We are thrilled to welcome back Prudence Foundation as the Disaster Tech Partner for Echelon X 2024!

Over the past three years, our collaboration with Prudence Foundation has centred around the SAFE STEPS D-Tech Awards, a platform dedicated to recognising and supporting startups with innovative technologies capable of mitigating the impact of natural disasters, preventing them, or expediting recovery efforts.

This year, Prudence Foundation takes centre stage at Echelon X 2024 with a dedicated pavilion that will showcase the groundbreaking work of 10 disaster tech startups. These startups, carefully curated for their exceptional contributions to disaster resilience, will not only be exhibiting their cutting-edge solutions but will also have the opportunity to present their innovations onstage.

Get Echelon X  tickets: Check today’s discounted rates

The partnership between Echelon and Prudence Foundation has always been rooted in a shared commitment to fostering technological advancements that make a positive impact on communities facing natural disasters. The SAFE STEPS D-Tech Awards have been instrumental in unearthing and promoting transformative solutions that have the potential to save lives, protect communities, and accelerate recovery in the aftermath of calamities.

At Echelon X 2024, attendees will have the unique opportunity to engage with these disaster tech startups, gaining firsthand insights into the technologies that could shape the future of disaster preparedness and response. The pavilion will serve as a hub of innovation, providing a platform for networking, collaboration, and a deeper understanding of the groundbreaking work being done in the disaster tech space.

In addition to the pavilion, the 10 selected startups will take the stage to share their stories, challenges, and triumphs. The presentations promise to be enlightening and inspiring, offering a glimpse into the transformative potential of technology in addressing the challenges posed by natural disasters.

Also read: The opportunities and future of disaster tech (D-Tech) in Southeast Asia

Come and be a part of this extraordinary opportunity to connect with the disaster tech pioneers, witness live demonstrations of their solutions, and contribute to the collective effort of building resilient communities.

Echelon X 2024 is not just a conference; it’s a convergence of minds dedicated to driving positive change through technology. As we embark on this journey with Prudence Foundation, we invite you to explore, learn, and be inspired by the incredible strides being made in the field of disaster tech. Together, let’s build a future where innovation becomes a powerful force for safeguarding our communities in times of need.

Join us at Echelon X 2024, where innovation meets impact, and together, we shape a more resilient and secure world. Get your tickets here.

The post Prudence Foundation returns as Echelon X 2024 Disaster Tech Partner appeared first on e27.

Singapore-based global invoice financing marketplace Incomlend has acquired LC Lite, a specialised Web3-powered trade finance marketplace, for an undisclosed amount.

The merger will empower Incomlend to operate through a new fintech platform, reaching crypto and fiat investors through trade finance as it looks to accelerate its expansion in the Middle East. The deal will also enable the fintech firm to bring a fresh offering of Web3 technology to its platform, creating a new asset class.

Also Read: Incomlend raises US$20M Series A for Asia, Europe expansion

Investors will have access to both platforms, which will coexist and continue to offer their own standalone fintech solutions. The firm plans to expand the fintech platform to support stablecoins transactions in the future.

Founded in 2016, Incomlend is an alternative cross-border trade finance platform. It claims to have processed over 6,000 transactions in over 50 countries worldwide.

Commenting about the deal, Incomlend Co-Founder and CEO Morgan Terigi said: “It empowers us to link the crypto and fiat spaces which is going to be crucial as both markets continue to expand and new technologies become available. The merger will also increase the liquidity of the marketplace, which will help to boost the UAE economy.”

Also Read: Why blockchain is instrumental for the future of trade finance

According to the ASEAN Briefing, the value of Singapore’s net inflow of Foreign Direct Investments (FDI) is projected to trend around SGD27.7 billion (US$21 billion) in 2024. A Statista report predicts crypto revenue in the country will show an annual growth rate (CAGR 2024-2028) of 8.8 per cent, resulting in a total amount of SGD642.7 by 2028.

—

X marks Echelon. Join us at Singapore EXPO on May 15-16 for the 10th edition of Asia’s leading tech and startup conference. Enjoy 2 days of building connections with potential investors, partners, and customers, exploring innovation, and sharing insights with 8,000+ key decision-makers of Asia’s tech ecosystem. Get your tickets here.

Want more from your Echelon experience? Be an Echelon X sponsor or exhibitor. Send enquiry here.

The post Invoice financing marketplace Incomlend acquires LC Lite to reach crypto, fiat investors appeared first on e27.

In the quest for impactful LinkedIn content, we’ve embraced a cutting-edge approach: creating our customised Generative Pre-trained Transformer (GPT), built upon the foundations of ChatGPT. This initiative addresses the challenge of producing authentic, engaging content that resonates with our LinkedIn audience.

Implementation and impact

Our journey with ChatGPT began not just as users but as innovators. By leveraging ChatGPT’s capabilities, we developed our unique version of a GPT tailored explicitly to our content needs. Our process involves:

• Initial drafting: We write a raw, unfiltered draft, embedding our insights and experiences.
• Consultation with our custom GPT: This draft is then reviewed by our GPT, which we’ve trained to ask critical questions like, “What works? What doesn’t? How can this be improved?”
• Analytical enhancement: Our GPT, equipped with ChatGPT’s analytical strengths, evaluates the draft, aligning it with our specific content pillars.
• Refinement: Suggestions from our GPT guide us in streamlining and enhancing the content.
• Finalisation: We apply the final touches, refining vital elements like the opening line and call to action based on our GPT’s feedback.

Also Read: Are large Vietnamese tech enterprises ‘indifferent’ when competing with ChatGPT?

This approach has led to a noticeable improvement in our content’s impact and engagement, significantly enhancing our branding on LinkedIn.

Challenges and solutions

A primary challenge was ensuring that the AI-assisted content retained our authentic voice. To address this, our initial drafts are always self-written, preserving the essence of our narrative. Our custom GPT then steps in as a collaborative partner, not a content creator, providing insights and suggestions while maintaining the authenticity of our voice.

