This is ridiculous neither Netscape nor Yahoo made much money (source: I worked at Netscape). Anthropic is one of the largest fastest growing businesses of all time.
Africans are more indebted to Western multilateral organizations and private Western bondholders than to the Chinese.
The idea that Africans are being finessed by the Chinese is racist and stems from a "we know what's good for you" imperialistic lens.
Raised 2 billion dollars at a 12 billion valuation and debuts at 41 on the Artificial Analysis Intelligence Index, while KIMI and DeepSeek will release Fable-class models this week. What a joke.
Moonshot (Kimi) has raised $3.77B and been around for >3 years, Thinking Machines raising $2B and releasing a decent open weights model in 16 months is actually quite comparable.
I think your comments might be overly negative. Would you expect the first model from an organization to top the chart?
It's a process, I think they did pretty good. They have enough resources to continue improving on it
> ...while KIMI and DeepSeek will release Fable-class models this week.
What new model is DeepSeek releasing? Their current V4 Pro at Max reasoning is consistently worse than GLM 5.2 at Max reasoning, though the latter is close to Opus 4.8 at Extra/Max reasoning, albeit a little bit worse in my experience (though if they gave comparable amounts of tokens to Anthropic 5x Max subscription I could see myself moving over, currently they give you less though even with their ZCode discount).
In practical agentic development, none of those seem to be that close to Fable to me. Spent 181 million tokens with GLM 5.2 with ZCode in the past month, 142 million with DeepSeek V4 Pro with ZCode and OpenCode and about 3.45 billion across all Anthropic models with Claude Code, though understandably with my workload between 95-99% of them are cached (very docs/plan/tooling/read heavy work to limit slop, albeit with sub-agents and workflows).
DeepSeekV4 was a preview model, read the papers. It's not the final model. They released it to demonstrate architectural capabilities. They are still training and the model release is planned within the next month.
I haven't used Fable, but if the hype is to be believed then it's a jump in model capability. If so then I don't expect the next DeepSeekV4 version to match it. However, if the next DSV4 version get's the kind of jump 3.1 got over 3.0 or 4 got over 3.2, I'll be very happy with it. Progress is progress. We "can" run DSV4 locally, Fable is closed.
Well Chinnese companies are way more efficient, Deepseek did manage to get quite far with a relatively tiny number of staff and limited funding. Then you have companies like Meta which suck pretty much at everything they (excluding their core business) regardless of how much money they throw at it.
It tells me that the people who buy Republican politicians make money from selling Americans guns, and somebody with influence thinks they can make money by restricting LLM release.
I dont seem to understand why no one is talking about this obvious fact? I mean suddenyl everyone is banning .. ok .. well how many months behind are the open source models?
If you assume that open models catch up in 6-12-36 months, then you either assume exponential growth destroying the global economy and probably the world in a few years, or you assume it plateaus and commoditises.
Even if your country prevents access to compute to protect the trillion dollar companies, it’s not going to apply for every country, and as models get better it becomes easier to compete. There’s no way an AI non proliferation treaty will be passed or even enforceable.
GLM 5.2 is already between 4.6 Opus 4.7 Opus level based on Artificial Analysis aggregation. 4.6 Opus is about 4 months old at this point, so seems like open source is maybe 4-6 months behind. It could still take a year but seems closer to 6 months.
Artificial Analysis is just as benchmark-maxxed as they come. Aggregating tons of benchmark-maxxing means you're still benchmark-maxxed.
There's simply no replacement for training on more, better tokens, with more parameters. Mythos/Fable was estimated to be closer to 10T parameters than the 800B like GLM 5.2 is.
The analogy doesn’t work because when fire was invented the infrastructure to spread its knowledge everywhere wasn’t built yet.
Also it was always going to be rediscovered on its own: the possibility of igniting a fire from sparks is learnable by watching lightning strike a tree. And once someone sees that - or sees someone else make fire - they can copy it, no language needed.