Pakistani-American Starts Defense-Focused AI Company

Amir Husain, a Pakistani-American AI expert, has started a defense-focused artificial intelligence company, according to builtinaustin.com.  Amir Husain's AI company SparkCognition has been building artificial intelligence and machine learning (AI/ML) software for its various clients since 2013. After closing on a $100 million Series C round last year, the company claims to be “one of the most valuable startups in Texas and one of the most valuable AI startups in the United States.” Earlier this year, Amir Husain and his wife Zaib, both University of Texas at Austin alumni, donated $5 million to launch "Artificial Intelligence Institute" at their alma mater. 

Pakistani-American Couple Amir and Zaib Husain

“We started to develop software capabilities for a variety of (Department of Defense) clients and partners in the defensive industry,” founder and CEO Amir Husain said in a virtual event announcing the new company, as reported by the Austin-American Statesman. “We invented AI-powered weapon systems, prototyped a few and secured patents for many more. We have learned rich lessons and identified the shortcomings that prevent us now, as a country, from taking the lead in this critical new area.”

The new defense-focused AI company has announced several members of its board of directors who have served in high-ranking positions in the United States government. Most prominent among them are retired US Marine Corps General John Allen, former Air Force Under Secretary Lisa Disbrow, retired Navy Admiral John M. Richardson and former Deputy Secretary of Defense Robert O. Work.

Artificial intelligence is now being seen as the future of modern warfare. AI-powered networked drone swarms have recently been successfully deployed in Azerbaijan-Armenia conflict and the Gulf region. 

Defense analysts believe that Turkish and Israeli drones have helped Azerbaijan achieve decisive victory against Armenia. "Azerbaijan’s drones owned the battlefield in Nagorno-Karabakh — and showed future of warfare" says the Washington Post headline as tweeted by drone warfare expert Franz-Stefan Gady. In 2019, dozens of cheap drones were deployed against Abqaiq and Khurais oil fields to cut Saudi Aramco's production by half, according to multiple media reports. Saudi and US officials have blamed Iran for the destructive hit. This was the first time that cheap drone swarms loaded with explosives dodged sophisticated air defense systems to hit critical infrastructure targets in the history of warfare.  

Amir Husain was born is Lahore, Pakistan in 1977.  Husain enrolled in the Punjab Institute of Computer Science at the age of 15 and graduated from it two years later with a bachelor's degree in computer science. Amir is a serial entrepreneur. He has started and sold several companies. He started SparkCognition in 2013 with Michael Dell as its first investor. 

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Comment by Riaz Haq on Sunday

On 27 August 2020, the Pakistan Air Force (PAF) announced that it formed an in-house ‘Centre of Artificial Intelligence and Computing’ (CENTAIC) to spearhead development in the field for both military and civilian purposes. In a statement, the PAF Chief of Air Staff (CAS), Air Chief Marshal (ACM) Mujahid Anwar Khan, said that CENTAIC will help the PAF incorporate artificial intelligence (AI) into its operational domain.

https://quwa.org/2020/08/30/pakistan-air-force-delves-into-artifici...

The scope of CENTAIC’s activities are not yet known to the public, but it may be researching into a number of key fields in AI, such as big data, machine learning, deep learning, predictive analytics and, potentially, natural language processing (NLP). Not only do each of these sub-fields apply to current and emerging air warfare applications – notably drone development – but the PAF will need to draw on these areas to drive its next-generation fighter aircraft (NGFA) aspirations. The creation of CENTAIC was inevitable.

The PAF had noted that CENTAIC could support the development of civilian applications. However, as the entity’s work matures in the way of aiding the PAF’s programs, CENTAIC may ultimately specialize in the domains directly relevant to the PAF. But the underlying infrastructure and knowledge/capacity creation could scale-out and result in sister-organizations – ideally both in the public and private sectors – to drive AI development for healthcare, manufacturing, resource management, and other areas.

However, in terms of specifically the PAF, the creation of CENTAIC could help the PAF indigenize many key – but non-tangible and less appreciable – inputs for its NGFA under Project Azm.

These inputs can range from algorithms for guidance systems for air-to-air and air-to-surface missiles, image processing for TV/IR seekers, sensor fusion, human-machine-interfaces (HMI), and other applications. While not as physically tangible as gas turbines or transmit-and-receive modules (TRM) for an active electronically scanned array (AESA) radar, AI research could eliminate barriers to outcomes that are simply unavailable to Pakistan.

