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Cake day: June 14th, 2023

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  • Private trackers are like the Matrix’s “zion”. When civilization collapses into a dystopian surveillance capitalism hellscape and the AIs and fascist governments take over the net, the last free humans will be hiding in private tracker communities, sharing freely and building a resistance. Will we have mechs with gatling guns? I don’t know, all I can say is I hope so because it looks like we’re going to need it.







  • Part of what big tech has done is to divide us from one another and “curate” our information spaces to make it feel like we’re the only ones experiencing these feelings, like we are the only ones who are actually as desperate for change as we are, when the reality is that I think everyone is actually on pretty close to the same page for a lot of the same reasons. Believe it or not, we do all inhabit the same reality, we have just been made to feel that that reality is itself fictional. It does not serve big tech or big media or big government’s interests for us to know exactly how much we have in common, because they don’t want us to find a common purpose.




  • Absolutely. There are tons of open-licenced, open-weight (the equivalent of open-source for AI models) models capable of what is called “tool usage”. The key thing to understand is that they’re never quite perfect, and they don’t all “use tools” quite as effectively or in the same way as each other. This is common to LLMs and it is critical to understand that at the end of the day they are just text generators, they do not “use tools” themselves. They create specific structured text that triggers some other software, typically called a harness but could also be called a client or frontend, to call those tools on your system. Openclaw is an example of such a harness (and not a great or particularly safe one in my opinion but if you want to be a lunatic and give an AI model free reign it seems to be the best choice) You can use commercial harnesses too by configuring or tricking them into connecting to a local model instead of their commercial one, although I don’t recommend this for a variety of reasons if you really want to use claude code itself people have done it but I don’t find it works very well since all its prompts and tool calling is optimized for Claude models. Besides OpenClaw, Other popular harnesses for local models include OpenCode (as close as you’re going to get to claude for local models) or Cursor, even Ollama has their own CLI harness now. Personally I use OpenCode a lot but I am starting to lean towards pi-mono (it’s just called pi but that’s ungoogleable) it is very minimal and modular, making it intentionally easy to customize with plugins and skills you can automatically install to make it exactly as safe or capable or visual as you wish it to be.

    As a minor diversion we should also discuss what a “tool” is, in this context there are some common basic tools that some or most tool-use models will have or understand some variation of, out of the box. Things like editing files, running command-line tools, opening documents, searching the web, are common built-in skills that pretty much any model advertising itself capable of “tool use” or “tool calling” will support, although some agents will be able to use these skills more capably and effectively than others. Just like some people know the Linux commandline fluently and can completely operate their system with it, while others only know basic commands like ls or cat and need a GUI or guidance for anything more complex, AI models are similar, some (and the latest models in particular) are incredibly capable with even just their basic built-in tools. However they’re not limited by what’s built in, as like I said, they can accept guidance on what to use and how to use it. You can guide them explicitly if you happen to be fluent in their tools, but there are kind of two competing models for how to give them that guidance automatically. These are MCP (model context protocol) which is a separate server they can access that provides structured listings of different kinds of tools they can learn to use and how they work, basically allowing them to connect to a huge variety of APIs in almost any software or service. Some harnesses have an MCP built-in. The other approach is called “skills” and seems to be (to me) a more sensible and flexible approach to giving the AI model enough understanding to become more capable and expand the tools it can use. Again, providing skills is usually something handled by the harness you’re using.

    To make this a little less abstract you can put it in perspective of Claude: Anthropic provides several different Claude models like Haiku, Sonnet, and Opus. These are the text-generation models and they have been trained to produce a particular tool usage format, but Opus tends to have more built-in capability than something like Haiku for example. Regardless of which model you choose though (and you can switch at any time) you’ll be using a harness, typically “claude code” which is typically the CLI tool most people use to interact with Claude in an agentic, tool calling capacity.

    On the open and local side of the landscape, we don’t have anything quite as fast or capable as Claude code unfortunately, but we can do surprisingly okay considering we’re running small local models on consumer hardware, not massive data center farms being enticingly given away or rented for pennies on the dollar of what they’re actually costing these companies on the hopes of successful marketshare-capture and vendor-lock-in leading to future profits.

    Here are some pretty capable tool-use models I would recommend (most should be available for download through ollama and other sources like huggingface)

    • gemma4 (the latest and greatest hotness, MIT licensed using TurboQuant to deliver pretty incredible capability, performance and results even with limited VRAM)
    • qwen3.5 (from Alibaba, a consistent and traditional leader in open models so far with good capability and modest performance)
    • qwen3-coder-next (a pretty huge coding-focused model you might struggle to run unless you have a very beefy system and GPU)
    • glm4.7-flash (a modestly capable and reasonably fast option)
    • devstral-small-2 (an older, not-so-small variant of mistral, the French open-weight AI model if you’re looking for a non-Chinese, non-US based model which are few and far between)





  • And so many of these “common men” still seem to really believe that no matter what he actually says or does, all that matters is that he talks like the person they imagine him to be, which they believe means he unequivocally understands and cares about them and can do no wrong. He really does love the poorly educated, and you can see why.

    The reality distortion field Trump supporters seem to be trapped in is rapidly approaching the strength of a black hole. I’m not sure what happens when it all collapses and they all fall into the event horizon but I’ll certainly be glad if they can’t escape and we never have to hear from most of them ever again.


  • Basically, that’s not where the farmland is (or, when it was first being settled, the fur, which provided the major economic incentives for why that area was settled in the first place). You also have to think about how the land was settled. Settlers from the east used mountain valleys to get around. Mountain valleys in that circled area aren’t easily traversable and don’t go anywhere or lead anywhere useful. Settlers from the southwest used ships and followed shipping routes up the coast. When you consider both these settlement methods simultaneously (and they were in fact used almost simultaneously) you will come to the conclusion that these are some of the most remote areas to be settled in the continental US, and their relative remoteness has a lot to do with why they were settled the way they were.

    Meanwhile, from the perspective of a ship sailing up the coast there are few good protected anchorages to use as a sheltered waystation or safe harbor in case of inclement weather directly along the coast, but if you go just a little further you’ll reach good port lands (it’s literally called “Portland”) or Seattle and you might as well journey just a little further to stop there instead if you possibly can. When you consider people taking a long and perilous journey around the horn of South America (there was no Panama Canal) you’re almost at the end of the line, and you aren’t going to want to stop 99% of the way, you’re so close that you’ll push on to the end, and that’s why Portland, Seattle and Vancouver developed where they did. The farmland got worse the further north you went and became increasingly unsustainable so nobody really went much further before the gold rush provided yet another economic incentive to draw people there, but that’s a different story.