Future outlook

Our future with AI in content creation is promising. We plan to refine our custom GPT further, exploring broader applications in storytelling and thematic content. This integration of AI offers an exciting glimpse into a future where human creativity synergises with technological efficiency.

Integrating a custom GPT, developed from ChatGPT, into our LinkedIn content strategy has been transformative. It illustrates the powerful role AI can play in augmenting human creativity, ensuring content is engaging and deeply resonant with our audience. As we continue to explore this synergy of AI and human insight, the potential for innovation in content creation seems boundless.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva

The post AI transforming LinkedIn content: Our custom GPT journey appeared first on e27.

Singapore-based digital M&A platform match.asia aims to address the traditional challenges of the mergers & acquisitions (M&As) process, such as inefficiency, limited outreach, low success rates and high costs — through a marketplace model. The free-to-list platform leverages its 1,000-plus global buyer network and expertise to improve the traditional approach.

In this interview, its founders Marcus Yeung (MY) and Patrick Linden (PL) discuss the inefficiencies, costs, and manual processes plaguing traditional M&A, sharing insights into the creation of match.asia.

Edited excerpts:

Can you elaborate on the specific challenges in Southeast Asia’s M&A landscape that led to the creation of match.asia and how your platform addresses them?

PL: Traditional M&A is complicated, inefficient, expensive, and only available to larger companies. From a founder’s perspective, it is a hit-and-miss process on an ad-hoc basis.

Having been through several M&A processes as a tech founder, I find it rather painful. You tend to spend US$10,000-20,000 on fixed retainers each month and spend probably 25 per cent of your time as a founder preparing and accompanying that process. After months of preparation, the advisor starts reaching out to potential buyers, which is very manual and slow. Things often only work out after spending over US$100,000 and a lot of time and effort.

Also Read: M&As: Key to building an embedded finance ecosystem

MY: We solve this through our unique marketplace, which has thousands of sellers and buyers and our data-based matching system, enabling sellers and buyers to match quickly. We do not charge sellers or buyers to list; all listings are done on a no-names basis, making it easy for sellers to list without risk.

What inspired the marketplace model for match.asia, and how does the data-based matching system contribute to ensuring high-quality matches in M&A transactions?

PL: The typical M&A process in Southeast Asia is basically stuck in the dark ages. With match.asia, we aim to revolutionise that. We use a curated marketplace model with thousands of sellers and buyers, utilising technology that underpins our data-based matching system. This will lead to a much higher number of successful transactions, ultimately benefiting the whole ecosystem significantly.

MY: Buying and selling property, cars, household goods, services — these have all moved to marketplace models. Even dating. M&A is one of the last markets, which is still largely manual and hit-and-miss.

As founders and M&A experts, we know the pain points of M&A and can see that M&A is ripe for disruption. We work closely with sellers to present their data to buyers so they can be easily found through data-based matching. Sellers like us as we are a no-risk way for them to explore opportunities with 1000s of buyers. Buyers like us because we make it easy for them to find serious sellers.

Could you share examples of how match.asia’s innovative approach has already increased the success rates of M&A transactions, particularly for Asian SMEs? How many deals have you facilitated so far?

PL: Since we went live two weeks ago, we have been inundated with requests to list on our platform. We have onboarded over 100 sellers and offer access to over 1,000 global buyers. Several matches have already been made between buyers and sellers.

Given your extensive combined experience in M&A and entrepreneurship, how do you see match.asia impacting the accessibility of M&A as a strategic option for SMEs in the region?

PL: Our vision for match.asia is to significantly enhance the accessibility of M&A activities for SMEs in SE Asia. Leveraging our deep experience in M&A and entrepreneurship, we aim to democratise the process, making it more transparent, efficient, and cost-effective. Our platform serves as a bridge, connecting sellers with a global pool of buyers and providing tools to streamline the process, thereby enlarging the ecosystem for everyone involved.

MY: Most SMEs cannot access M&A as a strategic option. In their eyes, it is too expensive, risky, and often unsuccessful. We aim to change this. Through our M&A marketplace, data-based matching and free confidential listings, all good SMEs of any size will be able to get on the radar screen of 1000s of potential buyers.

Can you walk us through the decision-making process behind the platform’s pricing model, where it is free to list for sellers and buyers, with a success fee payable only upon transaction closure?

PL: Our decision to make match.asia free for listing both sellers and buyers, with a success fee only upon closing a transaction, stems from our commitment to promoting accessibility and trust. We understand SMEs’ hesitancy regarding upfront costs and fixed retainers in traditional M&A processes. By eliminating these costs, we open doors for more businesses to explore strategic growth opportunities without financial risk. Our success fee model aligns our interests with those of our clients, ensuring we are successful only if our clients are successful. This will encourage more SMEs to list on our platform, attracting more buyers.

In what ways does match.asia maintain confidentiality for sellers, considering that listings are on a no-name basis? How has this feature been received in the market?

MY: M&A is a very sensitive topic, and many sellers do not want to be openly seen to be interested in M&A. That is why we list all sellers and buyers on a no-name basis, to allow them to exchange information without reservation. We also list key data in ranges and aim to strike the right balance between giving enough information for buyers to be able to decide whether the opportunity is attractive to them and not being too detailed to be a concern to the seller. If a buyer is interested in a seller, they can ask to contact the seller and request detailed information once an NDA has been signed. This way, the seller maintains complete control over its confidential information.

How does match.asia leverage the global buyer network and expertise of its sister company, Seabridge Partners? In what specific ways does this collaboration enhance the capabilities of match.asia?

MY: match.asia collaborates closely with its sister company, Seabridge Partners, leveraging its 12-plus years of experience and extensive global buyer network to enhance the platform’s capabilities.

Also Read: In good times and bad: An outstanding investor will stand by you

This partnership enriches match.asia with a vast pool of potential buyers, elevating the platform’s ability to facilitate successful M&A transactions quickly. SEAbridge is a leading IB boutique in SE Asia with deep expertise in running M&A processes and an extensive global buyer network.

Can you share insights into the role technology plays in disrupting the traditional M&A processes and how match.asia maximises efficiency and successful outcomes through its platform?

