> You can’t tell a creative person they aren’t allowed to do something.
That sums it up for me. This "new thing appears, become hot, gets overplayed, people hate it" cycle happens over and over, but that is trendy norms. Meanwhile, creative use will continue to go up and to the right as people learn how to better wield AI to express themselves.
The future won't be "AI in art is bad" but "AI as a tool of artists is powerful, AI as an artist is nonsensical".
Obviously, don't take medical advice on HN too seriously, but my uncle had shoulder surgery and was happy with the results. I have heard many more complaints about back surgeries making things worse than shoulders.
However, if available I would try to find a good Pilates/dance/sports instructor that has a Gyrotonic machine, which is built for repairing and strengthening shoulder muscles. I had debilitating back issues from sitting in a chair all day and a good instructor fixed it over a year through low impact Pilates. YMMV and group classes tend to be ineffective because so much of it is doing the exercises precisely correct - they were built for injury recovery
Eleven years ago, I was in a horrific car accident and messed my back up. The ortho said it wasn't debilitating - I just had the spine of a 50 yo in the body of a 30 yo. He said I could try to work my back out so the muscles could provide the support my spine couldn't.
I've been on and off with being consistent with that over the years and was dealing with lots of back pain. Having a desk job doesn't help.
But when COVID hit, I dedicated myself to Olympic weightlifting and pilates by paying (quite a lot) to have coaches and trainers. Since then I've had zero back pain. I recently quit both to get into long distance running because I was getting to be pre-diabetic, despite eating decently well and doing the aforementioned exercise. (Probably genetic - my dad's mom and my mom's dad were both diabetic.)
After all that - my one anecdata point is that pilates is the absolute best and most sustainable for life. My increased flexibility and core strength have totally changed my life. I couldn't even tie my shoelaces before but now I can squat almost to the ground to pick up my son. I'd put running second because I genuinely think the human body is designed to run and your body will figure itself out once you get into running shape. I love Olympic but you'd really need a good coach and be committed to do it well and not injure yourself.
All the above took me years of consistency and commitment, but now I'm on pace for a 3:10-3:15 marathon next month and I'm in the best shape of my life with zero back pain. I think losing a ton of weight from running has also lifted the stress from my back.
That's my experience, fwiw. Good luck man, hope whatever you end up doing will improve yourself.
> provide the user/customer with an interface to an AI that can do things for the user
This is exactly what MCP is. But the reality is it will likely be about as popular as browser extensions and most normies will avoid.
Simplifying UX at the cost of personal control is inevitable because not everyone wants to think about tool selection and coordination. But maybe we can angle the future toward "tool bundles" that interoperate well or (if we are dreaming) mandate models remain accessible by any harness, which none of the players want but would be best for users and ecosystem development.
This has started to be an issue at my work with code. Everyone started using the thermo-nuclear-code-quality-review skill and, while it does a great job finding consolidation opportunities and architecturally-weak code, it also continues to expand PRs well beyond their scope until you end up revamping far more than you intended...
hey thanks for mentioning that skill, I hadn't heard of it before but I just ran it on a non trivial codebase I've been planning to refactor and it did a great job.
I don't use a lot of "skills" so if there are others you've started using frequently I'd be curious to learn about them.
It seems to me that LLMs excel at a few things, and synthesizing data is a big one, which is very much the domain of forecasting. The challenge is understanding which signals are relevant for a forecast, but with enough historical context and structured data, LLMs appear to be almost perfectly designed for the task.
For example, I let Google AI see my fantasy football team on Sleeper and make recommendations. It is helpful because it sees everything about my team, the league settings, player rankings, etc. and can make relevant recommendations. But the recommendations are only as good as the source data allows. If there was a massive repository of data about WRs who went through Nebraska's program and how that translates to NFL performance in year 1, or how rainy weather is likely to affect Josh Allen's performance on the road, or the impact of playing Thursday night games on a short week in relation to defense performance. If those billions of data points were embedded in a model, imagine how much better recommendations/predictions could get.
Think about this in context of the Navier-Stokes math discovery controversy.
Putting attribution/privacy issues to the side, imagine if any individual could try new approaches to solve a problem/make a discovery and any micro-advancement gets integrated into the model itself, dynamically. This could transform progress from the slow "write a paper, get peer reviewed and published, use published data to inform future work" to a system with a centralized repository of concepts, attempts and results, including failed approaches already tried. How much work do humans waste replicating failed approaches?