Sensor fusion one such example. There is no off-the-shelf solution (independent of physical subsystems), so the PAF would either have to acquire it as-is from a willing supplier (which may carry limitations, such as requiring it to buy specific hardware), or develop it internally.

Likewise, Pakistan could also develop a myriad of intellectual property (IP) in AI, which may help it enter research and development (R&D) partnerships as an active contributor instead of a passive bystander. For a country that lacks industrial inputs, AI could emerge as an ‘equalizer’ for R&D growth.

AI is Essential for Future Air Combat Applications
In this article, we will refer to AI as an overarching field that includes the following sub-areas:

Big Data: This is the process of identifying trends, correlations, and other insights from disparate sources of information. The intended outcome of big data is to improve decision-making.

The PAF can draw data from a variety of sources, such as – among others – instrumentation equipment installed at the Sonmiani Weapon Testing Range (WTR), the Damage Tolerance Analysis/Structural Health Management (DTA/SHM) tools used at Pakistan Aeronautical Complex (PAC), or Air Combat Maneuvering Instrumentation (ACMI) pods, specific sensors within its aircraft, flight sorties, exercises, and other areas. Additionally, a little-known feature of the JF-17 is its heavily instrumented nature. As a result, PAF has thousands of hours of flight data from the JF-17. The establishment of CENTAIC may be driven by the desire to utilize this goldmine of flight data.

Comment by Riaz Haq on Sunday

In turn, the PAF can use the data to help it plan deployments, lower maintenance costs, cut maintenance downtime, and many other discrete outcomes for the service. Big data may also help with development by helping with design through the analysis of data from wind-tunnels and instrumented ranges.

https://quwa.org/2020/08/30/pakistan-air-force-delves-into-artifici...


Machine Learning (ML): ML is a form of AI that tries ‘learning’ from past data and results so as to make better decisions in the future. ML involves the use of algorithms to understand the data (which may come from the sources we listed above) and, in turn, help the planner make an informed decision. While it may sound like common sense, seldom do humans have enough time to manually read and understand all of the facts of a situation. So, inevitably, humans could end up compromising or “going with their gut” in the absence of information. In contrast, ML can do the heavy-lifting analysis across gigabytes or terabytes of data quicker, so it leaves the human decision-maker with fewer blind spots or uncertainties. Examples of application of ML include electronic warfare, online emergency flight plan generation, flight-model learning from flight data, adaptive flight control systems, and online optimal guidance for munitions.

Deep Learning: This is a sub-field of ML. It involves running different programs through different layers of data to pull conclusions or insights from several sources. Basically, where ML would use algorithms to interpret the data and help a human decide, deep learning tailors algorithms into ‘artificial neural networks’ that could make decisions autonomously. In other words, deep learning can enable for drones that can work on their own with limited human input or control. It may even help with the development of new generation terminal-stage seekers meant to attack moving and/or hidden targets. Deep learning will enable the operation of drone swarms and may lead to decision making AIs in loyal wingman drones.

Predictive Analytics: This is basically the use of data to determine what is most likely to occur next. One good example is aircraft maintenance. The PAF can use its existing inventory/requisition logs as well as its sensors on-board aircraft to set-up predictive maintenance and preventative maintenance schedules. In turn, it can reduce long-term repair costs, cut down-time, increase availability rates, especially for the JF-17.

Natural Language Processing (NLP): NLP enables computers to communicate with people. This might not seem important in an aviation context today, but it will be in the future. For example, a single NGFA could generate vast amounts of data from a dozen major sensors. If, for example, an enemy aircraft is trying to ‘paint’ the NGFA by radar, the NGFA could alert the pilot with a specific light or screen. This may be doable if that was the only information the pilot needed, but the pilot may also want to know about the current status of his/her ‘loyal wingman’ drones, or when to send a loitering munition into a terminal stage. The pilot has limited time and energy to read a giant screen of alerts. With NLP, the NGFA could converse with the pilot, thereby cutting the risk of information overload.

Potential Marquee Air Warfare Applications
Though the projects at CENTAIC may be at their early stages, one can see the PAF direct its AI/ML efforts the following areas. These projects can tie into its NGFA efforts both directly and in complementary ways.