PL: At match.Asia, technology disrupts traditional M&A by automating key phases like preparation, marketing, and matching, streamlining the process and enhancing efficiency. Our online marketplace of sellers and buyers and data-based matching system makes it easy for buyers and sellers to find their ideal partners. We have plans to leverage key technologies such as generative AI for broader automation across the M&A workflow, increasingly optimising outcomes over time.

As co-founders, how do you envision match.asia evolving in the future, and what impact do you hope it will have on the broader M&A ecosystem in Southeast Asia? How does match.asia align with the broader mission to make M&A more 
successful, accessible, and cost-effective for all parties involved, including 
sellers, buyers, and intermediaries in the M&A ecosystem?

PL: As co-founders, we envision match.asia not just establishing itself as the premier M&A platform in Southeast Asia but also as a catalyst for systemic change within the M&A ecosystem. Our ambition is to harness cutting-edge technology to redefine how M&A transactions are prepared, marketed and executed, making the process as seamless and efficient as possible. By doing so, we aim to significantly increase the volume of successful deals, bringing measurable benefits to sellers, buyers, and intermediaries alike. This vision extends beyond simplifying transactions — it’s about fostering a more vibrant, accessible, and dynamic M&A environment that propels economic growth and innovation across the region.

MY: Take the evolution of the real estate industry, for example. Just as property platforms like PropertyGuru revolutionised property transactions by increasing the numbers massively of sellers and buyers, making them more transparent and efficient, match.asia aims to transform the M&A landscape. Previously, property sales were cumbersome and limited in reach, just like the traditional M&A process today. Now, platforms enable broader access and smoother transactions, a model match.asia seeks to emulate M&A, thereby enlarging the ecosystem for all participants.

—

The post ‘M&A process in SEA is stuck in the dark age’: say match.asia co-founders appeared first on e27.

AI is like a game-changer, bringing new levels of creativity and efficiency to the table. At our agency, we’ve embraced AI, using it to transform everything from how we understand data to the way we connect with customers. The implementation of AI in marketing isn’t just a technological upgrade; it’s a venture steeped in ethical considerations, particularly concerning customer privacy and trust.

Implementation and impact

Our journey into AI-enabled marketing began with a clear goal: to deliver personalised, efficient, and impactful marketing solutions without compromising our clients’ trust. We introduced AI tools for data analysis, customer segmentation, and predictive modelling. These technologies allowed us to gain deeper insights into consumer behaviour and tailor our marketing efforts accordingly.

The impact was profound. Campaigns became more targeted, results more measurable, and strategies more adaptable. However, our success wasn’t just in the numbers; it was in the trust we maintained with our clients and their customers. By prioritising data security and ethical AI usage, we turned potential privacy concerns into a foundation of trust.

Challenges and solutions

Adopting AI wasn’t without its challenges. We were always mindful of safeguarding consumer data’s privacy and security for our clients. There was a lot of chatter and curiosity around topics we were grappling with internally.

Also Read: Leveraging AI and ML in supply chain management for smarter decision making

People were asking things like, “What’s the right way to handle consumer data using AI?” and “How can businesses keep this data safe?” These online discussions really got us thinking and pushed us to find effective solutions for these valid concerns.

Baseline standard of protection

To address these concerns, we established a baseline standard of protection for personal data in Singapore. We ensured compliance with privacy laws like PDPA for Singapore (GDPR in the EU and CCPA for the United States), optimised data encryption, and maintained transparency with our clients about data usage. Educating our team and clients about ethical AI practices was key. It was about constantly realigning them on the importance of ethical decision-making when using AI tools.

Minimise data collection

In the digital world we live in now, data is often viewed as an incredibly valuable asset. Therefore, it is tempting to collect as much as possible. However, this approach can lead to significant risks and ethical concerns.

The principle of data minimisation is about changing this mindset. It means actively choosing to only gather the data that is essential for the specific purpose you need it for. This practice is not just a good ethical stance; it’s a practical one.

By collecting only what is necessary, you reduce the volume of data that needs protection. This, in turn, lowers the risk and potential impact of data breaches. Fewer data points mean fewer opportunities for sensitive information to be exposed or misused.

On top of that, this approach aligns with the growing consumer demand for privacy and their right to control their personal information. In essence, data minimisation is about respecting the trust that consumers place in your organisation and being a responsible steward of their information.

AI transparency

Transparency in the use of AI is crucial in building and maintaining trust, not just with our clients but also with their end customers. When my team and I use AI, especially in areas that involve data processing or decision-making that could significantly impact individuals, we make it a point to be clear and upfront about it.

This transparency involves explaining what AI is being used for, how it works in simple terms, and what implications it might have for the individuals whose data is being processed. For instance, if we’re using AI for personalised marketing, we ensure our clients understand how the AI is creating these personalised experiences and what data it’s using.

Being transparent about AI also means being open about its limitations and the measures taken to address issues like potential biases. This level of openness helps demystify AI and reduces fears of an opaque, uncontrolled technology. Ultimately, AI transparency is not just about fulfilling a legal obligation; it’s about fostering a relationship of trust and ethical responsibility with clients and the wider public.

Also Read: How to unlock new horizons with generative AI

By addressing these aspects, we are better equipped to handle consumer data responsibly and ensure its safety in an AI-driven environment.

Future outlook

Looking forward, we are committed to exploring the potential of AI while upholding our ethical standards. Our future endeavours include enhancing AI transparency, improving customer data protection, and exploring AI’s role in creating more inclusive marketing strategies.

We believe that the future of AI in marketing is not just about leveraging technology for business growth; it’s about doing so responsibly, ethically, and with respect for consumer privacy and trust.

In conclusion

AI presents a world of opportunities in digital marketing, but it also demands a new level of ethical responsibility. At our agency, we are progressively working towards optimising these changes. It’s a gradual process of embracing this new paradigm, one where we see a chance to forge stronger, more trusting relationships with our clients and their customers.

