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A report in The Straits Times (Jan. 8, 2026) by Elisha Tushara outlines Republic Polytechnic’s plans to expand the use of artificial intelligence across its teaching and learning programmes. The move is presented as a concrete step to bring AI tools into the classroom in ways that mirror workplace practices.

One concrete example cited in the article is an AI‑driven chatbot created to train students studying hotel and leisure management. The chatbot can simulate guest interactions, giving learners a realistic environment to practise communication and problem‑solving without waiting for real guest encounters.

Republic Polytechnic has set a clear near‑term benchmark: by 2027, at least half of all discipline‑specific modules will incorporate AI tools used in the workplace. That target reflects an institutional push to embed practical AI experiences into the curriculum rather than treating AI as a separate or purely theoretical subject.

If implemented as described in the article, the initiative signals a shift toward aligning student learning more closely with the digital tools they will encounter on the job—using simulation and AI to supplement hands‑on practice and professional preparation.

A Dec. 17, 2024 piece from BEHRENS reminds us that mechanical watches are more than instruments for telling time — they are celebrations of craftsmanship, history and ingenuity. Even as the world moves deeper into the digital age, the article argues, the quiet allure of a finely made mechanical movement remains strong: these timepieces offer a tangible connection to tradition that a screen cannot replicate.

The article frames mechanical watches as a meeting point between past and present. On one hand they carry centuries of watchmaking techniques, visible in the finishing, the winding, and the delicate dance of gears and springs. On the other, contemporary developments and modern innovations have helped ensure that mechanical watches stay relevant to today’s audience, blending artistry with thoughtful technical updates.

Ultimately, BEHRENS presents a hopeful, balanced view: mechanical watches won’t simply vanish into obsolescence as the world digitizes. Instead, they persist as objects of meaning — heirlooms, expressions of craft, and bridges between tradition and the innovations that keep the craft alive. For anyone who values the story behind an object as much as its function, the future of mechanical watchmaking still looks bright.

On March 7, 2025 the Canadian Airports Council (CAC) issued a press release from Ottawa, ON responding to the federal government’s Policy Statement on Investment at National Airports System airports. The short announcement makes clear the CAC’s position: the Council welcomes the government’s policy statement and has formally responded to its direction on investment at National Airports System airports. The release was issued for immediate distribution and signals the aviation sector’s engagement with federal priorities for airport investment.

Republic Polytechnic’s Academy for Continuing Education (RP ACE) is positioning itself as a practical gateway for adult learners who want to keep their skills current and relevant. According to RP ACE’s programme overview, it offers a comprehensive suite of lifelong learning programmes designed specifically to provide adult learners with skills-upgrading opportunities.

Learners who go through RP ACE consistently describe the experience in terms that matter on the job. The knowledge gained has been called “invaluable” in professional endeavours — helping graduates make more informed decisions, implement best practices, and contribute effectively to their organisations. That testimonial captures the core promise of RP ACE: not just new credentials, but usable skills that change how people work.

For working adults thinking about upskilling, RP ACE’s approach highlights an important shift in education — from one-time qualifications to ongoing development that responds to real workplace needs. The emphasis on lifelong learning and practical outcomes makes it clear that RP ACE is focused on helping learners translate study into immediate, measurable impact in their careers.

Whether you’re aiming to refresh existing skills or add new ones to your toolkit, the RP ACE message is straightforward: targeted, professionally useful programmes can make a tangible difference, and the right learning can empower you to contribute more confidently and effectively at work.

Food security remains one of the most pressing global challenges of our time, but a revolution is quietly underway, driven by the transformative power of data and artificial intelligence (AI). The article “Reimagining Food Security with Data and AI” from the Patrick J. McGovern Foundation highlights how emerging technologies are reshaping every aspect of food systems—from farm to fork—in ways that could drastically reduce hunger and food waste.

Imagine a world where farmer-facing chatbots provide instant, expert advice to smallholder farmers, helping them combat pests, optimize crop yields, and navigate changing climate conditions. Picture sophisticated predictive analytics that allow food banks to forecast demand precisely, ensuring surplus donations are efficiently distributed to communities in need before food expires.

