Generative AI has been transformational; there has never been a period in human history where a person's efficiency exponentially increased this much through adopting new technology. The printing press allowed mass production of books; the industrial revolution gave businesses the ability to quickly and cheaply scale production; the internet allowed us to get information faster and simplify our decision-making process; the iPhone put a mini computer in everyone’s hands to produce anywhere, anytime. Yet, none of those gave you the capacity to do 100X, instantly, with no extra effort.
Let me give you a few examples that are applicable to people, and not just businesses:
These are just some examples of this tech being ‘productised’ and there are hundreds of other applications disrupting how we learn, work and play. Character AI or OtherHalf are ‘redefining’ companionship, Gendo AI changing how architects/interior designers work and Synthesia democratising video creation, to name a few.
Are all of these perfect? No, but we do not need them to be in order to see a boost in workforce productivity. Do businesses require a top-notch output? It depends on the use case, although the benefit of using GenAI's often imperfect solutions already outpaces the traditional approach in many cases.
Is there a bubble? No, and yes; the key lies in expectation vs reality and the answer is a bit trickier here but before getting into it, let’s compare some previous FOMO-fueled (and arguably popped) bubbles:
The biggest problem with these examples is that often, near-term tangible value vs. future promised value was too misaligned. Everyone expected those technologies to be able to transform society while making billions and good margins. Once investors understood that they were longer shots or unfeasible/unsustainable models, they dried up funding and moved on to the next thing. In my opinion, however, those investors that stick to their original thesis and help their portfolio evolve their business models will see the benefits.
Generative AI has also generated very high expectations but, differently from other bubbles, they are outperforming even the highest early expectations. GenAI startups have been expensive to build due to the scarcity of talent and the high cost of using top-of-the-range GPUs. Once those models are built and deployed, GenAI companies bring the best of all possible worlds:
Generative AI is not perfect and has a substantial amount of challenges ahead. From ethics & regulation or model accuracy to helping society understand that we will always need people. Yet, despite the challenges, businesses have adopted AI in record times.
Is there a bubble in Generative AI? Yes, and no. According to Pitchbook, $4.5bn was invested in GenAI in 2022 and a further $1.6bn in Q1 2023. Q2 will break all records after Inflection AI, ElevenLabs and Mistral AI, amongst others, announced their rounds. There is technically a bubble if you think about the pace at which startups are pivoting to GenAI or raising large rounds. There is also a bubble in startups doing foundational LLMs when the foundations have already been built. Yet, there is not a bubble in phase 2 of Generative AI: vertically-integrated applications.
Vertically-integrated GenAI companies are just getting started. They are the next natural layer in Generative AI because their applications harness the strength of foundational LLMs with proprietary datasets to solve niche problems in each industry. These applications will take productivity to a whole new level for everyone, across all industries. These companies are being built today.
Is there an actual bubble in Generative AI? No. The industry is just getting started and profits (yes, that positive thing at the end of the P&L) are real.