AI

Energy Experts on AI Tools for Building’s Sustainability:“Triple Win for Businesses, People, and Planet”

Donatas Karčiauskas, CEO of Exergio Research studies continue to highlight that aside from environmental benefits, AI-based platforms in building energy management deliver economic savings and improve occupant well-being. Energy experts provide real-case examples for these tools. Vilnius, Lithuania. Numerous studies delve into the potential of AI for buildings and their energy efficiency. While such AI-based platforms are often seen as primarily environmentally focused, the latest research showcases that they also deliver economic and social advantages. “Latest AI platforms that focus on energy performance also provide other benefits such as cost-efficiency and even better quality of work for energy-efficient building occupants, creating a triple win for businesses, people, and the planet,” said Donatas Karčiauskas, CEO of Exergio, a company that provides AI-based solutions for buildings’ energy performance. Energy performance experts provide insights on 3 key areas that benefit from such tools – environmental, economic, and social impact. AI Tools are Needed to Reach Net-Zero Goals The key aspect of implementing AI-for-energy tools in buildings is to reduce energy waste. It is particularly important in commercial buildings, where environmental impact is the highest due to energy consumption. By managing energy systems in real time, AI helps lower carbon emissions by ensuring sustainable use of resources. Unlike traditional systems that react to changes, AI can predict energy needs and adjust operations accordingly, leading to more sustainable building management. “With AI tools, we can fine-tune every aspect of a building’s energy use, squeezing out efficiencies that add to environmental gains. We have implemented such tools in office buildings and malls, where payback of deep renovations could take up to 10 years. It’s already too late to retrofit all the old build stock if we want to reach net-zero goals by 2050,” Karčiauskas explained. “AI, on the other hand, is capable of integrating thousands of […]

In the ‘age of AI,’ what does it mean to be smart?

As artificial intelligence gets better at predicting human behavior, a business psychologist encourages people to strengthen the uniquely human skills that machine learning has yet to tap. Tomas Chamorro-Premuzic has written, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique (Harvard Business Review Press). He explains why some AI algorithms model humanity as a simple species, how attention has become commoditised, and why the right questions are now more valuable than the right answers. Why did you write this book, now? I’m a professor of business psychology at Columbia University and UCL [University College London] and the chief innovation officer at ManpowerGroup. I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique is a book about the behavioural consequences or impact of artificial intelligence, including the dark side of human behaviour and what we should do to upgrade ourselves as a species. The book is written at a time that, in my view, could only be described as the AI age. Humans have always relied on technological inventiveness and innovation to shape their cultural and social evolution. Now, even the wider public is talking about things like ChatGPT and other conversational interfaces, and the tech giants are described mostly as data companies and as algorithmic prediction businesses. The book was very much written in the midst of the AI age, or under the influence of AI, because I wrote the bulk of this at the height of the pandemic when we had very little physical interaction or contact with other people outside of our nuclear families. This means I was heavily influenced by hyperconnectedness and the datafication of me. Everything I did was being datafied and subjected to the predictive powers of AI during 2020 and 2021. I can’t say that there won’t be a better era […]

Navigating technology trends

“Did you see the article about blockchain on the paper’s home page? I think we need blockchain, too.” “We should give all our IT to an offshore system integrator—that will save a lot of money. Our competitors are doing the same thing.” “We need to do something about generative AI right away!” Many who work in IT have heard variations of these statements from well-meaning senior colleagues. And given how much technology underpins so many trends, as well as the increasing pace of innovation, IT leaders can expect to hear more of them and feel pressure to act on them. Sometimes it makes a lot of sense to act quickly on a trend. Innovation, after all, is a hallmark of successful companies. But not all trends are created equal. The annals of many IT organisations are littered with bold initiatives in trends that created a lot of excitement but not much value. Moving quickly to chase a trend often bogs an organisation down, leads to wasted spend, and takes attention away from important priorities. For this reason, the ability to evaluate trends quickly and communicate their relevance to the business is becoming a critical capability for the modern CIO. In practice, it is rarely as simple as saying “yes” or “no” to investment in a particular trend. Trends are unpredictable, change with time, and their relevance to a given business often waxes or wanes. Instead, CIOs need a clear set of parameters to rely on both for evaluating trends and for determining which posture to take for engagement with them: first mover, fast follower, slow adopter, or sometimes non-partaker. Four guides for determining a trend’s relevance Disruptive business value: The trend can result in measurable value to the business. Independence: The trend allows the organisation to work in smaller, more independent units. Connectivity: The […]

