Regardless of what kind of tank we get we can turn Pakistan military into A.I. based warfare force using mathematically driven systems engineering implemented on off the shelf components. There are a lot of things we can do as technical ability to do so already exist within Pakistan.
For tank and other vehicle/soldier based warfare, we must develop situation aware distributed attack capability. This can be done initially using tanks only but later other vehicles and ultimately soldiers carrying anti-tank weapons. Nobody has it and we will have an upper hand always. The initiator always leads. I won’t say much but distributed attack means here simultaneously attacking vast regions by letting A.I. suggested maneuvers and targeting that maximizes damages while maintains safety margins.
Though it would mean adding more computing power in each vehicle and tank, but I have the feelings we can reduce nodal computations (e.g. each vehicle is node) to such a degree, that commercially available (and relatively cheap) data and image processing chips can be used. We will need to find a way to reduce information sharing data amount since it must be communicated in real time and in highly communication degrading battlefield environment (i.e. due to possible jamming attempts). It is possible to reduce data on some portions of the network and increase on others using A.I. driven self-organizing at-hock sensor networks such that minimum information transfer constraints are maintained or we at least have sufficiently fast processors to compensate using time-delay models.
For large scale cyber-physical systems general hardware/software verification via current logic based approaches is not possible. In plain English, mathematical proofs that all will work as required cannot be mathematically rigorously derived in general but only for specific situations). Therefore for such a cyber-physical system it would be impossible to confirm mathematically hardware-software verification, still we can definitely carry out verification with sufficient fidelity (i.e. simulation assisted models) so that even if a war last for a thousand years, we can cause massive damage with high probability, every day. Here verification means, our ability to be confident that the large scale system designed for such warfare will not suffer from unwanted or unexpected behavior, under all possible scenarios (i.e. unexpected mode of operations, glitches, data clogging etc.).
We would still need to separately process the received data to dynamically update evolution of enemy forces and create human-machine cognition of what is going on in the battle field not just for commander but for the A.I. system as well so that can keep getting smarter. That actually can be done with existing data-based A.I. (i.e. machine learning approaches).
A.I. despite its fancy name, won’t be that hard though it would take around 2 to 3 years to build basic integrated A.I. that has at one had sufficient structure to absorb ever increasing information complexity (i.e. can estimate/represent, and infer/predict dynamics of war assets, people, environmental and information based interaction of sufficiently complex nature) and yet can discriminate at a resolution where actions is most appropriate (i.e. based on the situation, and limited computational and other resources, should it focus on information disruption, feeding false information or bomb a certain vehicle cluster for maximum effect with minimum cost and so on). Current machine learning approaches can be scaled up to create such a system.
Pakistan already has people with expertise in data-driven A.I. My definition is as follows: Data driven A.I. is a kind of artificial intelligence that derives its structure and/or modifies itself in response to received data and then uses this self-modification to predict, classify/discriminate, control and or influence something out there.