TL;DR: For narrow, repetitive NLP tasks at high volume, a small fine-tuned model can be much cheaper (10x is possible) than a frontier LLM. The savings can be large, but mostly when the task is constrained & frequent enough to justify the extra engineering work.
TL;DR: Success in data science is inversely proportional to the number of times the same steps are repeated.
A lidar measures distance to the nearest object in-front of the sensor. For e.g., a lidar mounted on a robot can be used to detect obstacles in the path.
A lidar is more expensive but provides better accuracy and range than other methods such as
ultrasonic sensors
when measuring distance. In my effort to build an autonomous car, I chose to use a Neato robovaccum lidar - XV-11.
In this post I am writing down my experiences of working with it.
