A photo of Nei-Kuan Chia

Nei-Kuan Chia, Principal

Generative artificial intelligence reached a tipping point in 2023, and the race is on to test and apply AI and generative AI to enhance technology capabilities and boost productivity. Only a year ago, OpenAI introduced ChatGPT to the world and quickly captivated the attention of consumers and enterprises alike. While the segment is still relatively new, companies are investing billions of dollars to gain a strategic edge from this technology. According to McKinsey, generative AI is forecasted to add between $2.6 and $4.4 trillion in value to the global economy.

Applications such as ChatGPT are what is generally described as “horizontal platforms” and represent the first wave of AI; these types of platforms are broad and versatile AI systems with applications across various industries. The AI horizontal platform market generated $60 billion in revenue in 2023 and is expected to grow to $160 billion by 2026. Leading tech companies have raced to develop their AI systems led by OpenAI’s ChatGPT, Google’s Bard, Saleforce’s Einstein and Anthropic’s Claude.

At this point, it’s too early to tell if there will be a dominant AI model in the marketplace. At Socium, we have looked at various horizontal platforms and the industry as a whole. At the core of generative AI lies the need for machine-learning systems to digest data. However, more data is not always better, unless it can be fine-tuned and tailored to the business context. We believe that some of the most important parts of the AI ecosystem are the tools to train systems on the data — ones that will improve their accuracy and relevance for businesses. Therefore, our investment thesis is focused on the underlying infrastructure that can power any AI system.

Scale AI, our latest investment, is a crucial part of the AI ecosystem and infrastructure based on its Data Engine product that annotates, curates and cleans data for model training and inference-building. Scale Data Engine is redefining how AI creates value for enterprise organizations with full-stack platforms, fine-tuning and Reinforcement Learning Human Feedback (RLHF) that integrates with AI models to build better data. Not only does Scale AI power language learning models (LLMs), but its enterprise generative platform allows businesses to customize them. Simply put, Scale AI helps organizations in any sector implement AI by improving the underlying data for their specific goals and requirements.

We think that the quality and reliability of the data infrastructure is crucial to unlock the full potential of LLMs for companies and consumers. We see huge potential in Scale AI and are excited to back their vision and growth as they tap into the growing market while improving the outputs for enterprise needs across a wide span of industries.

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