Dean Murphy, commercial director - data provider products, Neudata

Understand how AI is impacting the alt data industry and how regulations and fast-paced developments are likely to impact your business

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Dr Miquel Noguer i Alonso, founder, Artificial Intelligence Finance Institute

We expect the benefits of AI to come in stages over the next decade – hardware and semiconductors have substantial AI exposure today but leadership will change once diffusion into infrastructure/devices shifts that value over time. In line with previous technological paradigm shifts, we would then expect a third wave much later from companies that can create usable applications on top of this infrastructure. We believe today's AI training stage precedes significantly larger future revenues from model deployment and AI inference. Enterprises will likely re-architect around AI, and companies that know how to use AI are likely to outgrow those that don't, in our view.

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Shawn Kim, asia tech strategist, Morgan Stanley

Collaborative Alpha in the age of Generative AI

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Until we reach above human-level artificial intelligence it’s likely that combining human with artificial intelligence will yield better outcomes than either alone.  How to find the optimal mix is non-trivial however.  In this presentation we tackle just that issue and ask – how can we best combine the strengths of humans and machines, avoid their respective weaknesses and become better investors?

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Gabriel Andraos, co-head of Voya Machine Intelligence, research & development, Voya Investment Management

Review latest AI developments in Asia as we touch on supply chain, political issues and language challenges

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Paris Tung, senior analyst, Neudata

Orbit will delve into maximizing the business benefits of Large Language Models (LLMs), accomplished with Orbit Insight and Orbit DataStudio. Explore how we've prepared LLMs to efficiently tackle the challenges around unstructured data and utilising methods for investment research, and insights generation.

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As companies strive to seamlessly integrate LLMs into their Target Operating Model (TOM), we'll address key questions surrounding model hallucinations, combining Chat GPT across a reliable data pool, and navigating unstructured data into machine-readable formats. Our goal? To nullify these challenges and generate value across your business.

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Da Wei, CEO, Orbit Financial Technology

Understand the differences between enterprise quality AI and consumer / GPT quality outputs.
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Data quality matter in finance, and errors lead to cascading problems across investment use cases. Most advancements in AI focuses on the breath of capabilities, not the depth or quality of output. The frameworks required to build an enterprise grade AI system is wholly different from a consumer grade one.
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Thomas Li, CEO, Daloopa

Gain an in-depth understanding of sentiments towards AI and whether this nascent technology will have the power to transform investment management

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Neo Yi Peng, independent quant strategist