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AI, underpinned by ML applied against quality data, has enormous potential to transform the way we work today, from workflow optimisation and talent management, to automation in business planning and finance, even anomaly detection. — AFP photo
ARTIFICIAL intelligence (AI) has by far grown leaps and bounds since its first introduction decades ago.
The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects. General intelligence – the ability to solve an arbitrary problem – is among the field’s long-term goals.
To solve these problems, AI researchers have adapted and integrated a wide range of problem-solving techniques, including search and mathematical optimisation, formal logic, artificial neural networks, and methods based on statistics, probability, and economics.
Business leaders understand that operational insight is key to unlocking business value. But getting to those insights – whether it’s within their own enterprise or across their supply chains – is a challenge upon itself.
This is where AI comes in. And a branch of AI – generative AI – is quickly taking up storm today. The various sub-fields of AI research are centered around particular goals and the use of particular tools.
Damian Leach
According to Damian Leach, chief technology officer of Asia Pacific and Japan at Workday, the pandemic-induced digitisation initiatives that organisations undertook in Malaysia are leading large corporations to look at new ways in which they can derive real-time insight for their operations.
“AI and machine learning (ML) are foundational to this next level of insight, data result generation, automation, and for creating an enhanced end user experience. With the rise of generative AI solutions such as ChatGPT, business leaders in Malaysia are met with new possibilities and use cases that have emerged alongside this next-generation technology,” he told BizHive in an interview.
Leach said AI, underpinned by ML applied against quality data, has enormous potential to transform the way we work today, from workflow optimisation and talent management, to automation in business planning and finance, even anomaly detection.
“For instance, in Malaysia, the implementation of automation in sectors such as financial services could result in notable advantages, such as enabling finance professionals to identify patterns, trends, map possible futures, and automatically highlight anomalies – enabling them to better manage risks, plan, and complete the financial close process in mere hours or minutes,” he said.
In the area of human resources, Leach said an AI-driven workforce optimisation solution could also help streamline manual processes such as analysing internal feedback and HR budgets, tailoring company policies to retain talent, and assessing the right skills to hire the right talent.
“This would help Malaysian organisations in their pursuit of digital transformation too, as shown in our recent Digital Agility Index study, we found that talent acquisition and retention were the biggest challenges cited by Malaysian organisations in their digital transformation efforts,” he explained.
“Adopting a skills-based people strategy optimised by AI solutions will also spur internal mobility while concurrently meeting employees’ desires to upskill and be provided with new opportunities, creating a more agile and capable workforce.
“The introduction of AI in workplace management, if applied using Data and ML transparently, can be a step in the right direction for greater equality in the workforce, by providing people with more objective and relevant information to enhance the decision-making process and help reduce unconscious bias.
“Equally, we need to be cautious which is why at Workday we are focused on ML-fuelled decision-making to surface insight to customers for them to ultimately decide.”
The new global study revealed that a majority of 12,000 employees (91 per cent) surveyed believe they would be more productive if their IT issues at work were resolved quickly and effectively. — AFP photo
Keeping employees on their toes
APART from employers, employees too see AI as a workplace disruptor. Nine in 10 employees (87 per cent) recognise that AI has a positive role to play in helping them stay productive, while eight in 10 (81 per cent) prefer a blend of AI and human interaction, according to a new study commissioned by Lenovo.
The new global study by YouGov revealed that a majority of 12,000 employees (91 per cent) surveyed believe they would be more productive if their information technology (IT) issues at work were resolved quickly and effectively.
Another 74 per cent say weak IT support has affected their motivation at work. Results show an efficient and effective IT support system needs to be in place to power today’s hybrid workforce.
Survey respondents see the key benefits of AI-powered IT being issue resolution with minimum disruption where AI can identify and resolve IT-related issues automatically, and in enabling 24/7 support even during weekends and holidays.
Lenovo vice president and general manager, global product services, John Stamer said as workplaces have evolved with the rise of hybrid work, IT support for employees clearly has not kept pace.
“With the growing adoption of cloud services, digital intelligence and the metaverse, organisations’ IT environments are only going to become more complex, so effective IT support will become even more essential to employee experience and morale,” he said.
With numerous organisations adopting AI and ML to reap the exponential benefits, Workday’s Leach said it is crucial for them to establish robust policies and safeguards to effectively manage the associated risks the technology brings.
“For instance, at Workday, we are committed to the development of trustworthy AI and ML solutions and provide clear documentation to customers on how our AI solutions are built, trained, and tested,” he said.
“We have a dedicated Machine Learning Trust team, composed of cross-disciplinary social and data scientists who work with members from our engineering, product, legal, privacy, and equity and inclusion Teams.
“Our ML Trust Team reviews technologies and advises leadership and Workday Teams across the company about how to put our Ethical AI principles into practice.
“Consistent with our core values of innovation and integrity, we look at existing and developing regulations, as well as best practice guidelines and frameworks from national and global standards organisations.”
