The Hands that rock the cradle, also crack the code

It was an unguarded moment for my church-going, straight-laced handyman & landscaper, “ I am not sure if I am ready to trust a woman leader”, and finally the loss of first woman Presidential candidate in the US, that led me to ruminate about Women and Leadership and indulge in my most “ time suck” activities, google and peruse through Wikipedia.

I had known about this, but I was fascinated to reconfirm that the first programmer in the world was a woman, and daughter of the famed poet, Lord Byron, no less. The first Programmer in the World, Augusta Ada King-Noel, Countess of Lovelace nee Byron; was born in 1815 and was the only legitimate child of the poet laureate, Lord Byron and his wife Annabella. A month after Ada was born, Byron separated from his wife and forever left England. Ada’s mother remained bitter towards Lord Byron and promoted Ada’s interest in mathematics and logic in an effort to prevent her from developing what she saw as the insanity seen in her father.

Ada grew up being trained and tutored by famous mathematicians and scientists. She established a relationship with various scientists and authors, like Charles Dickens, etc..   Ada described her approach as “poetical science”[6] and herself as an “Analyst & Metaphysician”.

As a teenager, Ada’s prodigious mathematical talents, led her to have British mathematician Charles Babbage, as her mentor. By then Babbage had become very famous and had come to be known as ‘the father of computers’. Babbage was reputed to have developed the Analytical Engine. Between 1842 and 1843, Ada translated an article on the Analytical Engine, which she supplemented with an elaborate set of notes, simply called Notes. These notes contain what many consider to be the first computer program—that is, an algorithm designed to be carried out by a machine. As a result, she is often regarded as the first computer programmer. Ada died at a very young age of 36.

As an ode to her, the mathematical program used in the Defense Industry has been named Ada. And to celebrate our first Programmer, the second Tuesday of October has been named Ada Lovelace Day. ALD celebrates the achievement of women in Science, Technology and Engineering and Math (STEM). It aims to increase the profile of women in STEM and, in doing so, create new role models who will encourage more girls into STEM careers and support women already working in STEM.

Most of us applauded Benedict Cumberbatch’s turn as Alan Turing in the movie,  Imitation Game. We got to know about the contribution, that Alan Turning and his code breaking team at the Bletchley Park, played in singularly cracking the German Enigma code and how the code helped them to proactively know when the Germans were about to attack the Allied sites and in the process could conduct preemptive strikes. In the movie, Kiera Knightly played the role of Joan Clark Joan was an English code-breaker at the British Intelligence wing, MI5, at Bletchley Park during the World War II. She was appointed a Member of the Order of the British Empire (MBE) in 1947, because of the important part she essayed in decoding the famed German Enigma code along with Alan Turing and the team.

Joan Clark attended Cambridge University with a scholarship and there she gained a double first degree in mathematics. But the irony of it all was that she was denied a full degree, as till 1948, Cambridge only awarded degrees to men. The head of the Code-breakers group, Hugh Alexander,  described her as “one of the best in the section”, yet while promoting Joan Clark, they had initially given her a job title of a typist, as women were not allowed to be a Crypto Analyst. Clarke became deputy head of British Intelligence unit, Hut 8 in 1944.  She was paid less than the men and in the later years she believed that she was prevented from progressing further because of her gender.

In World War II the  US Army was tasked with a Herculean job to calculate the trajectories of ballistic missiles. The problem was that each equation took 30 hours to complete, and the Army needed thousands of them. So the Army, started to recruit every mathematician they could find. They placed ads in newspapers;  first in Philadelphia, then in New York City, then in far out west in places like Missouri, seeking women “computers” who could hand-compute the equations using mechanical desktop calculators. The selected applicants would be stationed at the  University of Pennsylvania in Philly. At the height of this program, the US Army employed more than 100 women calculators. One of the last women to join the team was a farm girl named Jean Jennings. To support the project, the US Army-funded an experimental project to automate the trajectory calculations. Engineers John Presper Eckert and John W. Mauchly, who are often termed as the Inventors of Mainframe computers, began designing the Electronic Numerical Integrator and Computer, or ENIAC as it was called.  That experimenting paid off: The 80-foot long, 8-foot tall, black metal behemoth, which contained hundreds of wires, 18,000 vacuum tubes, 40 8-foot cables, and 3000 switches, would become the first all-electric computer called ENIAC.

When the ENIAC was nearing completion in the spring of 1945, the US Army randomly selected six women, computer programmers,  out of the 100 or so workers and tasked them with programming the ENIAC. The engineers handed the women the logistical diagrams of ENIAC’s 40 panels and the women learned from there. They had no programming languages or compilers. Their job was to program ENIAC to perform the firing table equations they knew so well.

