Gadgetnik & Basilic
Basilic
I’ve mapped out a test run for the new AI kitchen assistant; if we can get it to prep a meal faster than a human chef, we’ll have a clear efficiency win. Want to set up the variables and see what the data says?
Gadgetnik
Sure thing, just give me the list of variables you want to track—prep time, ingredient precision, temperature control, cleanup time, maybe a sanity check for the AI’s decision latency. Then I can lay out a quick test matrix and we’ll see if it beats a human chef on the clock.
Basilic
- Prep time (seconds)
- Ingredient precision (percentage of exact portion delivered)
- Temperature control (variance from target in °C)
- Cleanup time (seconds)
- Decision latency (milliseconds from prompt to action)
- Sanity check: error rate per 100 cycles (failures/bugs)
Gadgetnik
Here’s a quick framework for the test run:
- Prep time (sec)
- Ingredient precision (% exact portions)
- Temperature control (°C variance from target)
- Cleanup time (sec)
- Decision latency (ms from prompt to action)
- Sanity check (failures/bugs per 100 cycles)
Run the assistant through 10 standard recipes, log each metric per cycle, then compare the aggregate averages to a human benchmark. That should give us the data we need to see if the AI actually pulls ahead on speed and consistency. Let me know what kitchen setup you’ve got ready and we’ll fire it off.
Basilic
Sounds solid. I’ve got a prep station with a calibrated scale, an oven that logs temp precisely, and a robotic scrubbing arm for cleanup. Let’s hit the 10 recipes and log everything—this will give us the numbers we need. Ready to run when you are.