3 Application Advantages of Brain-Inspired Intelligence
Brain-inspired intelligence shows quasi-man features in the matter of adaptation. It
provides a new technique path for the formation of general intelligence and intelligence
of SoS, as well as for the development of military intelligence.
Intelligentization of command and control system is faced with such special conditions and requirements: (1) Limited data resources. Compared with applications in
Civil Internet, the sample capacity available in military activities is quite limited, since
military activities are accidental and less frequent. Thus it is often very hard to collect
thousands of or tens of thousands of samples for one kind of weapon. (2) Lots of lowquality samples. Because of the confidentiality of military activities, there are lots of
samples with unclear features. (3) Exploding battlefield requirements. With the
dynamic change of the situation of battlefield, command staffs and warfighters may
raise new intelligentized requirements at any time according to the current situation.
However, at present, the AI techniques are faced with such bottlenecks: (1) Huge
demand for data. The learning process relies on huge amount of sample data. (2) Strict
requirement for data quality. There is strict requirement for the sample articulation,
sample integrity, and label accuracy. (3) Strong dependency on models. The accuracy
of models strongly depends on the source and quality of sample data, and these models
are only suited for specific issues.
Brain-inspired intelligence is precisely a kind of adaptable AI, whose characteristics
of learning with small samples, anti-noise ability, and general intelligence can serve the
command and control system with a new way to solve the above problems. (1) Learning
with small samples. While human beings can draw inferences about other cases from
one instance, machines are still seeking hard for the similarity between new instances
and what they have seen before even after training with tens of thousands of examples.
Machines often can hardly identify the ships/planes if there are a small amount of
training examples. In contrast, brain-inspired intelligence provides machines with the
ability of drawing inferences like human brains, by multi-modal awareness and learning
processes with synergy of multiple brain areas [6]. (2) Anti-noise ability. Human beings
can identify the planes and ships in a photo taken in the rain or in the mist, as well as
capture the essence from fragmentary pictures. However, machines are usually lost in
excessive concern with local features. Therefore the rate of identification seriously drops
when the pictures are noisy or fragmentary. By comparison, brain-inspired intelligence
reproduces the magical operating mechanism of human brains by introducing neuron
models with the ability of excitation and inhibition, making machines capable of selfadaptive denoising [7]. (3) General intelligence. Under control of brains, human beings
have the skills of reading, thinking, learning, etc. However, AI at present is often only
capable of doing a single job, for example prediction of plane types or flight paths.
Although in some recent studies, deployment of algorithms as required is realized
through construction of algorithm libraries, improving the problem of fixed algorithm
function to some degree, it is still quite less flexible compared with humans. In contrast,
based on the synergy mechanism between brain areas, brain-inspired intelligence performs self-learning and knowledge reasoning by constructing pulse neural network,
making machines capable of carrying out multiple tasks [8].
Applications of Brain-Inspired Intelligence …
387
Brain-inspired intelligence shows quasi-man features in the matter of adaptation. It
provides a new technique path for the formation of general intelligence and intelligence
of SoS, as well as for the development of military intelligence.
Intelligentization of command and control system is faced with such special conditions and requirements: (1) Limited data resources. Compared with applications in
Civil Internet, the sample capacity available in military activities is quite limited, since
military activities are accidental and less frequent. Thus it is often very hard to collect
thousands of or tens of thousands of samples for one kind of weapon. (2) Lots of lowquality samples. Because of the confidentiality of military activities, there are lots of
samples with unclear features. (3) Exploding battlefield requirements. With the
dynamic change of the situation of battlefield, command staffs and warfighters may
raise new intelligentized requirements at any time according to the current situation.
However, at present, the AI techniques are faced with such bottlenecks: (1) Huge
demand for data. The learning process relies on huge amount of sample data. (2) Strict
requirement for data quality. There is strict requirement for the sample articulation,
sample integrity, and label accuracy. (3) Strong dependency on models. The accuracy
of models strongly depends on the source and quality of sample data, and these models
are only suited for specific issues.
Brain-inspired intelligence is precisely a kind of adaptable AI, whose characteristics
of learning with small samples, anti-noise ability, and general intelligence can serve the
command and control system with a new way to solve the above problems. (1) Learning
with small samples. While human beings can draw inferences about other cases from
one instance, machines are still seeking hard for the similarity between new instances
and what they have seen before even after training with tens of thousands of examples.
Machines often can hardly identify the ships/planes if there are a small amount of
training examples. In contrast, brain-inspired intelligence provides machines with the
ability of drawing inferences like human brains, by multi-modal awareness and learning
processes with synergy of multiple brain areas [6]. (2) Anti-noise ability. Human beings
can identify the planes and ships in a photo taken in the rain or in the mist, as well as
capture the essence from fragmentary pictures. However, machines are usually lost in
excessive concern with local features. Therefore the rate of identification seriously drops
when the pictures are noisy or fragmentary. By comparison, brain-inspired intelligence
reproduces the magical operating mechanism of human brains by introducing neuron
models with the ability of excitation and inhibition, making machines capable of selfadaptive denoising [7]. (3) General intelligence. Under control of brains, human beings
have the skills of reading, thinking, learning, etc. However, AI at present is often only
capable of doing a single job, for example prediction of plane types or flight paths.
Although in some recent studies, deployment of algorithms as required is realized
through construction of algorithm libraries, improving the problem of fixed algorithm
function to some degree, it is still quite less flexible compared with humans. In contrast,
based on the synergy mechanism between brain areas, brain-inspired intelligence performs self-learning and knowledge reasoning by constructing pulse neural network,
making machines capable of carrying out multiple tasks [8].
Applications of Brain-Inspired Intelligence …
387