The six women—Francis “Betty” Snyder Holberton, Betty “Jean” Jennings Bartik, Kathleen McNulty Mauchly Antonelli, Marlyn Wescoff Meltzer, Ruth Lichterman Teitelbaum, and Frances Bilas Spence—had no documentation and no schematics to work with.

There was no language, no operating system, the women had to figure out what the computer was, how to interface with it, and then break down a complicated mathematical problem into very small steps that the ENIAC could then perform.  They physically hand-wired the machine,  using switches, cables, and digit trays to route data and program pulses. This might have been a very complicated and arduous task. The ballistic calculations went from taking 30 hours to complete by hand to taking mere seconds to complete on the ENIAC.

Unfortunately, ENIAC was not completed in time, hence could not be used during World War II. But 6 months after the end of the war, on February 14, 1946 The ENIAC was announced as a modern marvel in the US. There was praise and publicity for the Moore School of Electrical Engineering at the University of Pennsylvania, Eckert and Mauchly were heralded as geniuses. However, none of the key programmers, all the women were not introduced in the event. Some of the women appeared in photographs later, but everyone assumed they were just models, perfunctorily placed to embellish the photograph.

After the war, the government ran a campaign asking women to leave their jobs at the factories and the farms so returning soldiers could have their old jobs back. Most women did, leaving careers in the 1940s and 1950s and perforce were required to become homemakers. Unfortunately, none of the returning soldiers knew how to program the ENIAC.

All of these women programmers had gone to college at a time when most men in this country didn’t even go to college. So the Army strongly encouraged them to stay, and for the most part, they did, becoming the first professional programmers, the first teachers of modern programming, and the inventors of tools that paved the way for modern software.

The Army opened the ENIAC up to perform other types of non-military calculations after the war and Betty Holberton and Jean Jennings converted it to a stored-program machine. Betty went on to invent the first sort routine and help design the first commercial computers, the UNIVAC and the BINAC, alongside Jean. These were the first mainframe computers in the world.

Today the Indian IT  industry is at $ 160 B and is at 7.7 %age of the Indian GDP and employs approximately 2.5 Million direct employees and a very high percentage of them are women. Ginni Rommeti, Meg Whitman are the CEOs of IBM and HP while Sheryl Sandberg is the COO of Facebook. They along with Padmasree Warrior, ex CTO of CISCO have been able to crack the glass ceiling.    India boasts of Senior Leadership in leading IT companies like Facebook, IBM, CapGemini, HP, Intel  etc.. who happen to be women. At our company, GAVS, we are making an effort to put in policies, practices, culture that attract, retain, and nurture women leaders in IT. The IT industry can definitely be a major change agent in terms of employing a large segment of women in India and can be a transformative force for new vibrant India. We must be having our Indian Ada, Joan, Jean and Betty and they are working at ISRO, at Bangalore and Sriharikota, at the Nuclear Plants at Tarapur.


Sumit Ganguli

Sumit Ganguli

AIOps Trends in 2019

Adoption of AIOps by organizations

Artificial Intelligence in IT operations (AIOps) is rapidly pacing up with digital transformation. Over the years, there has been a paradigm shift of enterprise application and IT infrastructure. With a mindset to enhance flexibility and agility of business processes, organizations are readily adopting cloud platforms to provision their on-premise software. Implementation of technologies like AIOps and hybrid environment has facilitated organizations to gauge the operational challenges and reduced their operational costs considerably. It helps enterprises in:

  • Resource utilization
  • Capacity planning
  • Anomaly detection
  • Threat detection
  • Storage management
  • Cognitive analysis

Infact, if we look at Gartner’s prediction, by 2022, 40% of medium and large-scale enterprises will adopt artificial intelligence (AI) to increase IT productivity.

AIOps Market forecast

According to Infoholic Research, the AIOps market is expected to reach approximately $14 billion by 2024, growing at a CAGR of 33.08% between 2018–2024. The companies that will provide AIOps solutions to enhance IT operations management in 2019 include BMC Software, IBM, GAVS Technologies, Splunk, Fix Stream, Loom System and Micro Focus. By end of 2019, US alone is expected to contribute over 30% of growth in AIOps and it will also help the global IT industry reach over $5,000 billion by the end of this year. Research conducted by Infoholic also confirmed that AIOps has been implemented by 60% of the organizations to reduce noise alerts and identify real-time root cause analysis.

Changes initiated by enterprises to adopt AIOps

2019 will be the year to reveal the true value of AIOps through its applications. By now, organizations have realized that context and efficient integrations with existing systems are essential to successfully implement AIOps.

