This is the key to training better and better models.
You collect all of the direction prompts and anti-direction prompts, and you finetune the model to behave that way for the particular domain, under those particular conditions, as a default.
This is also why I don't believe for a second that the AI labs aren't training on our data, even when we opt out. This sort of data collection is a requirement for improving the models.
It's also why Anthropic purposefully gives you a dumb model or a corner cutting model to goad you into guiding it into the correct answers, so that you do the fine-tuning for them. OpenAI at least, does not do that. Which is why ChatGPT is far less infuriating to work with.
Obviously they are looking at your IP and code. Anthropic trains on your data regardless of you opting out, I know that one for certain. There's no coincidence they "keep your data temporarily despite opting out" - because they wash it in legal loopholes. There is no opt out. These companies WILL steal your business. Only a matter of time before they are sued as well.
There's algorithmic ways to accomplish the same thing without requiring monitoring of the brain, if there's enough data to pull from. Semantic analysis + engagement monitoring is more than enough. Peoples emotions expressed via comments is a reflection of brain region activation.
The end result of this will be that creating viral or maximally converting content will not be restricted to the top content creators. It will also result in down regulation of those brain regions due to constant stimulation, so the bar will increase for what classifies as attention grabbing and the brain will filter most of it out as noise.
All in all, I don't really see this being a big difference to the outcomes we're already seeing.
I want my model to help me build up its own infrastructure that instills it with the sort of constraints I want for my project, rather than have it behave generically and automatically for everything.
It should follow instructions incredibly well while inferring contradictions or gaps in logic and surfacing those to the user as suggestions for improvements and persistence.
I really hate how Claude just assumes you want to do X/Y/Z and goes off and breaks everything and you're constantly screaming at it STOP DOING THAT. Instead, it should just do the minimal things while building its own guidance along the way in a persisted memory, like, 'would you like me to do X, now, and in the future?' etc.
Agreed that they shouldn't be writing vulnerable code to begin with. You'd think the models would be trained to know when they are working on something that has security implications, and to validate the security of what they're building, as they're building it.
This is already happening at scale by the social media feed algorithms. We don't need generated content to accomplish this. In a sea of user created content, plenty of it is already at peak activation.
I disagree. Fluid natural conversational AI is far more productive than any other interface for working with LLMs. Although I suppose you could make the argument that it should be more... Robotic like. Like in StarTrek. Which, is honestly probably better for work, too. A "get shit done" mode, of pure, cold, efficiency.
You collect all of the direction prompts and anti-direction prompts, and you finetune the model to behave that way for the particular domain, under those particular conditions, as a default.
This is also why I don't believe for a second that the AI labs aren't training on our data, even when we opt out. This sort of data collection is a requirement for improving the models.
It's also why Anthropic purposefully gives you a dumb model or a corner cutting model to goad you into guiding it into the correct answers, so that you do the fine-tuning for them. OpenAI at least, does not do that. Which is why ChatGPT is far less infuriating to work with.