As we move forward, we remain committed to balancing innovation with ethical practices, ensuring that our journey into AI-driven marketing is as responsible as it is revolutionary.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva

The post AI and ethics in digital marketing: Building trust in the tech era appeared first on e27.

Japan is ranked 7th globally among the best countries for education according to US News Ranking. Its educational system is widely recognised for its strengths in several key areas, contributing to its reputation for high-quality education. Specifically, Japan consistently performs well in international assessments like the Programme for International Student Assessment (PISA), showcasing strong proficiency in subjects like mathematics, science, and reading, reinforcing the country’s academic excellence. Additionally, Japan employs innovative teaching and learning methodologies such as group-oriented learning, hands-on activities, and problem-solving approaches.

Among the top five best universities in Japan, Nagoya University is known for its notable educational and research system, accomplishing high research quality of international standards that have yielded six Nobel laureates and nurturing some of Japan’s foremost leaders since its establishment in 1871.

In recent years, the university has taken a more significant leap towards fortifying its presence in Singapore and across Asia. After setting up the preparation office in BLOCK71 Singapore, the National University of Singapore’s (NUS) incubation hub in July 2023, the institution marked a significant milestone with the establishment of Nagoya University Global Campus Ltd. last November 2023 in Singapore.

Nagoya University is the first and only National University in Japan which established a legal entity and has placed a full-time faculty in Singapore. This strategic initiative serves as the cornerstone for augmenting education, research, industry-academia collaborations, and startup support activities within the region. As a testament to its commitment, Nagoya University has formed partnerships with various educational and research institutions, public agencies, and private companies, including NUS.

Nagoya University’s foundation of excellence

Situated in Japan’s fourth-largest city which is home to the biggest port in Japan, Nagoya University’s pivotal role in supporting industries such as automobile, aerospace, ceramics, and robotics underscores its symbiotic relationship with the manufacturing and industry hub of Asia. The largest automobile manufacturer in the world, Toyota Motor Corporation is also headquartered in Aichi, Japan where Nagoya is the capital city.

Nagoya University’s eminence in the realms of research and deep tech innovation is undeniable. With six Nobel Laureates accounting for 20% of awardees from Japan, it stands among the country’s leading institutions, contributing significantly to the country’s academic and research landscape. 

Also read: Strengthening mental healthcare in Asia through local data that enhances efficacy

Many world-class scientific research discoveries including the PMNS matrix, Okazaki fragment, Noyori asymmetric hydrogenation, Sakata model, and Blue LED were born at Nagoya University. Notably, the Nagoya University Hospital’s recognition as the “Newsweek” World’s Best Specialised Hospital in 2023 further underscores its multidisciplinary expertise and commitment to healthcare innovation.

The university’s sprawling network across Asia spans multiple countries including Cambodia, China, Indonesia, Laos, Philippines, Thailand, and Vietnam, among others, exemplified by its establishment of various educational and research centres and offices. These centres and offices signify Nagoya University’s dedication to fostering educational exchanges and collaborative research endeavours across diverse cultural landscapes in Asia.

Nagoya University’s strategic partnership with NUS

Nagoya University embodies a commitment to excellence and innovation. Its mission centres on nurturing an ecosystem conducive to groundbreaking research, educational advancement, and the cultivation of entrepreneurial spirit. Nagoya University’s emphasis on education and unwavering support from prestigious academic institutions are central to its reputation in Asia. This dedication has cultivated an environment that nurtures collaboration among Asian stakeholders, aiming not only to fortify Japan’s innovation landscape but also to drive advancements in the region’s educational domain. Being the first and only national university in Japan to set up a legal entity and place a full-time faculty in Singapore stands as a testament to Nagoya University’s dedication to building collaborations across Asia.

Moreover, the influx of its faculty members into Singapore and the establishment of NUS’ BLOCK71 office in Nagoya has spurred discussions about establishing new research bases in both Nagoya and Singapore. BLOCK71 is an initiative by NUS Enterprise in collaborative and strategic partnerships with established corporates and government agencies. It is a technology-focused ecosystem builder and global connector which catalyses and aggregates the startup community.

Growing beyond borders

As Japan seeks to be a part of an Asia innovation circle, collaboration with Asia regions, especially Southeast Asian countries, offers a wealth of opportunities. The diverse and glowing economies, populations, cultures, and technological landscapes within Southeast Asia present a fertile ground for cross-pollination of ideas and expertise.

By expanding its presence in the region, Japan can tap the unique strengths of Southeast Asian nations, leveraging their emerging tech ecosystems and young, dynamic, and glowing talent pool. This collaborative approach enhances Japan’s ability to access new markets and facilitates the exchange of knowledge, ultimately driving innovation through the synthesis of diverse perspectives and skills.

Also read: Empowering businesses: Lalamove’s impact on local enterprises

Nagoya University’s programmes and support mechanisms acknowledge the value of growing beyond borders, offering startups the avenues to tap diverse markets and opportunities across Asia and highlighting the importance of regional expansion for startups in today’s globalised world. For example, Nagoya University’s active involvement in exhibitions in Singapore such as InnovFest x Elevating Founders 2023, which was part of Asia Technology x Singapore 2023 and SWITCH 2023 (Singapore Week of Innovation & Technology) illustrates its dedication to supporting startups.

By setting up display booths with support from NUS Enterprise, the University provides a platform for startups to showcase their innovations and gain exposure to potential investors and collaborators. Through the joint efforts between NUS Enterprise and Nagoya University in the InnovFest 2023 and SWITCH 2023 exhibitions, they have provided a platform for 18 startups, amplifying their visibility and access to Asian markets and beyond.

The partnership between Nagoya University and NUS marks a major milestone with the launch of its first NUS Overseas Colleges (NOC) Japan entrepreneurial hub in Nagoya.

As part of this collaboration, two NUS PhD students will embark on their internship with the startups, MAP IV and AquaAge, incubating at Nagoya University laboratory. This initiative embodies the collaborative ethos driving both institutions in the fields of advanced technologies including 3D Mapping, artificial intelligence, deep learning, machine learning, and natural language processing.