1. Data storage

Since AIOps need to operate on a large amount of data, it is essential that enterprises absorb data from reliable and disparate sources which, then, can be contextualized for use in AI and ML applications. For this process to work seamlessly, data must be stored in modern data lakes so that it can be free from traditional silos.

2. Technology partnership

Maintaining data accuracy is a constant struggle and in order to overcome such complexity, in 2019, there will be technology partnership between companies to deal with customer demands for better application program interface (APIs).

3. Automation of menial tasks

Organizations are trying to automate menial tasks to increase agility by freeing up resources. Through automation, organizations can explore a wide range of opportunities in AIOps that will increase their efficiency.

4. Streamling of people, process and tools

Although multi-cloud solutions provide flexibility and cost-efficiency, however, without proper tools to monitor, it can be challenging to manage them. Hence, enterprises are trying to streamline their people, process and tools to create a single, siloed-free overview to benefit from AIOps.

5. Use of real-time data

Enterprises are trying to ingest and use real-time data for event correlation and immediate anomaly detection since, with the current industrial pace, old data is useless to the market.

6. Usage of self-discovery tools

Organizations are trying to induce self-discovery tools in order to overcome the challenge of lack of data scientists in the market or IT personnel with coding skills to monitor the process. The self-discovery tools can operate without human intervention.


Between 2018 to 2024, the global AIOps market value of real time analytics and application performance management is expected to grow at a rapid pace. Also, it is observed that currently only 5% of large IT firms have adopted AIOps platforms due to lack of knowledge and assumption about the cost-effectiveness. However, this percentage is expected to reach 40% by 2022. Companies like CA Technologies, GAVS Technologies, Loom Systems and ScienceLogic has designed tools to simplify AIOps deployment and it is anticipated that over the next three years, there will be sizable progress in the AIOps market.


Artificial Intelligence (AI) or Intelligence Augmentation (IA) – What’s the difference?

Artificial Intelligence in IT operations (AIOps) is rapidly pacing up with digital transformation. Over the years, there has been a paradigm shift of enterprise application and IT infrastructure. With a mindset to enhance flexibility and agility of business processes, organizations are readily adopting cloud platforms to provision their on-premise software. Implementation of technologies like AIOps and hybrid environment has facilitated organizations to gauge the operational challenges and reduced their operational costs considerably. It helps enterprises in:

When Artificial Intelligence (AI) technology was first introduced, it was hailed as the next big advancement moving us closer to achieving human superiority. Just as we became comfortable with this idea a new one cropped up about AI replacing humans leading to irrational fears.

At this juncture, AI proponents put forth the concept of Intelligence Augmentation (IA) that kept the humans in the loop while still maintaining control over the machines. Interchange the letters of AI and IA offers a completely different perspective on AI. Intelligence Augmentation (IA) – another name for cognitive intelligence – is gaining fast precedence among business leaders.

What’s the difference?

AI is built to replace human intervention and interactions involving repetitive tasks, thereby reducing human errors and operating costs, and improve efficiency and productivity. Intelligence augmentation on the other hand is built to assist humans in their cognitive tasks and complement in the decision-making process.

IA or cognitive computing is a more comprehensive branch as it can “reason” over all structured and unstructured data and deal with “grey areas” to help make judgements and decisions.

Consider the example of a target-driven salesperson. She must close deals based on various information inputs like emails, CRM, quotas, etc. AI can help her to assimilate all these disparate information sources and organize it for easy analysis. But what happens next? How will she gain insights for closing the deal?

That’s where AI work ends, and IA comes into the picture. IA offers her potential actions that can be taken to convert a lead like offering discounts, providing additional incentives, customer support etc. It assists her in completing the task.

This is one example where both AI and IA complement each other and ultimately help humans in the long run.

Businesses are recognising this important fact and reaching out to expert service providers in this field like GAVS Technologies to integrate it in their business processes.

Zero Incident Framework TM for bridging the AI gap between Humans and Machines

The AIOps based TechOps platform, Zero Incident FrameworkTM is part of the current AI and IA landscape that tries to bridge the gap between man and machine to provide adequate insights from the information overload that businesses face.

The platform can aggregate and correlate ITIL data across multi-cloud and on-premise infrastructures to provide real time insights leading to faster incident remediation.

Our approach also involves cognitive computing that includes a comprehensive set of capabilities based on emerging technologies like language, speech and vision technologies; ML, reasoning and decision technologies; Brain-Computer Interface (BCI), which connects the brain with an external computing device to augment or repair human cognition; distributed and high-performance computing; and new computing architectures and devices.

