Tech
14 Ways Smart Grids Will Transform Asia’s Energy Landscape by 2030
Explore the top 15 predictions for smart grid technologies in Asia, revolutionising energy production.
Published
7 months agoon
By
AIinAsia
TL;DR:
- Virtual Power Plants (VPPs) will stabilise grids and reduce pollution
- Smart grids will enhance cybersecurity and resilience against threats
- Community-based energy infrastructure will democratise energy distribution
Artificial Intelligence (AI) and Advanced Grid Innovation (AGI) are set to revolutionise the energy sector in Asia. Smart grid technologies, which use digital communication to monitor and manage energy flows, will transform the way energy is produced, distributed, and consumed. In this article, we explore 14 ways smart grid technologies will reshape Asia’s energy landscape by 2030, based on predictions from experts in the field.
- Virtual Power Plants (VPPs) for Grid Stability VPPs will play a crucial role in maintaining grid stability during extreme weather conditions and evolving consumption patterns. By leveraging smart grid technology, VPPs will balance the grid and reduce the need for polluting peaker plants. (Michael Smith, CPower)
- Enhanced Cybersecurity and Resilience Smart grid technologies will bolster cybersecurity and resilience against physical and virtual threats. Advanced sensors, monitoring systems, and data analytics will enable utilities to detect and respond to potential security breaches or equipment failures promptly. (Naresh Kumar Miryala, Meta)
- Community-Based Energy Infrastructure The rise of home-installed solar panels and other renewable resources will enable individuals to supply excess power back to the grid. This shift toward community-based, sustainable infrastructure will democratise energy distribution. (Viktor Trón, Swarm)
- Balancing Energy Generation and Storage Improvements in smart grid technologies will lead to better integration of battery technology. This will result in a harmonious relationship between energy generation and storage, helping to decentralise energy production. (WaiJe Coler, InfoTracer)
- Improved Fault Detection and Restoration New technologies will improve fault detection and restoration, allowing for rapid identification and isolation of issues to minimise power interruptions. Smart grids will also facilitate the integration of renewable energy sources. (Roman Reznikov, Intellias)
- Integration of Renewable Energy Sources Smart grid technologies will enable the efficient and reliable distribution of energy, allowing for real-time monitoring and management of energy usage. This will support the transition to more sustainable energy systems. (Adrien Nejkovic, Hearst Capital)
- Real-Time Energy Management AI-powered smart grid technologies will enable real-time pricing, generation, storage, and maintenance management. This will transform the energy landscape and address challenges related to renewable energy integration. (Gladwin Mendez, Simplyai)
- Unified Utilities for Efficiency Smart grid technologies will unify diverse utilities such as electricity, water, and gas into a single system. This will optimise energy usage, balance supply and demand dynamically, and boost efficiency. (Jabin Geevarghese George, Tata Consultancy Services)
- Better Demand Forecasting and Response AI-driven tools in smart grid technologies will aid in demand forecasting, preventative maintenance, and response to dynamic conditions impacting energy supply and grid resilience. (Merav Yuravlivker, Data Society)
- Lower Costs and Improved Reliability Smart grids will enable more efficient and resilient energy distribution, reducing outages and seamlessly incorporating renewable energy sources. This will lead to lower costs and improved reliability for consumers and providers. (Miguel Llorca, Torrent Group)
- Cybersecurity Technology Integration Smart grid technologies will integrate cybersecurity technology to ensure robust defence mechanisms are in place, protecting against increasingly sophisticated cyber threats. (Dan Sorensen, Air National Guard)
- Preemptive Fault Identification and Correction Smart grid technologies will enhance energy efficiency by enabling predictive maintenance, identifying and fixing faults preemptively, improving reliability, and reducing outages. (Andres Zunino, ZirconTech)
- Microgrids for Resilience and Sustainability Climate change and natural disasters will increase the need for microgrids, which function independently of the national grid. Microgrids using alternative energy will help achieve net-zero goals and reduce reliance on fossil fuels. (Simon Bennett, AVEVA)
- Decentralised Energy Production Smart grid technologies will empower consumers to become active participants in the energy market, enabling them to produce, store, and sell energy. This will increase the adoption of renewable sources and create a more resilient energy system. (Jo Webber, Pod)
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- To learn more about Smart Grids tap here.
