(Bloomberg) — Asian markets look set for a positive open, supported by improved sentiment over potential Federal Reserve rate cuts and reports that US officials may permit the sale of Nvidia AI chips to China.
Futures indicate shares in Australia and Hong Kong will climb in early trading after the S&P 500 closed 1% higher on Friday. China’s benchmark may be buoyed by advances in a gauge of US-listed counterparts on Friday, while Japanese markets are closed for a holiday.
Risk sentiment improved on Wall Street after Bloomberg News reported US officials are having early talks on whether to let Nvidia sell its H200 artificial intelligence chips to China. The market also got an injection of hope after Fed Bank of New York President John Williams suggested a near-term rate cut remains a possibility.
“Expect Asian markets to start on the front foot,” said Nick Twidale, chief market analyst at AT Global Markets. “But given the moves that we saw last week, and the potential for more volatility in the coming days, investors will be understandably hesitant to throw the kitchen sink on positive risk sentiment.”
Markets saw a resurgence in volatility last week, with uncertainty over the Fed’s ability to cut rates also unsettling investors, leading the dollar to notch its best weekly advance in a month. Assets favored by retail momentum traders like crypto and AI winners saw wild swings, with the selloff in Asian tech stocks causing the MSCI Asia-Pacific Index to drop the most since April.
US debt climbed on Friday after Williams, seen as a close ally to Chair Jerome Powell, said he sees room to ease policy in the near term, as downside risks to employment have increased while upside risks to inflation have eased. While traders boosted bets on a December cut, officials remain split on whether to lower rates, with Boston Fed chief Susan Collins indicating her mind isn’t made up about a policy move.
Elsewhere, the euro and pound were steady as fiscal pressures in Europe also take focus. France’s National Assembly rejected part of the 2026 budget in the early hours of Saturday morning, highlighting the uncertainties surrounding Prime Minister Sebastien Lecornu’s approach to tackling the bloated deficit.
The UK government at the weekend said it would freeze rail fares in the budget due Wednesday. It’s one of several affordability measures expected as Chancellor of the Exchequer Rachel Reeves seeks to offset the political pain of having to raise as much as £25 billion ($33 billion) in tax hikes and spending restraint to stabilize the UK’s public finances.
“The spending cuts and revenue raising measures must be judged by the market to be credible,” Commonwealth Bank of Australia strategists led by Joseph Capurso wrote in a note to clients. “The risk is the budget will be judged unfavorably, raising UK government bond yields and weighing on GBP/USD.”
In commodities, oil fell Friday as traders assessed the prospect of a Ukraine-Russia peace deal that would add supply to a saturated market. Gold closed slightly lower.
Some of the main moves in markets:
Currencies
The euro was little changed at $1.1513 as of 7:23 a.m. Tokyo time The Japanese yen was little changed at 156.47 per dollar The offshore yuan was little changed at 7.1066 per dollar The Australian dollar was little changed at $0.6458 Cryptocurrencies
Bitcoin was little changed at $87,908.98 Ether fell 0.2% to $2,833.48 Bonds
Australia’s 10-year yield declined one basis point to 4.45% Stocks
S&P/ASX 200 futures rose 1.1% on Friday Hang Seng futures rose 1.2%
Nov 24 (Reuters) – Qube Holdings (QUB.AX), opens new tab said on Monday that Macquarie Asset Management, a unit of Macquarie (MQG.AX), opens new tab, submitted a non-binding proposal to acquire all the shares of Qube, valuing the logistics firm at A$11.6 billion ($7.49 billion), including debt.
The offer of A$5.20 cash per share represents a 27.8% premium to Qube’s closing price of A$4.07 on Friday, and follows negotiations after a lower unsolicited offer, Qube said.
Sign up here.
“This proposal highlights the strength of Qube’s assets and operations. We will work constructively to ensure the best outcome for our shareholders,” Qube Chairman John Bevan stated.
The board of Qube, Australia’s largest integrated provider of import and export logistics, has signed an exclusivity agreement granting Macquarie Asset Management a due diligence period until February 1, 2026.
The offer price will be adjusted if Qube declares any future dividends.
The deal is subject to due diligence, regulatory approvals, and satisfactory completion of a scheme implementation agreement.
