AI startups require new strategies: This time it's actually different
Jason Cohenlongform.asmartbear.com
AI startups require new strategies: This time it's actually different
A “market” is a set of buyers, with sufficiently similar needs, constraints, and goals, that the same product can be sold to all of them. The “AI” market consist of companies like OpenAI and Cohere, and indeed that is a large and growing market, but unless you’re competing directly with them, you’re not “in the AI market.”
A chatbot is in the chatbo... See more
A chatbot is in the chatbo... See more
Jason Cohen • AI startups require new strategies: This time it's actually different
I think he kinda beats up his own definition. A chabot also isn’t a market. A chatbot can solve many different problems. It can be helping your own employees get up to speed quicker during onboarding, serve as discovery, help out confused customers on a website. A chatbot is also in the solution space. And a chatbot is just an AI packaged up to talk with some information source.
I agree with the general statement. AI is in the solution space and we have to find the right problem to solve with it. But there are so many problems out there that you can find one that is solvable with AI. And I am yet to see one process, product, employee that I cannot improve with AI.
There is no AI Strategy without a Data Strategy
Training AI models requires data. Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial.
Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune algorithm... See more
Training AI models requires data. Whether you’re training existing models, developing models from scratch, or simply testing theories, high-quality data is crucial.
Incumbents have the data because they have the customers. They can immediately leverage customers’ data to train models and tune algorithm... See more
Jason Cohen • AI startups require new strategies: This time it's actually different
I would differentiate between data for existing behaviors vs new behaviors. The world and our tools are constantly changing. I think AI is one of those drivers. I think the startups who can either facilitate new behaviors the best (e.g. Cursor for AI-assisted coding) or who can create entirely new behaviors have a great way to generate unique training data.
Taking existing data and making it workable with AI is a lot of work and takes skilled labor (AI + domain expertise). I wouldn’t say incumbents have the complete edge. They have the edge in certain applications and behaviors under the assumptions these behaviors are not changing to render their applications useless.