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Adrian’s Arena: Why I (Mostly) Switched from Google Search to Perplexity AI
Discover why Perplexity AI outshines Google for in-depth research. Learn about its direct answers, real-time updates, and advanced features like conversational queries and image generation. Perfect for professionals seeking smarter search solutions.
Published
2 weeks agoon
January 10, 2025
TL;DR:
- Perplexity AI is an AI-powered answer engine offering direct answers, real-time updates, and source transparency compared to Google’s link-based results.
- Key features include conversational queries, advanced AI models, file uploads, and an ad-free interface for productivity and research.
- The comparison of Perplexity vs Google highlights Perplexity’s edge in in-depth research and precision, while Google remains strong in location-based searches and ecosystem integration.
- Perplexity Pro offers premium features like unlimited searches, image generation, and advanced model selection, making it ideal for professionals and researchers.
Perplexity AI vs Google Search: Why? And Why Now?
As a tech enthusiast and guest blogger at AIinAsia.com, I am constantly exploring tools that elevate productivity and enhance research capabilities. Recently, I made the bold switch from Google Search to Perplexity AI, a decision that has fundamentally changed how I search, learn, and create. This article dives into why I made this switch, compares Perplexity vs Google, and provides actionable tips to maximise your experience with Perplexity AI.
Understanding Perplexity AI: A New Way to Search
Perplexity AI is more than just a search engine; it is an AI-powered answer engine designed to provide concise, accurate, and contextual information. Unlike traditional search engines like Google, which rely on indexing and ranking pages, Perplexity leverages large language models to synthesise answers, making it ideal for deep research and quick fact-checking.
Here are the key features that set Perplexity AI apart:
- Direct Answers: Unlike Google’s search results, which often require you to sift through multiple links, Perplexity delivers the exact information you need.
- Real-Time Updates: Perplexity’s real-time web search ensures the latest information is always at your fingertips.
- Conversational Capabilities: You can ask follow-up questions naturally, building on previous queries without starting anew.
- Source Transparency: Every answer includes citations, making it easy to verify the information.
Perplexity vs Google Search: How Do They Compare?
While Google Search has been the gold standard for internet searches, Perplexity AI introduces a fresh, efficient approach to retrieving and processing information. Here’s a head-to-head comparison:
Feature Google Perplexity AI Search Results List of links and ads Direct answers with source citations Real-Time Updates Indexed and algorithm-based Real-time, web-sourced information User Interaction Static queries Conversational follow-ups Source Verification Limited transparency Transparent citations for all answers File Uploads Not supported PDF and image uploads (Pro plan) AI Model Integration Not applicable Advanced models (GPT-4, Claude 3, etc.) Ad Experience Ad-heavy Ad-free, clean interface
While Google excels in location-based searches and its suite of integrated tools (e.g., Maps, Gmail, Drive), Perplexity AI stands out for deep research, precise answers, and time efficiency.
Why I Made the Switch
After weeks of using Perplexity AI, the benefits became clear:
- Time Efficiency: Perplexity’s direct answers save me hours I would otherwise spend scrolling through irrelevant search results.
- Ad-Free Interface: The distraction-free design allows me to focus entirely on the content.
- Comprehensive Answers: Compared to Google, Perplexity often provides more detailed and accurate responses.
- Enhanced Productivity: The ability to ask follow-up questions in a conversational style streamlines my research process.
While Google’s ecosystem remains invaluable for specific use cases, Perplexity AI has become my go-to tool for in-depth research and fact-checking.
Now don’t get me wrong, Google Search still has some key uses. For example:
- Instant information that usually doesn’t change: if I’m just quickly searching for instant info (e.g., an address or a phone number), I don’t want to wait for Perplexity to run a full query – just give me the info already!
- Google ecosystem: although I’ve changed my Chrome browser to default search with Perplexity, the Google ecosystem is so well connected that sometimes I want to skim reviews, see on a map, or skim the meta description of other pages. Again, speed is the name of the game here.
Best Practices for Perplexity AI
Maximising Perplexity AI’s potential involves leveraging its features and crafting effective prompts. Here’s how you can make the most of this innovative tool:
1. Use the “Focus” Feature
Narrow your search results by selecting specific content types, such as academic papers, videos, or social media insights.
- Example: Searching for “climate change statistics” in academic mode yields peer-reviewed studies rather than general articles.
2. Ask Follow-Up Questions
Dive deeper into topics without starting a new query.