This is not science fiction but the reality that AI and data innovations are enabling today. The article highlights key advances such as:
– AI-powered tools that monitor crop health using satellite imagery and real-time sensor data.
– Waste reduction models that identify inefficiencies along the supply chain, minimizing spoilage and loss.
– Chatbots and virtual assistants designed to support farmers in remote areas with timely recommendations.

What makes this technological shift truly promising is its potential to be inclusive and scalable. By harnessing AI to empower small-scale farmers and local communities, we can address food insecurity at its root while also promoting sustainable agricultural practices.

The intersection of data and AI in food security opens new pathways to resilience amid climate uncertainty and growing populations. From reducing waste to enhancing productivity, these tools promise a future where no one goes hungry, and food systems are smarter and more equitable.

As we move forward, it is crucial that these innovations remain driven by genuine needs and equity, ensuring that technology uplifts all who depend on the land for their livelihoods and nourishment. The future of food security, powered by data and AI, is bright—but it requires thoughtful collaboration and commitment to sustainability.

For anyone interested in the future of agriculture, technology, or global development, this article offers inspiring insights on how AI is reshaping our approach to one of humanity’s most vital challenges.

As we approach 2025, the landscape of dog ownership and pet care is evolving rapidly thanks to cutting-edge technology and innovative trends. Leading this transformation is the integration of artificial intelligence (AI) into every aspect of pet healthcare and lifestyle, creating a future where dogs are healthier, happier, and more connected to their humans than ever before.

One of the most exciting developments is AI-powered healthcare tools that enable real-time monitoring and early diagnostics. Advanced cameras and AI systems can now detect subtle changes in a pet’s activity, emotional state, and health indicators. This allows pet owners and veterinarians to intervene early, potentially saving lives and improving quality of life.

In addition to health monitoring, AI is revolutionizing daily care with smart devices. From automatic, self-cleaning litter boxes to programmable dog doors that reduce indoor accidents, technology is making pet care more convenient and hygienic. Interactive toys equipped with AI keep pets mentally stimulated and engaged, which supports their emotional well-being.

Moreover, AI-driven chatbots, booking tools, and voice agents are reshaping how pet care services operate, optimizing everything from appointment scheduling to personalized treatment plans.

Looking beyond traditional pets, AI pet companions—robots designed to offer friendship and interaction—are poised to become household members, especially for those unable to care for live animals. These AI pets can interpret emotional states and adapt their behavior, providing meaningful companionship.

The future of dog care in 2025 is bright, with AI and technology offering unprecedented opportunities for improving pet health, behavior understanding, and owner convenience. As we embrace these advancements, the bond between humans and their canine companions will grow deeper, supported by smart solutions that are as loving as they are intelligent.

In the rapidly evolving world of automation, the emergence of AI-driven agentic workflows is transforming how businesses operate. n8n, the powerful workflow automation platform, now offers users the ability to implement intelligent and adaptive AI agentic workflows that can revolutionize traditional automation processes.

AI agentic workflows in n8n are designed to be more than simple task automations; they enable autonomous decision-making and adaptive responses within workflows. Whether you’re looking to deploy a single AI agent or orchestrate complex multi-agent teams, n8n provides the tools and patterns needed to handle advanced automation scenarios effectively.

One fascinating use case highlighted in recent discussions and experiments involves integrating n8n with popular developer tools like GitHub Copilot and JIRA. This integration enables an autonomous AI workflow where:
– New JIRA tasks trigger the workflow
– Details from the task are parsed and analyzed
– AI classifies the development tasks
– GitHub Copilot is prompted to generate tailored code
– Pull requests are automatically created and linked back to JIRA
– The status in JIRA is updated accordingly

This kind of workflow showcases the true “agentic” nature of the automation: it plans, executes multi-step tasks, interacts with external APIs, monitors execution for errors, and retries when necessary.

Moreover, n8n’s flexibility allows users to import data from files, databases, or websites into AI-powered applications seamlessly, creating a bridge between traditional data sources and modern AI capabilities. With over 422 app integrations, the possibilities for customization and scaling are extensive.

However, like all AI systems, agentic workflows in n8n face challenges such as output consistency. Users have noted that AI models sometimes produce varying outputs for the same inputs, which can affect reliability in production. Solutions such as output parsers, retry mechanisms, and thoughtful workflow design help mitigate these issues.