On 12th January 2024, the NOC Nagoya August 2024 intake session was held in NUS, commencing the application process for the second batch of NUS PhD students.

Nagoya University’s unwavering commitment to Singapore and Asia, in partnership with NUS, demonstrates a proactive approach towards fostering educational, research, and entrepreneurial initiatives. Through these collaborative efforts, the university paves the way for innovative breakthroughs and sustained growth in the dynamic landscape of Asia’s academia and industry.

Also read: Omnichat hit a record-high of 10x revenue growth in the SEA market

By deepening ties with Southeast Asia through Nagoya University’s initiatives, Japan can take part in addressing shared concerns and help pool ideas and expertise for more effective solutions. This interconnectedness not only promotes technological innovation but also cultivates a broader understanding of the regional challenges at hand.

Ultimately, Nagoya University’s regional initiatives act as catalysts for a holistic approach to innovation, creating a collaborative ecosystem that benefits both Japan and Asia, especially the Southeast Asian region, in navigating the complexities of the changing world.

– –

This article is produced by the e27 team, sponsored by Nagoya University

We can share your story at e27, too. Engage the Southeast Asian tech ecosystem by bringing your story to the world. Visit us at e27.co/advertise to get started.

The post Nagoya University transforming from Singapore beyond Six Nobel Laureates appeared first on e27.

Generative AI, or artificial intelligence, has the power to change how we live and work in so many ways; our creativity is the only limit.

At a recent roundtable discussion with Qlik entitled The Future of Data Analytics in the Age of Generative AI, I shared my thoughts about how the newly released foundation models in language or Large language models (LLMs) as we call them today are reshaping the work landscape. LLMs like GPT4, Claude etc., have been fine-tuned using reinforcement learning with human feedback to enable different categories of uses case, as listed below:

LLM as a language facade

Using LLMs as a layer of communication between humans and machines will make talking to software as easy as talking to another person. Instead of clicking through menus, you would just tell the software what you want and facilitate a seamless flow of information, transforming the way we interact with technology.

LLM as a co-pilot

Envision your digital sidekick enhancing your productivity exponentially, a testament to the possibilities of generative AI. LLMs could aid software programmers, supercharging their efficiency. Similarly, artists could use these models for inspiration, discovering new and creative ideas they haven’t thought of before.

LLM as a role-player

The intricate world model these LLMs acquire through training with trillions of words enables them to don any role and act in character. The power of role-play is limited only by our imagination — they could be coaches, companions, or even therapists.

LLM as an orchestrator

Moving beyond single-step interaction, LLMs could handle a series of tasks, making abstract interactions more concrete. Imagine your digital personal assistant breaking down complex processes into sub-tasks and diligently completing them step by step.

Also Read: How to stay creative in the age of Generative AI and Web3

While we are only at the inception of this transformation, several early use cases have already started to gain traction:

Q&A bot based on a data corpus

In the current search engine paradigm, information synthesis is a manual process. Generative AI models like ChatGPT bridges this gap, internalizing and summarising vast amounts of data, offering succinct and accurate responses. The technology eliminates redundant research, enabling users to devote their time to higher-value tasks. We can also engineer them to cite the sources of information they present to ground them.

Customer service bot

AI models can now imitate a range of communication styles and interact with customers in unique ways, allowing for the customisation of content and its delivery. They can change how they talk, their empathy, and their style based on how they want to talk to the customer.

This allows us to not only personalise what we tell the customer but also how we say it. The depth and reasoning behind every response can be engineered, taking customer service to an unprecedented level.

Coaching

AI coaching assistants can now provide an intelligent, interactive training experience. Be it for sales forces or for children learning new concepts, the models can role-play, ask follow-up questions, and provide feedback, offering a personalised learning experience.

In sales training, the AI bot can pretend to be a customer and ask good follow-up questions, pushing trainees to think about what the customer needs and how to sell to them. In education, these bots can act as personal tutors for kids, helping them understand what they’re learning.

Only the beginning

The power of generative AI lies in its ability to democratise data, bringing unstructured and structured data together to unlock business value in enterprises.

We are actively collaborating with companies like Qlik, for example, to see how we might augment and automate manual tasks involved with data management in order to help companies boost their productivity with quality and governance in mind.

Imagination and innovation would carry us to a future of work that we envisage. The key value of AI is in human augmentation – shifting employees and human labour to higher-value work.

However, a lot of engineering still needs to be done to put safeguards in place to make this technology more robust, safe, and fit for customer interaction.

You can watch my full presentation here.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva Pro

This article was first published on June 7, 2023

The post How to unlock new horizons with generative AI appeared first on e27.

Supply chain management software has evolved tremendously over the last decade. With cutting-edge technologies like artificial intelligence (AI) and machine learning being incorporated, these solutions are getting smarter and more intuitive every day.

In this article, we’ll look at how AI and ML are changing the game for supply chain management software and enabling organizations to make better and faster data-driven decisions.

Smooth supply chain management software is key for business success in today’s complex and constantly shifting markets. Companies need to manage their supply chain well to deliver products and services while keeping optimal inventory levels.

This means collecting and analysing tons of data on suppliers, production, inventory, transportation, sales, and more. Trying to make sense of all that information manually is challenging and time-consuming.

This is where AI and ML come in super handy. They give companies advanced tools like demand forecasting, inventory optimisation, supplier relationship management, and logistics routing to uncover patterns and insights from complex data to optimise planning and operations in the supply chain. With supply chain management support from AI and ML, businesses can streamline operations, reduce costs, and better serve customers.

AI and ML for more accurate demand forecasting

Accurate demand forecasting is crucial for efficient inventory and production planning. Old-school forecasting relied on statistical methods like moving averages. However, these have limitations in identifying complex nonlinear patterns. AI and ML models can detect intricate relationships and patterns in historical sales data much better. By analysing bigger datasets with more parameters like promotions, pricing, seasons, events, etc., they provide super accurate demand predictions.