Unmanned Combat Aerial Vehicles (UCAV)
Be it ‘loyal wingman’ drones or deep-strike aircraft, future UCAV employment will require varying degrees of autonomous operation. In fact, Pakistan may already have a basis to start developing a ‘loyal wingman’ UAV by leveraging its existing cruise missile and target drone technologies [end of excerpt, subscribe to Quwa Premium to read the full article].

Comment by Riaz Haq on Sunday

War in the Caucasus: Lessons

by Ejaz Haider

https://www.thefridaytimes.com/war-in-the-caucasus-lessons/

Azerbaijan could either just swallow Armenian intransigence or wait for the right opportunity. It gambled on the latter.

But, and that’s important: war is serious business and cannot be undertaken lightly.

At the politico-strategic level, the growing differential between Azeri and Armenian economies unfolded in Baku’s favour. The bigger economy (oil revenues, tourism, higher exports etc) allowed Baku to spend more on defence. However, except for 2015 when Azerbaijan’s defence spending rose to 5.6% of its GDP, it averaged at just below 4% between 2009 and 2019. Armenia, while spending relatively more on defence as a percentage of its GDP, averaging 4.5%, could not catch up given the much smaller size of its economy. According to data by the Stockholm International and Peace Research Institute, Baku spent some USD24 billion on defence between 2009 and 2018. Armenia spent a little over USD4 billion for the same period.

Nonetheless, the economy is just one factor, though a very important one. A state intending to go to war must also have its diplomatic flanks covered. Armenia has always been a close ally of Russia. Russia’s relations with Azerbaijan have seen ebbs and flows. However, since 2018, Armenia-Russia relations despite a military pact (Russia also maintains a base in Armenia) have been strained while Moscow’s relations with Baku have improved.

Azerbaijan also has very close relations with Turkey for historical, ethnic and linguistic reasons. Armenia and Turkey have historically been inimical. Azerbaijan and Turkey might be two separate states, but they consider themselves the same people. Azerbaijan also has strong ties with Israel. Turkey is also the second most important state player in the Caucasus and under President Recep Tayyip Erdoğan has developed a complicated relationship with Russia, which considers the former Soviet republics as Moscow’s sphere of influence.

Azerbaijan has been buying military equipment from Turkey, Israel and Russia. Its military has very close ties with the Turkish military; both sides have been conducting joint exercises and Turkey has been training Azeri officers and ranks. Azerbaijan’s military training, deployment, employment of equipment and doctrinal development owes greatly to the Turkish military.

Lesson 2: if a state wants to go to war, it must have strong backers.

Azerbaijan also has a strong legal case on its conflict with Armenia and the separatist Armenian government (not even recognised by Armenia for that reason). The UN resolutions completely support Azerbaijan’s claims on N-K.

Lesson 3: it’s always good to have a strong legal case if a state wants to use force.

This is as far as the politico-strategic environment is concerned and Azerbaijan managed to create its asymmetric advantage over Armenia at that level.

But war, in the end, is a contest where the will of the fighting sides is tested. That’s where we come to the military-operational level. The lessons at this level are quite fascinating.

From the actual conduct of war it is clear that Armenia was fighting the previous war (when it had an edge) while Azerbaijan had planned its offensives for the present war. It showed superior planning (the opening phase targeted the relatively flatter southern districts abutting N-K) and execution. Here are some lessons.


Comment by Riaz Haq on Sunday

War in the Caucasus: Lessons

by Ejaz Haider

https://www.thefridaytimes.com/war-in-the-caucasus-lessons/



Here are some lessons.

1: If a fighting side cannot integrate the battle space with sensors, other electronic warfare systems and counter-drone measures, its land forces (troops, armour, infantry fighting vehicles, armoured personnel carriers, artillery guns, radar stations etc) will be in trouble. As has been noted by various analysts through the six weeks of the conflict, Azerbaijan used its Turkish Bayraktar TB-2 drone (which has four hard points for delivering laser-guided smart munitions) and Israeli Harop, which is a loitering munition optimised for suppression of enemy air defence (SEAD) ops. Given that it loiters, finds, acquires and attacks its target in a self-destruct, terminal mode, it’s also referred to as a kamikaze drone.

