QURIOSITY
VOLUME 09 ISSUE 10
OCTOBER 2018 MONTHLY NEWSLETTER OF QUANTINUUM
– The quant & analytics committee @ SIMSR
Editor’s Note Welcome to the latest issue of Quriosity, the monthly newsletter of Quantinuum! Quantinuum - the Quant and Analytics committee of K.J. Somaiya Institute of Management Studies and Research brings you the latest newsletter carrying information and articles which will enrich the young minds about the happenings in the field of quants, analytics, and mathematics. The objective of Quriosity is to publish up-to-date articles on data analytics, alongside relevant and insightful news. We intend the newsletter to be vibrant, engaging and accessible, and at the same time integrative. This issue includes a cover story on ChatBots as a Business application of AI. The sub-article explains the concept of “Data Monetization”. In the QuantGuru section, we have highlighted significant contributions of Dr. Harish Chandra in Mathematics. We have got some interesting information about updates in Data science and technology followed by some intriguing puzzles. If you wish to submit articles or news items, either individually or collaboratively, you are welcome to write to us at – quriosity.quantinuum@gmail.com Thank you and Happy Reading! Quriosity Editorial Team Quantinuum@SIMSR Editorial Team: VVNS Anudeep (+91 9441201685) Khushbu Mehta (+91 9930158610) Tanmay Nikam (+91 9699288587) Akshay Nandan R (+919176444022) Saumya Joshi (+91 9456684181) Abhishek Bawa (+91 9619995738) Kaustubh Karanje (+91 7738219050) Dhyan Baby K (+91 9809245308) Shubham Thakur (+91 7096045088)
Mentor: Prof. N.S.Nilakantan (+919820680741) Email – nilakantan@somaiya.edu
Team Leaders: Purav Shah (+918511929416) VVNS Anudeep (+919441201685) Yatharth Jaiswal (+919969698361)
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Contents TOPIC
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Cover Story Chat Bots Business Application of AI
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by Akshay Nandan
Sub-article Monetization of Data by Abhishek Bawa
Quant Guru – Harish Chandra (1923-1983)
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by Shubham Thakur
Curiosity Update by Saumya Joshi
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News Digest by Saumya Joshi
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Mentor’s Corner by Tanmay Nikam
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Internship Diary by Ashish Soni
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Quant Fun by Shubham Thakur
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Quant Connect 18
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Quant Cover Story Chat Bots – Business Application of AI The evolution of Artificial Intelligence has paved way to the adoption of various AI-based technologies by businesses, in order to improve their daily operations and offer better customer experience. One such technology is the chatbot, which is the new revolution of the AI-powered technology. A Chatbot is basically a computer program designed to simulate conversations with users on the web. The bots are equipped with natural language recognition which makes them interpret audio and textual inputs and respond precisely to the customers with summarized answers. They have the ability to understand the natural language used by the customers, and eventually hold conversations with them by interacting with them and answering their queries. This technology has been adopted not only by the leading tech firms but also by small and medium-sized businesses and startups, through which they connect with their customers or clients and optimize their processes.
For any organization, customer satisfaction is a top priority as it is impossible to sustain in a business with dissatisfied customers. Hence, it is crucial for a firm to constantly engage with their customers and address their queries and issues on time. However, it could be a challenging task to accommodate every single customer, as humans have their limitations in the form of limited working hours and cannot offer service around the clock. The AI-powered chatbots solve this problem by addressing these real-time queries effectively throughout the day, and thus offer a platform for these firms to continually engage with their
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customers and deliver an ideal customer experience. Also, it helps the customer support personnel by reducing the workload considerably, as there is a significant increase in the number of customers and their complaints across businesses. To achieve this, the chatbots are integrated with the customer support system, and the repetitive, straightforward queries are handled by the bots, whereas more complex queries and complaints are addressed by the support staff. The automation of repetitive tasks also increases the productivity of the employees, as they tend to be less productive while performing such tasks. The usage of chatbots makes the operations more cost-effective. Hiring employees for customer support and query handling comes at a high cost as more manpower is required to handle the queries received from the customers. This, in turn, increases the cost incurred by the company to a great extent. Chatbots help resolve this issue which has been there for a long period of time. A single bot can manage thousands of customers and communicate simultaneously with them in an effective and efficient manner. Unlike humans, chatbots can handle high capacity in no time. This technology finds its application in the area of marketing as well, in cases where businesses rely on data-driven decision making. Chatbots apply their machine learning capabilities to collect data from customers more efficiently. They study consumer behavior such as buying decisions, consumption patterns, media habits, preferences and goods purchased, which enables the marketers to gain insights about the market as well as understand their customers better, and subsequently develop strategies, products or campaigns that cater to their target audience. They also communicate with multiple people at a time via messaging apps and collect data from them, which saves human effort, time and money.