ML techniques like neural networks can continuously learn from new data. This allows real-time refinement of forecasts in response to emerging trends. Companies can react faster to changes in customer preferences. AI also enables automated monitoring of forecast accuracy and exception handling for products with unusual trends. Instead of relying on fixed formulas, AI-enabled systems continuously optimise algorithms and models based on results.

Also Read: Hacking customer engagement in Indonesia’s agri supply chain

For example, if demand rises during holiday seasons, ML models can factor this in automatically. As new products are launched or old ones are discontinued, the system adjusts estimations seamlessly. This level of automation and flexibility is impossible to achieve manually.

Smarter inventory optimisation

Keeping optimal inventory is crucial for customer service and working capital management. Too much stock leads to higher carrying costs and obsolescence risks. Too little causes lost sales and backorders. ML algorithms can consider fluctuating demand, supply uncertainties, logistics delays and other constraints to determine ideal stock levels across the network.

AI can also improve inventory productivity by automating warehouses. Computer vision guides autonomous robots to locate and move inventory efficiently. This accelerates order processing, improves accuracy and allows 24/7 operation.

For example, smart inventory optimisation systems can monitor shelf life, seasonal demand shifts, waste reduction goals and other factors to align stock with business objectives beyond just costs. AI enables leaner, flexible and eco-friendly inventory management.

Dynamic supply chain network optimisation

SCM software with AI capabilities can dynamically optimise supply chain networks in response to changing conditions. The AI engine processes massive data on costs, lead times, risks, transportation lanes, sourcing options, duties, exchange rates, etc. It then uses advanced algorithms to determine the optimal locations and capacity of suppliers, factories, warehouses, cross-docks and outlets to minimise costs and maximise service levels.

As conditions change, the system reruns simulations and adapts the supply chain network for optimal performance. Manual design of such complex global networks can take months. But AI-powered software can crunch through numerous scenarios in minutes to optimise the supply chain in real-time.

For instance, weather delays, port congestions or other disruptions can frequently alter transportation costs and lead times. AI enables shifting supply paths dynamically to maintain continuity at the lowest cost. Sudden demand surges can be met efficiently by recalibrating inventory deployment and capacities with AI’s help.

Smarter sourcing and procurement

AI is transforming sourcing and procurement through automation and data insights. For example, routine tasks like issuing RFQs, analysing bid responses and preparing contracts can be automated using AI. Chatbots allow natural language interactions to quickly address supplier queries.

Big data analytics uncovers trends like price changes, supply risks, quality issues, etc., to support strategic sourcing decisions. AI determines the right procurement strategies for different spending categories based on value drivers instead of reactive buying. This brings major savings with better supplier terms and reduced maverick spend.

Also Read: Enhancing cyber supply chain resilience: A vision for Singapore

AI can also analyse negotiations with suppliers to continuously improve negotiation strategies and outcomes. It provides insights into which suppliers have higher negotiation room or where bundling spending could get better terms. This allows systematic optimisation of value.

Proactive supply risk management

Supply disruptions can wreak havoc on businesses. ML applies sophisticated pattern recognition and probabilistic modelling on news feeds, financial reports, weather data, transport records, etc., to identify likely disruption causes like natural disasters, trade wars, production issues, strikes, etc.

It analyses the potential impact on capacities, lead times and costs across the network. AI simulation helps mitigate risks proactively through safety stock optimisation, alternate suppliers, route changes, etc. Instead of reacting to disruptions, organisations can get ahead of problems.

AI-driven supply risk management also enhances transparency across tier-two, three and lower-tier suppliers to uncover hidden risks. It enables building contingency plans and scenarios to handle disruptions smoothly. This minimises downtime and customer impact.

Continuous process improvements

AI tracks all supply chain processes and exceptions. It analyses the root causes of inefficiencies like long lead times, quality problems, inaccurate planning, stockouts, etc. AI also estimates the cost impact of process bottlenecks. It uses computer vision to monitor process adherence on factory floors.

The insights allow focused process improvements to enhance productivity. AI also alerts when critical process parameters exceed limits. This enables proactive troubleshooting before issues arise. The continuous feedback cycle sustains gains over the long run.

Also Read: #dltledgers unveils 2023 trends in supply chain digitisation

For instance, AI can track invoice processing times, identify delays from missing information or workload spikes and reroute tasks automatically to improve turnaround. It can adjust warehouse staffing based on order volumes to maintain speed. AI enables self-optimising supply chain processes.

The future with AI and blockchain

Blockchain provides secure, transparent distributed ledger technology to improve end-to-end supply chain traceability. Combining it with AI and ML unlocks more value. AI can analyse blockchain transactions to uncover patterns, risks and insights. Smart contracts enabled by blockchain allow automated workflow execution.

Blockchain establishes a unified data source across networks. AI analyses this data for continuous optimisation. Smart contracts automate execution without conflicts. Together, they enable seamless cross-organisation integration while ensuring trust, security and compliance. This next-gen supply chain architecture minimises inefficiencies, disputes and disruptions.

Final thoughts

With capabilities like machine learning, computer vision and natural language processing, AI-powered SCM solutions help companies achieve new benchmarks in speed, accuracy and efficiency. By leveraging the convergence of AI and blockchain, future supply chains will become intelligent, self-learning networks that maximise value. The possibilities are exciting as AI and ML progress rapidly. Companies that embrace these technologies today will gain a real competitive edge.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva

The post Leveraging AI and ML in supply chain management for smarter decision making appeared first on e27.

In today’s ever-evolving entrepreneurial landscape, the notion of startup success has transcended the boundaries of Silicon Valley. Aspiring entrepreneurs are no longer limited by geography, and their dreams of building globally successful ventures are now challenging Silicon Valley’s historical dominance as the go-to destination for startups.

Techstars itself began with three simple ideas: entrepreneurs create a better future for everyone, collaboration drives innovation, and great ideas can come from anywhere. So supporting founders looking to create successful startups globally is a mission we have long been engaged in.

Embracing new horizons: The potential of anywhere startups

It has never been easier to launch a startup. Advancements in artificial intelligence and technological tools have significantly simplified the process of starting a business, making it more accessible for entrepreneurs. For instance, the rise of e-commerce platforms has minimised the need for physical stores, enabling businesses to operate online and reach a global customer base.

