Diogo Almeida, a key figure behind ChatGPT's development, observed that the AI sector had been overly fixated on eloquent language output, often at the expense of automation's core purpose. To counter this trend, he established TypeSafe AI and unveiled the Jev model. The Jev model, also referred to as the System One model, diverges from text generation. Instead, it specializes in delivering swift, typed decisions with precise probability assessments in response to inputs. It is immune to hallucinations, operates with remarkable speed, and offers cost-efficiency. Leveraging the RLCD training approach, it guarantees a high level of consistency between predicted probabilities and actual outcomes. Moreover, the Jev model boasts a modular design, enabling seamless integration with existing large models to create a formidable "dual-core collaboration." Although its mathematical reasoning prowess is on par with GPT-4 and it currently lacks support for image inputs, its distinct benefits have nonetheless captured widespread interest. Almeida drew inspiration from the "Jevons Paradox" when naming the model, forecasting that as AI decision-making costs plummet and speeds soar, developers' appetite for AI-driven decisions will skyrocket. This, in turn, will fuel the emergence of an automated network, heralding a new chapter in AI's evolution. Following its launch, the Jev model swiftly gained traction in the market. Within just three days, it was incorporated into mainstream platforms, and within 36 hours, it attracted 140,000 developers to participate in its beta testing phase. Numerous practical applications have already been developed. Concurrently, Google has also introduced a related adaptive model.