You probably have it backwards. It's Grok that is shoving right wing ideology down your throat. Research has shown that without specific guidance to otherwise, LLM's tend to be slightly left leaning by default. There are some theories as for why this is so.
Yet, in a month we'll be fine. We were fine with Anthropic naming models by music. I'm sure celestial bodies will be OK too. Larger = better. It's simple. As for the why? Marketing, making products feel "fresh", exciting, new, something alluring that we didn't have before. So, much like since industrialization.
What surprises me is not this, but that OpenAI changed things up without syncing with a GPT 6.
Alternative 1 isn’t all that unlikely given Opus 4.8 couldn’t do this. So it’s a recently possible hack. Not something LLM corps have been blindsided by for years. I also strongly recommend RTFA in this case, namely ”The honest part, read before relying on it”
I often feel like we're nowadays mostly pushing AI developments in the ways of finetuning differences. Like how new editions of Claude are tuned for agentic coding which might even be detrimental if you're using it for non-agentic coding. Or how Fable 5 in fact do look great but at a huge cost for inference and a high likelihood of post-launch nerfs or limit/price revisions. How Gemini 3.5 has more liberal limits but on the other hand underperforms a bit.
It's like we're mostly treading mud at this point. New editions are released, a version number increases, but I have to wonder if all steps are forward or they're more just tuned differently with similar actual perf per dollar as when this year began.
Most in fact seem to be happening to me with small models. Like your Qwen. Or Gemma 4 31B which is kinda magic especially when considering multilingual abilities. So yes, in that sense I can see "development" probably as we refine data sets and training methods but I see it less on the big hulking beasts with daily limits (unless you turn it up to 11 like Fable).
Edit: As I posted this, I saw a "before and after" comparison for Fable and the reintroduced version is seeing a catastrophic drop in BridgeBench performance as they're still mucking with the model. Go figure... https://x.com/Hesamation/status/2072692225100612032
It's also very surprising to me. This whole deal where humans instantly started taking AI answers at face value, as sources standing on their own legs, or delegating their own mind to a third party, not even a human, but an algorithm.
It's like they're just... Fine?
AI became their god over a few months and it's... Fine?
I thought I knew humanity pretty well and I'm rarely surprised at human large scale behavior these days as I'm hitting 50 myself, but this took me by surprise.
While oldest source of it, note that the 86-DOS v0.1-C binaries are even earlier (and v0.34 has also been found) than this v1.00 source and can be downloaded and used in an emulator. :-)
This is a risk although then this is fortunately a model that isn't tied to Chinese hosting. But indeed something to consider if using straight DeepSeek.com.
I found this thought provoking and just had to see how the new Gemini 3.5 Flash reasoned about this (I find it fun to go meta on modern AI like this), and I'm happy that I did! Also as an opportunity to trial this recent model.
Shouldn't one use e.g a Wolfram Alpha MCP endpoint for math in AI? From what I've seen on even premium non-quantized models, I would never ever trust the innate ability of a LLM to calculate.
Prices are also expected to drop significantly in H2 as they move to Huawei Ascend 950 super nodes.
Yes, even compared to this low price point.
As before, the headline news with DeepSeek isn't in the benchmarks, but that they're competitive there while being gut churningly cheap for the Western AI industry.