I think AI startups become defensible as soon as they can leverage the positive feedback where user interaction with AI can lead to improving the model. For example midjourney can leverage user image preferences to collect training data, use the data to improve the model, and use the better model to attract even more users and collect even more training data for the next run. So if you built it in a weekend and get to market first, and the benefit of finetuning on user preferences is sufficient, it's quite defensible.
I also think talent/culture is a moat of its own. OpenAI is nothing without its people, but it's also unstoppable with them. Given the right culture/team a company can consistently produce banger models and stay ahead of the curve, which attracts more top talent and investment, and so on.
I generally agree with the article's point about the necessity of unique, proprietary data MOATs for AI startups. However, it's important to note the speed at which these startups need to act. A notable trend in AI adoption is the willingness of many to try new applications at least once. When ChatGPT was released for free, everyone and their aunt tried it. It had record user signups for a reason.
The appeal of AI, in its basic form, lies in task automation. This is particularly true for sectors yet untouched by AI and possessing significant data MOATs. These areas seem more open to considering AI solutions than before. A personal observation supporting this is my mother's experience. She struggles with basic digital tools like Gmail, yet she found ChatGPT intuitive and easy to use. The simplicity of typing a query and receiving a response resonated with her immediately. Most importantly, she immediately understood how this could evolve to automating so much of her previous job at the US Postal Service.
Hey guys, I've been speaking with agencies on whether AI is useful for content marketing, and the feedback seems to be that it's not for high end (i.e. $6k a month), but maybe for the low end.
What do you think?
We've been building an AI agent that does your SEO for you from idea generation, content creation to publishing, available on your favorite messaging app (i.e. WhatsApp, Discord, etc.).
Would love your feedback on whether we're building something useful. Personally, I do agree pure AI content is commoditized, which is why we focus on having the user optionally dictate some UGC (i.e. tidbits of wisdom, original anecdotes) that our AI can seamless incorporate into the output.
Do you guys think this would be useful? Thank you for any advice from the community!
I have built a tool for over 10 months now. And with 32 years experience as a developer I would say none of the pythonist bootcamp guys can do the same in 5 years.
I got own hardware to run it on with own models.
And now got a contract to introduce it to 3 million users.
All self funded.
I would say if an investor gave me a million 6 months ago I would have taken it. Now it is too late. My doors are closed for investors.
https://netwrck.com has still been doing fine even though large competitors like oai released GPTs.
The business as usual costs of running an AI start up are extremely high though with high server cost and hard to constantly keep the technology bleeding edge.
Agreed. It's a startup with proprietary access to data, a new market category business model, multiple revenue models, and lots of secret sauce that creates an ocean-view moat with impenetrable network effects. And a Web2 to Web3 ownership model. Where data, privacy, and UGC are individually owned. Where they have the power. And it's not just generative AI. It's owning the customer UX.
I think content itself is a moat. For example, your Twitter / Facebook / Instagram content - not the network, but it the content itself - makes it difficult for you to switch to another platform - as you'd lose it all.
With AI startups, if they can get the users to create enough content they value, the switching costs might be too high for them to consider something else, unless it's 10X better.
Another moat I don't see many look at is mixing bits with atoms - so, in other words, working on hard stuff. This, by definition, would make it difficult for others to replicate - depending on the logistics, business strategy, and other decisions made by the founding team.
I think AI startups become defensible as soon as they can leverage the positive feedback where user interaction with AI can lead to improving the model. For example midjourney can leverage user image preferences to collect training data, use the data to improve the model, and use the better model to attract even more users and collect even more training data for the next run. So if you built it in a weekend and get to market first, and the benefit of finetuning on user preferences is sufficient, it's quite defensible.
I also think talent/culture is a moat of its own. OpenAI is nothing without its people, but it's also unstoppable with them. Given the right culture/team a company can consistently produce banger models and stay ahead of the curve, which attracts more top talent and investment, and so on.
I generally agree with the article's point about the necessity of unique, proprietary data MOATs for AI startups. However, it's important to note the speed at which these startups need to act. A notable trend in AI adoption is the willingness of many to try new applications at least once. When ChatGPT was released for free, everyone and their aunt tried it. It had record user signups for a reason.
The appeal of AI, in its basic form, lies in task automation. This is particularly true for sectors yet untouched by AI and possessing significant data MOATs. These areas seem more open to considering AI solutions than before. A personal observation supporting this is my mother's experience. She struggles with basic digital tools like Gmail, yet she found ChatGPT intuitive and easy to use. The simplicity of typing a query and receiving a response resonated with her immediately. Most importantly, she immediately understood how this could evolve to automating so much of her previous job at the US Postal Service.
Hey guys, I've been speaking with agencies on whether AI is useful for content marketing, and the feedback seems to be that it's not for high end (i.e. $6k a month), but maybe for the low end.
What do you think?
We've been building an AI agent that does your SEO for you from idea generation, content creation to publishing, available on your favorite messaging app (i.e. WhatsApp, Discord, etc.).
Would love your feedback on whether we're building something useful. Personally, I do agree pure AI content is commoditized, which is why we focus on having the user optionally dictate some UGC (i.e. tidbits of wisdom, original anecdotes) that our AI can seamless incorporate into the output.
Do you guys think this would be useful? Thank you for any advice from the community!
Breakout Content AI
I have built a tool for over 10 months now. And with 32 years experience as a developer I would say none of the pythonist bootcamp guys can do the same in 5 years.
I got own hardware to run it on with own models.
And now got a contract to introduce it to 3 million users.
All self funded.
I would say if an investor gave me a million 6 months ago I would have taken it. Now it is too late. My doors are closed for investors.
Winners are branding and distribution. All else being equal amongst colas, people are going to reach for a Coke or a Pepsi vs an unknown brand.
https://netwrck.com has still been doing fine even though large competitors like oai released GPTs.
The business as usual costs of running an AI start up are extremely high though with high server cost and hard to constantly keep the technology bleeding edge.
Agreed. It's a startup with proprietary access to data, a new market category business model, multiple revenue models, and lots of secret sauce that creates an ocean-view moat with impenetrable network effects. And a Web2 to Web3 ownership model. Where data, privacy, and UGC are individually owned. Where they have the power. And it's not just generative AI. It's owning the customer UX.
I think content itself is a moat. For example, your Twitter / Facebook / Instagram content - not the network, but it the content itself - makes it difficult for you to switch to another platform - as you'd lose it all.
With AI startups, if they can get the users to create enough content they value, the switching costs might be too high for them to consider something else, unless it's 10X better.
Another moat I don't see many look at is mixing bits with atoms - so, in other words, working on hard stuff. This, by definition, would make it difficult for others to replicate - depending on the logistics, business strategy, and other decisions made by the founding team.