xilinx, and smaller players like Graphcore have already launched similar products to Qualcomm’s Cloud AI 100, targeting exactly the same audience and use-cases,” Su told Design News in an email. “According to ABI research cloud AI inferencing will reach US $7.5 billion in revenues by 2023. This market is so far dominated by Nvidia GPUs and Intel’s CPUs, but these platforms are not fully optimized for inference. Competition in this space is expected to heat up within the coming years, mainly with the emergence of more specialized hardware like the platform announced by Qualcomm.”
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Robotic Business Review (2019-02-25)
Beyond automation and control
Lian Jye Su, principal analyst at ABI Research, said the announcement of the RB3 comes at the right time for commercial robots that need to be autonomous, agile, intelligent, and self-aware of their environments.
Lian Jye Su, ABI Research
“For applications such as last-mile delivery, retail assistance, construction, tower inspection, construction and mining, robots need to support new capabilities beyond just function automation and control,” Jye Su said. “Thanks to its support for a wide range of sensors and the ability to use these sensors to dynamically manage, control, and schedule the robots’ functions, platforms such as Qualcomm Robotics RB3 Platform provides the robot with the required intelligence and enable them to make informed decisions during their operation in line with the task expected from them.”
Some of the company’s competitors have already launched similar platforms, including NVIDIA and its Jetson system, and Intel’s RealSense platform, although Jye Su said those have mainly focused on machine-vision applications that provide the robot a full autonomy for its operation. “In contrast, Qualcomm Robotics RB3 Platform comes with embedded connectivity, enabling robots to communicate with the outside world. This ability not only allows the robot to augment the self-awareness of its environment, but also provides the robot with additional capabilities including better collaboration with humans and machines.”
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Entrepreneur (2018-12-13)
New York-based research firm ABI Research released a report in July, which revealed that the investment plummeted in the first half of 2018, attracting only $1.6 billion. Last year, China overtook the US in terms of private sector investment, pulling in just shy of $5 billion, but the $1.6 billion invested in the first six months of this year is less than one-third of the US levels, according to ABI Research. “2017 had been a great year for China,” admits principal analyst of ABI Research, Lian Jye Su. He adds, “But most investments were focused only on a few successful startups, such as Bytedance, Sensetime, Face++, Cambricon Technologies and Horizon Robotics. As the industry continues to figure out new use cases and business models, the AI investment sentiment has become less based on hype and more on careful analysis of business models and use cases.”
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Financial Times (2018-11-15)
But China, where the hype — and funding — went into overdrive last year, the reversal has cut more deeply. China last year overtook the US in terms of private sector investment, pulling in just shy of $5bn, but the $1.6bn invested in the first six months of this year is less than one-third of US levels, according to ABI Research.
“[We’re] at a juncture where the generic use cases have been addressed,” said Lian Jye Su, principle analyst at the consultancy. “And building generic general purpose chatbots is much easier than specific algorithms for industries like banking, construction, or mining because you need industry knowledge and buy-in from the industry.”
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