Do specific units exists for measuring the intelligence of a machine?

One of the challenges of AI is defining Intelligence. If we could precisely define general intelligence then we could program it into a computer. After all an algorithm is a process so well defined that it can be run on a computer.

Narrow AI can be evaluated on its success at achieving goals in an environment. In domains such as computer vision and speech recognition narrow AI algorithms can be easily evaluated.

Many universities curate narrow AI tests. Fei-Fei Li a professor at Stanford who directs the Artificial Intelligence lab there organises the annual ImageNet Challenge. In 2012 Geoffrey Hinton famously won the competition by building a Deep Neural Network that could recognize pictures more accurately than humans can.

To my knowledge the testers commonly use Precision and recall evaluation metrics

Shane Legg and Marcus Hutter proposed one in 2006. The main descriptive quotes (see the paper for the actual formula):

Intelligence measures an agent’s general ability to achieve goals in a wide range of environments

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It is clear by construction that universal intelligence measures the general ability of an agent to perform well in a very wide range of environments, as required by our informal definition of intelligence given earlier. The definition places no restrictions on the internal workings of the agent; it only requires that the agent is capable of generating output and receiving input which includes a reward signal.

One thing you'll see quite often, is to declare a correspondence between a system and a human of a given age. For example "this program can answer questions about science approximately as well as an average 7 year old" or something of that nature.