($1 = 1.5477 Australian dollars)
Reporting by Adwitiya Srivastava in Bengaluru; Editing by Edmund Klamann and Richard Chang
Our Standards: The Thomson Reuters Trust Principles., opens new tab
SYDNEY--Australian logistics operator Qube granted Macquarie Asset Management exclusive due diligence after the local asset manager proposed a US$7.5 billion takeover.
Qube on Monday said that MAM, a unit of ASX-listed Macquarie Group, submitted an all-cash proposal worth 5.20 Australian dollars, or US$3.36, a share. The proposal implied an enterprise value of about A$11.6 billion, Qube said.
Qube, which offers import and export services including road and rail transport, said the proposal followed an initial lower-value approach from MAM.
Qube's directors intend to unanimously recommend the proposal if it is formalized as a binding offer.
MAM has exclusive due diligence until Feb. 1.
"The proposal from Macquarie Asset Management is a reflection of the strength of Qube's business model and our assets, and the quality of our people and culture," Qube Chairman John Bevan said.
How is the legendary automaker Ford Motor Company (NYSE: F) incorporating AI into its operations to innovate and transform its business for the 21st century?
Just over a century ago, Ford pioneered one of the most significant technology transformations of our times–the introduction of the automobile. In 1903, Henry Ford incorporated the Ford Motor Company in Dearborn, Michigan, followed by the introduction of the Ford Model T in 1908–widely credited with having revolutionized both transportation and American industry.
Today, Ford is betting on the next stage of technology innovation–AI. With annual revenues of $185 billion, Ford ranks 19 on the Fortune 1000, and markets automobiles and commercial vehicles across the globe. So, how does a company that pioneered an earlier era of innovation adopt the next wave, manifested by artificial intelligence (AI), to optimize its business operations for the next generation of customers?
AI and Data Leadership at Ford
I recently posed this question and others on the topic of AI and data transformation and leadership to Franziska (Fran) Bell, who has served as chief data, AI, and analytics officer (CDAAO) for Ford since January 2025. Bell previously was the CTO at bp and held tech executive roles at Toyota Research Institute and Uber. She earned a PhD in theoretical chemistry from the University of California, Berkeley. Earlier this year, Bell was recognized as Chief Data Officer of the Year and named to the AI100, Top 100 Women in AI and Top 100 Women in Tech.
Bell explains her AI and data leadership role at Ford, commenting, “My primary role is to closely partner with the business to drive improved user experiences and tangible business value at scale.” She adds, “My mandate is to ensure that we are not only leading in AI application but also treating our data as the strategic asset it is.”
Bell elaborates on her primary responsibilities, including:
Delivering Business Value: Ultimately, the mandate of the chief data, AI, and analytics officer at Ford is to ensure that the company’s investments in data and AI translate into measurable business impact.
Driving Strategy and Vision: As CDAIO for Ford, Bell is responsible for defining and aligning the company around its enterprise-wide Data and AI strategies to ensure that Ford is making the right investments to maintain a competitive edge.
Enabling the Business: Bell’s organization provides the foundational platforms, such as the Enterprise Data Platform (EDP), and democratized tools that empower teams across Ford to build and deploy AI solutions securely and efficiently. Bell notes that Ford had the foresight to centralize its data team 10 years ago. This provides the advantage, explains Bell, to “connect the dots across the company, and sets us up nicely to re-use technology, making us faster and more efficient.”
Governance and Oversight: Bell chairs Ford’s Enterprise Data Council, which governs the company’s data assets, platform usage, and technology investments. This ensures that Ford is using its resources effectively, avoiding duplicative efforts, and building on a common, scalable foundation. It also ensures that Ford is protecting personal information and ensuring Ford has the appropriate approaches to protecting consumer privacy.
Using AI and Data to Transform the Enterprise at Ford
AI is being developed as a core capability across Ford, notes Bell. Data is a fundamental underpinning to all aspects of Ford’s business, including design, engineering, testing and safety, manufacturing and quality, marketing and sales, as well as back-office systems and customer support. “We use data for virtually everything we do”, adds Bell. “For a company with a 120-year history, our unique and vast data sets—spanning decades of design, engineering, safety, connected vehicle, and manufacturing data—are invaluable.”