- Example: Start with “What are the latest trends in AI ethics?” and follow up with “How does this impact Southeast Asia’s tech industry?”
3. Organise Research with Collections
Save and categorise your queries into themed collections for easy reference.
- Example: Create a collection titled “AI in Education” to gather all related insights for an upcoming blog post.
4. Analyse Files
Upload PDFs (free plan) or PDFs and images (Pro plan) for instant analysis.
- Example: Upload a 50-page policy document and use the prompt, “Summarise key points related to data privacy.”
5. Experiment with Prompts
Crafting creative prompts unlocks Perplexity’s full potential. Here are some examples:
- Research: “List three successful renewable energy projects in Asia, with links to supporting articles.”
- Visuals: “Generate a useful description so that a generative AI can create an image of a futuristic underwater city with brass buildings.”
- Summaries: “Explain the economic impact of AI in 100 words.”
6. Leverage AI Model Selection
For Pro users, the ability to choose models like GPT-4 or Claude 3 adds precision to specific tasks.
- Example: Use GPT-4 for creative writing tasks, while Claude 3 is ideal for summarisation.
Free vs. Paid Plans: What’s the Difference?
Perplexity AI offers a free plan and a Pro version ($20/month or $200/year). Here’s a breakdown:
Free Plan:
- Unlimited quick searches
- 5 Pro searches per day (resets every 4 hours)
- PDF uploads for analysis
- Access to the standard Perplexity AI model
Pro Plan:
- Unlimited Pro searches
- Advanced AI models (GPT-4, Claude 3, and more)
- Unlimited file uploads (PDFs, images, etc.)
- Longer conversations and priority access to new features
- API access for developers
For casual users, the free plan suffices. For professionals or researchers, the Pro plan’s advanced features are well worth the investment.
Exploring Perplexity’s Image Generation Feature
Perplexity Pro includes an AI-driven image generation tool that adds a visual dimension to your research. Here’s how it works:
- Enter a descriptive query, such as “Generate a useful description so that a generative AI can create an image of a serene Japanese garden.”
- Choose a style: Painting, Photograph, Illustration, or Diagram.
- Select an AI model like DALLE 3 or Stable Diffusion XL for tailored results.
- Refine the prompt for even greater detail.
This feature is ideal for content creators and researchers looking to visually enhance their work. For instance, I used it to generate visuals for a blog post on AI’s role in urban development.
Conclusion: Perplexity vs Google—The Verdict
Switching from Google to Perplexity AI has been a transformative experience. While Google remains a strong player for general searches and location-based queries, Perplexity AI offers unparalleled advantages for in-depth research, precise answers, and enhanced productivity. Its conversational capabilities, real-time updates, and ad-free interface make it a compelling alternative.
Whether you’re a student, professional, or casual user, Perplexity AI’s innovative approach to search can redefine how you gather and process information. Give it a try, and you might just find yourself making the switch too.
Join the Conversation
What do you think about the Perplexity AI vs Google Search debate? Have you tried Perplexity AI, or do you think Google still reigns supreme? Or perhaps you prefer SearchGPT by Open AI? Share your experiences and thoughts below—how do you see the future of search evolving?
You may also like:
- Perplexity Introduces Pages: The Newest AI Article Generator
- Work Smarter, Not Harder: AI Hacks for Asian Professionals
- Or try the free version of Perplexity by tapping here.
Author
-
Adrian is an AI, marketing, and technology strategist based in Asia, with over 25 years of experience in the region. Originally from the UK, he has worked with some of the world’s largest tech companies and successfully built and sold several tech businesses. Currently, Adrian leads commercial strategy and negotiations at one of ASEAN’s largest AI companies. Driven by a passion to empower startups and small businesses, he dedicates his spare time to helping them boost performance and efficiency by embracing AI tools. His expertise spans growth and strategy, sales and marketing, go-to-market strategy, AI integration, startup mentoring, and investments. View all posts
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Learning
Machine Learning in Asia: How AI is Transforming Industries Across the Region
This article explores the transformative impact of machine learning across key industries in Asia, highlighting rapid market growth, regional leaders in AI adoption, and the challenges and opportunities driving innovation.
Published
2 weeks agoon
January 10, 2025By
AIinAsia
TL;DR
- Asia’s machine learning market is growing at a CAGR of 37.6%, poised to reach $225.91 billion by 2030.
- Key sectors transformed by AI include manufacturing, agriculture, healthcare, and finance.
