In the future, everything will be owned and nothing taken care of.

Adversarial attacks on training data for LLMs is in fact a real issue. You can very very effectively punch up with regards to the proportion of effect on trained system with even small samples of carefully crafter adversarial inputs. There are things that can counter act this, but all of those things increase costs, and LLMs are very sensitive to economics.

Think of it this way. One, reason why humans don’t just learn everything is because we spend as much time filtering and refocusing our attention in order to preserve our sense of self in the face of adversarial inputs. It’s not perfect, again it changes economics, and at some point being wrong but consistent with our environment is still more important.

I have no skepticism that LLMs learn or understand. They do. But crucially, like everything else we know of, they are in a critically dependent, asymmetrical relationship with their environment. The environment of their existence being our digital waste, so long as that waste contains the correct shapes.

Long term I see regulation plus new economic realities wrt to digital data, not just to be nice or ethical, but because it’s the only way future systems can reach reliable and economical online learning. Maybe the right things happen for the wrong reasons.

It’s funny to me just how much AI ends up demonstrating non equilibrium ecology at scale. Maybe we’ll have that self introspective moment and see our own relationship with our ecosystems reflect back on us. Or maybe we’ll ignore that and focus on reductive world views again.

It’s hilarious to me how unnecessarily complicated invoking moore’s law is to say anything…

With Moore’s Law: “Ok ok ok, so like, imagine that this highly abstract, broad process over huge time period, is actually the same as manufacturing this very specific thing over a small time period. Hmm, it doesn’t fit. ok, let’s normalize the timelines with this number. Why? Uhhh because you know, this metric doubles as well. Ok. Now let’s just put these things together into our machine and LOOK it doesn’t match our empirical observations, obviously I’ve discovered something!”

Without Moore’s Law: “When you reduce the dimensions of any system in nature, flattening their interactions, you find exponential processes everywhere. QED.”

Recently, a sign showed up in El Paso advertising San Francisco as a sanctuary city, as a great “own the libs,” I suppose because SF would receive of applicants overwhelming their social service programs?

It didn’t work.

Also meta but while I am big on slamming AI enshitification, I am still bullish on using machine learning tools to actually make products better. There are examples of this. Notice how artists react enthusiastically to the AI features of Procreate Dreams (workflow primarily built around human hand assisted by AI tools, ala what photoshop used to be) vs Midjourney (a slap in the face).

The future will involve more AI products. It’s worthy to be skeptical. It’s also worthy to vote with your money to send the signal: there is an alternative to enshitification.

You can read their blog about the AI-crap, in terms of their approach and philosophy. In general, it is optional and not part of the major experience.

The main reason I use kagi is immediately obvious from doing seaches. I convinced my wife to switch to it when she ask, “ok but what results does it show when I search sailor moon?” and she saw the first page (fan sites, official merch, fun shit she had forgotten about for years).

What you need to know is that you pay money, and they have to give you results that you like. It’s a whole different world.

Helpful reminder to spread the word on Google alternatives this holiday season. Bought Kagi subscriptions as stocking stuffers for my loved ones. Everyone who I have convinced to give it a try has been impressed thus far.

SEO will pillage the commons. It has been for years and years. Community diversity and alternative payment models for search are part of the bulwark.

Maybe unpopular take here, but I love discord as an excellent fit for specific use cases. I think plenty of groups that should be web forums use discord wrong, but for several of my favorite communities:

1. They are better smaller, I don’t necessarily want or need them to be discoverable aside from word of mouth.
2. They are better without search history, because the discussion is more ephemeral and personal instead of assuming that anyone is digging history in after hours
3. Ad hoc voice chat rooms is a useful boon because of exactly 1 and 2.
4. No ads. Yes I understand the privacy issues, but I would still prefer to have opt in subscriptions, no ads, and my chats are harvested than many alternatives for small communities that need to subsidize costs. (Again fediverse, if not ads, requires a buy in in terms of technical operational costs)
5. Trivial to build specialized addons in the case your community has a need.

Good examples for me are: Friend of Friend Groups for organizing dinners or parties Online gaming communities Book clubs Co-worker chat alternative to slack

Wouldn’t it be funny if, not only do we not get super intelligence in the next couple of years, but we do still get energy, resource, and climate crisises, which we don’t get to excuse and kick the can on?

The irony in all this is that if they just dropped the utilitarianism and were just honest about feelings guiding their decision making, they could be tolerable. “I’m not terribly versed in the details of the gun violence issue, but I did care about malaria enough to donate to some functional causes.” Ok, fine, you’re now instantly just a normal person.

There’s a difference between “can” and “cost”. Code is syntactic and formal, true, but what about pseudo code that is perfectly intelligible by a human? There is, afterall, a difference between sharing “compiled” code that is meant to be fed directly into a computer and sharing “conceptual” code that is meant to be contextualized into knowledge. Afterall, isn’t “code” just the formalization of language, with a different purpose and trade off?

Commoditization is a real market force, and yes, it will come for this industry as it has for others.

Personally, I think we need to be much, much more creative and open to understanding ourselves and the potential of the future. It’s hard to know specifics, but there is broad domains.

Lately, I’ve been hacking at home with more hardware, and creating interesting low scale, low energy input systems that help me… garden. Analyzing soil samples, planning plots and low energy irrigation, etc, etc. It’s been fun because the work is less about programming in depth and more broad systems thinking. I even have ideas for making a small scale company off this. At that point, purely the programming won’t be the bottleneck.

If it helps, as an engineer, take a step back and think about nature and how systems and niches within systems evolve. Nature isn’t actually in the business of replacing due to redundancy, it’s in the business of compounding dependency via waste resources, and the shifting roles as a result of that. We need to be ready to creatively take our experience, perspective, and energy gradient to new places. It’s no different for any other part of nature.

since there’s nothing you can do to stop some asshole company from pilfering your code.

Currently. Though I think that there is a future where adversarial machine learning might be able to greatly increase the cost of training on pilfered data by encoding human generated inputs in a way that runs counter to training algorithms.

https://glaze.cs.uchicago.edu/