Bell elaborates, “Our strategy is centered on capitalizing on Ford’s data advantage.” She continues, “We’re not just collecting data; we are positioning it as a core corporate asset through our Enterprise Data Platform (EDP). This is the cornerstone of our efforts, designed to be the authoritative source for analytics and AI-driven insights.” Ford is combining its wealth of data with work to deeply embed AI as a core capability across every business function.”
Ford is moving beyond isolated projects to create a truly integrated and intelligent ecosystem of AI and data. Bell explains, “This means weaving AI into the fabric of our core processes—from the initial design concept all the way through to manufacturing and the customer ownership experience.” She adds, “The goal is to create a holistic system where data and insights flow seamlessly, allowing us to innovate faster and drive business value at Ford’s scale.”
Central to this vision at Ford is the concept of AI as a digital partner for the Ford workforce. Bell explains, “We believe AI’s greatest value is realized not by replacing human ingenuity, but by augmenting it.” She continues, “We are building powerful ‘human-machine teams’ where AI assists in complex data analysis, runs simulations, and automates repetitive tasks, freeing our talented engineers, designers, and business leaders to focus on what they do best: strategic thinking, creative problem-solving, and building the future of mobility.”
Ford’s ‘Big Bet’ AI Projects
Central to Ford’s plans to use AI to deliver transformative value across business lines is the idea of what Ford calls its “big bet” AI projects. Bell comments, “While these projects are designed to deliver transformative value across the business, we are at the same time democratizing access, encouraging individuals to use AI in their jobs, and seeing lots of projects percolate up out of experimentation.” Examples of Ford’s AI initiatives include:
AI-Accelerated Vehicle Design: Ford designers now use generative AI to turn a single sketch or use a set of parameters to render hundreds of high-fidelity images and 3D models almost instantly. This elevates Ford designers to creative directors, allowing them to explore a vastly wider range of possibilities.
Virtual Wind Tunnel: Ford has developed proprietary AI models that reduce the time for a complex aerodynamic simulation from 15 hours to approximately 10 seconds (a 5000x speed increase), with results that are within 2.3% of the traditional physics-based models. This allows Ford engineers to iterate and optimize designs at a speed that was previously unimaginable.
AI-Powered Customer Support: Ford has launched an AI agent on the Ford.com site that acts as a single front door for customer questions. It can query multiple knowledge bases, access tools like a towing calculator, and synthesize the information into one clear, referenced answer, dramatically improving the customer experience.
AI-Supercharged Code Reviews: In software engineering, Ford has implemented an AI-assisted “code reviews-as-a-service” capability. Early results with over 1,000 software engineers have shown a 3x reduction in cycle time, allowing Ford to innovate on digital experiences much faster.
Building an AI & Data Business Culture within Ford
One of the greatest challenges that organizations face in adopting AI and data within their businesses is due to cultural obstacles, according to 92% of organizations surveyed.
Ford is taking measures to build an AI and data culture which will lay a foundation for adoption and business success. Bell explains, “Building a data and AI-driven culture is about empowerment and collaboration — where we constantly show quantifiable business wins and solve real problems across Ford’s business.” She continues, “Along that path, we are making internal data, analytics and AI products intuitive to use, putting the human user at the core of the experience.”
Bell elaborates, “Our data and AI teams are integrated with the various parts of the business, so that data and AI are being deployed where they solve the biggest business problems.” She notes, “Our philosophy is that AI’s greatest value is realized when it augments our talented workforce, creating powerful “human-machine teams.” Bell notes that to achieve this outcome, Ford has focused on three key areas:
Democratizing Access: Ford is currently providing employees at all levels of the organization with access to AI tools and platforms. FordLLM is the internal Ford platform where teams have access to the latest large language models and other AI tools and agents. This puts AI in employees’ hands and is proving very useful for internal productivity, notes Bell. She notes that Ford is currently seeing about 50,000 weekly active users, which represents significant repeated usage.
Fostering an AI-Powered Workforce: Ford is committed to continuous training and upskilling to ensure its workforce can operate at the highest level. Bell explains that it is the goal within Ford to integrate AI where it can augment human potential and not just automate tasks. Bell explains that this means, “co-designing future workflows with our people.” In the first half of 2025, she notes that AI training has reached 10,000 employees within Ford.
