The Creative Class

Ruled by engineers: how China gets things done, leaving the US in the dust

Mark Beeson, Adjunct Professor, Australia-China Relations Institute, University of Technology Sydney. In modern times, the world’s most powerful and influential states have also had the largest economies. When the United States overtook Britain in the early 20th century, it was only a question of time before it assumed international political leadership too. Indeed, the failure to assume this role is widely thought to explain the duration of the Great Depression and the turmoil of the period between the two world wars. At a time when American hegemony seems to be in terminal decline and China might overtake the US economically, plausible and original explanations of their relative fates are welcome. Dan Wang’s Breakneck: China’s Quest to Engineer the Future, succeeds on both counts. At the heart of this very readable book is Wang’s argument that there is a profound difference between the two rivals: the US is run by lawyers and China is ruled by engineers. Wang is perfectly placed to unpack this deceptively simple idea, having been born in China and spent large chunks of his relatively short life there and in the US. He is a keen and shrewd observer of both societies, and the book is sprinkled with personal anecdotes and illustrations of his key claims. Consequently, it’s not a conventional “academic” account, but that may come as a relief to many prospective readers. Lawyers versus engineers The biggest difference between China and the US today, according to Wang, is not the sort of ideological differences that distinguished America’s competition with the Soviet Union, but their respective abilities to get things done. “The greatest trick that the Communist Party ever pulled off is masquerading as leftist,” Wang argues. “China is an engineering state, which can’t stop itself from building, facing off against America’s lawyerly society, which blocks everything it can.” There […]

European researchers develop energy-efficient machine vision inspired by human eyesight and the brain

Drawing inspiration from human eyesight, a European research project led by VTT has developed machine vision mimicking the cooperation of the eye and nervous system, implemented as edge-computing circuits. Edge computing means processing data where it is generated and where the results of computing are needed. This enables, for instance, intelligent robots and drones that can operate independently in a rescue mission after an earthquake without constant network connections or bulky batteries. Launched in 2021, the MISEL project (Multispectral Intelligent Vision System with Embedded Low-Power Neural Computing) is now nearing completion. Coordinated by VTT Technical Research Centre of Finland, the project has combined neuromorphic computing—which mimics the way the brain processes information—with semiconductor technologies. “Our goal is to build truly smart devices that can make observations and decisions on their own, without sending data to supercomputers or the cloud. Neuromorphic computing can be hundreds or even thousands of times more energy-efficient than conventional digital processing,” explains Jacek Flak, Research Team Leader at VTT, who coordinates the project. The MISEL project received nearly EUR 5 million in funding from the EU’s Horizon 2020 programme. Alongside VTT, partners include the universities of Łódź, Lund, Santiago de Compostela, and Wuppertal, the Fraunhofer Institute, France’s LNE national research institute, and the companies Kovilta Oy (Finland) and AMO GmbH (Germany). The consortium unites expertise across disciplines, including materials science, electronics, and algorithm design. Smarter mobile devices without constant connectivity Artificial intelligence typically requires either good network connectivity to cloud services or substantial local computing power. However, the MISEL project brings intelligence to the edge—directly into the devices themselves. This approach allows battery-powered systems to process and interpret sensory data quickly and with low power consumption, while also reducing cybersecurity privacy risks. “Imagine a drone searching for survivors after an earthquake through smoke, dust, and debris. It needs to interpret […]

Could a ‘grey swan’ event bring down the AI revolution?