Is a one-size fits all AI guideline ideal? Should organisations tailor their AI guidelines depending on the type of AI employed? Leach said the rapidly evolving AI and ML landscape is vast and complex, with different types of models that come with their unique strengths, weaknesses, and modes of operation.
“Deterministic rule-based AI models have been overshadowed by data-driven Machine Learning models. Even within ML models, various forms such as supervised, unsupervised, and reinforcement learning can be applied in different situations.
“The common denominator is the need to have standardised ethical principles and guidelines that guide the use of AI across all organisations.
“For successful adoption of AI, it is necessary to establish effective guardrails and respective governance, framework guides, and policies to manage the risks associated with emerging AI technologies, such as generative AI, to help ensure that these innovations are developed and used safely and responsibly.
“For AI and ML to deliver on the possibilities it offers, it must be trustworthy, and it must augment human activity, rather than displace it.”
AI and ML policy needs to cover access to third party tools to understand, and if needed restrict, data being sent to and analysed by open source products that are freely available over the world wide web. — AFP photo
What can companies do to allay employees’ concerns
AI and ML policy needs to cover access to third party tools to understand, and if needed restrict, data being sent to and analysed by open source products that are freely available over the world wide web.
This comes as AI and ML being deployed in the workplace that has been built into existing SaaS products needs to be met with a level of trust, and should be seen as a tool to help humans perform their tasks better – not to replace humans.
“Understanding the ethical AI and ML guidelines and principles that the respective SaaS company has will go a long way in ensuring positive outcomes and growth opportunities for employees and the organisation as a whole.
“Companies also need to help ensure that people are at the centre of AI and ML decision-making.
“At Workday, no decision is fully automated by our AI and ML technology, and our practices help ensure that people are the final decision-makers.
“We maintain a human-in-the-loop approach to using AI and ML, making people more productive, better informed, and enabling them to solve problems they didn’t think
they could solve before.
“These are some of the promises of AI and ML, and we are just getting started with imagining how it will shape the future of work.
“By prioritising trustworthy and ethical AI and ML infused applications, whilst keeping humans at the centre of decision-making, Malaysian organisations can ensure a successful deployment of AI and ML technologies while allaying employee and management concerns.”
The speed of advancements in Generative AI and LLM and perhaps even hybrid language models with federated learning today have shown us just how quickly technology can evolve and we are just seeing the tip of the iceberg when it comes to the possibilities ahead. — AFP photo
What is the future of AI and ML-based solutions?
AS for the future of work, this will likely be revolutionised by the unlimited possibilities powered by AI and ML-based solutions.
This comes as the speed of advancements in Generative AI and Large Language Models (LLM) and perhaps even hybrid language models with federated learning today have shown us just how quickly technology can evolve and we are just seeing the tip of the iceberg when it comes to the possibilities ahead.
“We envision that the future workforce will be more agile, adaptable, and inclusive, providing greater opportunities for individuals with unconventional backgrounds to succeed,” Leach said.
“AI and ML will be at the forefront of enabling dynamic and flexible workforces in the future, with its ability to improve talent management and enhance the employee experience.
“With Workday’s Skills Cloud for instance, AI and ML are used to analyse the way skills are managed, mined, related, and used, allowing leaders to drive a skills-driven transformation in their organisations.
“Moving to a skills-based workplace means delivering a job marketplace for supporting internal development opportunities, and also creating ‘gig work’ for short assignment based opportunities to meet agile requirements.
“As with all technologies that are promising, there are always challenges in harnessing technology in the right way and for the right purposes.
“In the months and years ahead, as much attention may be paid to embedding ML technologies in business support systems and operations, as would be paid to the ethical and fair use of such technologies.
“As the technology and the adoption matures, so might the regulations that govern the use of the technology.
“This is where we lean on the past to potentially predict the future, considering Data regulations GDPR as an example, could the same be true for setting regulations around AI and ML?”
Google is bringing new generative AI capabilities to its Google Cloud AI portfolio to help developers and organisations access enterprise-level safety, security, privacy, as well as integrate with their existing Google Cloud solutions. — AFP photo
Google unveils generative AI on Google Cloud, Google Workspace
ON a global scale, Google introduced the next wave of generative AI innovation across core areas of its business.
Developers and businesses can now try new APIs and products that make it easy, safe, and scalable to start building with Google’s best AI models through Google Cloud and a new prototyping environment called MakerSuite.
In Google Workspace, the company is introducing new features that help users harness the power of generative AI to create, connect, and collaborate.
“Breakthroughs in generative AI are fundamentally changing how people interact with technology – and at Google, we’ve been responsibly developing large language models so we can safely bring them to our products,” said Thomas Kurian, chief executive officer of Google Cloud in a statement mid-March.
“Our goal is to continue to be bold and responsible in our approach and partner with others to improve our AI models so they’re safe and helpful for everyone.
“We’re excited by the potential of generative AI and the opportunities it will unlock – from helping people express themselves creatively, to helping developers build brand new types of applications, to transforming how businesses and governments engage their customers and constituents.”
For developers looking to build the next generation of applications with generative AI, Google is introducing the PaLM application programming interface (API), a new offering that makes it easy and safe to experiment with Google’s best large language models.