For low-code enthusiasts and developers alike, n8n’s platform offers a practical and powerful way to harness AI’s potential within workflows without starting from scratch. Whether you’re experimenting with prototypes or deploying robust production systems, agentic workflows in n8n open new doors to efficient, intelligent automation.

In summary, if you’re looking to elevate your automation strategy, exploring AI agentic workflows with n8n is a game-changer. It’s not just about automating tasks anymore; it’s about creating workflows that think, decide, and act autonomously — all while integrating smoothly with the tools and data you rely on every day.

In a geopolitical twist that feels ripped from satire, the debate over Greenland’s future has exploded into one of the hottest topics in international relations. Recently, calls from former President Donald Trump to acquire, and even potentially invade, Greenland have escalated from campaign trail bluster to the halls of Congress and the Pentagon. But there’s a crucial detail that can’t be ignored: any US attempt at forcibly seizing Greenland would trigger far more than a diplomatic crisis—it would spark a war with NATO itself.

As reported by ABC News, Republican Congressman Michael McCaul, Chair of the House Foreign Affairs Committee, minced no words: “Any U.S. invasion of Greenland would mean war with NATO itself.” Greenland, though often pictured as a remote, icy outcrop, is an autonomous territory of Denmark—a founding member of the North Atlantic Treaty Organization. Under Article 5 of the treaty, an attack on one member is considered an attack on all.

Why would the US want Greenland? The answer lies in its billionaire real estate—rare earth minerals, vast untapped resources, and a strategic position in the Arctic that is increasingly significant due to climate change and renewed great power competition. But this isn’t the 19th century. Nations can’t simply be bought, sold, or conquered at whim.

McCaul’s stark warning comes amid bipartisan concern in Washington, as many fear such a move would not only be militarily foolhardy but shatter decades-old alliances overnight. The chorus of critics isn’t just domestic: European capitals are on high alert, Denmark has firmly rebuffed any consideration of selling the island, and Greenlandic leaders have declared their home is not for sale—or conquest.

The episode has generated new calls in Congress to proactively bar any use of force, with lawmakers scrambling to introduce resolutions that would block funding or authorization for any military operation against the island. The message from both sides of the aisle is clear: America cannot afford to sacrifice its global leadership, its alliances, or its international reputation for a fantasy.

In short, any serious move to invade or acquire Greenland by force would not only be legally and morally indefensible—it would be a declaration of war against America’s closest friends. One hopes that cool heads prevail, and this latest chapter in foreign policy adventurism melts away as quickly as last year’s Arctic snows.

Artificial Intelligence (AI) is undoubtedly transforming our world, powering everything from convenience-driven tech to groundbreaking scientific research. However, behind this digital marvel lies a pressing and often overlooked issue: AI’s environmental impact.

The sprawling data centers that house AI servers are notorious for their massive electricity consumption and generation of toxic electronic waste. Most of this electricity still comes from fossil fuels, contributing significantly to climate change. Training complex AI models, like those with billions of parameters, requires vast amounts of computational power, which translates into substantial carbon footprints. For instance, training a single large language model can consume thousands of megawatt hours of electricity and release hundreds of tons of carbon.

Moreover, the environmental toll extends beyond just energy use. The heat dissipation needs from these centers lead to enormous water consumption for cooling, putting additional stress on already limited freshwater resources in many regions. AI’s environmental impacts are unevenly distributed globally, often exacerbating inequalities by disproportionately affecting disadvantaged communities.

Experts also warn about higher-order effects—AI’s potential misuse to generate misinformation about climate change could undermine global climate action efforts. This underlines the importance of ensuring ethical and responsible AI use.

So, what can be done? Solutions require a multifaceted approach:

1. Transitioning data centers to renewable energy to reduce reliance on fossil fuels.
2. Designing more energy-efficient AI algorithms and hardware.
3. Implementing stricter regulations and environmental standards for AI infrastructure.
4. Equitably managing AI’s deployment to avoid exacerbating environmental injustices.
5. Promoting transparency from tech giants about AI’s true environmental costs.

By balancing AI’s phenomenal capabilities with conscious sustainability efforts, we can harness its benefits without compromising the planet’s health. As AI continues to evolve, so must our strategies to mitigate its environmental footprint. This is crucial to ensure AI contributes positively to the fight against climate change rather than becoming another major contributor to the crisis.