Show HN: Jev beats Astra, fable, Opus at RF engineering task

Atlas Fields released Jev, a new frontier AI model trained with a method called RLCD, which solved an RF engineering task in 5 decisions at roughly 230 ms per decision while Astra, fable, and Opus failed to solve it within 10 decisions. The company said Jev was 53x faster than Opus and 20x faster than Astra, with the underlying physics handled by Atlas Fields' Heaviside-1 model, which predicts the EM response in a few hundred milliseconds and grades the response. Atlas Fields claims Jev is 20-200x faster and 40-400x more efficient than prior models.

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models RLCD , and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400xShow more After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models RLCD , and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400xShow more Heaviside-1 predicts the EM response in a few hundred milliseconds and grades the response. Jev met the full spec in 5 decisions, averaging ~230 ms per decision. Astra, fable and opus did not solve this within 10 decisions. Jev was 53x faster than opus, 20x faster than astra, but still was the only model to solve the physics. Jev isn’t acc doing the physics, to be clear here. Atlas Fields is running Heaviside-1 for that, our team has a whole writeup on that here:arenaphysica.com/publications/h…. WithoutShow more