Championing Responsible AI: Trust is paramount at Ford. Bell explains, “We champion a ‘human-in-the-loop’ model, where human oversight provides essential judgment and validation.” She continues, “Our AI principles, guided by our AI Technology Council and Ethics Hub, ensure that we innovate responsibly, with a strong focus on data privacy and transparent governance.”
Delivering Business Value from AI and Data Investments at Ford
Delivery of business value from its AI and data investments is a top organizational priority for Ford. Bell explains, “We measure the value of our data and AI investments through a disciplined framework that combines financial rigor with key operational metrics.” She continues, “We have a robust process, run in close partnership with our Finance team, to ensure every significant AI project has a clear business case.”
Beyond direct financial returns, Ford measures business value through a balanced scorecard of key performance indicators (KPIs) that reflect the company’s strategic priorities, including:
Accelerated Delivery: Ford tracks reductions in the cycle times of critical processes. By delivering products and features to market faster–in engineering design, software development, and other domains–Ford can create a significant competitive advantage.
Improved Quality and Reduced Costs: Ford measures the impact of AI on product quality and operational efficiency. This includes tracking improvements in manufacturing defect detection, which in turn helps reduce potential warranty costs and enhances customer satisfaction.
Enhanced Agility: Ford assesses the ability to make faster, more informed decisions across the company. By making data and self-service AI tools more accessible, Ford empowers its teams to respond more quickly to market shifts and customer needs.
Bell comments, “In some cases, business value is achieved by solving quality issues earlier and faster than we have traditionally been able to do. She continues, “In another case, AI is helping software coders with code review, making it three times faster than it used to be.” Bell concludes, “We continuously track the business outcomes of these initiatives to ensure they deliver on their promised value.”
Planning for an AI Future at Ford
Looking ahead to the future, Ford is being tested by forces that are reshaping the automotive industry. These include adapting to technological leaps forward and responding to the emergence of new competitors. The ability to leverage the transformation potential of AI and data will be distinguishing factors for those companies that continue to innovate and lead.
Bell reflects on change and the future of the automotive industry. “At Ford, we see the application of data and AI as fundamental tools to transform our entire enterprise, improve the user experience, and drive tangible business value,” comments Bell. She elaborates, “We view data and AI as critical strategic assets that provide a significant competitive edge. By effectively leveraging these assets, we can develop innovative AI applications rapidly and securely that differentiate us from competitors, from optimizing supply chains to personalizing the customer experience.”
AI and data leadership starts at the top and extends across the Ford organization. “Our leaders are hands-on, actively using our new AI tools themselves”, explains Bell. “By becoming practitioners, our leaders not only gain a deeper understanding of the technology’s potential but also serve as powerful advocates, championing adoption and encouraging employees to integrate these capabilities into their daily work.” She adds, “Our leadership team at Ford is not just embracing data and AI–they are driving it as a core component of our business strategy.”
Bell sums up, “This visible, top-down engagement sends a powerful message across the organization–AI is not just a Tech initiative; it is a fundamental part of how Ford will lead and compete. We think AI will deliver significant business results that will improve cost and quality, make us a more agile business, and will enable Ford to vigorously compete in the future of this industry.” She concludes, “We are making AI available to every employee at Ford, and in doing so we are helping make our teams smarter, faster, and more effective as we redefine automotive excellence.”
Closed reduction is often used to treat distal radius fractures (DRFs). After that, splint immobilization is used to keep the bone in the right position. But, long—term immobilization can cause problems like joint stiffness, long—lasting swelling, and slow bone healing. Rehabilitation training is a commonly employed recovery modality following conservative management of fractures. However, its efficacy is often suboptimal, primarily attributable to two key factors: nonstandardized rehabilitation protocol design and poor patient compliance with prescribed training regimens in terms of both adherence to schedule and completion of required exercise dosage. Earlier studies show that Fu’s Subcutaneous Needling (FSN) therapy can lessen wrist pain and swelling, and also improve joint movement in patients with fractures of DRFs. But we need more evidence to prove it works. This trial wants to see if combining FSN therapy with rehabilitation training can help promote fracture healing and improve post-fracture symptoms in DRFs better and safer when added to conservative treatment, compared to using sham FSN therapy with rehab exercises.
