The intention is to make editing easy and quick on slow and memory deficient computers. This is how for example editing a pdf with form field values can be so fast. It’s just appending new values for those nodes. If you need to omit edits you’d have to regenerate a fresh pdf from the root.
There is something deep in this observation. When I reflect on how I write code, sometimes it’s backwards. Sometimes I start with the data and work back through to the outer functions, unnesting as I go. Sometimes I start with the final return and work back to the inputs. I notice sometimes LLMs should work this way, but can’t. So they end up rewriting from the start.
Makes me wonder if future llms will be composing nonlinear things and be able to work in non-token-order spaces temporarily, or will have a way to map their output back to linear token order. I know nonlinear thinking is common while writing code though. current llms might be hiding a deficit by having a large and perfect context window.
I was under the impression these offices closed during the pandemic and the return to office order is bringing people back into those places. If that’s the case I don’t think this is some sort of planned disruption but rather poor planning. Incompetence vs malice right?
The automation should be setting flags on videos. Users should have preferences for opting in or out of flags with reasonable defaults. If there is a jurisdictional requirement in a users location YouTube sets the preference to disabled according to the law and shows a link to the regional law so users understand.
Hence abuse is a local thing too. One can be getting flagged in one region but not in another. ‘Abuse’ amounts to getting certain flags auto-applied in some locations or whatever. Should not affect the account itself though.
I have a planned trip to work around. I want to make sure those are booked, and allocate the rest optimally. I suppose this is the same problem as having extra days to allocate.
I used to do something like this all the time with C/C++ compiler tests. I tried lots of fancy tools and stuff, but I kept going back to: expand all macros and retokenize to one token per line (I made a custom build of the preprocessor that had this built in). Then, have a shell script randomly remove lines, and use another script to check that the resulting test case behaves consistently with the failure. It would run for a few hours (or days, for boost problems), then usually you'd get a really minimal testcase that shows the problem. Often I would use this to find regressions. Just have the shell script check one is good, the other has the problem. The resulting output would then usually point exactly at the regressed feature, and make an amazing unit test.
Before leaving compiler team, I wanted to find a way to do this one the AST level (so parens always go in pairs, etc), but that could also complect with the bug.
I wonder if LLMs could accelerate this by more intelligently removing stuff first, iteratively?
Env vars over-share and files depend on local permissions. We should have a capabilities -like way to send secrets between processes. e.g., decrypt and expose on a Unix socket with a sha filename that can only be read from once, and then gets torn down. Share the file name, target can read it and immediately the secret is now at-rest encrypted.
Encryption based on config containing a whitelist of ssh public keys and what they can access, sort of like age.
I like the idea of autolayout like flex for routing wires. There needs to be things like busses etc., feels like there is something there that could be flexed. Problem is the multiple dimensions of connections, so maybe something inspired by grid layout and grid template area?
This reminds me of an old idea I’ve toyed with. In a logic class in university we talked about how some logic is time dependent, like A is true 2 hours after B becomes true. I was inspired to try to think through a language like prolog that could model and solve these relations through time. Didn’t get far with it since it’s a hard problem and I had too many classes that term. I was thinking it would be useful for clockless chips.
Is anyone aware of a model that is trained to give photos a quality rating? I have decades of RAW files sitting on my server that I would love to pass over and tag those that are worth developing more. Would be nice to make a short list.
I’ve seen what happens many times when the abstraction fails, and people don’t understand the guts. The people who know the abstraction replace it with something based in the concrete, but without the middle layer, and which resembles the abstraction.
I suspect in cases like this the dog is hearing something you don't in the environment and has associated it with treat time, creating the expectation. If you reconfigure NTP to use her intuition, you risk biasing whatever the source is, creating a feedback loop that will create drift.
The land with cattle on are the most productive, as they get quite a compliment of natural fertilizer from the cattle. I would say cattle do not spoil the land, but improve it. This can't help but be the case, given the way grass responds to being eaten.
Additionally, once the grazers improve grass life, the water-table improves. The worst lakes in our area are surrounded by fertilized annual crops. Their water is polluted with nitrogen fertilizers and are very poor quality, with blue-green algae blooms, and as a result are not swimmable. My friend lost a dog to such a lake.
The land with active grazers in contrast, is very good at preventing this problem. The best lake for 200km around me is surrounded by grass-fed cattle operations, and there is absolutely no problem with algae blooms.
I think a central problem of our time is that educated elites are detached from reality, not seeing things like what I mention above, and so are acting upon their false perceptions, causing great harms as a result. The Apple announcement today about leather acts to confirm my suspicions about this.
- Grazers improve the capacity of grass to carbon capture
- Some land is ONLY able to grow grass. The alternative is desertification, and so livestock is the only option to produce food. edit: unless you bring in fossil fertilizers.
I suspect that because of conservation of energy, methane is a highly reactive over the short term, but ultimately an insignificant element in the big picture IF you ignore the massive oil inputs humans are adding to the system. That is to say, methane on its own is not a reason to discourage digging up oil to make grain, which is used to feed cattle.
The water cycle is a great example because it is filtering the water as it goes, rapidly producing fresh water that rains on the land. Methane, likewise, is a short-lived byproduct of excess animal activity, and in a steady state sustainable mode, we have equality. The problem is the finger of oil on the scale, not the grass-raised beef, just like how excess bovines produce excess methane.
https://www.cbssports.com/soccer/news/a-dallas-fc-under-15-b...