Azerbaijan employed both drones very effectively against Armenian tanks, IFVs/APCs, ground radars and artillery pieces.

Corollary: Armenian military had to hide its armour and mechanised assets and couldn’t employ them usefully in offensive mode. While it’s too early, as some analysts have suggested, that the era of the MBT and mechanised infantry is over, the conflict clearly tells us that without adequate counter-measures, armour and mechanised columns will be badly exposed to the intelligence, surveillance and reconnaissance capabilities and firepower of combat drones.

Azerbaijan integrated its ground-based fire power (indirect artillery fire, multi-barrel rocket launchers) with ISR data from the drones and used that for target acquisition and engagement. It seems to have learnt both the use of combat drones and integrating them with land-based firepower from operations conducted by the Turkish military in northern Syria against the Syrian Arab Army.
The conflict has also shown how combat drones can perform in SEAD and DEAD (destruction of enemy air defence) operations. Again, the Azeri military seems to have learnt this from the Turkish military. Bayraktar TB-2 has made a name for itself in Syria and Libya for successfully hunting the Russian-made Pantsir short- to medium-range mobile AD system. Like the Turkish military, Azerbaijan also used the MAM-L smart micro-munition against Armenia’s Strela system (9K33 and 9K35), a highly mobile, short-range surface-to-air missile.
The effective employment of combat drones against land forces, integrating them with ground-based firepower and using them for SEAD/DEAD missions not only managed to destroy much of Armenia’s offensive capability while also degrading its defences, but, by extension, made it easier for Azerbaijan to use its own armour, APCs and ground forces to capture and hold territory. In other words, Azerbaijan first dented the Armenian offensive and defensive capabilities and then used its land forces in a traditional offensive mode to capture and hold territory.
This is of course an overview of how the conflict unfolded. It does not mean that future wars will always be fought like this. Adversaries with symmetrical capabilities will have to further innovate to establish an asymmetrical advantage. There are other emerging technologies that are changing, and will change, the conduct of war in ways that one can only conjecture about at this time.

There is also the issue of escalation dominance and spirals, especially between adversaries that are nuclear armed. That raises other questions apropos of how effectively operations can be conducted and how, if at all, they can be conducted without the two sides getting into a spiral that could lead to crossing the nuclear thresholds.

The most important point to note, however, is the nexus between innovation (both in planning and employment of equipment and systems) and creating and maintaining an asymmetric advantage. That is what Azerbaijan achieved in this war. And that is why it has emerged as the victor.

Comment by Riaz Haq on Sunday

How does drone warfare impact India’s preparedness?

https://www.indiatoday.in/news-analysis/story/drone-india-learn-aze...

With neighbours such as Pakistan and China, threat lies for India at any given point of time. Bolstering its military with the latest technology is the need of the hour, for which India has already been making moves in the combat drone/UCAV spectrum. The Indian Army is in possession of around 90 Heron Surveillance drones and the Harop loitering munition. Additionally, the army is planning to acquire more of these from Israel.

In August this year, the defence approved the upgrade of Heron UAVs. The upgrade will include arming some of these drones, sources in Indian security establishment said. The decision comes amid the India-China standoff as the Indian military is preparing to enhance its surveillance capabilities at the Line of Actual Control (LAC). The Heron UAVs are already being used in the forward areas of Ladakh.

India is also looking to expedite its testing of the indigenous surveillance drones ‘Rustom-2’ before inducting them into service.

During the defence expo in Lucknow in February this year, Hindustan Aeronautics Limited (HAL) and Israel Aerospace Industries (IAI) from Israel and Dynnamatic Technologies Limited signed an agreement for manufacturing of drones.

The Indian Army also opted for the SpyLite mini-UAV for high-altitude aerial surveillance. This is built by Cyient Solutions & Systems (CSS), a joint venture between Cyient Ltd (India) and BlueBird Aero Systems (Israel).

With the opening of the American drone market, India is also exploring the possibility of acquiring several GA-ASI MQ-9 Reapers from the US subject to approval.

Talking about threats from neighbours, Pakistan has a plethora of options to choose from if it decides to expand its already existing combat drone options. Both Turkey and China design and manufacture high-end drone equipment. On the other hand, India will hope to bank upon Israel and the US.