Methods and analysis
This single-center, sham-controlled clinical trial will enroll 84 eligible patients, randomly allocated to two groups (n = 42). The intervention group will receive FSN therapy, while the control group will undergo sham FSN therapy. The treatment schedule includes three sessions in the first week post-reduction, two sessions per week in weeks 2–3, and one session per week in weeks 4–8, totaling 12 sessions. The primary outcome is the time to radiographic union, assessed using a modified Radiographic Union Score for Tibial fractures (RUST) adapted for distal radius fractures. Secondary outcomes include complications (e.g., pain, swelling), functional recovery (measured by the Disabilities of the Arm, Shoulder, and Hand [DASH] score), and radiographic parameters (e.g., volar tilt, radial height).
Discussion
This study is expected to validate the clinical value of FSN therapy as a safe and effective adjunctive approach for rehabilitation following DRFs, bridging the technical gap between conventional conservative treatment and functional recovery.
‘The feedback from students reflects a growing desire for partnership. They aren’t just asking for permission to use AI, they’re asking for guidance, collaboration, and trust.’ Last year we published an article about Queensland teachers working with academics on an action research project into student use of generative AI and their motivations for turning to the tech. In this update, Georgia Wignall – Senior Education Officer of Pedagogy at Queensland Department of Education – shares fresh insights from students, and how focused professional learning communities are being used to help teachers respond to this feedback.
In 2024, Balmoral State High School partnered with the UQ Learning Lab to investigate student motivations for using generative AI tools like ChatGPT, Gemini and Copilot in their learning. The goal was simple: to better understand how and why students were leaning on these tools, and to use that insight to inform teaching practice.
The findings revealed a clear need to build teacher capability, rethink assessment design, and provide students with explicit guidance around the ethical use of AI.
A year on, we still recognise the importance of explicit instruction around ethical and responsible use of AI tools. However, our current focus centres on building teacher capability through professional learning communities (PLCs) and exploring how assessment can be redesigned to reflect the realities of AI-enhanced learning.
These PLCs, established across Balmoral SHS, Holland Park SHS, and Brisbane Bayside State College, have become a space for teachers to share practice, experiment with AI tools, and reflect on how to support students in meaningful, ethical ways. Most importantly, they’ve reminded teachers that we are co-learners in this space. We’re not just teaching students about AI, we’re learning alongside them.
To ensure our understanding of student attitudes and behaviours remains accurate, we’ve continued to collect data. This year, we expanded to include student voice from Holland Park SHS and Brisbane Bayside SC (711 participates across year levels – 352 females, 318 males, 14 non-binary and 27 unidentified).
The most recent results offer insights into how students are using AI, what they believe about its ethical boundaries, and how they want teachers to support them.
What’s changed? What’s stayed the same?
Across all 3 schools, student use of AI tools has become more widespread and nuanced. Similar to the 2024 findings, students are using AI across a range of subjects – English, Science, and Maths top the list, with 49% of students reporting using AI in 3 or more subjects, and female students tending to use AI more diversely across the curriculum.
When it comes to the perceptions of cheating and using AI tools ethically, only 24-34% of students believe using AI is cheating. Younger students (years 7 and 8) are still more likely to view AI use as dishonest, while senior students tend to see it as a legitimate support tool. Regardless of age, students consistently agree that copying and pasting AI-generated work is unethical. However, using AI for feedback, grammar checks, or idea generation is seen as acceptable and even helpful.
The most common uses of AI across the schools were for explaining hard concepts (69%), generating ideas (67%), and supporting grammar and punctuation (49%). These numbers reflect a shift from novelty to utility. Seemingly, students are choosing to use AI not to shortcut learning, but to scaffold it.
It helps me learn by explaining hard concepts in a simple way where teachers can’t always provide the same kind of detail. – year 11 student
Trying to answer questions by Googling is too inefficient nowadays. AI allows you to ask a question and get an immediate relevant answer. – year 10 student
AI helps me get going with assignments and generate ideas as well as sources that I can use. – year 11 student
What students want from teachers
One of the most encouraging continuations we’ve seen is in how students view their teachers’ role in supporting AI use. Emerging last year, students want greater clarity and precision around ‘what’s ok’ and ‘what’s not’ – and they want us to be honest about how we’re using it ourselves. Most of all, they want support, not suspicion. Based on our survey students want:
Clear boundaries between ethical and unethical AI use
Practical demonstrations of how AI can support learning
Transparency about how teachers themselves use AI
Non-judgmental support when students are exploring AI tools
Encourage AI in situations where it is valid, and demonstrate the many mistakes made by AI and the importance of fact-checking. – year 12 student
Stop accusing students of using it over stupid things like (em) dashes … maybe ask the student if they know what the word means. – year 10 student
Support it while setting boundaries. – year 9 student
The feedback from students reflects a growing desire for partnership. They aren’t just asking for permission to use AI, they’re asking for guidance, collaboration, and trust.
