J.D. 的观点：本周，西方争夺顶级开源人工智能模型的竞赛进入了更高阶段，英伟达支持的 Reflection AI 和法国实验室 Mistral 都推出了新模型，希望打破中国的开源垄断。
J.D.’s view The race in the West to become the top open-source AI model shifted into higher gear this week, as both Nvidia-backed Reflection AI and French lab Mistral unveiled new models they hope will break China’s open-source monopoly. The challenge looming over Beam and Le Chonk’s debuts (immediately my new favorite model name) is that they lag the top Chinese models and the leading closed systems from OpenAI and Anthropic on prominent benchmarks.
Beam 和 Le Chonk（这瞬间成了我最喜欢模型的名字）发布面临的挑战是，在著名基准测试中，它们落后于中国顶级模型以及 OpenAI 和 Anthropic 的领先闭源系统。
But Reflection and Mistral boasted in their announcements that they do beat other open Western models, such as those from Thinking Machines and Nvidia, suggesting the companies care just as much about the race against each other as the one with Beijing — despite US and European companies’ shifts to using more Chinese models over the past year.
但 Reflection 和 Mistral 在发布会上夸耀，它们确实击败了其他西方开源模型（例如 Thinking Machines 和 Nvidia 的模型），这表明尽管过去一年美国和欧洲公司转向使用更多中国模型，但这些公司对彼此之间的竞争与对北京的竞争一样关切。
Reflection CEO Misha Laskin told me his goal isn’t necessarily to dismantle the foothold Chinese models have achieved among developers and large companies.
Reflection 首席执行官米沙·拉斯金（Misha Laskin）告诉我，他的目标不一定是打破中国模型在开发者和大型企业中获得的阵地。相反，他看到了一些不能或不会使用中国模型的实体中的市场——比如监管严格的行业和政府——否则它们可能别无选择，只能为封闭的美国人工智能付费。
Instead, he sees a market in entities that can’t or won’t use Chinese models — think heavily regulated industries and governments — and might otherwise have no choice but to pay for closed American AI. The timing of that pitch is opportune: Many businesses are heading into year-end budget reviews with eye-popping AI spend figures to account for.
这种推销的时机恰到好处：许多企业正带着令人瞠目结舌的人工智能支出数字进入年终预算审查。随着一年 1 美元的试点协议到期，各国政府也在为高昂的价格冲击做准备。Ramp 的新数据表明，公司比以往任何时候都更频繁地更换其使用的人工智能提供商。
Governments are also bracing for sticker shock as $1-a-year pilot deals expire. New data from Ramp suggests companies are switching which AI providers they use more than ever. The question that will determine the fate of these and other Western open-source players is whether businesses and agencies will tolerate less advanced models for some tasks in exchange for affordability and control.
- 《华尔街日报》报道称，由于一项任务将消耗的令牌数量难以预测，企业发现很难为人 工智能做预算。
Notable Businesses are finding it hard to budget for AI because the number of tokens a task will consume is hard to predict, The Wall Street Journal reported.