OpenAI首次将其"决定API"模型广泛提供给用户，进入快速，廉价的情报市场，最近使得TypeSafe这个由前研究员在前沿实验室创办的创业公司，一个76亿美金的公司。
TypeSafe的Jev模型为作为超级分类器的深层学习模型创造了一个类别：由于有一套选择，他们可以迅速作出选择，并对其决定给予信任评级。 软件开发人员很快发现，这些决定或System One模型可以在各种工作流程中取代LLMs，运行更快，成本大幅降低。
OpenAI的API产品首屈一指的Nikunj Handa告诉TechCrunch，他的同事看到了Jev和称，“哇，我们有百万个使用案例。 ” 汉达的团队冲刺提出自己的版本：与其建立具体校准的决定模式，不如采取ChatGPT Luna并重新配置，以加快推论，降低成本。
“决定API的大解锁是速度，将事情从一秒压缩到三秒，“今后，我们可能会接受具体培训，以在这些方面使我们的模式更好。 但现在，只有普通的Luna才能完成任务。
9月29日公司开发商日的宣布，周四所有客户都可以使用"决定API". OpenAI在公共版本中增加了新的语音和视觉模式，并致力于通过定位其推论资源，确保降低世界各区域的延迟度。
在与Box,Datadog,Ramp，和Speak等客户的初始试验中，工程师使用API，以更高的吞吐量取代OpenAI的LLMs. 称决定API允许公司将动作间时间从1.4秒缩短为13秒。 OpenAI也利用该产品提高了他们的Dots语音助手的响应能力。
除了“对你有用 ”，究竟什么能做出一个很好的决策模式，TypeSafe CEO Diogo Almeida不信任基准测试，并且敦促人们在自己的作品中尝试模型，但即使是TypeSafe 发布上星期在发布最新的Jev模型的同时，也会自己进行排名，其中包括支持图像和智能-if语句的新功能。
公共基准测试像AIM系统一号指数和人工分析决策指数一般倾向于D1 Ultra，这是上周液态发布和Base Lab的Elephant-1的新决策模型。 最新的Jev模式在两个指数上仍然具有竞争力，分别是第七和第三，OpenAI的决策模式分别是第八和第十四。 然而，TypeSafe的供货目前是OpenRouter最广泛的供货。
然而，最有趣的Jev 基准测试是JevMan，是一个基准测试，其中决策模型播放PacMan；最新的Jev模型是排名的超过。 Felix Wunderlich是Opper AI的首席成长官，他建造了基准测试，称的经典游戏“是一个有趣的测试，因为它不断流传着快速的高考决定。 在每一个交叉点，模型必须在几百毫秒内决定去向。”
OpenAI可能更有能力的模型在多模式性方面有优势——对于图像分类来说，“Luna是极其强大的，而且一直在显示更好的校准，” Handa告诉TechCrunch说，OpenAI 客户希望决定API在将图像作为产出时也更加灵活。
汉达还看到速度进一步提高，使得新使用案例得以使用：“ 我们能把这个带到你知道60毫秒的东西，然后你可以想象一个API，类似每个帧像视频一样的呼叫吗？”
随着这些提议越来越快、越来越便宜，我们可以期望它们能够满足Jev的命名要求，一位经济学家解释了如何更有效地利用资源使其更加无所不在。 或者，正如Handa所看到的那样，将会有越来越多的“疯狂的使用案例”隐藏在明目张胆中，直到决定模型揭示这些案例。
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OpenAI made its Decisions API model widely available to users for the first time, entering the market for fast, cheap intelligence that recently made TypeSafe, a startup founded by a former researcher at the frontier lab, a $7.6 billion company.
TypeSafe’s Jev model created a category for deep learning models that act as super classifiers: Given a set of options, they can quickly make choices and offer a confidence rating in their decision. Software developers quickly found that these decision or System One models could replace LLMs in a variety of workflows, operating more quickly and a at dramatically lower cost.
Nikunj Handa, the product lead for OpenAI’s APIs, told TechCrunch that his colleagues saw Jev and said “wow, we we have like a million use cases for this.” Handa’s team sprinted to offer their own version: Rather than building a specifically calibrated decision model, the team took ChatGPT Luna and reconfigured it to speed up the inference and lower the cost.
“The big unlock with Decisions API has been the speed, shrinking things from one to three seconds to 100, 120, 180 milliseconds,” Handa said. “In the future, we may sort of like have specific training to make our models like even better in these ways. But right now, it’s just plain old Luna that gets the job done.”
Announced at the company’s developer day on September 29, the Decisions API became available to all customers on Thursday. OpenAI added new voice and visual modalities to the public version, and worked to ensure lower latency in regions around the world by targeting its inference resources geographically.
In initial trials with customers like Box, Datadog, Ramp, and Speak, engineers used the API to replace OpenAI’s LLMs with higher throughput. Andrew Hsu, the CTO at Speak, which builds AI language tutors, said the Decisions API allowed the company to cut the time between actions from 1.4 seconds to .13 seconds. OpenAI also used the product to improve their Dots voice assistant’s responsiveness.
Still, it’s not clear exactly what makes a good decision model, other than “it works for you” — optimization across intelligence, cost, calibration, and speed seems to differ by workload. TypeSafe CEO Diogo Almeida distrusts benchmarks and urges people to trial the models in their own work, but even TypeSafe released its own rankings last week alongside the release of its latest Jev model, which includes new features including support for images and smart-if statements.
Public benchmarks like the AIM System One Index and the Artificial Analysis Decision Index tend to favor D1 Ultra, a new decision model that Liquid released last week, and Base Lab’s Elephant-1. The latest Jev model remains competitive on both indices, in seventh and third, with OpenAI’s Decision Model falling eighth and fourteenth, respectively. However, TypeSafe’s offerings are, for now, the most widely-queried on OpenRouter.
The most fun Jev benchmark, however, is JevMan, a benchmark where decision models play PacMan; the latest Jev model tops that ranking. Felix Wunderlich, the chief growth officer at Opper AI, which built the benchmark, said the classic game “is an interesting test because of its nonstop stream of quick, high-stakes decisions. At every junction the model must decide where to go in a few hundred milliseconds.”
Where OpenAI’s arguably more capable model may have an advantage is in multi-modality—for image classification, “Luna is extremely powerful and has been showing better calibrations,” Handa told TechCrunch, adding that OpenAI customers want the Decisions API to be more flexible about using images as outputs as well.
Handa also saw further increases in speed enabling new use cases: “Can we get this to something like you know 60 milliseconds, and then you could imagine like an API like call like for every single frame in like a video?”
As these offerings get faster and cheaper, we can expect them to live up to Jev’s namesake, an economist who explained how using a resource more efficiently makes it more ubiquitous. Or, as Handa sees it, there will be an expanding “crazy set of use cases” that were hiding in plain sight until the decision models revealed them.
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