Some businesses utilize the potential of chatbots to improve customer experience, in their order processing. Companies like Domino’s and Taco Bell use chatbots to engage with their customers and process their orders with ease. They are programmed to offer add-ons for their order and replace one ingredient with another. They can also place orders based on the customer’s order history. Similarly, this technology is applied in e-commerce as well. It offers customers a better
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experience in terms of online shopping, customer service and product selection. For instance, customers can now tell the bot what they require or the criteria that they have, instead of browsing the website until they find what they have been looking for; the bot would extract and list all the items that match their criteria. Today, businesses are looking to develop apps in order to engage with their customers. However, the cost to develop an app that is efficient and customer friendly is significantly high. On the other hand, the chatbots utilize messaging apps like WhatsApp and Facebook Messenger that are widely used, instead of developing a unique app. Hence, if this technology continues to evolve, chatbots might even replace smartphone apps in the near future. References: www.comparethecloud.net www.marutitech.com www.chatbotslife.com www.blog.appliedai.com
By Akshay Nandan R PG CORE (2018-20)
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Quant Sub Article Monetization of Data
What does one mean by monetization of data? Monetization of data is the process by which a business entity can generate economic benefits from the available sources of data. Data monetization leverages the advantage of data not only collected directly through operations but also through data connected by sensors and other entities participating in the operations. Collection of data through indirect channels can add a lot of benefits to the business entities aiming to solve abstract business problems or firms involved in qualitative market research such as Kantar Millward Brown and Neilson. There are 3 ethical and regulatory groups involved in data monetization: 1. Individual data creator: This entity generates files and records through their own efforts. They could also be the owner of a device (E.g. a sensor or a mobile phone) that generates data. This entity claims the ownership of the data. 2. The business entity: This entity generates data during its operations. 3. Internet platforms and service providers: E.g. Google or Facebook. These platforms or service providers require a user to forgo some ownership interest in their data in exchange for use of the platform. Once the individual entity forgoes the ownership of the data, these platforms claim ownership of the data. The benefits of monetizing data 1.
This would help in improving decision-making by making real-time decisions, i.e. used in the case of Amazon which would be explained shortly.
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By monetizing data, companies could increase their profits by decreasing the cost involved in obtaining extra data from alternative sources due to improvements in inferential techniques. 3. This would also help companies target their products to a specific market segment. 2.
Taking Amazon as an example Amazon provides an online shopping platform for their customers. Here a customer searches some item on the Amazon website. Based on the searches made by the customer, Amazon would track their searching patterns and would then suggest the customers with alternative options. By doing so, Amazon provides the customers with a variety of options. This increases the chances of the customer to buy a product from their platform. The above example would be a case of Amazon monetizing the search options of the individuals. Monetizing data collected indirectly from various sources is the biggest research point for the tech companies and Market research companies moving forward since business problems are becoming more abstract due to faster changes in need of customer demands (especially in the technology side such as mobile phones and laptops).
Fig.1. Utility data monetization framework Future Areas where data monetization could be used 1. FMCG companies aiming to sell healthier snack options to the fitness conscious consumers.  Here data monetization can be used to track the buying patterns of these consumers in online sights. 2. Financial companies and brokers could use data monetization which would help their clients for investment planning and portfolio management.  Depending on the data collected from their clients, alternative investment plans could be suggested to them.
