Artificial Intelligence in Telangana

Artificial Intelligence is the next big thing in the information technology sector. Artificial intelligence refers to the capability of a machine to analyze a situation and then make a decision based on its inherent logic and requirements. For example, self driving cars use real time artificial intelligence. When a smart car moves on the road, the hardware of the car gives real time feed to the car software about its surroundings. The brain of the car then itself decides the speed, direction and moves of the car based on the information it has. Given the immense potential and already proved applications of artificial intelligence, the government of Telangana has decided to boost this field in its state.

The Scope

Artificial intelligence is capable of absolutely altering the human-machine interactions. While most present day machines act as dumb objects, which respond to human commands, machines which run on artificial intelligence won’t need constant human attention. These machines will not only be capable of repairing and charging themselves on their own, the exciting part about these machines will be their ability to evolve like any other life form. This would mean that every next generation of machines will be more adept to the local requirements and modify itself accordingly without any direct human feedback. Given the fact that human beings are now aiming for inter-planetary missions within the next ten years and looking into the possibilities of starting a civilization on other planets outside earth, smart machines can definitely help humans in this process.

The Past

Telangana already has a strong infrastructure for the information technology sector. A hoard of multi national companies are based in Telanagana and the state has contributed significantly in the development of information technology.

The Present

The government of Telangana is tying up with the National Association of Software and Service Companies (NASSCOM) to set up a Centre of Excellence for Data Science and Artificial Intelligence centre in Hyderabad, the capital of Telangana. The government hopes that indigenous research in data science and artificial intelligence can make a huge social impact, specially in the public health sector. Artificial intelligence is already being used by several companies in the fields of transport, finance, data analysis and communication.  The government wants to consolidate and streamline the efforts in this direction by building state-of-the-art infrastructure for research in the fields of data science and artificial intelligence.

The government is investing around 40 crores rupees in a joint public private initiative to develop infrastructure for data science and artificial intelligence research. The local government wants to streamline the ongoing efforts in this direction and amplify the impact that the local professionals can create at the global level.

The future

The recent developments in data science, combined with the rise in the speed of computing, specially with growing potential of quantum computing, can alter the entire human machine interaction process in the coming future. It is expected that the artificial intelligence and data science industry is capable of generating billions of dollars in revenues by 2025. At the same time generate employment for around 150,000 professionals in the coming 10 years.

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How AI (Artificial Intelligence) Can Introduce Banking Reforms?

Banking in the contemporary world cannot be imagined without 2 words- digital disruption and problem loans. Both these are seen as separate matters. Only few realise that they must rather complement each other to create a synergistic effect.

Digital platforms and interfaces can be seen everywhere. These have completely modified the lives of banking staff and clients. Every bank tries to provide data analytics to facilitate customer interaction, revenue generation, enhancing productivity and Customer relationship management.

The operating model for banks is driven by the following factors:

1. Impact of technology especially open source technology
2. Analytics tools Eg. Hadoop
3. Artificial Intelligence systems
4. Internet of things (IOT)
5. Intuitive automation

Banks have initiated the digital drive. Investments and retail space are most prominent players. Corporate banking and risk management applications started off late. The most crucial problem in the Indian banking sector is the sluggish adoption of digitisation in problem loan areas. Everyday newspapers talk of the following aspects.

1. Recapitalisation models
2. Problem loans
3. Resolution through IBC and NCLT
4. Overleveraging

Why is RPA required in banking systems?

Though banks have access to digital platforms, there are many limitations in their functional efficiency. It is believed that adoption of robots will mitigate the lack of transparency. Robotic Process Automation (RPA) can target the deficits in banking sector and improve customer relationship management (CRM). Retail and consumer banking offers will be better communicated to customers.

Sources of errors in banking

The biggest sources of banking errors are their Non Performing Assets(NPA’s).The problems created by borrowers are

1. Cash misutilization
2. Non effective project management
3. Improperly designed corporate structure
4. Excess leverage

Banks on the other hand cause issues like

1. Divergent loan appraisal standards
2. Lack of common database
3. Dependence on imperfect business models
4. Lack of regular notification to statutory authorities.

Strategies for problem solving

Solution of such problems needs a rational and modern approach. Possible steps could be
1. Deploying standard open source and analytics tools/Dashboards

2. Distributing insights
3. Adopting AI for removing subjective appraisals or prejudiced decisions.
4. Loan management using Block Chain Technology

Scope for future improvements

Many banks have promptly responded to Early Warning Signals(EWS). They have invested in deployment of Big Data and Analytics for creating dashboards. However the application is manual at first level. Use of Robotic Process Automation with EWS analytics can help take quick steps to counter existing problems. Algorithmic models and analytics can trace patterns of fund pilferage from numerous points in BFSI. The application of RPA and Block Chain Technology will bring transparency, DBMS, reliability and accessibility in banking units.  In future, we may see the adoption of solution structures using Geotagging and NFC.
The inclusion of process enhancement and automated databases will augment efficiency in decision making. Documented analyses will be accessible for validation and audits. So the banker’s fear of proving accountability in a banker will be dissolved. Data Sciences and RPA can play significant roles in framing legislation’s or policy making.

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Artificial Intelligence Is Being Used For Detection Of Heart Diseases

Google is spearheading yet another interesting application of artificial intelligence: to predict the cardiovascular health of an individual. If this happens, it will be a breakthrough in the field of health care.

The methodology

Google has developed an artificial intelligence algorithm which can tell if a person is at a risk of contracting a heart disease by scanning a person’s retina. An article was published recently in the Nature journal Biomedical Engineering describing this research. Google collected retina scans and medical data of around three hundred thousand patients. Google then trained a deep learning algorithm they have developed to predict cardiovascular risks in any patient by feeding the retina scan and medical data to the algorithm.

Deep learning algorithms are self-learning algorithms which make correlations between the data that is fed to them. Based on the retina scan images and the medical data history of the respective patient, the algorithm teaches itself if there is any recurring correlation between the features of the retina visible in the scan and the medical history of the patient.

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This algorithm was then run on two completely independent datasets, one consisting of almost twelve thousand patients and the other of around thousand patients. The deep learning algorithm was systematically shown the retina scan of patients who had suffered a heart attack in the last five years and those who had a completely normal cardiac history. The algorithm successfully predicted seventy percent of the time the patients who have had a cardiac problem in recent history. This result was encouraging. However, a seventy percent success rate says that the deep learning algorithm is not robust enough yet to be used in day to day practical purposes.

Other applications

Same as retina scan, this methodology can also be applied to make correlations between data from a patients blood and their cardiovascular health. Depending on the blood data, Google artificial intelligence can predict heart diseases, as well as the possibility of an upcoming heart attack or heart stroke. It is also possible to tell if the patient smokes or not, their blood pressure, and their age group.

Lily Peng, an MD and  the lead researcher for this project at Google, is hoping to use artificial intelligence in other fields of medical diagnosis as well. She hopes that soon deep learning algorithms can be used for the prediction of cancer and its possible solutions.

The future of artificial intelligence in medical research

Lily Peng says that we should keep our expectations low at this point of time. A day where artificial intelligence can be used for medical diagnosis with certainty is still a few years away. The present accuracy is fairly low. However the present results show a lot of optimism for the future. Deep Learning algorithms get more and more smarter as more data is fed to them. Ms. Peng admits that the total data which has been fed to the present algorithm is still not enough.  As the number of data points fed to this algorithm increases, it will increase the accuracy of the predictions.

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