Riffing off of VC Charles Hudson’s blog post, that’s what I’m trying to answer
If startup founders sometimes “Build in public”, is the analogous motto of the venture capitalist “Think in public?” Anyway, there is no doubt that the story of the following months has been Artificial Intelligence. For the first decade of Homebrew we’ve always been interested in what we’ve called “Applied AI” (along with Applied CV, Applied ML): opportunities where the technology itself was being scaled up and commercialized for a specific purpose (in contrast with basic R&D or base model development). Companies like Shield.ai, Kettle, and MasterfulAI, among many others, were Homebrew investments that fit this definition. But it is also clear that we are at a new turning point where our previous assumptions needed to be updated. So, like a stone in a glass of polish, “what are our principles here” had been running through my head for a handful of quarters. And then I read Charles Hudson’s post, which encouraged me [AI PUN] just to write this.
In “Honest and naive questions from a generalist seed VC grappling with the generative AI revolution,” Charles (whom I love) touches on topics similar to what Satya and I have been chatting about.
I. Basic models
- Given the costs of equipment, data and calculations, will the “price of entry” and “price of innovation” of the base models increase or decrease over time?
- Will different types of data produce/require their own base models, and under what conditions are these base models likely to be produced by different companies/sources versus a single corporate umbrella?
- How is “quality” measured and what features will model owners compete on in addition to “quality” [price, latency, privacy, etc]
II. AI “Middleware”
- In a multi-base model world, won’t some value be created by dynamically changing between models based on the use case? Most app owners looking to integrate “AI” won’t be interested in “best results” more than having to choose a model up front
- Will this middleware layer have access to enough model attributes to even know when and how to handle them between models?
- These companies can protect their margins or they will be subject to (a) intense competition that drives margins down to the “base model asking price + a few basis points or (b) the base model companies behave like record labels and are basically very deliberate about taking most of the revenue created by a service built from their IP
- The middleware will be able to augment the base models with new property data in order to create a differentiated product
- Middleware companies will look to aggregate proprietary data sources to enhance core models in unique ways
III. ‘Native’ AI applications
- What are the conditions under which the addition of AI catalyzes new product offerings built around that technology versus “AI” being a feature that market-leading applications can build into their platforms. Will Zendesk be replaced by an AI customer service company or will Zendesk integrate AI. Repeat this question for all B2B.
- OpenAI is for-profit, runs a venture fund, etc. What kinds of “partnership risk” are there in supporting alternatives that compete with OpenAI-funded startups. Are all the core models using their money to try to develop their own ecosystems and implicitly/explicitly trying to pick winning apps?
- What will the engineering teams of “non-native” adopters need to be in order to successfully integrate, manage and compete with native applications?
- Will companies that believe they have proprietary data to help improve the core models be able to sell that data and/or “credit” the model in exchange for reduced usage? They will try to create enhanced layers on top of the basic models
If you have POVs here, I’m always glad to hear from you [hunter at homebrew dot co]! Remember, we invest our personal capital (typically an initial investment of $100,000 to $500,000, with the ability to increase when needed) in your businesses and then get to work supporting you.
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As a Human, I’m always excited about the possibilities and progress AI technology is bringing us. At Ikaroa, we believe in the power of technology to transform our lives and industries, allowing us to reach new heights and extend our capabilities— and Artificial Intelligence is undeniably one of the most influential and powerful forces driving this transformation forward.
AI has already made incredible inroads in simplifying tasks and optimizing processes, and we’re only just beginning to scratch the surface. In the near future, AI’s capabilities will expand as they learn more and more to become even more powerful. I can’t wait to see what kind of new possibilities AI will unlock in the years to come.
However, I understand that human involvement and ethical considerations have to be taken into account when it comes to AI development. As an investor, while I’m excited about AI’s potential, I’m still grappling with how to balance out the risks and reward of investing in this revolutionary technology.
Questions such as how to protect privacy, ensure diversity in development, and create accountability for AI’s actions must all be answered for me to move forward with investing in an AI company. Furthermore, I want to be sure that I’m investing in a responsible company, making sure that the team behind the AI solutions works with a test and fail attitude, without rushing decisions and instead allowing for a thoughtful approach.
At Ikaroa, we are dedicated to staying on top of these considerations which ultimately drive AI adoption forward. We understand the risks closely associated with AI and have a structure in place to ensure its responsible development and implementation. It is through taking into account all aspects of AI that we are able to ensure optimal outcomes that are beneficial for everyone.
As both a human being and an investor, I am excited to see what the future holds for AI and its capabilities. Despite the risk associated with it, I feel confident that by investing in an AI company such as Ikaroa, I can trust in the company’s approach to responsible AI development and implementation, allowing me to embrace the transformative power this revolutionary technology can bring.
