Aveni CEO Joseph Twigg and lead NLP engineer Iria Del Rio recently discussed the meteoric rise of ChatGPT and other large language models, the forces that have led us to this point, and what it signifies for the world of financial advice and services.
ChatGPT’s release has triggered a seismic shift in technology, catapulting AI and concepts like large language models and generative AI into the global spotlight. With its unprecedented growth rate, ChatGPT has accumulated 100 million users within a span of two months and has been the subject of almost 70 million news articles. We’re on the brink of a new era where LLMs will dramatically alter the way we operate, with all sectors, including wealth management and financial advice, poised for significant transformation.
Aveni explained that ChatGPT is a game-changer in the realm of Natural Language Processing and a prime example of a large language model. These models excel at predicting subsequent words based on a given context, whether for lengthy paragraphs or extensive text. They learn from text available on the internet, making them a kind of black box technology. However, ongoing research and techniques like fact-checking and traceability are helping to demystify these models’ responses.
Before looking at its potential, Aveni looked back at its rapid transformation in just a few years.
The AI landscape saw a significant shift in 2018 with the advent of the Transformer architecture, a probabilistic model designed for content generation. This model, though powerful, was soon surpassed by GPT2 and then GPT3. The models were further improved by implementing an instruction-based training approach, augmented with a technique called Reinforce. This helped align the model output with human expectations, thereby controlling any biased or toxic responses.
The phenomenon of emergence is observable in nature, physics, and now, in large language models. As these models grow in size, they begin to demonstrate capabilities previously unseen. We’ve seen this with GPT models as they progress from millions to billions, and potentially trillions of parameters during training, Aveni stated.
The combination of LLMs with other tools proves extremely advantageous in financial services. However, since these models are trained on time-bound data, it is crucial to keep the information up-to-date and accessible on the internet. In a regulated sector like financial services, domain expertise and risk management are crucial.
Despite the advances in AI, it is not poised to replace financial advisor jobs in the immediate future. Navigating the regulatory landscape with AI-derived advice is complex, and it’s still uncertain if it aligns with consumer preferences. However, the effective use of AI could usher in a productivity revolution, allowing advisors to handle 2-3 times more clients without compromising on service quality.
The productivity revolution hinges on ‘human plus’ activity. AI has traditionally been deployed in niche areas like fraud detection, cyber analytics, and customer experience management. Now, the industry is moving towards a broader application of AI, with AI assistants becoming a part of our daily lives, thereby reducing administrative burden. This will allow advisors to focus more on relationship and customer support.
Aveni has developed Aveni Assist, based on the GPT3.5 Turbo model. It’s been designed specifically for financial advice and wealth management. It uses prompt engineering, information retrieval mechanisms, and traceability algorithms to ensure accurate data output. Aveni Assist can streamline the workflow, reducing a typical three-hour task to 15 to 30 minutes. We believe this will revolutionize the administrative and risk management burden in the sector.
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