This paper introduces "Shai" a 10B level large language model specifically designed for the asset management industry, built upon an open-source foundational model. With continuous pre-training and fine-tuning using a targeted corpus, Shai demonstrates enhanced performance in tasks relevant to its domain, outperforming baseline models. Our research includes the development of an innovative evaluation framework, which integrates professional qualification exams, tailored tasks, open-ended question answering, and safety assessments, to comprehensively assess Shai's capabilities. Furthermore, we discuss the challenges and implications of utilizing large language models like GPT-4 for performance assessment in asset management, suggesting a combination of automated evaluation and human judgment. Shai's development, showcasing the potential and versatility of 10Blevel large language models in the financial sector with significant performance and modest computational requirements, hopes to provide practical insights and methodologies to assist industry peers in their similar endeavors. Recent advancements in Large Language Models (LLMs) have resulted in breakthroughs, with 100B-level models like GPT-4 [1], LLaMa2 [2], ChatGLM[3], BLOOM[4], Falcon[5] and PaLM2[6] leading the way in natural language processing (NLP) capabilities. These models have shown an exceptional ability to generate natural and coherent text, understand complex contexts, and adapt to a wide variety of tasks and scenarios. Besides the general LLM development, domain specific LLM development is also flourishing, where the domains span from law[7; 8; 9] to health care[10; 11; 12; 13] and finance[14; 15; 16; 17] etc.

Vectorspace AI, a subsidiary of Vector Space Biosciences, Inc., now enables cryptocurrency exchanges with a thematic crypto baskets REST API available here. This API enables an exchange to offer tradable baskets of cryptos related to a theme, event or topic of any kind in real-time. The API is designed to spawn an ecosystem of new products for retail traders and investors providing them with abilities similar to hedge funds or asset management companies operating advanced data engineering pipelines. "It's like having your own dedicated NLP, AI, or Machine Learning pipeline," remarked Kasian Franks, Founder and CEO of Vector Space Biosciences, Inc. "This opens up a new world of thematic investing where baskets of cryptos or stocks can be generated based on a theme or global event in real-time using similar'language modeling' techniques used to predict the way proteins fold by DeepMind's AlphaFold2." VectorScreen is an additional filtering package powered by the core crypto baskets API, enabling advanced screening and filtering resulting in additional alpha.

The world of Capital Markets is changing. Soon there will be no room for traditional players without digital capabilities – markets will become increasingly efficient and the margin pool will shrink. Being the first to deploy a winning strategy from a particular data set (or group of data sets) requires asset managers to learn, build and master the latest computing techniques. Artificial Intelligence and Data Science in Trading provides senior management from funds - fundamental to systematic - and investment banks with the latest tools and techniques to maximize margins and discover a competitive edge. By attending, you will learn from 95 world-class speakers, from leading asset management companies, academia and technology providers.