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Challenges to data monetization for Internet Platforms and Service providers With the recent controversies emerging from these platforms (e.g. Facebook which was involved in the Cambridge Analytica controversy) and stricter government regulations would be some of the challenges faced by these giant tech companies. Recently the Indian government has launched a policy for companies such as Visa, MasterCard and American Express to create data centers in India which would prevent Indian data entering the data centers of other countries. This would be a big challenge to these tech companies who would be monetizing Indian citizen’s data. With individuals now being educated upon the impact of privacy through various government initiatives, Tech companies would be required to find out alternative ways for leveraging the indirect data to improve the compliance with the laws of the country. References: https://www.indigoadvisorygroup.com/blog/monetizing-utility-datawww.marutitech.com https://www.cleverbridge.com/corporate/three-approaches-to-monetizing-data/
By Abhishek Bawa PG CORE (2018-20)
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Quant Guru Harish Chandra (1923-1983) Harish Chandra was born on 11th October 1923 at Kanpur. Kanpur is small industrial town near Allahabad. He took his university education at B.N.S.D College, Kanpur and at the University of Allahabad, during this period he developed his interest for physics. Later on he studied Paul Dirac’s treatise on Quantum Mechanics. He was awarded his master’s degree in 1943 after that he decided to go to Bangalore and work further on theoretical physics. After a short period of time, Harish Chandra went to Cambridge and started his Ph.D. under Paul Dirac’s guidance. Here, he started to develop affection for Mathematics. During his tenure at Cambridge, he attended lectures of Wolfgang Ernst Pauli. During one of those lectures he pointed out a small mistake in Pauli’s work and after that they became lifelong friends. In 1947, he received his Ph.D. and after that he went to USA. Paul Dirac visited Princeton for one year and Harish Chandra worked as his assistant during this time. He was greatly influenced by works of Hermann Weyl and Claude Chevalley, both great mathematicians of their age. From 1950 to 1963, he was at the Columbia University and during this time he was very productive. He worked on semisimple lie groups and had close contacts with Andre Weil. He became a member of National Academy of Science of the USA and Fellow of the royal Society in year 1973. He received the Cole Prize of the American Mathematical Society in 1954. Harish Chandra worked at the Institute for Advanced Study at Princeton from 1963. He was appointed as IBM Von Neumann Professor in year 1968. The National Science Academy honored him with the Srinivasa Ramanujan Medal in year 1974. After this, he received Padma Bhushan – The Indian Civilian honour in 1977. In 1981, Yale University gave him an honorary degree. He died on October,16th 1983 due to a heart attack. Before that, he had survived three such life threatening cardiac attacks. Harish-Chandra's c-function
c (λ) = cs0 (λ) (Where cs0 represents Harish Chandra’s c-function) Harish Chandra contributed to Mathematics in various fields, but c-Function derived by him is a special Jewel. In his work on spherical functions on semi-simple Lie groups, Harish Chandra showed that these functions asymptotic behavior is governed by a certain meromorphic function c. While, he showed that the function determined the Plancherell measure for the spherical transform on G, it was found that this c-function plays many other roles in the representation theory of G and in analysis on various Homogeneous Spaces of G. References: http://www.nasonline.org/publications/biographical-memoirs/memoir-pdfs/harish-chandra.pdf https://link.springer.com/chapter/10.1007/978-94-011-1078-5_2 https://en.wikipedia.org/wiki/Harish-Chandra%27s_c-function
By Shubham Thakur PG - IB (2018-20)
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Curiosity Update ---This updates readers on space exploration around the world including our own ISRO’s efforts.
Cameras inspired by Mantis Shrimp vision help Autonomous Vehicles perform better To improve the efficiency of autonomous vehicles, scientists are taking inspirations from unlikely sources like “the sea”. The camera inspired by Mantis Shrimp vision, detects polarized light or light waves which vibrate in a single plane. It has around half a million sensors that capture a wide range of light and dark spots in a single frame, mimicking the vision of mantis shrimps. This is an important breakthrough as the camera can take a wider range of light intensities, measured in decibels, than other digital or polarized cameras. The camera size is quite small and would use many of the same parts as common digital camera, so its estimated cost is as little as $10. The new cameras pick up a higher level of detail bringing other cars, pedestrians and bicyclists more clearly into view.
ISRO-Space Technology Incubation Center(S-TIC) A new Space Technology Incubation Center(S-TIC) has recently been inaugurated in Agartala, Tripura. The new incubator will bring India’s most talented minds together to work on cutting edge technologies useful for space industry. It will focus on building rockets, communication satellites and remote sensing applications. It also will provide employment opportunities to students, particularly those who are in final year and thinking about a startup enterprise in space technologies. ISRO Chairman K Sivan said that S-TIC will provide tremendous opportunities, and will help bring forth space-related innovation. One of the ideas developed in Agartala center could be a part of the 2022 Gaganyaan mission.
