Generative AI Startup Strategy Case Studies | Sramana Mitra

The 1Mby1M Methodology is based on case studies. In this course, Sramana Mitra shares the tribal knowledge of tech entrepreneurs by giving students the rare seat at the table with the entrepreneurs, investors and thought leaders who provide the most instructive perspectives on how to build a thriving business. Through these conversations, students gain access to case studies exploring the alleys of entrepreneurship. Sramana’s synthesis of key learnings and incisive analysis add great depth to each discussion.

Ever since ChatGPT was made available to the general public, everybody is talking about how it will impact the world as we know it.

ChatGPT is a generative pre-trained transformer (GPT) built on top of OpenAI’s GPT-3 family of large language models (LLMs). Generative AI is trained on vast amounts of data that enable it to understand and respond like a human. It helps create new content from previously created content. It can write and debug computer programs, compose music, plays, and student essays, and answer test questions.

OpenAI’s Journey and Financials

OpenAI was originally founded in 2015 with a stated goal of promoting and developing friendly AI in a way that benefits humanity as a whole. Sam Altman, Elon Musk, Greg Brockman, Reid Hoffman, Jessica Livingston, Peter Thiel, AWS, Infosys, and YC Research pledged over $1 billion to the venture.

In 2019, OpenAI entered into a $1 billion deal with Microsoft. For using Azure Cloud Platform, it would give Microsoft the first opportunity to commercially leverage early results from OpenAI’s research. Microsoft has invested an additional $2 billion and also become a key backer of OpenAI’s Startup Fund, OpenAI’s AI-focused venture and tech incubator program.

OpenAI charges developers licensing its technology about $0.0004 to $0.02 to generate 750 words of text and about $0.016 to $0.020 to create an image from a written prompt. It expects revenue of $200 million in 2023 and $1 billion by 2024. It has been valued at $20 billion in a secondary share sale.

OpenAI’s Competitor Landscape – Bard, Cohere, Stability AI

Within a month of its launch, ChatGPT had answered queries for over 1 million users. This raised questions about the threat to Google’s dominance in the $200 billion online search market. Google has recently introduced Bard, a conversational AI service powered by Language Model for Dialogue Applications (LaMDA). It expects to soon have AI-powered features in Search to process multiple perspectives into easy-to-digest formats.

Google will be releasing Bard initially with a lightweight model to make sure Bard’s responses meet a high bar for quality, safety and is grounded in real-world information. Next month, it will start onboarding individual developers, creators, and enterprises so they can try its Generative Language API.

There are several lesser-known startups working on varied use cases. Cohere, which has a Google Cloud Partnership, plans to introduce a new dialogue model to let enterprise users generate text and engage with the model to refine the output. It has raised $175 million so far from investors including Index Ventures, Tiger Global and AI luminaries Geoffrey Hinton, Fei-Fei Li, and Pieter Abbeel. It is looking to raise more funds at a valuation of $6 billion. I like Cohere for its B2B strategy and its stated focus on supporting developers who want to piggyback and build applications on their platform.

Piggybacking is a capital efficient strategy of entrepreneurship. Generative AI is going to be a great platform to piggyback on and build your startup in a capital efficient manner. Learn how you can build startups by piggybacking on cutting edge technology AI platforms by taking this Udemy course on Bootstrapping by Piggybacking.

Stability AI released its open source text-to-image AI generator called Stable Diffusion last year. Stable Diffusion is the main competitor for Open AI’s Dall-E, a text-to-image AI program. In October 2022, Stability raised $101 million in a seed round led by Coatue Management and Lightspeed Venture Partners at a $1 billion valuation.

The first step to building a successful AI startup is to stay on top of this fast-paced industry and build an effective AI application around your own domain knowledge. One way to go about learning how to do this would be to take our How to Build an AI Startup course on Udemy.

Global investment in AI surged from $12.75 billion in 2015 to $93.5 billion in 2021. The AI market is expected to grow at 39.4% CAGR to $422.37 billion by 2028. This decade, clearly, is going to be about AI, especially LLM (large language models) and Generative AI platforms.

However, the AI platform vendors realize that the best way for them to get to accurate, actionable applications is by opening up to developers who bring specific domain expertise to the table, train their models on domain-specific data sets, and build domain-specific workflows. This is why Platform-as-a-Service (PaaS) will become the standard operating procedure of this industry. Developer ecosystems piggybacking on platforms will become the norm.

If you are a developer / entrepreneur playing this game, you will also want to beef up your knowledge of how to bootstrap by piggybacking and how to leverage domain knowledge to build AI startups.

For now, let’s start by listening and learning from some Founders who are successfully building Generative AI startups.

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