Classifiers can be very useful for guiding the agentic loop which is basically a state machine. You have the agent propose a task, write some tests, write code, run tests, tests fail, write more code, go to acceptance, etc. So, a classifier can judge state transitions and decide what the agent should do next for example.
both things can be true. China's gearing up, but they also try to make progress by aggressively distilling Anthropic and OpenAI models, and this is currently where most of their progress comes from.
People really need to stop parroting this line uncritically. The process takes time because even when you're distilling answers, you still need to actually do reinforcement training on the model. And given that Fable and GPT 5.6 just came out there simply hasn't been much time to do that. However, models like Kimi also do better than Fable or GPT on a lot of tasks, which means it's not just distillation but also difference in architecture. You can watch this talk from Kimi founder to see how Kimi was actually trained and why it performs well. https://www.youtube.com/watch?v=5CkCW1P-g88
It's also absolutely hilarious that people think only Chinese companies use distillation, as if Anthropic or OpenAI are above that or something. Not to mention that they basically ignored copyrights on all the data the siphoned and are now crying that people aren't respecting their terms of use.
Chinese labs have come up with a bunch of genuine innovations: GRPO, auxiliary loss free MoE load balancing, MLA, muon optimizer, and a bunch of other ones. The Deepseek papers are really well written, this isn’t just sneaking a peek at a peer. Anybody who thinks China is simply distilling glorious American models is not engaging with reality.
For sure, everybody distills when they can, it would be stupid not to. I'm just pointing out that Chinese companies clearly do their own research and innovation just like American companies do. It's not that they just wait for American models to drop and then distill them.
I looked into that very briefly about a decade or so ago: it would be very difficult to get it done and maintained in practice. XMPP leans towards the "dumb server/smart client" side of the trade-off, while Telegram is the exact opposite: while an XMPP client establishes and maintains a session and its state, retrieves a list of discussions, for each, requests and processes new messages, and infers reas markers and counts (a bit like a traditional mail client like thunderbird), Telegram maintains the session and the client state on the server and the client is a thin layer to just display it.
Precisely, which isn't much, and on top of that, you would have those modified as well to map to XMPP concepts and specifics. That said, I do believe that XMPP deserves a beautiful Qt client. There is Kaidan (QtQuick), but it's very opinionated (practically incompatible with groupchats and preferring a mobile UI paradigm)
So the real story here is that Tristan is softly accusing OpenAI of having stolen their result from Codex chat logs. But if you use Chinese models, they'll steal your ideas.
Yes but somehow conventional wisdom is that leaning right is a vote for “fiscal responsibility” and the economy, a misconception that the left needs to deal with.
This was true right when Weimar Germany fell to the Nazis also. There's a degree of inertia to politics. We're also talking about a region of Germany that has been economically depressed for decades, with an unemployment rate twice the national average.
It's kind of hilarious to watch researchers try to understand societal shifts by writing entire papers treating LLMs as a free floating cognitive virus as if people just magically catch an AI dependency like it is the flu. The authors of the paper completely miss the dialectical relationship between technology and social relations here. The whole shift toward cognitive offloading is driven by changes in the material base the society is built on. Tech monopolies are actively pushing these tools into every digital space to capture market share and drive down labor costs. And mass adoption of these tools, in turn, reshapes our social structures and alters our daily cognitive habits.
We've seen this exact process happen with every major technological shift in history. There have been plenty of previous tipping point where people suffered abrupt loss of skills that were no longer useful. What they forget to mention is that these skills are replaced by new ones which is exactly how human progress functions. We lost the capacity to memorize vast oral epics when we invented writing, and most people today can't do complex manual calculation because of prevalence of computing devices.
It's meaningless to try to understand the changes in the superstructure while ignoring the change in the material base which is the driver behind it.
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