By Saumya Joshi PG CORE (2018-20)
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Quant News Digest Seven Chatbot building platforms from India that are revolutionizing businesses With chatbots gaining mainstream adoption in every domain and revolutionizing humancomputer interactions, these virtual assistants have begun to transform the customer service landscape in India. Not only is it making the execution of a task easier, it has brought a convenience in the way queries are solved. Reference: https://www.analyticsindiamag.com/7-chatbot-building-platforms-from-india-thatare-revolutionising-businesses/
Artificial Intelligence: The values that should guide the AI revolution Advanced artificial intelligence algorithms have the ability to take over tasks traditionally reserved for skilled human operators, such as driving a truck or performing a medical diagnosis. What once was the stuff of science fiction is now reality. This technology has made tremendous leaps in the last decade, yet it remains nowhere near its full potential. Reference: http://analytics-magazine.org/artificial-intelligence-the-values-that-should-guidethe-ai-revolution/
Data Operations problems created by deep learning Thanks to the dramatic uptick in GPU capabilities, gone are the days when data scientists created and ran models in a one-off manual process. This is good news because the one-off model was typically not optimized to get the best results. The bad news is that with an increase in the total number of models created—including iterations over time—the amount of data used as inputs and generated by the models quickly spirals out of control. The additional bad news is that there are a variety of complexities associated with model, data, job, and workflow management. Reference: http://www.dbta.com/BigDataQuarterly/Articles/Data-Operations-Problems-Created-by-DeepLearning-127412.aspx
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Text Mining 101: A stepwise introduction to topic modeling using latent Semantic Analysis (using Python) Have you ever been inside a well-maintained library? I’m always incredibly impressed with the way the librarians keep everything organized, by name, content, and other topics. But if you gave these librarians thousands of books and asked them to arrange each book on the basis of their genre, they will struggle to accomplish this task in a day, let alone an hour! Reference: https://www.analyticsvidhya.com/blog/2018/10/stepwise-guide-topic-modeling-latent-semanticanalysis/
Google Speech Vs Amazon Transcribe: The War of Speech Technology The text-to-speech technology has made our lives very easy. It is helping us save time and effort, and is delivering required information in a jiffy. This area of speech recognition technologies is being explored and empowered by tech giants Google and Amazon with the help of their products Google Speech and Amazon Transcribe respectively. Here we are listing a quick comparative analysis of both of them with respect to certain common features, as below. Reference: https://www.analyticsindiamag.com/google-speech-vs-amazon-transcribe-the-war-of-speechtechnology/
By Saumya Joshi PG CORE (2018-20)
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Mentor’s Corner Dr. Nilakantan Narasinganallur was invited for an information session on 3rd October, 2018 about Paul Wilmott’s Certificate in Quantitative Finance. The session was hosted by Alex Ferber- CQF learning Manager and led by Dr. Randeep Gug, director of the institute. Certificate in Quantitative Finance program run by Dr. Paul Wilmott is a Global standard in financial engineering. It is awarded by CQF institute and it is delivered by Fitch Learning. The program is constantly evolving to keep abreast with changes in industry. The program is delivered online by globally recognized experts twice a year in January and in June. The program includes: Three optional primers – refreshers ahead of the program. These preliminaries in mathematics, programming and finance cover the key concepts needed for quant finance. Six modules and advanced electives constitute the actual program with the tools and skills needed. Module one – consists of building blocks of quant finance, Module two – deals with topics related to Quantitative Risk and Return, Module three – covers concepts related to Equities and Currencies, Module four – has literature related to Data Science and Machine Learning, Module five – helps understand Fixed Income concepts, and Module six – Credit Products and Risks. Other than the six modules, there are also advanced electives which cover topics such as algorithmic trading, volatility modelling and risk management. Lifelong Learning library – which helps in keeping up to date throughout career. The learning library consists of over 850 hours of lectures on subjects related to finance with more content being added and updated regularly. To apply for the certification, one has to apply online on www.cqf.com/apply. The certification offers two study options: Full program – complete the program in six months Level I and Level II – complete the program in two three-month levels A final three-hour optional exam at the end of the program provides an opportunity for delegates who score 80% and above to receive distinction grade. The CQF alumni network provides a global networking opportunity as its community consist of people coming from diverse backgrounds and occupations dealing with variety of responsibilities. Dr. Nilakantan would be pleased to guide anyone who wants to find out more about the career options in quantitative finance and benefits of the Certificate in Quantitative Finance program.