Digital marketing tools have made it easier to promote products and services, targeting specific audiences with precision. Cloud computing has revolutionised data storage and collaboration, reducing infrastructure costs and facilitating remote work.

Even the entrepreneur’s ability to raise business capital has been somewhat democratised by crowdfunding platforms that give them access to a range of sponsors and investors. These technological advancements have significantly reduced barriers and empowered entrepreneurs to pursue their business ideas with greater ease and efficiency from anywhere in the world.

The untapped potential of ‘anywhere Startups’ has been further reinforced by the COVID-19 pandemic. The advent of remote work and enhanced access to resources have given rise to vibrant startup ecosystems in unexpected corners of the world, making entrepreneurship a global phenomenon.

According to a survey report by McKinsey & Company, the global pandemic accelerated the digitisation of customer interactions with companies by several years.  At the height of the pandemic, several startups were still successfully launched and operated outside of Silicon Valley, showing entrepreneurs that success knows no geographic limits.

With the internet as their powerful ally, entrepreneurs now have the ability to connect with customers, investors, talents, and mentors on a global scale. This newfound freedom empowers them to pursue their dreams and build successful ventures beyond the traditional confines of Silicon Valley.

The role of geography and community

Geography still plays a pivotal role in shaping startup success. Each region possesses unique strengths, resources, regulatory climates, challenges, and market demands that must be navigated by entrepreneurs.

Also Read: Echelon: How increased emphasis on ESG elements in fund management will affect early stage startups

To maximise these strengths and navigate the challenges effectively,  it is necessary to fan the flames of entrepreneurial collaboration and startup community engagement within the region. This is the very reason several governments across the globe are now paying attention to promoting initiatives that bring entrepreneurs together and grow their local ecosystems.

A good example of such initiatives is the Anjal Z Techstars founder catalyst program which is a partnership between the Abu Dhabi Early Childhood Authority and Techstars to help edutech startups from across the globe get localised to Abu Dhabi.

To further support the regional development of startup communities globally, Techstars also offers a startup community catalyst that is a combination of multiple programs aimed at igniting and scaling startup communities from the ground up in partner regions. The fostering of local entrepreneurial communities sparks innovation and collaboration.

It can also create a nurturing environment that provides easier access to talent, support, and industry-specific knowledge relative to the region.  By understanding the local landscape and building collaborative communities, entrepreneurs in these regions can better leverage their geographic advantages and key into untapped opportunities.

Pre-accelerators and mentorship: Nurturing the entrepreneurial potential

From the initial spark of an idea to the eventual launch of a product and beyond, the entrepreneurial path is filled with challenges and uncertainties. Many founders usually venture in not knowing what to expect. However, pre-accelerator programs and mentorship can help bridge the gap and provide support during these crucial early stages. 

As the world’s largest pre-seed investor,  Techstars knows firsthand the value of mentorship to early-stage entrepreneurs, and that is why our community programs, such as Startup Weekends and Founder Catalysts, are meticulously designed to help founders with the necessary mentorship and support they need through every milestone of their early entrepreneurial journey- that is, from refining their ideas and defining their value proposition to preparing for future investments in our accelerator programs. 

Techstars collaboration: Fostering startup diversity

Diversity and inclusion have become imperative in the startup industry, and Techstars actively collaborates with entrepreneurs from diverse backgrounds and regions to foster a more inclusive ecosystem.

Entrepreneurs and partners that collaborate with Techstars are exposed to global networks and funding opportunities, as well as a supportive community of diverse mentors, entrepreneurs, and investors. These interactions can break down cultural and regional barriers. It also causes founders and partners to be open-minded and embrace global perspectives.

Also Read: Empowering startup entrepreneurs: Harnessing benefits of Web3

A community of diverse entrepreneurs brings fresh ideas, cultural insights, and innovative solutions to the table. The collective expertise and experience shared by mentors and peers empower entrepreneurs to challenge the status quo, disrupt industries, and build scalable startups.

Building the entrepreneurs and thriving communities of the future

Throughout our quest to support founders, we have found that a collaborative and strategic approach is always required when building startup communities. To build the entrepreneurs of tomorrow, we must first start by empowering the children and youth of today, not just in the US.

We can do this by prioritising entrepreneurial education, whether in the form of pre-accelerators, accelerators, and Tech hubs or actively in our schools and universities. This will help young individuals develop an entrepreneurial mindset and equip them with the skills and knowledge needed to navigate the startup landscape. Strengthening our collaborations between academia, industry, and government can drive research and development, further encouraging innovation and breakthrough technologies.

Additionally, fostering a culture of risk-taking and embracing failure as a learning experience is also essential for entrepreneurial growth. Promoting diversity and inclusivity within the entrepreneurial ecosystem is also key to unlocking new perspectives and driving innovation.

Lastly, continuous support and investment in emerging technologies and industries will help create thriving entrepreneurial hubs that shape the future of economies and industries.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva Pro

This article was first published on June 8, 2023

The post Embracing global entrepreneurship: Redefining startup success beyond Silicon Valley appeared first on e27.

In the dynamic world of Web3 startups, understanding and implementing effective financial models is crucial for achieving long-term success. The emergence of blockchain technology and decentralised finance (DeFi) has revolutionised the way startups operate, presenting unique challenges and opportunities. To navigate this rapidly evolving landscape, entrepreneurs need to adopt innovative approaches to financial planning and management.

In this comprehensive guide, we will explore the guiding principles for developing robust financial models tailored specifically to Web3 startups. From revenue streams to token economics and risk management, we will delve into the key aspects that drive financial success in this exciting domain.

Understanding the Web3 landscape

Before diving into the intricacies of financial modelling for Web3 startups, it is essential to have a comprehensive understanding of the fundamental concepts that define the Web3 landscape.

By familiarising themselves with decentralised finance (DeFi), non-fungible tokens (NFTs), smart contracts, and other essential components of the Web3 ecosystem, startups can align their financial models with the specific dynamics of the decentralised world.