Cameron Shackwell, Sessional Academic, School of Information Systems, Queensland University of Technology The term “black swan” refers to a shocking event on nobody’s radar until it actually happens. This has become a byword in risk analysis since a book called The Black Swan by Nassim Nicholas Taleb was published in 2007. A frequently cited example is the 9/11 attacks. Fewer people have heard of “grey swans”. Derived from Taleb’s work, grey swans are rare but more foreseeable events. That is, things we know could have a massive impact, but we don’t (or won’t) adequately prepare for. COVID was a good example: precedents for a global pandemic existed, but the world was caught off guard anyway. Although he sometimes uses the term, Taleb doesn’t appear to be a big fan of grey swans. He’s previously expressed frustration that his concepts are often misused, which can lead to sloppy thinking about the deeper issues of truly unforeseeable risks. But it’s hard to deny there is a spectrum of predictability, and it’s easier to see some major shocks coming. Perhaps nowhere is this more obvious than in the world of artificial intelligence (AI). Putting our eggs in one basket Increasingly, the future of the global economy and human thriving has become tied to a single technological story: the AI revolution. It has turned philosophical questions about risk into a multitrillion-dollar dilemma about how we align ourselves with possible futures. US tech company Nvidia, which dominates the market for AI chips, recently surpassed US$5 trillion (about A$7.7 trillion) in market value. The “Magnificent Seven” US tech stocks – Amazon, Alphabet (Google), Apple, Meta, Microsoft, Nvidia and Tesla – now make up about 40% of the S&P 500 stock index. The impact of a collapse for these companies – and a stock market bust – would be devastating at a global level, not just financially but also in terms of dashed hopes for […]

Top tips for securing the investment your manufacturing business needs to grow

-Andrew Mamonitis, Vice President – APAC, Manufacturing Division, ECI Software Solutions It pays to optimise your processes and practices before expanding or bringing an external investor on board. Despite challenging conditions, manufacturing businesses are looking for ways to grow their share of the domestic market and pursue potentially lucrative export opportunities. A low Australian dollar, coupled with our country’s reputation for quality and reliability, is making it easier for some manufacturers, particularly those in the agri-business sector, to get an ‘in’ to new markets, in Asia Pacific and further afield. Seeking funding for growth Taking advantage of an opportunity to diversify your range or expand your customer base generally means upfront investment is required. You may need to acquire new equipment or additional inventory, for example, take on extra staff, or run marketing and business development campaigns. Unless your business has a sizeable sum stashed away, that means borrowing from the bank or bringing an external investor on board. But before writing a cheque, or approving a loan, any potential backer will want to see evidence that your sales are strong, your business is profitable and you’re running a tight ship. If you’re not able to demonstrate you have efficient systems and processes in place, and a solid pipeline of work, you may find it tricky to secure the funds you need to grow. Show me the money Presenting your business in the best possible light starts with showing you’re on top of your finances. Up-to-date accounts, accurate forecasting, rigorous revenue management and a strong understanding of your cash flow are all essential. So is visibility into your customer base. Being able to identify your largest and most profitable accounts and supply a detailed picture of their buying behaviours builds credibility, as does knowing which of your customers […]

Research shows CPG leaders are investing in AI and talent to stay competitive

Rockwell Automation Report finds CPG Industry prioritising innovation over cost cutting Rockwell Automation has announced the results of the 10th annual State of Smart Manufacturing Report: Consumer Packaged Goods (CPG) Edition. The findings highlight how manufacturers are placing greater importance on innovation, workforce development, and long-term growth strategies. The CPG industry is facing pressure on multiple fronts, from the growth of store brands to the demand for faster innovation and more sustainable products. At the same time, consumer loyalty is harder to earn, and expectations for customisation and transparency are rising. In response to this, CPG companies are moving away from small-scale technology pilots and investing in solutions that deliver measurable results across the organisation. The combination of workforce training, better use of data, and more adaptable systems is helping these manufacturers stay competitive while managing complexity. And as private-label brands expand and consumer expectations evolve, CPG leaders are prioritising investments that help them compete more effectively in a crowded and fast-changing market. Notable Key Trends from 2024 to 2025: Rising Competition Leads Industry Concerns: In 2024, economic uncertainty and inflation were main challenges noted in our annual survey. In 2025, competition has taken the lead, driven by increased market pressure from private-label products and changing consumer buying habits. Technology Needs to Work for People: Companies are focusing less on simply adopting new tools and more on making sure new technology fits their teams and operations. Usability and scalability are now critical factors in technological decisions. Capabilities CPG leaders are looking for in their workforce include communications/teamwork (86%), adaptability/flexibility (85%), while analytical thinking and cybersecurity practices are tied (84%). AI and Robotics Lead Investment Priorities: At the heart of technology investment decisions is a shift in thinking. 70% of CPG manufacturers say they are investing in AI, robotics, and simulation […]

