An inventor named Trevor E Chandler has claimed to have create an artificial intelligence that is capable of determining its own purpose, so to speak. The AI gets an initial code which, emergently, it ultimately overcomes, creating its own code to define its purpose, and thus action. This seems perfectly safe. I wonder if we can combine this AI with nanotechnology and just, you know, see what happens. Let’s create a nanotech ai that can replicate itself and develop its own purpose. That should be fun.
As usual, the claims might not meet the much more prosaic reality an inventor is hyping. We won’t be anytime soon seeing nanobots go up our noses and turn us into Biden voters, or, worse, Dallas Cowboys fans, but it does mean developing more autonomously developing tech that can positively enhance our ability to process and refine the world around us.
New Type of Artificial Intelligence can Self-Create and Self-Improve its Source Code
From www.einnews.com
2022-02-09 13:00:00
Excerpt:
A new type of artificial intelligence has been created with the capability to advance its own source code, persist, and use its learning across use cases, and through code generation and modification, advance its action set and objectives beyond their starting state without the need for human intervention.
Trevor E. Chandler, the inventor states, “All existing artificial intelligence is limited by human bias. We either tell the AI what actions it can perform or give it data that represents actions it can use. This stunts the potential of our systems, preventing them from achieving emergence. My new approach has overcome this, and other serious issues with machine learning today, resulting in a machine learning system generating emergent actions beyond its initial actions list or data and emergent objectives beyond its initial objectives.”.
This new type of machine learning automatically searches for, finds, and uses code from other artificially Intelligent components as its starting state, continually writing code into itself from preexisting systems, then modifying its own source code as it advances its action set beyond its starting state through use of a built-in code generating and evaluation artificial intelligence. This allows useful information from preexisting machine learning systems to be utilized, not wasted, but only as a starting point…..
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