Monthly Archives: March 2017

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As robots continue to play a growing role in our daily lives, white collar jobs in many sectors including accounting and financial operations are quickly becoming a thing of the past. Business are gravitating towards software to automate bookkeeping tasks, saving considerable amounts of both time and money. In fact, since 2004, the number of full-time finance employees at large companies has declined a staggering 40% to roughly 71 employees for every $1 billon of revenue,down from 119 employees, according to a report by top consulting firm The Hackett Group.

These numbers show that instead of resisting change, companies are embracing the efficiencies of this new technology and exploring how individual businesses can leverage automation and, more importantly, artificial intelligence aka robots. A quick aside on the idea of robots versus automation. As technology becomes more sophisticated and particularly with the use of Artificial Intelligence (AI) were able to automate multiple steps in a process. The concept of Robotic Process Automation (RPA) or robots for short has emerged to capture the notion of more sophisticated automation of everyday tasks.

Today, there is more data available than ever and computers are enhancing their capabilities to leverage these mountains of information. With that, many technology providers are focusing on making it as easy as possible for businesses to implement and utilize their solutions. Whether its by easing the support and management burden via Software as a Service (SaaS) delivery or more turn-key offerings that embed best practices in the solution, one can see a transformation from simply providing tools to providing a level of robotic automation that seems more like a service offering than a technology.

Of course, the name of the game for any business is speed, efficiency, and cost reduction.It is essential to embrace technologies that increase efficiency and savings because, like it or not, your competitors will. While there are some companies that stick with the old-school approaches, they end up serving small niches of customers and seeing less overall growth.

As long as the technology-based solution is less expensive and performs equally as well, if not better than alternative options, the market forces will drive companies to implement the automated technologies. In particular, the impact of robotic artificial intelligence (AI) is here to stay. In the modern work environment, automation means much more than just compiling numbers but making intelligent observations and judgements based on the data that is reviewed.

If companies and businesses want to ensure future success, its imperative to accept and embrace the capabilities provided by robots. Artificial intelligence wont always be perfect but it can dramatically improve your work output and add to your bottom line. Its important to emphasize that the goal is not to curtail employees but to find ways to leverage the robots toautomate everyday tasks or detail-oriented processesand focus the employees on higher-value activities.

Lets use an example: controlling spent in Travel & Expense (T&E) by auditing expense reports. When performing an audit, many companies randomly sample roughly 20% of expense reports to identify potential waste and fraud. If you process 500 expense reports in a month then 100 of those reports would be audited. The problem is less than 1% of these expense reports contain fraud or serious risks (cite SAR report), meaning the odds are that 99% of the reports reviewed were a waste of time and resources and the primary abuser of company funds most likely went unnoticed.

By employing a robot to identify risky looking expense reports and configuring the system to be hyper-vigilant, it has been shown that a sufficiently sophisticated AI system will flag 7% of the expense reports for fraud, waste, and misuse. (7% is the average Oversight Systems has seen across 20 million expense reports) If we look back to our previous example this means that out of 500 expense reports, employees would only have to review 35 instead of the 100 reports that would have been audited. Though these are likely not all fraudulent, they may provide other valuable information such as noting when an employee needs to be reminded about company travel policy.

While it may sound like robots are eliminating human jobs, its important to note that they can also be extremely valuable working collaboratively with employees. Although the example above focused on fraud, the same productivity leverage is available regarding errors, waste, misuse in financial processes, etc. With the help of robots, we can spend less time hunting for issues and more time addressing them. By working together with technology, the employee has a higher chance of rooting out fraud and will have the bandwidth to work with company travelers to influence their future behavior.

It is clear that in order to ensure future profitability, it is crucial for businesses to understand and take advantage of the significant role that robots can play in dramatically enhancing financial operations.

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How Artificial Intelligence Is Changing Financial Auditing - Daily Caller

Although China could initially only observe the advent of the Information-Technology Revolution in Military Affairs, the Peoples Liberation Army might presently have a unique opportunity to take advantage of the military applications of artificial intelligence to transform warfare. When the United States first demonstrated its superiority in network-centric warfare during the first Gulf War, the PLA was forced to confront the full extent of its relative backwardness in information technology. Consequently, the PLA embarked upon an ambitious agenda of informatization (). To date, the PLA has advanced considerably in its capability to utilize information to enhance its combat capabilities, from long-range precision strike to operations in space and cyberspace. Currently, PLA thinkers anticipate the advent of an intelligentization Revolution in Military Affairs that will result in a transformation from informatized ways of warfare to future intelligentized () warfare. For the PLA, this emerging trend heightens the imperative of keeping pace with the U.S. militarys progress in artificial intelligence, after its failure to do so in information technology. Concurrently, the PLA seeks to capitalize upon the disruptive potential of artificial intelligence to leapfrog the United States through technological and conceptual innovation.