Hands free tool changes for smarter machining

Peter Pettersson, Sandvik Coromant Imagine a factory where the lights are off, not because no one is home, but because automated systems are working around the clock to keep production lines running with minimal human intervention. These futuristic setups are quickly becoming a reality, with touchless tool changes at the core of the automated machine cell. Unmanned machining represents a significant leap in manufacturing, where machines operate independently without the need for human supervision. Driven by CNC technology, robotics and automation software, these systems can run continuously — in some cases, 24/7 — performing tasks such as turning, cutting, milling and drilling with high accuracy. This approach enhances productivity, reduces errors and allows for efficient, around-the-clock operation. While many view unmanned machining as a futuristic approach to manufacturing production, Sandvik Coromant began reaping its benefits back in the 1980s. Going hands free Some 40 years ago, Sandvik Coromant’s production site in Gimo, Sweden, used a form of automatic tool change (ATC) that facilitated the changeover of machine tools without human input. The solution was offered as a product to customers, but it didn’t prove popular. Many could not grasp how ATC could save their machine shop time and enhance their productivity and the offering was dissolved. Fast forward a few decades and Sandvik Coromant continued to see value where others could not. This time around, the company worked with a machine builder to develop a second ATC solution. Again, it was implemented at the Gimo production facility and continues to run across several machine cells today. Using conventional tool management methods, a lathe could run without human input for around four-to-eight hours. After that, the tool would reach the end of its life and a human worker would need to stop what they’re doing to manually switch the tool with […]

Beneq launches Transform XP – Redefining atomic control in ALD

Second-generation platform delivers advanced control, in-cycle annealing, and high-throughput performance for Wide Bandgap power and RF device manufacturing Beneq introduces the Beneq Transform XP, a second-generation ALD platform developed to meet the performance demands of Wide Bandgap (WBG) power and RF device technology development and manufacturing. Building on the proven Beneq Transform platform, the new system adds advanced ALD control, faster cycle times, and greater process capabilities in a high-throughput format. The Beneq Transform XP features a second-generation, flow-optimized 25-wafer mini-batch thermal ALD reactor that achieves breakthrough deposition rates with single-digit-second cycle times for common ALD oxides and nitrides. Refined flow and pressure dynamics ensure exceptional within-wafer and wafer-to-wafer uniformity – even at a few nm film thicknesses – while precise dwell-time control delivers excellent conformality on high-aspect-ratio structures. Transform XP also introduces advanced PEALD process control to precisely manage low-energy ions. This enables optimized plasma pre-cleaning and deposition, resulting in improved interface quality, tunable passivation, and enhanced device performance and reliability. The system integrates in-cycle annealing, a proprietary step that densifies and purifies films to achieve stoichiometric, low-impurity materials and crystalline alignment, such as AlN lattice orientation. “Transform XP is in response to the next wave of device challenges in power and RF manufacturing,” said Dr. Mikko Söderlund, Head of Sales, Semiconductor ALD at Beneq. “Customers value the original Transform® for its versatility and reliability. With XP, we introduce capabilities they specifically asked for – improved ion control, faster cycles, and in-cycle film densification – all in a versatile platform.” With over a dozen Beneq Transform clusters installed globally for WBG pilot and production use, and more than 100 process modules shipped, Beneq continues to support leading IDMs, foundries, and RTOs advancing More-than-Moore technologies.