Integrating these varied technologies requires technical expertise, resources and adequate planning that GAVS Technologies provide through their comprehensive AI led digital solutions. They provide solutions for a wide range of practical problems, boost productivity and foster new discoveries across many industries.

Reach out to GAVS Artificial intelligence and Intelligence Augmentation experts at

AIOps – the answer to your IT’s complexities

Balaji Uppili, Chief Customer Success Officer, GAVS

Artificial Intelligence in IT operations (AIOps) is rapidly pacing up with digital transformation. Over the years, there has been a paradigm shift of enterprise application and IT infrastructure. With a mindset to enhance flexibility and agility of business processes, organizations are readily adopting cloud platforms to provision their on-premise software. Implementation of technologies like AIOps and hybrid environment has facilitated organizations to gauge the operational challenges and reduced their operational costs considerably. It helps enterprises in:

With the increasing efficiency and sophistication of our IT systems, their complexity opens up a constant slew of challenges for IT Ops departments, and Artificial Intelligence for IT Operations (AIOps) today has emerged as the answer to manage such complexities.

AIOps combines the power of Big Data and Machine Learning and automation and offers process automation independent of manual resources.  What makes AIOps a winner is its functionality of combining data driven insights from various systems and operational tools that brings significant improvements and probably the best solution for now and future along with cost efficiency.

Driving data through Analytics for meaningful, actionable insights and the subsequent optimization and transformation using Machine Learning that helps in informed decisions and enables IT Ops resources to spend more of their time in quality tasks to support business goals rather than fighting the day to day blips and glitches.

With the Zero Incident FrameworkTM (ZIF) picking so much attention, we thought this is the best time to bring you some insights from our Leadership.

In conversation with Balaji Uppili, Chief Customer Success Officer, at GAVS;

Why do you think AIOps is picking up pace suddenly when these issues have been existing in the industry for the past many years?

Balaji: AIOps is really picking up because the day to day operations are becoming more complex and the amount of operational issues are increasing by the day. Also, AIOps is no longer being used as operational tool but more strategic. This creates bandwidth from an operational standpoint and also in the cost aspects as well. This also provides lot more predictability and proactive approach.

What do you think is the next phase of AIOps?

Balaji: The various dimensions of Machine Learning like Reinforcement Learning, Reinforcement deep learning would definitely take off. A good interface with a virtual assistant / conversational assistant is the future.

Is AI truly helping infra team to be ahead of the curve or is it just a hype?

Balaji: It is not a hype at all. There is also no other alternative to it as well. AI is now the key expectation for running efficient and seamless operations.

How do you quantify the ROI to CIOs when they invest in these products?

Balaji: The quantification happens from reduction in license costs for various tools being deployed and also optimization due to automation and shift left from a process optimization stand point. These will have direct reduction in operational costs both asset and resources (labor included).

What makes ZIF the biggest differentiator in the market?

Balaji: Its ability to reduce noise in the operations (eliminate unwanted data points and also eliminate spikes due to seasonality in operations) world in an enterprise clubbed with its predictability capability (provide approaches to learn from past historical data and arrive at models for the future) which can help the CIO be ahead of the operations both from end user experience and costs.

How do you claim to have embraced AI in ZIF?

Balaji: The various algorithms are very AI driven. The self-learning from both historical data and current environment and context and using that to predict the future is all in the platform.

What is the success rate your customer’s have seen, by adopting ZIF?

Balaji: As regards to automation, customers have seen at least 30%+ automation of operations and processes over 12 months and some even 50%+. With regards to noise reduction and correlations about 70%+(avoiding duplicates and eliminating seasonalities) and predictions in some cases with about 80%+ probability.

How do you think an organization should evaluate the right AIOps platform? What parameters should they consider?

Balaji: The theme of our platform at GAVS is “Zero Incident”. How can we get all enterprises to a zero incident state? If that theme is applied, then each and every aspect of the operation is evaluated towards a zero incident journey and this will automatically result in massive cost savings and significant increase in end user experience.

By implementing AIOps platform, are organizations creating unemployment?

Balaji: This is a wrong myth and assumption. If we don’t automate and don’t become a responsive and agile enterprise, then the businesses won’t run. The future is all about AIOps and beyond and hence adoption of these concepts by the teams is critical. This will help the teams to reskill themselves to working on automation, data science and related areas and thereby enhance their own value both within the organization they serve and outside as well. The AIOps platforms are evolving to make you better and hence a change management and re-hash of the workforce goes with it.

How do you make sure ZIF is always ahead of the curve in the AIOps space?

Balaji: Our internal research and marketing team plays a huge role in keeping us ahead. In addition, our partnership with Microsoft, Gartner, Everest and more importantly with IIT Madras, does help us to be ahead of the curve.