- Countries like Singapore, China, Japan, and South Korea are leading AI adoption, while others are rapidly catching up.
- Challenges like data governance and skill gaps persist but present opportunities for growth and collaboration.
The Rise of Machine Learning in Asia
Artificial intelligence (AI) and machine learning (ML) are reshaping industries across Asia, driving innovation, enhancing efficiency, and addressing unique regional challenges. As the world’s fastest-growing AI market, Asia is poised to reap significant economic benefits from this technological revolution. Let’s explore how AI and ML are transforming key sectors across the region.
Economic Impact and Market Growth
The adoption of AI in Asia is projected to deliver substantial economic benefits. According to McKinsey, AI could contribute an additional $1 trillion to Southeast Asia’s economy by 2030. The Asia Pacific machine learning market is also expected to grow at a compound annual growth rate (CAGR) of 37.6% from 2022 to 2030, reaching $225.91 billion by the end of the forecast period (source).
Key Industries Transformed by AI
Manufacturing and Automation
AI is revolutionising the manufacturing landscape in Asia, particularly in countries like Vietnam and Thailand. Predictive maintenance systems, increased production output, and enhanced efficiency are redefining industrial processes. Estimates suggest that AI could boost Southeast Asia’s manufacturing productivity by 20% to 30% by 2030.
Agriculture and Food Security
In agriculture-dependent nations such as Indonesia and the Philippines, AI is playing a critical role in optimising crop yields, monitoring soil health, and improving logistics. Precision agriculture and automated drones are becoming essential tools, especially as the region grapples with food security concerns driven by climate change.
Healthcare
As reported by GITEX Asia, AI-powered solutions are transforming healthcare delivery across Asia, making medical services more accessible and efficient, particularly in remote areas. From diagnostics to virtual healthcare platforms, these technologies are enabling faster treatments, reducing patient wait times, and supporting personalised care.
Financial Services
The financial sector is leveraging AI for fraud detection, customer personalisation, and automated support services. AI-driven credit risk assessment models are helping financial institutions extend services to underserved populations, promoting financial inclusion for individuals without traditional credit histories (as reported by the ABD Institute).
AI Adoption Across Asian Countries
AI adoption varies significantly across Asia, with several countries taking notable strides:
- Singapore is positioning itself as the region’s AI hub, with significant investments in AI development across multiple sectors.
- China is expected to generate more data than the US by 2025, creating a strong foundation for AI development.
- Japan and South Korea are leading the way in AI research and development, particularly in robotics and autonomous vehicles.
- Indonesia, Malaysia, and Thailand are increasingly adopting AI in agriculture, healthcare, and smart city projects.
Challenges and Opportunities
Despite the rapid growth, challenges persist:
- Uneven AI Readiness: Infrastructure and adoption levels vary widely across the region.
- Data Governance: Robust frameworks are needed to ensure ethical use of AI.
- Skill Gaps: A shortage of skilled professionals is limiting progress.
- AI Anxiety: Concerns about job displacement remain prevalent.
These challenges present opportunities for collaboration and innovation. Governments are addressing these issues through national strategies, regulatory sandboxes, and increased funding for research and development (28).
The Future of AI in Asia
As AI continues to evolve, its impact on industries across Asia will deepen. Emerging trends to watch include:
- Generative AI: Transforming e-commerce, travel, and gaming sectors.
- Sustainability Efforts: AI is being used for weather prediction, biodiversity conservation, and other environmental initiatives.
- Industrial Operations: By 2026, 20% of industrial operations are expected to adopt AI/ML for vision-based systems and robotic processes.
Conclusion
The AI revolution in Asia is well underway, transforming industries and driving economic growth. With continued investments in research, development, and implementation, the region is positioned to become a global leader in AI innovation. By addressing challenges and fostering collaboration, Asia can fully harness AI’s potential to drive inclusive growth and tackle pressing regional issues.
Join the Conversation
What unique challenges or opportunities do you think Asia faces as it becomes a global leader in AI? Share your thoughts below!
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Exploring Computer Science at NUS: Opportunities, Insights, and What to Expect
The National University of Singapore (NUS) offers one of Asia’s most esteemed Computer Science programmes, blending academic excellence with industry relevance. Renowned for its rigorous curriculum and innovative research, the programme equips students with skills in areas like artificial intelligence, cybersecurity, and software development. With diverse electives, capstone projects, and global industry connections, NUS fosters a holistic learning environment. Graduates enjoy high employability, landing roles in leading tech companies and startups worldwide. Beyond academics, students thrive in vibrant campus activities, internships, and hackathons, preparing them for dynamic tech careers. This article explores what makes the NUS Computer Science programme a launchpad for success.
