A common trope repeated in the media and behind closed doors is that incumbents, not startups, are best positioned to take advantage of AI. In this line of thinking, AI is a sustaining technology that reinforces the positions of existing players, rather than a disruptive force that empowers new entrants. There is certainly some truth to this perspective, particularly for startups that focused on increasing the productivity of employees pursuing their
"What’s critical in each of these cases is that these are not explicitly productivity improvements to existing employees for existing workflows. Instead, they take markets that were constrained by all the effort, friction, and cost of hiring and working with people, and unlock them. Exactly the type of market that gets overlooked by an incumbent."
It's easy to see large tech shifts as sustaining or efficiency innovations in the moment, because those uses are immediately obvious. In ~2000, Larry Ellison thought Amazon was a nice proof of concept, but he was holding his breath for when Neiman Marcus finally made the shift online. AI is going to sweep the floor with business process automation, but to think that the only impact of infinite, almost-free text, code, audio and imagery is a better ratio on a balance sheet, will seem laughable in hindsight. AI is an empowering technology – regardless of what the New Church of Finance thinks. The internet-native business are, on balance, the best businesses in the history of mankind. I'd be surprized if the same didn't turn out to be true for AI-native ones.
One concept I like is that while the raw capacity of something like an LLM is increasing continuously over time, there's a hard threshold at which it crosses from being [not at all useful] to [useful] for a given application. Until we get true human-level AI-generated audio, ElevenLabs is impossible...but the second we do, it's a 10x improvement. Feels like part of the reason it's harder to spot these opportunities in advance.
Something that interests me with AI is how it can be used to optimize processes in niche verticals. Here's one example I've come across lately: Industrial Data Labs is building an AI Sales copilot that helps inside sales teams at industrial distributors operate more efficiently, respond to more customer inquiries, and generate more sales. And it's only possible due AI.
I think of this kind of use case as 'applied AI,' as opposed to 'foundational AI' that you see with OpenAI, Google, etc. I think that most of the value in foundational AI will accrue to incumbents, largely because it is, or will become, commoditized tech. But for niche verticals, applied AI looks to be very promising.
It does make you think.. what do you make of investment opportunities to create AI "shields" for the receiving end? Along with the opportunities you describe, output is going to increase by orders of magnitude, and frankly, probably with quite high signal-to-noise ratio.
It's easy to picture a world with crisp and concise inputs creating the most imaginary media living in this synthetic, ballooned world, then being reduced to something crisp and concise on the other end.
How do you see their relevance in the near future, and what strategies could they employ for defense? For instance, how many of the current AI companies might be overtaken by a more general AI, similar to what happened with AskPDF and ChatGPT4?
Glad to read more from you recently! Most people are concerned with the supply/output but not yet clear what happens on the demand/consumption side. Let's consider just one example for simplicity: YouTube.
Supply: Let's assume all these text, video, editing and image tools let current creators create more content, allow more people to create content, and each unit of content created is 'better'. Supply and quality of 'content' is gonna go up a LOT. This is a great thing overall...but....
Demand: On the human side, (mostly) humans consume the content and the rate of growth of humans will be more limited. Each human also has a limit on leisure / content hours, and I don't expect that to change much short-term.
How will such content output be consumed / discovered / curated? What new modalities or improvements will consumers need to be able to pick through the supply growth / or better process such volume? In this example, how would let's say YouTube as a product need to change to address that supply/demand imbalance? Yes, some better personalization, yes perhaps AI can summarize some of this net new content into the spark notes but overall something might have to change / give.
What needs to change on the consumption side to enable users to adapt / better absorb that content?
"What’s critical in each of these cases is that these are not explicitly productivity improvements to existing employees for existing workflows. Instead, they take markets that were constrained by all the effort, friction, and cost of hiring and working with people, and unlock them. Exactly the type of market that gets overlooked by an incumbent."
🎯
It's easy to see large tech shifts as sustaining or efficiency innovations in the moment, because those uses are immediately obvious. In ~2000, Larry Ellison thought Amazon was a nice proof of concept, but he was holding his breath for when Neiman Marcus finally made the shift online. AI is going to sweep the floor with business process automation, but to think that the only impact of infinite, almost-free text, code, audio and imagery is a better ratio on a balance sheet, will seem laughable in hindsight. AI is an empowering technology – regardless of what the New Church of Finance thinks. The internet-native business are, on balance, the best businesses in the history of mankind. I'd be surprized if the same didn't turn out to be true for AI-native ones.
One concept I like is that while the raw capacity of something like an LLM is increasing continuously over time, there's a hard threshold at which it crosses from being [not at all useful] to [useful] for a given application. Until we get true human-level AI-generated audio, ElevenLabs is impossible...but the second we do, it's a 10x improvement. Feels like part of the reason it's harder to spot these opportunities in advance.
Something that interests me with AI is how it can be used to optimize processes in niche verticals. Here's one example I've come across lately: Industrial Data Labs is building an AI Sales copilot that helps inside sales teams at industrial distributors operate more efficiently, respond to more customer inquiries, and generate more sales. And it's only possible due AI.
I think of this kind of use case as 'applied AI,' as opposed to 'foundational AI' that you see with OpenAI, Google, etc. I think that most of the value in foundational AI will accrue to incumbents, largely because it is, or will become, commoditized tech. But for niche verticals, applied AI looks to be very promising.
Hi Sarah, great writing as always.
It does make you think.. what do you make of investment opportunities to create AI "shields" for the receiving end? Along with the opportunities you describe, output is going to increase by orders of magnitude, and frankly, probably with quite high signal-to-noise ratio.
It's easy to picture a world with crisp and concise inputs creating the most imaginary media living in this synthetic, ballooned world, then being reduced to something crisp and concise on the other end.
How do you see their relevance in the near future, and what strategies could they employ for defense? For instance, how many of the current AI companies might be overtaken by a more general AI, similar to what happened with AskPDF and ChatGPT4?
Glad to read more from you recently! Most people are concerned with the supply/output but not yet clear what happens on the demand/consumption side. Let's consider just one example for simplicity: YouTube.
Supply: Let's assume all these text, video, editing and image tools let current creators create more content, allow more people to create content, and each unit of content created is 'better'. Supply and quality of 'content' is gonna go up a LOT. This is a great thing overall...but....
Demand: On the human side, (mostly) humans consume the content and the rate of growth of humans will be more limited. Each human also has a limit on leisure / content hours, and I don't expect that to change much short-term.
How will such content output be consumed / discovered / curated? What new modalities or improvements will consumers need to be able to pick through the supply growth / or better process such volume? In this example, how would let's say YouTube as a product need to change to address that supply/demand imbalance? Yes, some better personalization, yes perhaps AI can summarize some of this net new content into the spark notes but overall something might have to change / give.
What needs to change on the consumption side to enable users to adapt / better absorb that content?