How AI will transform manufacturing

-Robert Le Busque, Regional Vice-President, Asia Pacific, Verizon Business In Australia, the rapid development of artificial intelligence (AI) has coincided with the Government’s announcement of the $15 billion National Reconstruction Fund (NRF), $1 billion of which will be dedicated to reinvigorating, accelerating, and building up advanced manufacturing capabilities. As businesses have already started adopting AI for various use cases, the Government has also recently launched a public consultation to seek advice on how to mitigate any potential risks and ensure it is applied responsibly. One of these uses cases is advanced manufacturing, which is a broad term that encompasses technologies applied to any manufacturing facility, including application software and AI tools to augment and generate higher value manufacturing output. Advanced manufacturing is also likely to use AI to embed faster and safer means of production and better operations management for industrial processes. Generating speed, safety and enhanced production Part of removing human error to make manufacturing safer and faster means reducing reliance on human observation. As machinery drivers and operators are among the top three occupation groups with the highest rate of work-related injuries in Australia at 6.5 percent in the 2021-2022 financial year, this makes a use case for AI analytics in augmenting workplace health and safety. High precision tracking, for example, detects faults in machinery micro-components at a scale previously unachievable – this improves productivity, output, and profitability for manufacturing companies. AI analytics can match workers’ physical position in relation to how they interact with machines, particularly heavy industrial machinery, facilitating a more comprehensive understanding of safety in workplace operations and injury. AI software can also manage workflows more effectively by identifying and allocating tasks. This can be taken one step further, with large site and heavy industrial manufacturing operations using digital twins to optimise these workflows – […]

The Interview: Marcelo Tarkieltaub, Regional Director, Southeast Asia, Rockwell Automation

Focusing on Rockwell Automation’s Industry Outlook, the growth of industrial automation & smart manufacturing in Asia Pacific, highlighting both the benefits and gaps that businesses must navigate in this growing market. Tell me about Rockwell Automation’s Industry Outlook for the manufacturing sector in Asia Pacific Rockwell Automation’s Industry Outlook for the manufacturing sector in Asia Pacific showcases a promising landscape. Manufacturing is one of the most significant contributors to the Asia-Pacific economy and is undergoing rapid transformation. Some key factors that are influencing the manufacturing sector include: Technological Advancements: The integration of cutting-edge manufacturing technologies, including automation and IoT, is transforming the manufacturing sector, leading to enhanced efficiency. According to our State of Smart Manufacturing Report, close to half (44%) of APAC manufacturers plan to adopt smart manufacturing within the next year; out of this, China (80%), Australia (60%) and India (59%) are already using some components of smart manufacturing. Sustainability and Environmental Regulations: An increasing emphasis on sustainability and environmental regulations is driving changes in manufacturing practices and product requirements. Again, our State of Smart Manufacturing report cites that for the 94% of APAC manufacturers who have formal or informal environmental, social and governance (ESG) policies in place, close to half (48%) cite “a competitive differentiator” as the top driving factor for pursuing ESG initiatives. Economic Growth: The overall economic growth and stability of countries in the Asia Pacific region can have a significant impact on manufacturing. Rapidly growing economies drive increased demand for manufactured goods. How is smart manufacturing growing in Asia Pacific? Smart manufacturing is growing in the region driven by a combination of factors including technological advancements, government support, and the region’s strong manufacturing base. APAC is home to some of the world’s leading technology companies and has a strong presence in industries such as electronics, […]

Who is Sam Altman?