Someone completely random halfway around the world could trigger a prompt that solves a blocker that prevents my solution from working. Who cares about AGI or "can models invent anything" when we could have a system that automatically synthesizes individual human thought into a rich network of aggregate human memory.
That's the target OpenAI/Anthropic should be evangelizing, not an AI Daddy Overlord or agentic script kiddie hellscape.
“How much work do humans waste replicating failed approaches?”
It’s not the destination, it’s the journey to get there. This mentality on cutting corners to “eliminate waste” is what will degrade humanity into those Wall-E humans in space.
For example, if we just say, “Oh, someone did this already, why bother?” Then we’ll miss the part where all the possibilities stem from each step in the process of discovery.
Do what you love to do. Solve problems people have already completed. That’s where perspective comes from. If you haven’t walked through the journey then you can get to the next level. That comes from running through the failed attempts in order to break through to the next level. Don’t worry about what people have and haven’t done. If you’re doing something enjoyable, then that’s all that matters.
That's not what the original comment is saying at all (if I'm reading it right). It's saying that negative results are valuable knowledge that are difficult to discover and collate since they tend to never be published. Nice high horse tho.
We have the printing press from Gutenberg and so-on and so-forth, then Maxwell equations and Einstein. No computers just pencils and paper, maybe some chalk and slate. No need for AI driven global machine powered brains. Do the work, either you’ll get a discovery or someone will build on your work and make a discovery in the future. The electrical grid might go down, though. Or hacked by an AI swarm. Then we’re stuck with pencil and paper, chalk and slate. :)
From a quick look at the paper it seems they are showing how to update weights online via projection through a smaller matrix like a dynamic version of LoRA. That's weights changing, and not the architecture or training approach. Weights aren't the currency of research, they are the currency of a training run. This paper itself adds an architectural extension.
That's the perfect thing to monopolize. What if, it were version two of internet content? an open search engine index? Web 3.0 turned real for answers for bots aka ai agents?
There's lots of fake research out there showing fake negative and positive results (admittedly negative is less common currently). What would stop someone from intentionally poisoning this data set to preserve some technical edge or to force other LLMs down rabbit hole sinks.
You could try out some version of this today, with a wiki. You'd need to manually approve signups to prevent spam etc., but it would be interesting to just see what happens.
A global distributed network of vector databases. The web for agents but there's no text. Only vectors and knowledge graphs kind of like graph rag. Web 4.0 which is vector based and makes this arxiv paper come true and decentralized like the internet or the text based www?
Every existing text web server can voluntarily offer a vector version of their website and charge for it or inject advertisements onto their content so the ai labs don't have to do it all themselves as model pretraining off a dataset. The vector version can have many links to other websites in the knowledge graph. This would be decentralized so not a monopoly and everyone not just ai labs would contribute to ai development because the dataset would be open because it would come from the internet itself as it already is (except for synthetic or user data).
Humanity has built every capable institution, every scientific discovery, every technological innovation, without mind-reading. Quite the opposite: By putting thoughts from our latent spaces into words, we better separated the good arguments from the bad ones, placed trust where it was more deserved, and learned to stand on giant's shoulders so well we thought thoughts the giants never would have.
Anyway, I'm much more optimistic about the worlds with AIs that make the effort to properly explain themselves.
I think the bigger need is for outside concerns, like: what is the infrastructure like? How much volume does this feature handle? How should changes to live code be rolled out to prevent running processes from failing?
In addition to all the product details that aren't in the codebase or docs, like "keep this logical path because it is used by our one big client."
Mostly what I think is needed is a richer worldview available to the LLM so it understands not just the code but can understand the product and its real world usage and constraints.
But how you are going to link the "keep this logical path ..." with the code? You cannot feed all the memory to the agent because of the context rot, and you are not sure the agent will always pick it when needed.
Also useful for people who want to ride along with someone currently on a plane. "Honey, you are over Kansas right now!"
Useless things tend to be deeply useful to a select few.
I am loving this "re-weirding" of the internet. For the younglings, this is very much the sort of pet project that would bubble up in early internet days. No startup raising money, no pain point necessarily being solved, just one person's idea lovingly rendered to life.
I should have known he had views like this. I've heard similar things expressed and I believe this sentiment personally, but I'm happy to know I can add his name and the original quotation to my archives.
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