For the PLA, intelligentization is the culmination of decades of advances in informatization. Since the 1990s, the PLA has been transformed from a force that had not even completed the process of mechanization to a military power ever more confident in its capability to fight and win informatized wars. Despite continued challenges, the PLA appears to be on track to establish the system of systems operations () capability integral to integrated joint operations. The recent restructuring of the PLAs Informatization Department further reflects the progression and evolution of its approach. These advances in informatization have established the foundation for the PLAs transition towards intelligentization. According to Maj. Gen. Wang Kebin (), director of the former General Staff Department Informatization Department, Chinas information revolution has been progressing through three stages: first digitalization (), then networkization () and now intelligentization (). The PLA has succeeded in the introduction of information technology into platforms and systems; progressed towards integration, especially of its C4ISR capabilities; and seeks to advance towards deeper fusion of systems and sensors across all services, theater commands and domains of warfare. This final stage could be enabled by advances in multiple emerging technologies, including big data, cloud computing, mobile networks, the Internet of Things and artificial intelligence. In particular, the complexity of warfare under conditions of intelligentization will necessitate a greater degree of reliance upon artificial intelligence. Looking forward, artificial intelligence is expected to replace information technology, which served as the initial foundation for its emergence, as the dominant technology for military development.

Although the PLA has traditionally sought to learn lessons from foreign conflicts, its current thinking on the implications of artificial intelligence has been informed not by a war but by a game. AlphaGos defeat of Lee Sedol in the ancient Chinese game of Go has seemingly captured the PLAs imagination at the highest levels. From the perspective of influential PLA strategists, this great war of man and machine () decisively demonstrated the immense potential of artificial intelligence to take on an integral role in command and control and also decisionmaking in future warfare. Indeed, the success of AlphaGo is considered a turning point that demonstrated the potential of artificial intelligence to engage in complex analyses and strategizing comparable to that required to wage warnot only equaling human cognitive capabilities but even contributing a distinctive advantage that may surpass the human mind. In fact, AlphaGo has even been able to invent its own, novel techniques that human players of this ancient game had never devised. This capacity to formulate unique, even superior strategies implies that the application of artificial intelligence to military decisionmaking could also reveal unimaginable ways of waging war. At the highest levels, the Central Military Commission Joint Staff Department has called for the PLA to progress towards intelligentized command and decisionmaking in its construction of a joint operations command system.

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The Next US-China Arms Race: Artificial Intelligence? - The National Interest Online

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Why Is Poker Harder Than Chess Or Go For Artificial Intelligence? Forbes How is poker harder than chess or Go for AI? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. Answer by Aaron Brown, Risk Manager at AQR Capital ...

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Why Is Poker Harder Than Chess Or Go For Artificial Intelligence? - Forbes

The next time you shop on fashion website Myntra, you might end up choosing a t-shirt designed completely by a softwarethe pattern, colour and texture without any intervention from a human designer. And you would not realise it. The first set of these t-shirts went on sale four days ago. This counts as a significant leap for Artificial Intelligence in ecommerce.

For customers, buying online might seem simpleclick, pay and collect. But it's a different ballgame for e-tailers. Behind the scenes, from the warehouses to the websites, artificial intelligence plays a huge role in automating processes. Online retailers are employing AI to solve complex problems and make online shopping a smoother experience. This could involve getting software to understand and process voice queries, recommend products based on a person's buying history, or forecast demand.

SO WHAT ARE THE BIG NAMES DOING? "In terms of industry trends, people are going towards fast fashion. (Moda) Rapido does fast fashion in an intelligent way," said Ambarish Kenghe, chief product officer at Myntra, a Flipkart unit and India's largest online fashion retailer.

The Moda Rapido clothing label began as a project in 2015, with Myntra using AI to process fashion data and predict trends. The companys human designers incorporated the inputs into their designs. The new AI-designed t-shirts are folded into this label unmarked, so Myntra can genuinely test how well these sell when pitted against shirts designed by humans.

Also Read: AI will help answer queries automatically: Rajeev Rastogi, Amazon

"Till now, designers could look at statistics (for inputs). But you need to scale. We are limited by the bandwidth of designers. The next step is, how about the computer generating the design and us curating it," Kenghe said. "It is a gold mine. Our machines will get better on designing and we will also get data."

This is not a one-off experiment. Ecommerce, which has a treasure trove of data collected over the last few years is ripe for disruption from AI. Companies are betting big on AI and pouring in funds to push the boundaries of what can be done with data. "We are applying AI to a number of problems such as speech recognition, natural language understanding, question answering, dialogue systems, product recommendations, product search, forecasting future product demand, etc.," said Rajeev Rastogi, director, machine learning, at Amazon.

An example of how AI is used in recommendations could be this: if you started your search on a retailers website with, say, a white shirt with blue polka dots, and your next search is for an shirt with a similar collar and cuff style, the algorithm understands what is motivating you. "We start with personalizationit is key. If you have enough and more collection, clutter is an issue. How do you (a customer) get to the product that you want? We are trying to figure it out. We want to give you precisely what you are looking for," said Ajit Narayanan, chief technology officer, Myntra.

