Assistive or enabling technologies aim to create more accessible and inclusive solutions for people living with disabilities. This is critical, since many such users rely on technology for daily activities such as mobility and communication. While the problems are global, there are unique challenges that exist in the Asia Pacific region when it comes to developing assistive technologies, particularly assistive devices. The United Nations Economic and Social Commission for Asia and the Pacific (UN ESCAP) estimates that 650 million people in the Asia-Pacific region live with a disability.4 It is also well understood that disability statistics in the region could be significantly underreported.

Petheo leads the firm's projects and partnerships in the Asia-Pacific region and advises globally on international development and humanitarian assistance. She also works on preparedness in the Asia-Pacific region with the United States Agency for International Development. "We're doing programming on the engagement of the private sector in disaster risk management in Indonesia, which is a very disaster-prone country," she says. "Smaller and medium-sized businesses are important contributors to job creation and economic development. When they go down, the impact on lives, livelihoods, and the community's ability to respond and recover effectively is extreme. We work to strengthen their own understanding of their risk and that of their surrounding community, lead them through an action-planning process to build resilience, and link that with larger policy initiatives at the national level."

By Sachin Bhalla According to Market Research Company Technavio, the global data center market size is poised to grow by $304.87 million between 2020 and 2024. It will grow at an even faster pace in the Asia-Pacific region. An S&P study reveals that between 2017 and 2022, the Asia-Pacific region would reach an estimated 10% CAGR compared to the global data center industry that is expected to clock a 7% CAGR. The data center industry is undergoing changes to serve the needs in today's business landscape. It comes to no surprise when we hear organisations discuss their plans to enhance their data center infrastructure with technologies like Artificial Intelligence (AI) and focus on automation to improve uptime while controlling costs--all of which are important for companies to drive operational efficiency and business resiliency.

Deep learning, a subset of machine learning and artificial intelligence (AI), has been there since a while, but became an overnight "sensation" when in 2016, Google's AI program, a robot player beat human grandmaster Lee Seedol in the famed game of AlphaGo . Since then, deep learning training and learning methods became widely acknowledged for "humanizing" machines. Many of the advanced automation capabilities now found in enterprise AI platforms are due to the rapid growth of ML and deep learning technologies, as researchers predict deep learning to provide formidable momentum for the adoption and growth of AI, even though most of these experiments are in their infancy. By definition, deep learning is a powerful tool for enterprises looking to gain actionable insights and enable automated responses to a flood of data, especially unstructured data, from all kinds of devices, Internet of Things (IoT), social media and – of course – from corporate data systems. From that perspective deep learning works incredibly well with unstructured data, such as images, sound, time-series of events and so on.

Spending on artificial intelligence (AI) in the Asia-Pacific region is expected to surge by more than 50 percent on an annual basis to US$6.2 billion this year, market advisory firm International Data Corp (IDC) said. "Artificial intelligence is having an impact across many industries with widespread utilization, but is still at a nascent stage in the Asia-Pacific," IDC associate market analyst for Asia-Pacific Ritika Srivastava said in a report on Friday last week. "From providing chatbots for better customer service to improving the efficiency of operations and tasks for their business models, industries like banking, retail and professional services are spending in this technology at scale," Srivastava said. The banking industry would lead the way in spending on AI and contribute about 10.7 percent of overall spending in the Asia-Pacific region, the report said. Banks would mostly focus on AI/cognitive systems for fraud analysis and investigation, while also investing in automated customer service agents, it said.

Even though the benefits of artificial intelligence are widely acknowledged, a survey performed by Gartner, Inc. shows that the adoption of AI is slow. Only more than 10% of the companies that were surveyed have utilized or deployed AI in their businesses. Furthermore, the role of AI in marketing is more established in the Asia-Pacific region as compared to other areas. Let's take a closer look at what contributed to the current state of AI adoption among marketers. The fast evolution of technology has widened the use of AI for marketers.

TECHNOLOGY is heralded for its ability to transform the workplace by increasing productivity, agility, and job satisfaction. Recently, we have seen the prolific adoption of Robotic Process Automation (RPA) within the workplace. Otherwise known as software bots, RPA has the power to process and extract data, and integrate with other technologies. RPA is able to automate many rules-based processes and repetitive tasks within the business. It acts as a solution to streamline many back-end processes that often overwhelm employees, by shifting many of these responsibilities from humans to machines.

In the past few decades, sci-fi films have elevated the awareness of intelligent machines among mass audiences. Last year, Google's AlphaGo program beat a team comprising five of the best human Go players in the world. With Go being one of the most abstract strategy board games ever designed for humans, AI's ability to win placed the overarching technology's growing capabilities firmly under the spotlight. The rise of the machines – and what that means for humans – has been a hot topic. These machines, commonly depicted as sentient robots trying to overthrow humans, have in fact been highly misrepresented.

Companies in the Asia-Pacific region are ahead in the adoption of disruptive technologies such as Internet of Things, artificial intelligence, says a recent global survey of chief information officers (CIOs)by by Gartner, Inc. The survey covers CIOs worldwide, including 537 across 17 countries in Asia/Pacific (113 of those in Australia and New Zealand) and represents approximately $3.4 trillion in revenue/public sector budgets and $49 billion in IT spending. According to the survey, about 43 per cent of surveyed CIOs in Asia-Pacific region have said that either they have deployed or have plans for deployment of IoT technologies, compared to 37 per cent globally. Some 37 per cent have deployed AI compared to 25 per cent globally. In the region, 28 per cent CIOs have made investments in conversational interfaces, 20 per cent in virtual reality (VR) and augmented reality, while 13 per cent have adopted blockchain or distributed ledger technology.

More than two-thirds of U.S. life sciences CEOs say their organizations are ready to adopt advanced artificial intelligence technology, but they acknowledge there are barriers – such as skills, complexity and costs – to implementing it, the KPMG's 2017 CEO Outlook found. KPMG's survey also found that more than 90 percent of CEOs were forecasting annual revenue growth of less than 5 percent for the next three years, reflecting less optimism than the 2016 survey. The level of readiness among U.S. life sciences companies -- with 68 percent of CEOs saying they are prepared for artificial intelligence – exceeds the 22 percent from Asian-Pacific companies and 47 percent of European organizations whose leaders expressed that their organizations were ready. Two-thirds of U.S. executives at the largest pharma and medical device makers were also concerned about integrating this emerging technology into business processes. The biggest barriers to implementing new technologies were the lack of internal skills/knowledge (35 percent) and the complexity of implementations (16 percent), followed by the lack of budget (14 percent), according to the 43 CEOS of the largest U.S. life sciences companies who were surveyed.