Maximilian Schreiner
Max is the managing editor of THE DECODER, bringing his background in philosophy to explore questions of consciousness and whether machines truly think or just pretend to.
Read full article about: Prompt engineering in LLMs is finding the right vector program
LLMs (Large Language Models) like OpenAI's GPT-4 act as repositories for millions of vector programs mined from human-generated data learned as a by-product of language compression, says AI researcher François Chollet. Prompt engineering then involves searching for the right "program key" and "program argument(s)" to accomplish a given task more accurately. Chollet expects that as LLMs evolve, prompt engineering will remain critical, but can be automated for a seamless user experience. This is in line with recent ideas from labs such as Deepmind, which is exploring automated prompt engineering.
My interpretation of prompt engineering is this:
1. A LLM is a repository of many (millions) of vector programs mined from human-generated data, learned implicitly as a by-product of language compression. A "vector program" is just a very non-linear function that maps part of…
— François Chollet (@fchollet) October 3, 2023
Read full article about: Microscale internal combustion engine powers insect robot
Researchers at Cornell University have developed a tiny quadruped robot powered by combustion actuators fueled by methane and oxygen. The insect-sized robot, published in Science, can jump 59 centimeters straight up and walk while carrying 22 times its own weight. The researchers aim to apply the power generated by the combustion actuators to large-scale, variable-recruitment musculature for stronger, more agile robots. "Putting thousands of these actuators in bundles over a rigid endoskeleton could allow for dexterous and fast land-based hybrid robots," said one researcher.
