SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

Trade-off between Opaque and Transparent AI

AI can be classified into Opaque and transparent Systems. Opaque AI is the black box where it is not evident why AI operates in a certain way. Though it is effective,it just means that there is higher risk associated with predictions and insights. Transparent AI is when technology does explain how it reaches its decisions using data at hand.But a company often prefers opaque AI, if the insights provided help in actually growth of the company. The need for transparency is a constraint on AI. And opaqueness might prove more effective. There is a trade-off between the two. When GDPR comes into effect,banks in The EU will be legally obliged to explain how they operate. Opaque AI will not work here ,although it might be more effective.Businesses should be able to control the kind of AI to be used in a given situation,its ethics and accuracy. Read more at: https://cognitiveworld.com/articles/choosing-between-opaque-ai-and-transparent-ai

 

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Connected Car Network Transforming the Transportation Industry.

To improve road safety and to help build the infrastructure for self driving cars,government and private companies are coming together to build connected-car platforms. The Utah government has partnered with Panasonic on the smart road network. They will be working on installing sensors on road. These will collect and transmit data that will alert vehicles,staff and control traffic signal as well. CIRRUS,an IoT application program is the data platform used that assists data sharing among transport departments,network operations and vehicle information systems using V2X as a data source. This emerging technology will make roads safer and less congested.Carmakers too are working on the connected car network to incorporate them into their self driving cars. The market for vehicle connectivity is predicted to be huge. Read more at: https://www.aitrends.com/selfdrivingcars/connected-car-platforms-making-headway-microsoft-taking-a-lead-role/

 

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Artificial Intelligence: A powerful tool for mental health crisis

Mental health crisis is a matter of huge concern in recent times where one-fourth of the adult population is estimated to be affected by mental disorders. Depression alone affects roughly 300 million people around the globe, as stated by World Health Organization. Artificial Intelligence (AI) offers multiple opportunities to people suffering from mental disorders. Computational Psychiatry and specialized chatbots for counselling and therapeutic services are the two emerging fields where AI is expected to yield the biggest benefit. Computational Psychiatry combines multiple levels and types of computation with multiple types of data to improve understanding, diagnostics, prediction and treatment of mental disorders. Besides, AI can help researches discover physical symptoms of mental illness and track within the body the effectiveness of various interventions. Moreover chatbots provide immediate counselling services to the patients at a cost which is lower than seeing a psychiatrist or psychologist. This has expanded the coverage to a broader circle of people who require treatment. Thus the development of AI for mental health promises better access and better care at a cost that won’t break the bank. Read more at: https://datafloq.com/read/artificial-intelligence-for-mental-health/6558

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Machine learning and the future of beauty industry

Machine learning is progressively transforming the way we work, live and interact. It is effectively applied in almost all sectors with beauty industry being no exception. Machine learning can help the beauty industry in several ways. It is expected that computer vision would help recognize facial features, analyze the data obtained and come up with a prediction or conclusion about the appearance. At present, data scientists are working on AI systems that have the ability to understand human face. If it works out, we no longer require to physically test out new looks and products. Data analysis will lead to better cosmetics. Leveraging data means better, long-lasting formulas. Nowadays, startups and industry leaders are offering machine-based advice on finding one’s personal style. For instance, Sephora and Mira uses worldwide tests and computer vision helping customers choose the perfect combination of foundation, complexion, etc. Some businesses like Olay have developed applications to determine skin needs of customers and come up with personalized products. Thus Artificial Intelligence with its machine learning and computer vision can go a long way in ensuring customer satisfaction. Read more at: https://medium.com/sciforce/machine-learning-changing-the-beauty-industry-ab3a2fa0aaf

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Big Data in Economic Prosperity

Big Data, if utilized properly, is believed to become the historic driver of progress. It plays an important role in the fields of public security, healthcare, poverty, to name a few. Video surveillance and facial recognition using big data is far more effective than reviewing the footages manually, which can be erroneous. It also helps in avoiding cybersecurity threats. Predictive models using big data can predict for future attacks even before their occurrence. With the application of big data in healthcare sector, there has been a shift from treating illnesses to proactively maintaining our health and taking certain measure for preventive care. It plays an immense role in the education sector as well. By understanding the needs of each district, it gives schools the opportunity to build innovative educational techniques. Big data solves urban transportation problem by enabling government agencies develop alternate routes to ease traffic. It helps in alleviating the dangers of food scarcity. It is time to embrace big data as it opens up opportunities to encourage economic prosperity. Read more at: https://datafloq.com/read/5-applications-big-data-in-government/65

