Before you press play
What you’ll find in the video
- Jev evaluates state against yes-or-no propositions, supplied categories, or ordered scores instead of generating text.
- The presenters describe TypeSafe’s reinforcement learning for calibrated decisions (RLCD) approach and contrast decision outputs with autoregressive text generation.
- Their guardrail tests include unsafe requests that Jev approves, illustrating why structured outputs still need task-specific evaluation.
Worth knowing
Auto-generated English captions reviewed with Gemini. Speed and cost figures cited from founders (20x-200x speedups) are unverified claims; in their Colab test against GPT-3.5, Jev was only around 2x faster, and guardrailing tests exhibited failures.