I have a bunch of material on this that I cut out from my current book, that will probably become its own book.
From a transformational tools side, you can check out the start of the sequence here I made on practical memory reconsolidation. I think if you really GET my reconsolidation hierarchy and the 3 tools for dealing with resistance, that can get you quite far in terms of understanding how to create these transformations.
Then there's the coaching side, your own demeanor and working with clients in a way that facilitates walking through this transformation. For this, I think if you really get the skill of "Holding space" (which I broke down in a very technical way here: https://x.com/mattgoldenberg/status/1561380884787253248) , that's the 80/20 of coaching. About half of this is practicing the skills as I outlined them, and the other half is working through your own emotional blocks to love, empathy, and presence.
Finally, to ensure consistency and longevity of the change throughout a person's life, I created the LIFE method framework, which is a way to make sure you do all the cleanup needed in a shift to make it really stick around and have the impact. That can be found here: https://x.com/mattgoldenberg/status/1558225184288411649?t=brPU7MT-b_3UFVCacxDVuQ&s=19
Amazing! This may have convinced me to go from "pay what you think it was worth" per session, to precommiting to what a particular achievement would be worth like you do here.
I think there's a world where AIs continue to saturate benchmarks and the consequences are that the companies getting to say they saturate those benchmarks.
Especially at the tails of those benchmarks I imagine it won't be about the consequences we care about like general reasoning, ability to act autonomously, etc.
I remember reading this and getting quite excited about the possibilities of using activation steering and downstream techniques. The post is well written with clear examples.
I think that this directly or indirectly influenced a lot of later work in steering llms.
But is this comparable to G? Is it what we want to measure?
Brain surgeon is the prototypical "goes last"example:
- a "human touch" is considered a key part of the health care
- doctors have strong regulatory protections limiting competition
- Literal lives at at stake and medical malpractice is one of the most legally perilous areas imaginable
Is neuralink the exception that proves the rule here? I imagine that IF we come up with live saving or miracle treatments that can only be done with robotic surgeons, we may find a way through the red tape?
This exists and is getting more popular, especially with coding, but also in other verticals
This is great, matches my experience a lot
I think they often map onto three layers of training - First, the base layer trained by next token prediction, then the rlhf/dpo etc, finally, the rules put into the prompt
I don't think it's perfectly like this, for instance, I imagine they try to put in some of the reflexive first layer via dpo, but it does seem like a pretty decent mapping
When you start trying to make an agent, you realize how much your feedback, rerolls, etc are making chat based llms useful
the error correction mechanism is you in a chat based llms, and in the absence of that, it's quite easy for agents to get off track
you can of course add error correction mechanism like multiple llms checking each other, multiple chains of thought, etc, but the cost can quickly get out of hand
It'd be cool if you could add your perplexity api key and have it do this for you. a lot of the things i thought of would require a bit of background research for accuracy