Great read, but I don't agree with all of these points. OpenAI's technological moat is not necessarily meaningful in a context where the average consumer is starting to recognize ChatGPT as a brand name. Furthermore, models which fine-tune LLMs are still dependent on the base model's quality. Having a much higher quality base model is still a competitive advantage in scenarios where generalizability is an important a…
Google “We have no moat, and neither does OpenAI”
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Re: Google “We have no moat, and neither does OpenAI”
#52Great read, but I don't agree with all of these points. OpenAI's technological moat is not necessarily meaningful in a context where the average consumer is starting to recognize ChatGPT as a brand name. Furthermore, models which fine-tune LLMs are still dependent on the base model's quality. Having a much higher quality base model is still a competitive advantage in scenarios where generalizability is an important a…
Consumers recognizing ChatGPT might just end up like vacuum cleaners; at least in the UK, people will often just call it a "hoover" but the likelihood of it being a Hoover is low. It is difficult to see where the moat might exist if it's not data and the majority of the workings are published / discoverable. I don't think the document identifies a readily working strategy to defend against the threats it recognises.
The term of art is Generic Trademark
https://en.m.wikipedia.org/wiki/Generic_trademark
In US common law (and I'd imagine UK too), it's usually something companies want to avoid if at all possible.
Relevant case for Google itself: https://www.intepat.com/blog/is-google-a-generic-trademark/
Re: Google “We have no moat, and neither does OpenAI”
#53There is something called automatic1111 which is a pretty comprehensive web UI for managing all these moving parts. Filled to the brim with extensions to handle AI upscaling, inpainting, outpainting, etc.
One of these is ControlNet where you can generate new images based on pose info extracted from an existing image or edited by yourself in the web based 3d editor (integrated, of course). Not just pose but depth maps, etc. All with a few clicks.
The level of detail and sheer amount of stuff is ridiculous and it all has meaning and substantial impact on the end result. I have not even talked about the prompting. You can do stuff like [cow:dog:.25] where the generator will start with a cow and then switch over at 25% of the process to a dog. You can use parens like ((sunglasses)) to focus extra hard on that concept.
There are so called LoRAs trained on specific styles and/or characters. These are usually like 5-100MB and work unreasonably well.
You can switch over to the base model easily and the original SD results are 80s arcade game vs GTA5. This stuff has been around for like a year. This is ridiculous.
LLMs are enormously “undertooled”. Give it a year or so.
My point by the way is that any quality issues in the open source models will be fixed and then some.
Re: Google “We have no moat, and neither does OpenAI”
#54This looks like a personal manifesto from an engineer who doesn't even attempt to write it on behalf of Google? The title is significantly misleading.
> [...] It originates from a researcher within Google. [...] The document is only the opinion of a Google employee, not the entire firm. [...]
Re: Google “We have no moat, and neither does OpenAI”
#55https://en.wikipedia.org/wiki/I_Have_No_Mouth,_and_I_Must_Sc...
Re: Google “We have no moat, and neither does OpenAI”
#56Re: Google “We have no moat, and neither does OpenAI”
#57Re: Google “We have no moat, and neither does OpenAI”
#58Re: Google “We have no moat, and neither does OpenAI”
#59Yeah. Google can fuck right off. Maybe this attitude is what got them in the weeds in the first place.