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Utilization of AI to refine the entertainment marketing strategies

Merging entertainment with data is a well-known concept. The marketers and content-creators have always focused on strategies that will resonate with the audiences and keep them engaged. Over the past few years, there has been an evolution of AI in the marketing strategies of content creators, brands, networks, etc. AI uses the deep learning algorithms that can digest, asses and contextualize unstructured data quickly to derive actionable insights. AI can analyze millions of pieces of content at a time, with the help of deep learning which is undoubtedly beneficial for the content creators and marketers. Deep learning helps in predicting whether a campaign will be successful even before it starts. Thus marketers are increasingly turning to deep learning algorithms to make better sense of the contents. Read more at: https://www.thedrum.com/industryinsights/2019/04/03/the-evolution-ai-entertainment-marketing

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Criminals making felonious use of Artificial Intelligence

Cyber criminals, also known as hackers, use computer systems to access business and personal information for malicious purposes. There is no doubt that criminals are the most creative people in the world and the development of Artificial Intelligence has only made them stronger. Since the tutorials and tools for its development is widely available in the public domain, AIs use for attacking purpose is hugely unrestrained. Machine learning poisoning is one of the ways for criminals to circumvent the effectiveness of AI. Today we live in a world of chatbots. Most people do not realize how much personal information AI-driven bots may know about them, which makes them easy prey for experienced cybercriminals. Moreover criminals could harness machine learning technology to sift through huge quantities of stolen records of individuals to create more targeted phishing emails. However the biggest fear remains in the fact that the fully unstoppable AI creature will seize the world one day. Thus AI security abuse must be prevented and humans being much better than machines must understand its cause and effect. Read more at: https://resources.infosecinstitute.com/criminals-can-exploit-ai/#gref

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Predictive Analytics helping retailers in customer retention

Predictive Analytics make predictions about the future events based on current data. These days retailers use it to determine the future needs of the customers. The biggest challenge faced by retailers today is customer retention. Predictive Analytics is bringing about a huge change in the retail experience altogether. Eminent retailers like Amazon is using predictive analytics to make customer recommendations based on purchasing history. Furthermore, development in Artificial Intelligence and machine learning is boosting its use. These developments in turn are helping the retailers gain a competitive edge. However tech giants like Google, Microsoft tend to keep the cutting-edge innovations for them. The new and innovative predictive analytics must level the playing field for small medium industries. Read more at: https://channels.theinnovationenterprise.com/articles/retail-reaping-rewards-predictive-analysis

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Revolutionizing Indian Agriculture with digital farming tools

Since the emergence of Green Revolution in the 1960s, Indian policies have focused on ensuring national food security. However the small and the marginal farmers suffered a lot as the Green Revolution policies failed to increase their income. This has resulted in an increase in farm indebtedness and distress leading to farmer suicides all over the country. Over the last few decades Indian agriculture has seen massive technological developments and opportunities. The recent policies focus on increasing farmer incomes through digital innovations to give the farmers greater access to technology, risk management, finance and markets. Digital innovations enable the farmers to have credits at lesser risk and cost. Digital extension services provide real-time advice to farmers .Among the innumerable obstacles faced by Indian farmers, some include distance from the market, dependence on moneylenders for access to capital, huge cost of transportation, etc. Digital solutions are seen as a way to overcome these obstacles by providing farmers transparency and unmediated market access. Thus digital innovations are greatly helpful in improving farmers’ livelihoods and Indian Agriculture as a whole by making it more market-oriented. Read more at: https://www.thehindubusinessline.com/opinion/the-digital-route-to-transforming-farm-sector/article26006290.ece

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MACHINE LEARNING OPTIMIZING CUSTOMER EXPERIENCE

Machine learning applies artificial intelligence to automatically learn and improve from experience without being explicitly programmed. Machine learning applications are generally applied to those areas which involve processing lots of a data; a field where humans aren’t well-equipped. Machine learning applies discovered insights in ways that can optimize the customer experience. Chatbots provide effective solutions by stimulating an interaction with a customer service representative or resolving simple inquiries. Machine learning helps chatbots learn when to give specific responses, from where to gather necessary information and most importantly when they should hand off a conversation to a human agent. Virtual assistants, with the help of machine learning focus on specific areas where they can provide assistance to the customers. In order to continually optimize, customer service needs measurable analytics. Machine learning can help add a predictive element to support analytics. Thus machine learning helps in delivering better customer experiences. Read more at: https://www.business2community.com/brandviews/zendesk/how-is-machine-learning-being-used-in-customer-service-02215814

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Predictive Analytics in the Oil and Gas Industry Increasing Transmission of Information