Decentralised finance (DeFi)

Decentralised finance, or DeFi, refers to the use of blockchain technology and smart contracts to create financial applications that operate without intermediaries. Traditional financial services such as lending, borrowing, trading, and asset management are redesigned and decentralised, offering increased transparency, security, and accessibility to users. In the Web3 ecosystem, DeFi protocols enable startups to develop innovative financial products and services while removing traditional gatekeepers.

Web3 startups should explore various DeFi applications, including decentralised exchanges (DEXs), lending platforms, yield farming, and liquidity provision. By understanding the mechanics and potential risks associated with these platforms, startups can strategically incorporate DeFi elements into their financial models, leveraging the benefits they offer while mitigating any associated risks.

Non-fungible tokens (NFTs)

Non-fungible tokens, or NFTs, have gained significant attention in the Web3 world. NFTs are unique digital assets that can represent ownership or proof of authenticity for a wide range of digital and physical items, such as artwork, collectibles, virtual real estate, and more. NFTs are typically built on blockchain platforms like Ethereum, allowing for verifiable ownership and provable scarcity.

Also Read: Sony & UMG join forces with Snowcrash to revive NFTs: Here’s why the digital trend is far from dead

For Web3 startups, NFTs present an exciting avenue for monetisation and user engagement. By incorporating NFTs into their financial models, startups can explore revenue streams such as NFT sales, licensing, fractional ownership, and royalties. Understanding the dynamics of NFT markets, including trends, valuations, and user preferences, will be crucial in designing effective monetisation strategies.

Smart contracts

Smart contracts are self-executing contracts with the terms of the agreement directly written into code. These contracts automatically execute predefined actions when specific conditions are met, eliminating the need for intermediaries and enhancing the security and efficiency of transactions. Smart contracts are a fundamental building block of the Web3 ecosystem, enabling a wide range of applications, including decentralised exchanges, decentralised finance protocols, and more.

Web3 startups should grasp the concept of smart contracts and their potential applications. By leveraging smart contracts in their financial models, startups can automate processes, reduce costs, and ensure trust and transparency in their operations.

Understanding the programming languages used for smart contract development, such as Solidity, and the associated best practices will be essential for startups seeking to harness the full potential of this technology.

Web3 ecosystem and interactions

In addition to DeFi, NFTs, and smart contracts, there are numerous other components within the Web3 ecosystem that startups should be familiar with. These include decentralised storage solutions, identity management systems, oracle services, governance mechanisms, and more.

Understanding the interactions and dependencies between these components will enable startups to design financial models that account for the broader Web3 infrastructure and the potential synergies it offers.

By comprehending the dynamics of the Web3 landscape, startups can leverage the power of decentralised technologies in their financial models. This understanding will allow them to identify relevant revenue streams, incorporate token economics, assess risks and opportunities, and make informed decisions that align with the unique challenges and opportunities of the decentralised world.

Principles of financial modelling for Web3 startups

Understanding blockchain economics

Web3 startups are built upon blockchain technology. The financial model for such startups must reflect an understanding of the underlying blockchain economics. Factors like gas fees (transaction costs on a blockchain), mining rewards, and tokenomics (economic system around the token of a specific blockchain) will have significant implications on the startup’s financial dynamics.

Incorporating tokenisation

Web3 startups often use tokens as a mode of value exchange within their ecosystem. These tokens can serve various functions like utility tokens (providing users with access to a product or service) or security tokens (representing ownership in an asset). Their volatility in value needs to be factored into financial projections, and possible capital gain scenarios must be accounted for.

Handling regulatory uncertainty

Given the relatively novel nature of Web3 and the ensuing regulatory ambiguities, startups in this domain need to model the potential financial impacts of regulatory changes. This could include costs for compliance, penalties, or changes in user behaviour resulting from such regulatory decisions.

Forecasting user growth

User adoption and growth are vital to Web3 startups, with direct implications on financial performance. The financial model should consider different growth scenarios and examine the corresponding impacts on revenues and costs.

Accounting for network effects

The value of Web3 startups often grows as the network expands. This phenomenon, called network effects, should be incorporated into financial projections, including the impact of growth on value and costs.

Building a financial model for a Web3 startup

Now, let’s walk through a simplified version of building a financial model for a Web3 startup.

Revenue estimation

For most Web3 startups, revenues may come from transaction fees, staking rewards, or selling tokens. It’s crucial to forecast revenues based on estimated growth, token value changes, and market dynamics.

Also Read: Web3 startups: The next big thing investors are flocking to

Cost projection

On the expense side, typical costs include development, operations, and marketing. Additionally, costs unique to Web3, like gas fees or smart contract audits, must be accounted for.

Financial statements

Build the traditional profit and loss statement, balance sheet, and cash flow statement. However, these will likely need modifications. For example, balance sheets might need to include token reserves, while the cash flow statement needs to account for cryptocurrency flows.

Scenario analysis

Given the volatility and uncertainty in the Web3 space, it’s critical to model different scenarios to understand potential outcomes and risks.

Valuation

Valuing a Web3 startup is challenging, given the scarcity of comparable companies, token price volatility, and regulatory risks. Techniques like Discounted Cash Flow (DCF), token economy valuations, or using multiples from a few existing similar companies can provide some guidance.

Final thoughts

Developing robust financial models is essential for the success of Web3 startups. By understanding the principles of financial modelling specific to the Web3 ecosystem, entrepreneurs can make informed decisions, attract investors, and navigate the challenges and opportunities in this dynamic landscape.

Incorporating elements such as blockchain economics, tokenisation, regulatory considerations, user growth forecasting, and network effects will enable startups to build comprehensive financial models that drive sustainable growth and long-term success. Through diligent research, analysis, and scenario planning, Web3 startups can optimise their financial strategies and position themselves for success in this exciting and rapidly evolving domain.

—

Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic

Join our e27 Telegram group, FB community, or like the e27 Facebook page

Image credit: Canva Pro

The article was first published on June 6, 2023

The post Financial models for Web3 startups: Guiding principles for success appeared first on e27.