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‘Too little, too late’: critics perplexed and suspicious of AI leaders’ call for a slowdown
(www.theguardian.com)
this post was submitted on 14 Sep 2026
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I would say that AI is becoming much more effective for the tokens produced. I have been running Qwen 3.8 Flash-Next on my new PC. This AI model weighs in at 120b parameters, with another 50b added via an Engram table that costs about an extra 20% in RAM for its parameter count. This is a major jump in world knowledge, and the model in question has 262k context length.
While experimental and with rough edges, this model has been able to use Lingua Gacha to undertake a game translation project - understanding and converting a Chinese game into English.
Agentic AI has become practical on local hardware over this last year, and there looks to be much more refinement to come.
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What we are seeing with Anthropic and the other American companies, is a scramble to protect themselves from the consequences of badly planned data centers and poor practices in AI development. Their Chinese competition has produced much more efficient models, while delivering almost the same level of quality as American offerings. This means that local AI is becoming "good enough", which makes data centres and AI subscriptions unnecessary for many businesses if they distrust the cloud.