With regards to the use of combat drones in our part of the world (read India’s border with Pakistan and China) drone warfare may not be as successful as it was in the Armenian context. This is because both India and Pakistan have heavy air defence systems.


Unless India completely dominates the air warfare, drones may not be as successful when it comes to combat operations. The induction of Rafale may help India with this regard.

China is the bigger player when it comes to drones and unmanned aerial vehicles (UAVs). It has invested a lot of effort in developing civilian drones and the same has been translated into them developing combat drones. China is one of the leading countries when it comes to R&D concerning drone technology.

China also possesses anti-drone technology used to jam signals that disrupt drones or shoot incoming drones in order to divert or destroy them.


With China’s growing dominance in global drone market and Pakistan’s proximity with Beijing, India needs to quickly adapt to the changing game of drone warfare as it is likely to become even more prevalent in coming years.

----------

UCAVs also have a less carrying capacity compared to fighter jets. Hence, they are used in small but precise attacks rather than air-based raids that jets usually engage in. Azerbaijan used a new method of precision warfare that best compliments the use of such drones. This was only possible for rich and well-established militaries before, but now technology has made this more accessible to countries like Azerbaijan.

To name a few, countries with outstanding border conflicts include India, Pakistan, Serbia, Ukraine and many others. All these nations have already started purchasing attack drones and UCAVs.

The combat drone market can further explode by the Trump administration's push to deregulate their armed drone sales in a bid to allow the US manufacturers to compete in an export market dominated by China, Israel and Turkey.

Comment by Riaz Haq on Sunday

The Impact of
Artificial Intelligence
on Strategic Stability
and Nuclear Risk
Volume III
South Asian Perspectives
edited by petr topychkanov


https://www.sipri.org/sites/default/files/2020-04/impact_of_ai_on_s...



The ongoing renaissance of artificial intelligence (AI) is reshaping the world. Just
like many other developing countries, India and Pakistan—the two nuclear-armed
states of South Asia—are exploring the subsequent opportunities for economic and
social change. Their political leaders seem to prioritize civilian applications of AI
over the military, and public attention reflects the political priorities. National
efforts to militarize AI do not receive the same public coverage as civilian AI
developments.
Meanwhile, according to the available open-source information, India and
Pakistan are increasingly interested in the potential benefits of AI for defence and
security. This might be one of the reasons why an expert debate on the opportunities and risks posed by the AI renaissance in the military realm has started
in recent years. However, the debate suffers from large gaps, particularly in the
emerging discussion on the potential impact of AI on strategic stability and
nuclear risk in South Asia. This issue has been underexplored by scholars studying South Asia from both inside and outside the region.
This edited volume—which follows earlier volumes on Euro-Atlantic and East
Asian perspectives—tries to fill the gaps in the scholarly debate on this important
topic and to facilitate further regional debate. It is based on a workshop held in
Colombo in February 2019. The eight expert contributors—from South Asia and
around the world—reflect the variety of issues, approaches and views.
It is clear from a comparative study of the state of adoption of AI in South
Asia that India and Pakistan are playing catch-up in the world competition on
military AI. Compared to the United States, China and Russia, India’s advances
are modest, while Pakistan’s are even less visible. One of the reasons seems to
be under-resourcing and inefficiencies in defence research and state industries.
These prohibit the development and adoption of emerging technologies within a
reasonable time frame.

However, according to contributors from India and Pakistan, both countries are well aware of the strategic significance of AI. They see AI as one of many enablers of the mutual strategic balance. India must also take into consideration the role of AI in the military build-up of China, one of its long-term security concerns.
In assessing the strategic significance of AI, the expert contributors—regardless of their origin—agree that AI is a double-edged sword. On the one hand, AI could enhance nuclear command and control, early warning, intelligence surveillance and reconnaissance (ISR), and the physical security of nuclear capabilities, among other areas. In this way it would improve states’ sense of security. On the other hand, the same advances could cast doubt on the survivability of their respective second-strike capabilities. This doubt would stimulate more aggressive nuclear postures that could increase nuclear risk.

Comment by ZAHRA ZAFAR on Tuesday

Amir Husain's AI company SparkCognition has been building artificial intelligence and machine learning (AI/ML) software for its various clients since 2013. After closing on a $100 million Series C round last year, the company claims to be “one of the most valuable startups in Texas and one of the most valuable AI startups in the United States.” 

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