5 Things You Should Know About GenAI Company Valuations

Recently, GenAI has been particularly noteworthy, giving rise to a new breed of tech startups that have quickly ascended to unicorn status. However, the journey to the top is not without its challenges. From the astronomical costs of training large language models to the discrepancy between soaring valuations and modest revenues, the AI industry presents a complex landscape.

Rise of GenAI Unicorns

Here are the top 5 things you need to know:

1. The Rise of AI Unicorns: The AI industry is a high-stakes game, no doubt about it. But guess what? Generative AI has already produced 13 unicorns, including big names like OpenAI, Anthropic, HuggingFace, Cohere, and Jasper. And these startups are hitting the billion-dollar mark faster than their peers in other sectors. We’re talking an average of 3.6 years to reach unicorn status, compared to the 7-year average for the entire unicorn club. Impressive, indeed.
2. OpenAI and the Billion-Dollar Club: OpenAI, a unicorn since 2019, has seen its valuation skyrocket 10x since then, leading the pack with a whopping $29B valuation. Anthropic, Cohere, and Hugging Face aren’t far behind. These unicorns are developing their own large language models, a task that requires substantial financial resources.
3. The Challenges of Training and Serving Large Language Models: Training these models is no walk in the park. They learn by predicting the next word in a massive amount of internet text, picking up both the good and the bad. To make them more user-friendly, they undergo a two-step process involving a dataset of user instruction and output answers, followed by a human feedback process. This process isn’t cheap. Training a model like Meta’s LLaMa can cost up to $5 million in just 21 days. And running these models? That’s another hefty bill. Rumor has it that running ChatGPT costs OpenAI around $700,000 every day.
4. Soaring Valuations Amid Modest Revenues: There’s a lot of hype around AI, and it’s led to a significant gap between these companies’ soaring valuations and their modest revenues. But investors are betting big on the future potential of AI technology, despite the current revenue figures.
5. Investor Confidence in AI: Even in an economic downturn, AI companies are attracting significant investments. Investors have strong confidence in the founding teams, many of whom have previously led successful startups and teams at tech giants like Meta and DeepMind.

So, there you have it. Whether these investments will be visionary or a spectacular misjudgment, only time will tell. But one thing’s for sure: these startups are becoming key players in several industries and are fueling ambitions to create an AI landscape that combines technological prowess with robust regulatory oversight. Stay tuned, because it is just getting started!