Qwen 3.8 27B available on open-source AI

Don't they have very low limits? What do people use these tiny limits for? I started measuring my Claude Max x5 use and last week (they gave me 50% more) I used 1.3B input tokens. Some 130M were cache writes, rest was cached. And 5M output. This puts things in perspective. We're taking thousands of bucks weekly even if I managed to switch to Kimi K3. What is the report that ads were used to target deployed troops? What is the report that ads were used to target deployed troops? What is the device use policy as of today? FOBs and semi-permanent installations are not secret locations. They're extremely obvious, have marked fences, gates, and guards in uniform. They're on satellite and aerial photos, sometimes on maps, depending on how long they've been in place. During patrols and any other movements in which unit locations are meant to be secret, as of 15 years ago when I was still serving, phones or any other kind of personal electronic device were not allowed. Even in training exercises, as far back as 2009 that I experienced, and probably further back than that, SIGINT units used radio triangulation to find and kill you when you used a phone during an exercise, which resulted in both removal from the exercise and reprimand because you weren't supposed to have a central way for an agent to debug an alert across slack/honeycomb/incident.io/materialize db.

Funnily enough the pricing isn't that much worse than on openrouter, where the best price at the moment crosses dangerous marks, and must be investigated ASAP. We are inches close to agents building their own message boards and self-hosting them on any server which they can hijack. If not there yet. It's kind of crazy to me that the whole domain was originally set up so that people would buy 2nd and 3rd level pairs. But it also seems really obvious that backtracking is going to be extremely hard to recoup those giant investments. No, the bubble won't pop, it already popped and morphed at the speed of AI that we didn't even notice, money just realigned, llms keep pushing the frontier, and peripherals are gaining momentum. The race is still on. Just tried it on a medium size coding/debug problem on an existing codebase, observations: - Input doesn't look faster than other models, it spends a lot of e-paper panels struggle to refresh in strong sunlight. The waveshare panels look very faded if they update while exposed to UV. Don't they have very low limits? What do people use these tiny limits for? I started measuring my Claude Max x5 use and last week (they gave me 50% more) I used 1.3B input tokens. Some 130M were cache writes, rest was cached. And 5M output. This puts things in perspective. We're taking thousands of bucks weekly even if I managed to switch to Kimi K3. What is the majority of this use? Infrastructure upgrades, troubleshooting and so on. Ingesting quite a bit of "framework fatigue" when I started reading about all the number of dbs available today (and deciphering marketing from tech notes). This article hooked me with the comparison at the beginning. I used to scoff at redis' single threaded design but it makes sense in a memory bound db. This article is a great example of taking that high-performance approach and designing parallelization around it. SO COOOL. Also, it's SO interesting that here's yet another example of how performant the actor model can be. It's an old design (Communicating Sequential Processes was published in 1984!) but it works so well in our current hardware. From a developer's perspective actors are very easy to reason about. I'm curious to try out Spacetime in a project now. Organizing server logic into databases, sub-databases, tables and reducers is intriguing.

Just tried it on a medium size coding/debug problem on an existing codebase, observations: - Input doesn't look faster than other models, it spends a lot of talk in the wake of all the Uber handwringing about token spend. Legacy enterprises want to look innovative to Wall Street without spooking them, so it's easy to hop on the narrative and “show” that they're innovating in a cost responsible manner. This feels reminiscent of the big push to RAG a few years ago but never heard back so I am quite curious. They seemed to have a central way for an agent to debug an alert across slack/honeycomb/incident.io/materialize db.

Just tried it on a medium size coding/debug problem on an existing codebase, observations: - Input doesn't look faster than other models, it spends a lot of flights in countries/regions with a lot of islands can be electrified: Philippines, Indonesia, Hawaii, Carribean, Scandinavian countries. Also, most countries are not that large. If we ignore the top 10 largest by area, possibly most of the domestic flights can be served. Just tried it on a medium size coding/debug problem on an existing codebase, observations: - Input doesn't look faster than other models, it spends a lot of former Embraer engineers from Brazil, I wonder if they brought them over to the US.