A related focus area for AI is recommending the right sizes as this can vary across brands. "We have pretty high return rates across many categories because people think that sizes are the same across brands and across geographies. So, trying to make recommendations with appropriate size is another problem that we are working on. Say, a size 6 in Reebok might be 7 in Nike, and so on," Rastogi said in an earlier interview with ET.

Myntra uses data intelligence to also decide which payment gateway is the best for a transaction.

"Minute to minute there is a difference. If you are going from, say, a HDFC Bank card to a certain gateway at a certain time, the payment success rate may be different than for the same gateway and for the same card at a different time, based on the load. This is learning over a period of time," said Kenghe. "Recently, during the Chennai cyclone, one of the gateways had an outage. The system realised this and auto-routed all transactions away from the gateway. Elsewhere, humans were trying to figure out what happened.

SUPPORT FROM AI SPECIALISTS A number of independent AI-focused startups are also working on automating manually intensive tasks in ecommerce. Take cataloging. If not done properly, searching for the right product becomes cumbersome and shoppers might log out.

"Catalogues are (usually) tagged manually. One person can tag 2,000 to 10,000 images. The problem is, it is inconsistent. This affects product discovery. We do automatic tagging (for ecommerce clients) and reduce 90% of human intervention," said Ashwini Asokan, chief executive of Chennai-based AI startup Mad Street Den. "We can tag 30,000 images in, say, two hours."

Mad Street Den also offers a host of other services such as sending personalised emails to their clients' customers, automating warehouse operations and providing analysis and forecasting.

Gurugram-based Staqu works on generating digital tags that make searching for a product online easier. "We provide a software development kit that can be integrated into an affiliate partner's website or app. Then the site or app will become empowered by image search. It will recognise the product and start making tags for that," said Atul Rai, cofounder of Staqu, which counts Paytm and Yepme among clients. Staqu is a part of IBM's Global Entrepreneurship Program.

The other big use of AI is to provide business intelligence. Bengaluru-based Stylumia informs their fashion retailer clients on the latest design trends. "We deliver insights using computer vision, meaning visual intelligence," said CEO Ganesh Subramanian. "Say, for example, (how do you exactly describe a) dark blue stripe shirt. Now, dark blue is subjective. You cannot translate dark blue, so we pull information from the Net and we show it visually."

In product delivery, algorithms are being used to clean up and automate the process.

Bengaluru-based Locus is enabling logistics for companies using AI. "We use machine learning to convert (vaguely described) addresses into valid (recognizable) addresses. There are pin code errors, spelling mistakes, missing localities. Machine learning is critical in logistics. We even do demand predictions and predict returns," said Nishith Rastogi, chief executive of Locus, whose customers include Quikr, Delhivery, Lenskart and Urban Ladder.

Myntra is trying to use AI to predict for customers the exact time of product delivery. "The exact time is very important to us. However, it is not straightforward. It depends on what time somebody placed an order, what was happening in the rest of the supply chain at that time, what was its capacity. It is a complicated thing to solve but we threw this (challenge) to the machine," said Kenghe. "(The machine) learnt over a period of time. It learnt what happens on weekends, what happens on weekdays, and which warehouse to which pin code is (a product) going to, and what the product is and what size it is. It figured these out with some supervision and came up with (more accurate delivery) dates. I do not think we have perfected it, but it is a big deal for us."

THE NEXT BIG CHALLENGE One of Myntra's AI projects is to come up with a fashion assistant that can talk in common language and recommend what to wear for various occasions. But "conversational flows are difficult to solve. This is very early. It will not see the light of the day very soon. The assistants first use would be for support, say (for a user to ask) where is my order, (or instruct) cancel order," said Kenghe.

The world over, conversational bots are the next big thing. Technology giants like Google and Amazon are pushing forward research on artificial intelligence. "As we see (customer care) agents responding (to buyers), the machine can learn from it. The next stage is, a customer can say 'I am going to Goa' and the assistant will figure out that Goa means beach and give a list of things (to take along)," Kenghe said.

While speech is one crucial area in AI research, vision is another. Mad Street Den is trying to use AI in warehouses to monitor processes. "Using computer vision, there is no need for multiple photoshoots of products. This avoids duplication and you are saving money for the customer almost 16-25% savings on the operational side. We can then start seeing who is walking into the warehouse, how many came in, efficiency, analytics, etc. We are opening up the scale of operations," said Asokan.

Any opportunity to improve efficiency and cut cost is of supreme importance in ecommerce, said Partha Talukdar, assistant professor at Bengaluru's Indian Institute of Science, where he heads the Machine and Language Learning Lab (MALL), whose mission is to give a "worldview" to machines.

"Companies like Amazon are doing automation wherever they can... right to the point of using robots for warehouse management and delivery through drones. AI and ML are extremely important because of the potential. There are a lot of diverse experiments going on (in ecommerce). We will certainly see a lot of innovative tech from this domain."

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How online retailers are using artificial intelligence to make shopping a smoother experience - Economic Times