Published
2 weeks agoon
January 10, 2025By
AIinAsia
TL;DR:
- World-Class Programme: NUS Computer Science is globally ranked, offering cutting-edge education in AI, cybersecurity, and software development.
- Customisable Curriculum: Students explore diverse electives, hands-on projects, and specialisations tailored to their career goals.
- Vibrant Campus Life: Hackathons, internships, and industry events provide holistic learning experiences and networking opportunities.
- Bright Career Prospects: Graduates are highly sought after by top tech companies, startups, and global organisations.
The NUS Computer Science programme is a top choice for aspiring tech leaders in Asia
The National University of Singapore (NUS) stands as a beacon of excellence in education, and its Computer Science programme is among the most sought after in Asia. Whether you’re a prospective student, a parent, or an industry observer, understanding what makes the Computer Science programme at NUS exceptional can provide valuable insights. This article unpacks the key aspects of the programme, career opportunities it opens up, and what to expect if you’re considering joining this prestigious institution.
Why Choose Computer Science at NUS?
- Global Reputation:
Ranked consistently among the top universities globally, NUS is recognised for its rigorous academics and cutting-edge research. The Computer Science department, in particular, is celebrated for its contributions to artificial intelligence, cybersecurity, and data analytics. - Industry Connections:
NUS maintains close ties with leading tech companies, from global giants like Google and Meta to Singapore-based innovators like Grab and Sea Group. This connection ensures that students gain practical skills aligned with industry demands. - Diverse Curriculum:
The programme offers a balanced mix of theoretical knowledge and hands-on experience. Students can explore areas such as software engineering, machine learning, and even niche fields like quantum computing.
A Look at the Curriculum
The NUS Computer Science programme is designed to be both comprehensive and flexible, catering to a wide range of interests and career goals.
- Core Modules: These build foundational knowledge in programming, algorithms, and computer systems.
- Electives: Students can customise their learning experience, choosing from modules like Computational Biology, Artificial Intelligence, and Blockchain Technology.
- Capstone Projects: In their final year, students undertake capstone projects, collaborating with industry partners or pursuing research under faculty supervision.
For those seeking further customisation, double degrees and specialisations in fields like Business Analytics or Game Development offer additional pathways to success.
Life Beyond the Classroom
NUS offers a vibrant campus life, with student clubs, hackathons, and industry events creating a holistic learning environment. Highlights include:
- Hack&Roll: One of the largest hackathons in Singapore, giving students a platform to showcase their creativity and technical skills.
- Internship Opportunities: Embedded in the curriculum, internships allow students to gain real-world experience and apply their knowledge in dynamic settings.
Career Prospects for NUS Computer Science Graduates
Graduates from NUS Computer Science enjoy a high employability rate, with many securing roles in software development, data science, and product management. Companies actively recruiting from NUS include tech powerhouses, startups, and government agencies.
Moreover, the programme’s global outlook prepares students for roles beyond Singapore, with alumni making waves in Silicon Valley and other international tech hubs.
Tips for Aspiring Students
- Build a Strong Foundation: Brush up on programming languages like Python or Java before enrolling.
- Stay Curious: Engage in online courses or projects to showcase your passion for the field.
- Leverage Resources: NUS offers world-class libraries, labs, and mentorship opportunities—make the most of them!
Final Thoughts
Studying Computer Science at NUS isn’t just about earning a degree—it’s about being part of a transformative journey that shapes future leaders in technology. With its stellar reputation, innovative curriculum, and extensive industry ties, the programme equips students to thrive in an ever-evolving digital world.
If you’re ready to dive into one of Asia’s premier Computer Science programmes, NUS offers not just an education but an unparalleled launchpad for your tech career.
Join the Conversation:
What excites you most about Computer Science at NUS? Share your thoughts in the comments or reach out for more insights!
You may also like:
- The Future of Science: Can AI Automate Research?
- AI and Asian Gen Z is A Slang-Filled Digital Dialogue
- Unravelling the Mystery of AI Consciousness
- Tap here to learn more at the NUS website.
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