Where to next?
As we move forward, our next steps are grounded in the work we’ve already begun through our PLCs. They have allowed us to build capability in a collaborative, low-pressure environment, where experimentation and shared learning are encouraged.
Each school’s goal now is to gradually transition from these PLCs into whole-school capability building. We want every teacher to feel confident not only in using generative AI themselves, but in guiding students through its ethical and effective use. This shift will support the redesign of assessment practices and ensure that explicit instruction around AI is embedded across subjects, not just in isolated pockets.
Most importantly, we’re embracing the idea that we are co-learners in this space. AI is evolving rapidly, and none of us have all the answers. But by learning together, asking questions, and staying curious, we can shape a learning environment that is both future-focused and grounded in integrity.
Finally, I would like to thank the staff and students at Balmoral SHS, Holland Park SHS, and Brisbane Bayside SC for their participation in this work. Their insights, openness, and willingness to engage have been invaluable. This collaboration continues to shape our understanding and strengthen our shared commitment to co-learning, ethical practice and future-focused education.
Bitcoin’s price has seen a dramatic drop over the past month, dragging its elusive creator’s purported net worth down with it.
Just over a month ago, Satoshi Nakamoto’s total Bitcoin holdings were valued at $137 billion, according to Arkham Intelligence data, based on wallets believed to be connected to the pseudonymous creator.
This made Satoshi the 11th richest person—if it is a single person, that is—in the world, when compared to the Forbes billionaires list, ahead of the likes of Microsoft co-founder Bill Gates. (Forbes doesn’t track Satoshi, to be clear.)
However, with Bitcoin’s decline of more than 30% to a recent price of $87,281, from its all-time high of $126,080 set in early October, Satoshi’s net worth has fallen to $95.8 billion in just over a month. This now places the mysterious founder as the 20th richest person in the world, poorer than Gates at $104.4 billion.
Satoshi Nakamoto is the pseudonym adopted by the creator of Bitcoin when they wrote the white paper in 2008, as well as when talking on forums or via email. Despite countless attempts to unmask Satoshi’s true identity—including a high-profile HBO documentary last year—no one has successfully convinced the public that they have found the right person.
Bitcoin, XRP and Dogecoin Pummeled as Crypto Liquidations Top $2.2 Billion
Crypto experts have been able to determine how much Bitcoin the creator holds. Identified using what is called the Patoshi Pattern—a distinctive pattern of mining only found in the earliest Bitcoin blocks—experts estimate that Satoshi owns approximately 1.1 million BTC, close to the 1.096 million BTC tally that Arkham Intelligence tracks.
That said, Satoshi’s real net worth could be potentially much different from this figure, as we do not know of any off-chain or non-Bitcoin holdings. Equally, Forbes calculates the net worth of billionaires using the individual’s public holdings and estimates the value of private holdings, which could be inaccurate.
Regardless of Satoshi’s exact net worth, it’s safe to assume that $95.8 billion is a significant portion of their net worth. For that reason, some believe the elusive creator may step out from the shadows as quantum computing advancements threaten to break Bitcoin, also known as Q-Day.
BitMine Shares Tumble After Earnings as Ethereum Price Falls, Treasury Hype Fades
Proposals have already been made to freeze Satoshi’s Bitcoin due to the looming quantum “existential threat.” Others have suggested a Bitcoin hard fork to quantum-proof the entire network.
However, Joseph Chalom—the co-CEO of SharpLink Gaming, a leading Ethereum treasury company—previously told Decrypt that he believes Satoshi may reveal themself as this hurdle is attempted.
“I have a wild idea that at some point—five, 10 years from now—when the Bitcoin network needs to be quantum-proofed, there will be some really important decisions around standards and encryption,” Chalom said in September. “There’ll be decisions about whether you need to hard fork the protocol [and] what you do with wallets that are dormant.”
