In a world driven by technological advancements, the value generated by AI has been a subject of great interest and debate. Surprisingly, the previous wave of AI value seemed to favor incumbents over startups, despite the significant activity seen in the startup ecosystem. To understand this phenomenon better, we can examine the patterns observed in previous waves of technology adoption.

In a world driven by technological advancements, the value generated by AI has been a subject of great interest and debate. Surprisingly, the previous wave of AI value seemed to favor incumbents over startups, despite the significant activity seen in the startup ecosystem. To understand this phenomenon better, we can examine the patterns observed in previous waves of technology adoption.

During the first internet wave, startups like Google, Amazon, Paypal, Ebay, Salesforce, Facebook, and Netflix emerged as major players, capturing a substantial portion of the value. However, incumbents such as Microsoft, Apple, IBM, Oracle, and Adobe also managed to extend their franchises onto the internet and secure a share of the value. This resulted in a relatively balanced split of value, with startups possibly accounting for around 60-70% and incumbents for the remaining 30-40%.

In the mobile era, the scenario changed, and incumbents like Apple and Google took the lead in capturing value. Notably, even mobile versions of incumbents' apps, such as Salesforce on the iPhone, dominated the market. However, startups such as Whatsapp, Uber, Doordash, Instagram, and Instacart still managed to carve out a significant share of the value. This time, the split seemed to favor incumbents more, with startups possibly accounting for only 20% of the value.

Crypto, on the other hand, witnessed a different trend altogether. The value creation in this domain was almost entirely captured by startups like Bitcoin, Ethereum, Coinbase, Binance, and FTX. Existing financial services or infrastructure companies had minimal participation in this wave of value creation. This unique characteristic of crypto highlights the potential for startups to dominate in certain niches where incumbents may struggle to adapt.

To challenge an incumbent as a startup, you typically need to create something significantly better that overcomes the incumbent's distribution channels, capital, and pre-existing product moats. Alternatively, focusing on a new customer segment or distribution moat that the incumbent cannot effectively serve can also give startups an edge. In general, startups need to deliver a product that is at least 10 times better than what the incumbents offer.

One possible reason why incumbents have historically dominated the AI landscape is their data advantage. However, this advantage may be diminishing as companies leverage the broader internet as an initial training set and adopt models that work robustly with smaller data sets. This leveling of the playing field could potentially open up more opportunities for startups to capture value in the AI space.

While many AI companies in the past directly competed with incumbents or operated in challenging markets, the current wave of AI innovation feels different. The speed of innovation across various areas is remarkable, and the technology seems dramatically stronger than before. This enhanced technology strength enables startups to create products that are 10 times better, thus overcoming incumbent advantages.

Although GPT-3, a notable AI model, has shown promise, it has not yet given rise to a wave of startups building substantial businesses on it. However, the emergence of a 5-10 times better model could create a whole new ecosystem of startups while augmenting the offerings of incumbents. Additionally, the presence of infrastructure-centric companies like OpenAI, Stability.AI, Hugging Face, Weights and Biases, and others signifies the growth of a supportive ecosystem that provides startups with access to essential technologies.

Furthermore, there are specific use cases where AI can significantly enhance productivity. Highly repetitive and highly paid tasks, such as coding, creating marketing copy, or generating website images, can benefit from AI-powered workflow tools. By integrating AI features into these workflow tools, startups can provide users with a core and useful part of their broader workflow.

However, it is crucial to avoid falling into the trap of looking for problems that fit the technology rather than identifying actual end-user needs. The key is to focus on serving the needs of real users and untapped markets that can benefit from the current wave of AI technology. Understanding the end users' pain points and delivering solutions that address those pain points will be the key to success.

Looking ahead, it seems that startups are finally entering an era where they can realize significant value from AI. The combination of technological advancements, a supportive ecosystem, and a focus on addressing user needs creates an exciting landscape for startups to thrive.

Before concluding, let's highlight three actionable pieces of advice for startups venturing into the AI space:

1. Build something dramatically better: To compete with incumbents, startups need to create products that are at least 10 times better. Focus on delivering a solution that surpasses existing offerings in terms of performance, user experience, or other crucial metrics.

2. Identify untapped markets or customer segments: Look for areas where incumbents are unable to effectively serve due to various constraints. By targeting these untapped markets, startups can find opportunities to capture value and establish a strong foothold.

3. Prioritize user needs: Instead of being driven solely by the capabilities of AI technology, put the needs of end users at the forefront. Understand their pain points, and design solutions that directly address those pain points. This user-centric approach will increase the chances of success.

In conclusion, the AI landscape has seen a shift in value distribution from incumbents to startups. While incumbents have historically held an advantage, technological advancements and a focus on user needs present an opportunity for startups to capture a larger share of the value. By building superior products, targeting untapped markets, and prioritizing user needs, startups can position themselves for success in the AI-driven future. Exciting times lie ahead!