With the advancements brought in by GPT models, GPT-4o being the latest, creating sustainable AI startups that leverage artificial intelligence and can last and grow over time has become increasingly important.
In a recent podcast, OpenAI chief Sam Altman spoke about how to either create a business that thrives even if the next AI model isn’t significantly better, or develop a system that gets more useful as AI models improve or advance.
Additionally, he favoured not building an “AI business” in most cases, but rather a business that uses AI as a technology. Giving an example, he drew parallels to the early days of the App Store, where many people built simple apps like Flashlight which became obsolete with an iOS upgrade.
Meanwhile companies like Uber established sustainable businesses as smartphones improved, leveraging phones as the key technology that significantly enabled their operations.
How OpenAI Plans to Monetise
Recently, OpenAI made GPT-4o available to everyone for free (with usage limits), offering features like browsing, data analysis, and memory.
Additionally, Plus users will receive up to 5x higher limits and earliest access to features like the new macOS desktop app and next-generation voice and video capabilities. The move highlights OpenAI’s efforts to encourage upgrades to their monetisation plans, as discussed in the podcast.
Altman said that they are yet to figure out ways to make an expensive technology like GPT-4 available to users for free. He emphasised that while they aim to provide advanced AI tools for free or at a minimal cost as part of their mission, the high expenses currently pose a significant barrier.
Meanwhile, OpenAI recently became a Reddit advertising partner, which likely indicates that the company can leverage Reddit’s large user base to advertise its own products and services, potentially driving more customers and revenue.
OpenAI’s revenue for this year has surpassed the $2-billion mark, according to reports from the Financial Times. Therefore, like OpenAI showcasing its continuous revenue generation, startups must also ensure they can sustain their business models in the long run.
Do startups need to follow big companies
A few days ago, Cred founder Kunal Shah cast a wide net asking people on X this direct question: “Who is building an AI application in India”, receiving nearly 300-400 responses.
Dharmesh BA, who is working on a stealth startup, noted that many products were simply wrappers around existing models in various modalities. He categorised these apps as CRUD (Create, Read, Update, Delete) and warned that building apps based on the assumption that OpenAI or current LLMs can’t perform specific tasks could lead to a disaster.
Each time OpenAI updates or releases a new version, many startups find themselves rendered obsolete because the enhanced capabilities of OpenAI often solve the problems these startups were aiming to address.
When OpenAI introduced ChatGPT Enterprise, it sent shockwaves across several SaaS startups that had developed products around ChatGPT or offered wrappers based on ChatGPT APIs for business clients.
Additionally, Dharmesh’s post highlighted a perspective that attempts to confine an extremely powerful technology, like LLMs—which can be compared to a genie capable of doing anything—into a limited space such as mobile apps or websites.
These technologies are capable of much more complicated and valuable work, and by limiting their potential, we are not utilising them in the medium they are meant to reside in.
What about Indian Startups
In yet another post on X, the Cred founder said that early-stage startups should be easy to iterate and late-stage startups should be hard to distract. This highlights the mentality of Indian startups that are not iterating and not innovating enough.
In India, researchers and enterprises should prioritise building large models, technical benchmarking, and AI industrial standardisation over developing specific use case apps, which are easily replicated and improved upon.
Most envision LLMs as operating systems where users choose their own apps, but these apps’ longevity depends on the base provider, like OpenAI’s architecture.
But as AIM wrote, the question remains as to why such research isn’t being conducted domestically, especially as tech giants like OpenAI and Google focus more on Indic languages, posing a threat to those developing for the Indian ecosystem.