A new firm has stepped into the oil and gas industry that uses AI to convey real-time oil analytics to its users. It uses of satellite tracking data and reports from different organizations,including customs,JODI and statistical agencies to build its own database and draw insights. According to the founders, speed and accuracy is what makes the venture unique. The data is more reliable and AI helps in demand, supply analysis in seconds. Algorithms in predictive analytics can be used to forecast prices as well. This is where AI is superior to human,they have predictive abilities. Change in methods of gaining insights is coming from small ,focused and specialized solutions that come together to form a comprehensive solution. Read more at: https://oilprice.com/Energy/Energy-General/Robots-Take-Over-Oil-Trade-And-OPEC-Is-Scared-To-Death.html#

 

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reCaptcha V3: Boon or Curse?

Google’s internet bot detector has evolved over the years from Captcha to reCaptcha to reCaptcha V3. Now, no more boxes need to be checked, nor is identifying objects or alphabets required. Studying the way an individual navigates through a website, conclusions can be drawn on it being a bot or not. This improvement however comes in at the cost of the user’s privacy. According to a researcher, Google uses cookies to identify whether a user is a bot or not; the same cookies which enable us to open new tabs and open accounts without the need of logging in everytime. Another researcher however states that a browser connected with a Google account is more secure than the one which isn’t. Hence, although security is gained, more of the user’s data is also going into the hands of Google. Read more at: https://www.fastcompany.com/90369697/googles-new-recaptcha-has-a-dark-side

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How crowded will your bus be?

Google maps new features not only includes the updates of traffic, but also how crowded the public transport will be. Google has been asking people to fill up forms wherein they are asked about their departure time and number of seats available. This data helped the Google maps in predicting the peak time and the most populated stops. Similar study has been done about predicting the crowds at restaurants. Also, delays in bus and their expected time of arrival is notified by the Google maps, which are available on both Windows and iOS for almost 200 cities. Read more at https://techcrunch.com/2019/06/27/google-maps-can-now-predict-how-crowded-your-bus-or-train-will-be/

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Bots entering e-commerce

Walmart acquired Flipkart is one of the two biggest e-commerce platforms in India with eight million shipments per month on an average. With ever increasing speed of people coming online each day, Walmart new Automated Guided Vehicles (AGVs) will help in meeting these demands faster. This pilot project of sortation will be applied at Flipkart’s Soukya sortation center in Bangalore, where the 100 self-guided robots will sort the packages according to the delivery pin codes. While these AVGs are expected to increase efficiency by 60%, i.e. 4500 shipments in an hour, the easy mobility of the AVGs will always help Flipkart in expansion of supply chain operations. However, according to Jeff Bezos, AVGs won’t take away employment opportunities but only increase efficiency. Read more at https://www.businessinsider.in/flipkart-announces-delivery-robots-automation/articleshow/68493938.cms

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Create Value from Waste: How AI aids Waste Management.

Sensors, robots and vision systems have entered the recycling industry. They have improved the accuracy of segregating different types of plastics and items contaminated with food and other substances. The increased sorting rate is a bonus. One start-up is focused on recycling robots. Their system is trained by being shown millions of images. Its most recent dual robot system called Cortex can sort, pick and place items at 160 units per minute. The company has sold AI driven robots to a Japanese company to separate reusable materials such as electronic equipments. demolition debris and. Another start-up supplies sensors that provides information about moisture and chlorine levels. Their latest innovation is material sensor that can detect PET trays and a laser feature that can identify blank objects and silicon cartridges. Read more about the AI behind these innovations at: https://www.aitrends.com/ai-in-industry/ai-helping-recyling-industry-improve-accuracy-speed-sorting-rate/

 

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Classifying Artificial intelligence.

 

The field of AI is largely unexplored and we have only scratched the surface of what AI is really capable of.Understand the AI types will allow us to gain perspective on its capabilities and impacts in future.The degree to which an AI system can imitate human performance is used as a criterion for determining the type of AI.Based on this, AI is classified into two types-One type is based on classifying AI enabled machines based on their resemblance to the human mind , ability to think and feel.According to this system,the four types of AI are-reactive machines,limited theory machines,theory of mind and self aware AI.The second type of AI classification usually used in tech has three categories- Artificial Narrow Intelligence(ANI),Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI). Read more at: https://cognitiveworld.com/articles/7-types-artificial-intelligence

 

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Machine learning Applications in the growing e-Commerce Industry

E-commerce is one of the fastest growing industries globally that grew by 18% in 2018. E-commerce is data-driven but there is lack of knowledge and uncertainty in the sector. