Large Language Models: 5 takeaways for SMEs

Deepak Sarda, Vice President of Engineering, Endowus

Every significant stride in human history has hinged on one key factor: communication. Our world, our societies, and our cultures have been shaped by our ability to connect and share ideas, stories, and knowledge. The advent of computers and the internet supercharged this exchange, facilitating unprecedented levels of global interaction.

But these interactions have largely been human-driven. As computers can’t independently process or understand ambiguous human language(s), they need precise instructions to ‘communicate’. This gave birth to programming, a complex language for ‘talking’ to machines.

The stark contrast between human communication, with its richness and adaptability, and the rigid structure of machine communication became more evident as our dependence on technology grew. But the emergence of Large Language Models (LLMs) is gradually bridging this gap, making computers capable of adapting their communication in a more human-like way.

Humans learn by experiencing, observing, and replicating. Early AI research sought to emulate this process but faltered due to the paucity of data and computational power. The AI domain then shifted focus to task-specific learning models, such as fraud detection and image recognition. However, the surge of data from the internet and the advent of GPUs – initially designed for gaming, but exceptionally apt for data processing – revived the ‘learning by example’ approach, leading to the creation of LLMs.

LLMs, fundamentally, are software capable of interacting through various mediums – text, voice, images, and video – mimicking the ambiguity and adaptability characteristic of human communication. As humans use foundational communication skills to learn, garner feedback, and improve upon other skills, LLMs can be directed to do the same. Instead of creating task specific AI, we can take a LLM that is capable of generalised communication and teach it task specific skills. This opens up significant opportunities to streamline and automate many tasks and processes that currently require extensive custom software development.

This paradigm shift heralds a revolution in communication: human-to-computer, human-to-human, and computer-to-computer.

Human-to-Computer Communication

LLMs promise a future where we don’t need to meticulously instruct computers on every task, thereby eliminating the necessity of programmers for each task. Picture using Excel: remember the thrill of employing a function to automate a process? Now imagine applying this excitement to every part of your life. By describing your needs in plain language and providing a few examples, an LLM assistant can become your digital butler, ready to carry out your requests. It’s an era of human augmentation that we’re only beginning to explore.  This is also the area with the most investment today, be that in the form of better chatbots for customer service, or AI assistants that speed up data analysis and content creation.

Applying these technologies to the wealth management space, Endowus is actively pursuing several LLM initiatives to enhance our services and provide our customers with an increasingly seamless, digitally-enabled experience. This will be accomplished through the design and launch of a variety of AI-driven Chatbots, and a Fund Recommendation Engine that adopts a natural conversational style to capture customers’ goals and provide sophisticated, personalised recommendations.

Human-to-Human Communication

LLMs are fundamentally about understanding human communication in all its forms and across all mediums. This understanding is not language-specific – it merely requires an abundance of examples.

Consequently, LLMs are poised to catalyse a revolution in language translation, rendering high-quality translations imbued with the original text’s nuance, idiom, and metaphor. Imagine reading ‘Anna Karenina’ or ‘The Three-Body Problem’ in any language, with no delay for translation and no compromise on quality.

As this technology matures, translations will be done in real time, enabling us to speak with each other in our native languages & yet understand each other completely. The fabled Babel Fish from ‘The Hitchhiker’s Guide to the Galaxy’ is on the verge of becoming a reality.

For businesses, this represents a significant leverage opportunity for efficiently translating all forms of marketing and business communications to support regional aspirations and expansion into new markets. Endowus brought our successful fee-only business model to launch in Hong Kong last month, and we utilised machine-aided translations in building out our website.

Computer-to-Computer Communication

As someone whose background is that of a software developer, I find the potential of LLMs in computer-to-computer communication particularly fascinating. The dream of autonomous software agents, previously restrained by their inability to adapt to new scenarios, now appears within reach.

Do you recall that cinematic moment in Independence Day when Jeff Goldblum’s character audaciously infects an alien spacecraft with a computer virus? As a software programmer, I always found that scene a bit hard to swallow. I mean, here on Earth, we face hurdles in getting a simple Windows app to run seamlessly on a Mac, and vice versa. Yet in the realm of Hollywood, we somehow managed to implant our human-made software, a computer virus, into an entirely alien tech!

With LLMs, software agents could negotiate a shared language (a protocol in software terms), enabling them to interact without needing human intermediaries. That scenario from Independence Day is completely in the realm of possibility now!

As we look to the future, I foresee software development focusing on two key areas: the foundational, involving making LLMs more efficient and cost-effective, and the applied, involving leveraging LLMs in diverse contexts. Traditional programming might still exist, but it will morph into a specialised dialect, akin to doctors or physicists communicating using their domain specific terminology.

The Future

Large Language Models signify a profound shift in the communication paradigm, offering a path towards a more intertwined human-digital world. It’s about harnessing practical solutions that enrich our lives, transforming our reality by infusing it with elements of a previously imagined futuristic sci-fi world. As custodians of this technology, we must handle it with care, ensuring that it aligns with our values and serves our collective needs.

As we navigate this new frontier, it’s crucial to embrace the possibilities while acknowledging the accompanying challenges. By treating this progress with thoughtful curiosity, we can orchestrate a future where technology becomes an integral and harmonious part of our daily interactions and communications.

Top 5 takeaways for SMEs

1. Streamlined Automation

SMEs can leverage LLMs to automate repetitive tasks and processes, freeing up valuable time and resources. By providing clear instructions and examples, LLMs can learn and adapt to perform various tasks, reducing the need for manual intervention.

2. Enhanced Customer Service

LLMs can be utilised to improve customer interactions and support. By training LLMs with customer data and queries, SMEs can develop AI-powered chatbots or virtual assistants that can provide personalised and efficient customer service, leading to higher customer satisfaction and retention.

3. Language Translation and Localisation

SMEs with global operations can benefit from LLMs’ language translation capabilities. LLMs can enable accurate and nuanced translations of marketing content, product information, and customer communications, facilitating effective communication with international markets and expanding business opportunities.

4. Content Creation and Curation

LLMs can assist SMEs in generating engaging and high-quality content for marketing purposes. By providing LLMs with examples and guidelines, businesses can automate content creation, such as blog articles, social media posts, and product descriptions, saving time and ensuring consistent messaging.

5. Data Analysis and Insights

SMEs can leverage LLMs for data analysis and extracting valuable insights. LLMs can process fairly large volumes of text data, identify patterns, and generate meaningful reports, aiding in decision-making and providing a competitive edge.