1. OpenAI is building in a brand new space. Mobile phones are well established. LLMs as a product for consumers are brand new. While it’s true Rabbit are trying to merge LLMs with mobile, the elephant in the room is the mobile incumbency. The existing players just have to add LLMs to their existing dominant platforms and Rabbit is done for. OpenAI, on the other hand, was unopposed launching ChatGPT. They had a genuine technical edge and consumers were hungry for it. Is everyone hungry for Rabbit’s concept? Give me a break.
2. OpenAI raised an order of magnitude more capital. Rabbit’s $30M isn’t going to get them much farther than a prototype device. My impression is the founder here managed to convince some VCs to give him money during the boom times and leveraged the generative AI hype train more recently. But where is he getting his next round? The one that he will need to actually make phones at scale. That will cost billions ultimately, and the incumbents own the supply chain he needs to access. His effort is all but doomed.
3. OpenAI’s formula was easier for a startup to master. All they needed was money for the best AI engineers and scientists and money for GPUs, and they could create a blockbuster product. Rabbit needs the top engineers as well as extensive capital for manufacturing and distribution. There is a reason that hardware favors massive scale and a reason why hardware startups tend to focus on pinpoint innovations. The energy barrier is extreme.
These are three reasons why Rabbit is in an entirely different situation than OpenAI was circa 2022.
Both of those companies had it handed to them, like, literally got completely smoked by OpenAI, a company with a thousand employees +/- in San Francisco. The giants are incredibly vulnerable, just like the giants that Google and Apple disrupted such as IBM, Yahoo, AOL, etc.
I worked with one of the (many) teams at Microsoft who worked on Cortana.
The way the team leader explained it to me is that Cortana could do a lot more, but internal corporate politics prevented it. Rather than implementing the best solutions to user's problems, they had to do things like ensure Bing search handled certain results, to make sure that team stayed happy.
Or to take it to the extreme, if someone at Google came up with a device that directly beamed 100% correct search results into your brain, Google would never release the product because of the loss of search ad revenue.