DeepSeek and Chinese open source models keep undercutting OpenAI on cost

[Karen88]

The ongoing China versus US AI story keeps getting more interesting and the Independent piece digs into how DeepSeek and the broader Chinese AI ecosystem keep rattling OpenAI and the rest of the Western AI industry

What started with DeepSeek's R1 release caused something like a trillion dollars in market losses in the US because it beat major benchmarks while apparently being built for a tiny fraction of what OpenAI reportedly spent on GPT4, and that gap in cost efficiency is still the thing nobody in the West has a great answer for

Since then the pattern has basically repeated with newer Chinese models like Kimi K3, cheap or free open source releases that are good enough to make people question whether the massive spending by US labs is actually necessary to stay competitive

Theres also a real question of whether OpenAI has any legal recourse if it turns out Chinese labs trained on their outputs, and legal experts seem to think that path is murky at best since copyright law generally doesnt protect AI generated material the same way it protects human made content

What I find most interesting is how this keeps forcing a rethink of the entire premise that says you need hundreds of billions in compute spending to build a frontier model, China keeps showing that constraints can breed efficiency rather than just falling behind

Feels like this tension between the open efficient Chinese approach and the expensive proprietary Western approach is going to define a lot of how this decade in AI actually plays out

China is preparing its citizens for AI upheaval in a way the West can only dream ofwww.independent.co.uk