On Friday, OpenAI’s high-flying chief executive Sam Altman was unexpectedly fired by the company’s board. Co-founder and chief technology officer Greg Brockman was also removed as the board president, after which he promptly resigned. Now it looks like Sam Altman has ended up at Microsoft. In an unexpected twist, talks began about potentially reinstating Altman in some capacity following an outpouring of industry and investor support for him and several OpenAI researchers who quit their jobs in solidarity. OpenAI’s board found a new CEO –Emmett Shear – in record time. Shear, the former CEO of Twitch, will now take over from Murati as interim CEO. It has been an epic backstabbing scene worthy of the HBO drama Succession. While many have speculated about why the board may have forced Altman out, details remain scarce. What we can say is the decision to fire Altman will likely put a dent in OpenAI’s commercial progress. An unusual company structure OpenAI is the hottest company in tech today, having released the ChatGPT chatbot and DALL-E image generator onto a largely unsuspecting public. The company’s mission is simple: to develop artificial general intelligence (AGI) – that is, an AI which is as smart or smarter than a human – and to do so for the public good. Many were starting to believe OpenAI could succeed at this goal. But developing AGI isn’t just a technical challenge. It’s a major management and economic nightmare. How can you ensure the vast power and wealth generated by AGI doesn’t subvert the company’s goal to seek the public good? Many individuals within OpenAI and the wider tech community worry AI is progressing too fast. A global race in AI development is underway and the commercial pressure to succeed is immense. Following its launch, ChatGPT quickly became the fastest-growing app […]

AI helps the impossible become possible

When Sandvik Coromant engineers, Henrik Loikkanen and Jakob Pettersson, were tasked with creating an AI-generated, stainless steel synthesis of some of history’s most famous works of art, their metal cutting expertise was put to the ultimate test. In partnership with Sandvik Group, Sandvik Coromant has developed a statue for the history books. Made using AI modelling and cutting-edge manufacturing solutions, the sculpture combines the dynamic poses of Michelangelo’s work, the musculature craftmanship of Auguste Rodin, the somber tones of Käthe Kollwitz, Takamura Kotaro’s Japanese influence and Augusta Savage’s inspirational defiance to unite some of history’s most famous artists from a period spanning 500 years. Weighing 500 kilograms and standing at 150 cm tall, the Impossible Statue was officially inaugurated at Tekniska Museet, Sweden’s National Museum of Science and Technology, in April 2023. Producing a statue in such a way has never been done before. So how did Loikkanen, Pettersson and the team craft this blend of art and science, past and future? When AI meets art AI has been around for some time, with intelligent machines tasked with performing activities that normally require human intelligence, such as visual perception, speech recognition, decision-making, language translation and problem-solving. Its concept dates back decades with the earliest program written in 1951 by Christopher Strachey, later director of the Programming Research Group at the University of Oxford. But the emergence of new, conversational AI programs such as Google’s Bard and ChatGPT open up even more applications of the technology. Today, the achievements of AI seem almost limitless — it can even create art. After establishing a 2D design that brought together the styles of the five artists, Sandvik began translating the model into a complete 3D image. Using depth estimators to build the 3D model, human pose-estimators to refine the body, videogame algorithms to […]

How to keep AI developing without compromising safety and security

Christina Montgomery Francesca Rossi The introduction of generative AI systems into the public domain exposed people all over the world to new technological possibilities, implications, and even consequences many had yet to consider. Thanks to systems like ChatGPT, just about anyone can now use advanced AI models that are not only capable of detecting patterns, honing data, and making recommendations as earlier versions of AI would, but also moving beyond that to create new content, develop original chat responses, and more. A turning point for AI When ethically designed and responsibly brought to market, generative AI capabilities support unprecedented opportunities to benefit business and society. They can help create better customer service and improve healthcare systems and legal services. They also can support and augment human creativity, expedite scientific discoveries, and mobilize more effective ways to address climate challenges. We are at a critical inflection point in AI’s development and use and its potential to accelerate human progress. However, this huge potential comes with risks, such as the generation of fake content and harmful text, possible privacy leaks, amplification of bias, and a profound lack of transparency into how these systems operate. It is critical, therefore, that we question what AI could mean for the future of the workforce, democracy, creativity, and the overall well-being of humans and our planet. The need for new AI ethics standards Some tech leaders recently called for a six-month pause in the training of more powerful AI systems to allow for the creation of new ethics standards. While the intentions and motivations of the letter were undoubtedly good, it misses a fundamental point: these systems are within our control today, as are the solutions. Responsible training, together with an ethics by design approach over the whole AI pipeline, supported by a multi-stakeholder collaboration around AI, can make […]

News Ticker

AI