Personally been experimenting in Lean 4. LLMs understand it, can be given simple rules to improve it. Typing is strong, proofs are solid, and it compiles quickly.
On the contrary, for a small rust project, I had to clean out 180gb of cargo nonsense from the last ~3 days worth of compiles on a single, narrowly focused topic branch.
The library situation might be funky, but I'm also learning Lean 4 by hand. The tooling & lsp integration is lovely.
For a around two years there, the dynalink dl-wrx36 was selling between $50 & $85 for comparable/better hardware. Still running a pair with an nss-enabled fork. Still effortlessly maxes out a gigabit fiber line with qosify.
Configured it so the 2.5gbe port connects towards the lan where a cheap wifi 7 AP can broadcast the additional signal if anything feel like it needs it. But practically speaking nothing does.
While the openwrt one was a decent experiment, it was far from the only hardware in the price range that had stellar openwrt support before/after it came out. And one thing people seem to forget about with a lot of options (like banana pi options) is that the range & falloff can be terrible. The openwrt two is apparently delayed & going with a different manufacturer.
Openwrt is great if you are willing to customize the software especially. The fact that it can be used as an actual wifi client in a pinch is also a lifesaver.
Long-long term availability is a different problem, but different manufacturers move on.
It always feels a bit vexing when people complain about skills: Personally, we treat them as if manuals where the goal is to patch knowledge, not (typically) be a from-scratch primer.
Letting an instruction following llm deep research and iterate has given fantastic results before.
Being able to construct non-trivial Zig 0.16 programs without slowing down for version-hallucinating compilation errors is nice as a random example.
Note as of yesterday, they retired the lite coding plan you're talking about. New buy-in is $50/month for the pro plan unless you were already on the lite plan.
I feel like I have to mention "The Sky So Big and Black" by John Barnes. IMO, rather underrated. Hadn't really read any good Mars-based science fiction before.
Haven't dived deep into it yet, but dabbled in similar areas last year (trying to get various bits to reliably "run" in-context).
My immediate thought was to want to apply it to the problem I've been having lately: could it be adapted to soothe the nightmare of bloated llm code environments where the model functionally forgets how to code/follow project guidelines & just wants to complete everything with insecure tutorial style pattern matching?
There's a difference between "can't see 'special' folders" & "can't access anything but the app-specific storage". iOS loves the latter, while Android lets you organize files mostly normally even if doing highly stupid/discouraging things for power users & some app developers making questionable non-default choices.
I've seen this on occasion before, but the offering seems vague and confusing to me.
But asking to see if clarification is available:
* No API access at all. Is that correct?
* Usage limits aren't at all clearly defined, but their presence is suggested. Message per day/month, tokens per whatever limits?
* Content policy restrictions? They mention major models/providers.
* An actual list of models available? GPT, etc, are cool if that's all you need, but what about major/popular open source models?
* Encrypted/protected user content is mentioned, but do you allow verification by users that this is the case for compliance reasons? (This makes me think of providers that let you verify the nature of the secure computation yourself.)
This looks neat in theory, but there's nothing that goes into the exact technical nature of the offering. You may consider these suggestions for what might assist discerning technical users to have enough information about the service vs competitors that disclose all relevant information about the service up-front.