Deeptech: Emerging Frontiers — Mini Blog #4
Deeptech Investible themes in Generative AI
In this week’s post, we’ll go over some of the use cases Generative AI is powering across industries and 3 investable themes we’re excited about here at pi
Generative AI is transforming every industry as we know it . With the right starter prompts to an appropriate large language model (LLM), it is now possible to generate personalized messages from one’s favourite celebrities, generate fully functional websites and even create fully animated 3D worlds.
Some themes in Gen AI that we’re excited by are:
- AI based coding co-pilots:
Devs are increasingly turning to AI chatbots and GitHub CoPilot rather than Stack Overflow message boards. (Stack Overflow traffic was down ~14% in March) Coding co-pilots can make suggestions and explain code, considering what users type and other context from their accounts, like the programming languages they’re using. Challenges around security vulnerabilities in AI generated code and copyright implications of training on publicly available code remain to be solved
2. 2D and 3D asset creation:
Marketers, game developers, and artists have to continually produce 2D and 3D content with limited time and resources. Increasingly, they will be able to set creative direction and then hand off much of the time consuming and repetitive execution to AI generators — unlocking large creative markets like gaming, VR, and cinema. Gaming in particular holds enormous promise, with some interesting applications being scene and texture generation based on text or image prompts, infrastructure to train one’s own 3D asset generator based on their art style
3. Drug Discovery and Therapeutics
Designing a novel drug requires scientists to select and validate candidates experimentally from a vast chemical space through trial and error. Using generative AI and a combination of other computational tools (such as Alphafold, NVIDIA’s BioNeMo) scientists can quickly iterate over the design space to tailor biological molecules for therapeutics with desired properties. (Gartner forecasts 50% of all drug discovery initiatives to have some element of Generative AI in them by 2025) Some interesting applications include protein sequence design, lead optimisation and novel molecule generation. We’re super excited about generative biology and have had the privilege to partner with Aridni and Trisha (Can tag) from ImmunitoAI, who are doing great work in the antibody discovery space.
Another overarching theme across Generative AI that interests us is the core infrastructure layer (LLMs and LLMOps) powering all these applications. More on this next week!