Jobs and the future of work

How to build the skills needed for the age of AI AI is changing how we work and what skills workers need to thrive in a world of intelligent machines and cognitive computing. Only a sliver of education initiatives are devoted to AI and these are not yet integrated into most education systems. Collaborative initiatives between education and industry can accelerate the transition to a greener, more efficient and inclusive world where jobs and skills development pathways are readily available. New technologies can be exciting and disruptive at the same time. Over the past few years, no innovation has been more contentious than artificial intelligence (AI). It is changing the way we think about when, where and how we work and what skills workers need to thrive in a world of intelligent machines and cognitive computing. But it comes with a colossal caveat How will it affect jobs and livelihoods? And, what steps can we take now to futureproof our workforces and equip them with the skills and know-how they’ll need to succeed in a more digital, automated and fast-paced jobs market? Job displacement – or job reconfiguration – is a primary concern. Labour-intensive work, such as assembling electronics or automobiles, handling materials and overseeing supply chains – careers that employ tens of millions of workers, which are critical to the economies of many developing countries – will certainly be impacted as AI-powered activities, such as quality control and robotics, replace some jobs. Knowledge-based workers in industries such as banking, marketing, and human resources may already need to skill-up to coexist with sophisticated technologies for financial analysis, algorithmic trading, predictive analytics and software development. AI will massively impact the workforce The IMF recently estimated that almost 40% of jobs will be impacted by AI. This effect varies by a country’s income level, […]

Agents for growth: Turning AI promise into impact

As CEOs and CMOs ask where AI is moving from hype to real results, frontrunners demonstrate that tighter human–AI collaboration and sharper governance is required. A global retailer sees demand for a top product surge in one region while inventory piles up in another. Within seconds, a team of AI agents reallocates ad spend, adjusts pricing, reroutes stock, and refreshes creative assets to offers that match shopper intent. In this scenario, what comes next is coordinated action triggered by customer signals, orchestrating business growth in real time. This is not a fantasy scenario; it’s the new frontier of AI in growth functions. Agentic AI embeds automated reasoning directly into marketing, sales, and customer service workflows. We estimate that agentic AI will power more than 60 percent of the increased value that AI is expected to generate from deployments in marketing and sales. It’s no exaggeration to say that marketing and sales represent the tip of the spear when it comes to translating agentic AI’s potential into meaningful value. Early leaders are already seeing measurable impact. For example, according to McKinsey analysis, some Fortune 250 companies have estimated that they are seeing campaign creation and execution speed up 15-fold, driven by faster innovation cycles and process optimisation. The value from agentic AI comes from the tasks it is able to do. Unlike gen AI and chatbots that largely assist in the completion of marketing and sales tasks, AI agents can act, decide, and collaborate. They are able, for example, to optimize prices, advance leads, tailor offers and manage customer interactions end-to-end. As organisations deepen their adoption of agentic AI, gains can scale. Analysis shows that effective and scaled agent deployments could deliver productivity improvements of three to five percent annually and potentially lift growth by 10 percent or more. Most organisations, however, […]

Using AI to enable scalable, autonomous operations

By Troy Mahr, director – Kalypso. Kalypso – acquired by Rockwell Automation in 2020 – is a diverse team of consultants, innovators, strategists, data scientists and technologists. What we consistently hear from industry leaders is the need for real-time visibility across their global operations, which is key to ensuring their operations stay agile and scalable. However, achieving this isn’t possible without removing laggy manual data collection through the deployment of connected assets and contextualised data. By eliminating data silos and unlocking industrial data and artificial intelligence (AI) capabilities, companies can enable autonomous decision-making that optimises costs, efficiency, and production resilience. This moves their organisation closer to achieving autonomous operations. Autonomous operations are the manifestation of “self-governing” systems at every step of the manufacturing process. These systems derive their autonomy from data-led decision-making models that enable them to reliably adapt their behaviour in response to dynamic environments during operation without any manual intervention. Achieving autonomy across an enterprise requires capabilities that span the full intelligence spectrum, from observation and inference to decision-making and action. These capabilities are relevant across all operational areas, including product design, manufacturing, supply chain, distribution, direct-to-customer channels, and demand forecasting. Manufacturing operations, in particular, have seen progress through Model Predictive Control (MPC), which continuously analyses real-time and forecasted data to optimise process control within defined constraints. While MPC is a strong example within manufacturing, broader autonomy demands extending similar intelligent systems across the enterprise. This journey is captured in the industrial AI maturity pyramid, which outlines a progression from basic data integration and visualisation to predictive analytics, prescriptive decision-making, and ultimately, autonomous operations. As organisations climb this pyramid, they adopt machine learning, real-time automation, and self-learning systems. Each stage requires not just technological upgrades but also cultural and structural transformation. Asset Monitoring: Find Downtime Root Causes Looking at […]

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