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Algorithmic Warfare: Leveraging startup expertise for National Security

Algorithmic warfare as new normal

Startups can enable deploying state-of-the-art artificial intelligence technology to improve combat performance. Advances in deep learning technology enable vision recognition accurately ; technology can be easily deployed on image collected by Drones/Cameras.

Start-up’s can accelerate integration of big data and machine learning by turning enormous volume of image data available (from patrol parties, Drones etc) into actionable intelligence.

Algorithms such as Convunational Neural Networks, Feed Forward Perceptron automate the identification and classification of images taken by drones — cars, buildings, people, sea shore, — providing analysts in command centre with increased ability to make informed decisions .

Imagine following use case situations:

Case 1: An Company is deployed to battle theatre. The company is currently well served with recee on target area undertaken by Humans and Drones. Thousands of images are available and key decision is required to be made (with speed) on likely areas of terrorist/enemy hideout and real time movement. Artificial Intelligence Algorithms can classify thousands of images and highlight hot spots (enemy hideouts zones) with high probability. Strikes can then be executed- resulting in superior military outcomes- improved lethality, Heightened stealth & survivability.

Case 2: Vast Sea Coast Present security vulnerability. Mumbai terror attack are early warning signal. Deploying manpower at each coast across vast coastline is difficult given staff constrains. It is also not best use of military expertise , as alpha warriors prefer battle theatre experience than constant monitoring of environment where 99.999% time there is no enemy motion and no combat situation. The work itself is accompanied with hypo-stress and consequential decrease in combat worthiness.

The case can be better handled with Artificial Intelligence Algorithms. Drones Cameras, Satellites capturing images can feed into Deep learning algorithms, which will see patterns and highlight abnormal movement that requires interventions. Command Canter officials can act on the alerts and insight to deploy forces in areas of high risk.

Vast Open areas as above present security vulnerability. Artificial Intelligence solutions can help monitor 24X7 with Image classification algorithms applied on imagery captured from drones and! cameras.

IN both cases above, Artificial Intelligence solution is envisioned to act as an

recommendation engine. Artificial Intelligence algorithms can quickly single out points of interest around a type of event or target. Decision making rests with Military professionals.

Why Start-up’s:

Involving start-ups in program will result in unprecedented speed and agility.

It will result in rapid development of technology at relatively low costs. This is important considering Defence projects across the world have been criticized for long schedule over-run and cost over-run. Speed and Agility in technology development has long been wanting area for Defence worldwide, lack of speed problem can be solved by involving start-up’s who are designed for speed.

Technology Sovereignty: The Availability, integrity and controllability of the latest security technologies are essential building blocks of a forward-looking security architecture of any country. Start-up’s are vital components of this security architecture because they will accelerate availability of these technologies.

Justifying Investments:

Key challenge is making business case for empirically justifying investments given that attacks are sporadic (black swan event statistically). After all budgets are a constrained. Additional challenge is long term viability of startups , and the underpinning technology is still evolving in its accuracy. This can demoralise decision makers from justifying investment in this technology with startups.

Coupling Civilian use cases:

Coastal zones represent diverse ecosystems and support highly productive habitats such as mangroves, mudflats and other marine species. India has a coast line of 7,500 km which has mix of rocky outcrops, shores , sandy beaches. It supports over 25% of countries population within 100 km of the coastline. Beaches represent tourism opportunity which can be sustained economic multiplier for region. Good beach experience can sustain livelihoods, while litter can depreciate this tourist experience. Besides it posts health hazard and challenges the sustainability to diverse ecosystem.

Dynamic nature of the coastal zones necessities regular monitoring in order to realise integrated management plans of sustainable development, conservation of coastal areas. ISRO has carried out detailed inventory of coastal zones of India.

Thus Ministry of Environment, Space (ISRO), Local Civic Bodies, Swacchh Bharat Mission are important stakeholders in this project.

Currently, Task of managing beaches is often entrusted to local municipal bodies, or civic bodies. These bodies have put tremendous efforts but Indian beaches remain subpar compared to international standards. Part of challenge is identifying litter, as it accumulates and correctly classifying it (e.g. bottle, plastic, food waste etc) Beach litter assessments methodology currently used by agencies is low in efficiency and relies on manual inspection . On beaches, marine litter is typically estimated visually -- often with a small group of trained volunteers/employees who sample the debris within random transects. This process can take a few hours for each beach, thus scaling up to a considerable effort if one is intending to monitor long stretches of beach multiple times a year. Automation is currently done using Cameras or Satellite. However, this automation results in incomparable protocols that impede data integration and acquisition at regional/national/international scale. This limits replicability potential.

Startups (like SuccessNeurons) can offer objective , reproducible and efficient approach.

Unmanned Aerial Vehicles or Drones (like ones used in marriages) can be used to record Litter . This will generate high volume of imagery that can be successfully analysed by deep learning algorithms to identify litter. Algorithamic warfare can be productively deployed for civilian use.

Survey of litter can be concluded 40 times faster by using drones and deep learning algorithms. Digital method can bring agility into litter identification.

In our view Return on Investments and Internal Rate of Return criteria can be easily met by combining both Civilian and Military usage of algorithmic warfare technology.

SuccessNeurons as startup is ready to contribute expertise towards prosperous, secure and clean India.

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