Today, Google is making an efficient model available, in terms of size and capabilities, and other sizes will be added soon.
The API also comes with an intuitive tool called MakerSuite, which lets developers quickly prototype ideas and, over time, will have features for prompt engineering, synthetic data generation, and custom-model tuning – all supported by robust safety tools.
Google is bringing new generative AI capabilities to its Google Cloud AI portfolio to help developers and organisations access enterprise-level safety, security, privacy, as well as integrate with their existing Google Cloud solutions.
Across these, Google Cloud ensures organizations have complete control over if, how, and for what their data is used.
Starting today, trusted testers are accessing Generative AI support in Vertex AI and Generative AI App Builder. If you are interested in updates on early access opportunities, please join the Google Cloud Innovators technical community.
In addition to announcing new AI innovations, Google Cloud is committed to being the most open cloud provider.
Today, the company is bringing the best of Google’s infrastructure, AI products, and foundation models to partners at every layer of the AI stack.
This includes chipmakers; companies building foundation models and AI platforms; technology partners enabling companies to develop and deploy ML models; app builders solving customer use cases with generative AI; and global services and consulting firms that help enterprise customers implement all of this technology at scale.
Google Cloud is launching Built with Google Cloud AI, a new initiative that helps independent software vendor (ISV) partners get started with building applications using Google Cloud AI services.
The initiative provides dedicated access to Google Cloud expertise, training, and co-marketing support to help partners build capacity and go to market.
To enable more AI-first startups, Google Cloud is also expanding the Google for Startups Cloud Program, with exclusive benefits for AI startups (seed to series A).
Lipovsky explains that Malaysia is being targeted by cyberattackers on the global stage.
ESET: Malaysian firms can leverage advanced AI, ML for enhanced cybersecurity
WITH almost RM600 million in losses recorded in 2022 due to cybercrime, businesses and organisations in Malaysia are urged to get ready for the age of generative AI and be better equipped against cyberthreats.
The latest edition of the ESET Security Days revealed how natural language processing (NLP) transformers, similar to technology behind generative AI, can be used in cybersecurity defenders to enhance the detection of various threats, such as ransomware, targeted attacks, phishing and security vulnerabilities.
“As cyber threats continue to grow in complexity and frequency, ESET Security Days 2023 emphasised the utmost importance of understanding and addressing these threats to safeguard sensitive data, protect digital assets, and ensure the resilience of businesses and individuals in an increasingly interconnected and AI-driven world,” said Robert Lipovsky, ESET principal threat intelligence researcher.
Lipovsky explained that Malaysia is being targeted by cyberattackers on the global stage. He said among some significant findings by ESET showed a 38 per cent increase in malware detection in the country last year compared to 2021.
“Topping the list of these detections was a very old exploit, (CVE-2017-11882) affecting Microsoft Office, which has been patched in 2017. Another exploit that is on our radar is Log4j, which has also been patched since it was first reported in 2021.
“It is incredibly worrying that our telemetry detected a 407 per cent increase in Log4j exploits in Malaysia in the first four months of 2023 compared to the end of last year – with old vulnerabilities still being used to target organisations in Malaysia.”
On the other hand, he added that remote desktop protocol attacks (RDP), which made headlines in the past three years due to the remote working trend, have dropped by 90 per cent in 2022.
“Our insights reinforced the fact that threat actors are constantly adapting their strategy to target organisations in Malaysia based on emerging trends in the country as well as what cybercriminals find work best,” Lipovsky said.
Industry specialists also acknowledged the need to be prepared against AI-assisted threats such as generative AI tools being used to generate deepfake content or voice-based attacks for sophisticated social engineering tactics.
A major difference between the current cloud computing design and ChatGPT, as well as AIGC, is the design of data centres. — AFP photo
ChatGPT poised to revolutionise data centre industry
AI chatbot, ChatGPT, is poised to cause a revolutionary impact on the data centre industry, said an expert.
According to a Bernama feature, GDS Services Ltd senior vice-president for international business Jimmy Yu said a major difference between the current cloud computing design and ChatGPT, as well as artificial intelligence-generated content (AIGC), is the design of data centres.
“It brings up opportunities for countries like Malaysia, Indonesia and Thailand, within the region, to have a larger scale of resources in terms of land, utility, and renewables.
“This is not much-being location specific. For the larger deployment of AIGC, any company simply needs scalable resources and a simple internet connection,” he said at a panel session titled ‘The Future of Green Data Centre’ at the Huawei Asia Pacific Partners Conference 2023 in Shenzen, China.
“With AI machine learning, the computing is going to continue (working). You just need to make sure that works.
“We have been building data centres for cloud service providers and we probably have to think about new ways on how we should do that for the new sectors, especially the AIGC,” said Yu.
He also said that GDS Services, a leading developer and operator of high-performance data centres in China, has seen a lot of hyper-scale data centre sectors moving into new sectors such as the AIGC.
“When this industry really grows and with more adoptions, we will see larger growth points for our industries,” Yu added.
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