By Tanmay Nikam PGDM FS (2018-20)
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Internship Diaries Savex Technologies Pvt Ltd is the 3rd largest Information and Communication Technology Distributor in India. Headquartered in Mumbai. Savex has 86 Sales offices and 42 Stocking locations across the country. My experience with Savex was a great learning curvature for me, it not only helped me to leverage the knowledge acquired during the course but also developed my logical thinking ability. Further I had great companions to learn from and got to interact with subsequent teams and departments. Understanding the coordination between them has given me a great insight on how an e-commerce business works. From the click of a button to place an order to the delivery at your doorstep is through heaps and lots of steps and activities performed by subsequent teams who work rigorously to get the right product to the right place at the right time. The company is very ethical and they will always respect your thoughts and ideas, this encouraged me to go even further and come up with some great suggestions and later I even worked with the teams to implement three of those recommendations. The selection process was quite smooth, the day started with a Pre Placement Addressable followed by questions and answers. The first round was an aptitude test which was pen and paper based out of which around 50 students were shortlisted for Group Discussions. GD topics were abstract, they basically check your communication and thought process during a GD. Post this there were around 20 students shortlisted for Personal Interviews, there was a panel a 3 members one of them was HR and other two were technical. In the interviews they test you on both Technical and ‘Fit for company’ attributes. Being Confident and ability to think on my feet helped me to crack it. All the best!
By Ashish Soni PGDM Core (2017-19)
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Quant Fun 1) An infection spreads among the squares of an nXn checkerboard in the following manner. If a square has two or more infected neighbors, it becomes infected itself. (Each square has 4 neighbors only!). Prove that you cannot infect the whole board if you begin with fewer than n infected squares.
2) There is a 6x8 rectangular chocolate bar made up of small 1x1 bits. We want to break it into the 48 bits. We can break one piece of chocolate horizontally or vertically, but cannot break two pieces together! What is the minimum number of breaks required? 3) We want to construct a structure made as follows: imagine that two long cylindrical pillars each with radius 1 intersect at right angles and their centers also intersect. What is the volume of this intersection? 4)
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Solution: 1) Not possible, if k<n. - Solution : The key observation here is that the total perimeter of all infected areas never increases. If we prove this then the answer to the riddle follows because n-1 cells have perimeter at most 4n-4 while the whole board requires 4n. Whenever a new cell gets infected it needed to be connected to at least two infected cells. Those two edges of the neighbouring cells disappear from the perimeter. And since our new cell has only 2 remaining edges no more than two new edges can be added to the perimeter. Thus there's no way for the length of the perimeter to increase. 2) 47- Solution : For a chocolate of size mxn, we need mn - 1 steps. By breaking an existing piece horizontally or vertically, we merely increase the total number of pieces by one. Starting from 1 piece, we need (mn-1) steps to get to mn pieces. Another way to reach the same conclusion is to focus on "bottom left corners of squares": Keep the chocolate rectangle in front of you and start drawing lines corresponding to cuts. Each cut "exposes" one new bottom left corner of some square. Initially, only one square's bottom left corner is exposed. In the end, all mn squares have their bottom left corners exposed. 3) 16/3 - Solution : If you cut the intersection by a horizontal plane at distance z from center, the cut will be a square with side-length 2*sqrt( 1-z^2). Integrate to get volume 16/3. Another way is to imagine the largest possible sphere inscribed at the center of intersection. The sphere should have a radius of 1. At each cut perpendicular to the z-axis, the circle from the sphere is inscribed in the square from the intersection as well, So Area of cut-circle = (Pi/4)*Area of cut-square. This is true for all z, hence Volume of sphere = (Pi/4)*Volume of Intersection, this also gives 16/3. 4)
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October 2018 Quantinuum, the Quant and Analytics committee of K.J. Somaiya Institute of Management Studies and Research aims to empower students and professionals alike to organize and understand numbers and, in turn, to make good and rational decisions as future managers. The newsletter published monthly consists of a gamut of articles for readers ranging from beginners to advanced learners so as to further enrich the young minds understand the contributions made to the field of mathematics along with a couple of brain- racking sections of Sudoku to tickle the gray cells. For any further queries and feedback, please contact the following address: K.J. Somaiya Institute of Management Studies and Research, Vidya Nagar, Vidyavihar, Ghatkopar East, Mumbai -400077 or drop us a mail at quriosity.quantinuum@gmail.com Mentor: Prof. N.S.Nilakantan (+919820680741) Email â&#x20AC;&#x201C; nilakantan@somaiya.edu Team Leaders: Purav Shah (+918511929416) VVNS Anudeep (+919441201685) Yatharth Jaiswal (+919969698361)
Editorial Team: VVNS Anudeep (+91 9441201685) Khushbu Mehta (+91 9930158610) Tanmay Nikam (+91 9699288587) Akshay Nandan R (+919176444022) Saumya Joshi (+91 9456684181) Abhishek Bawa (+91 9619995738) Kaustubh Karanje (+91 7738219050) Dhyan Baby K (+91 9809245308) Shubham Thakur (+91 7096045088)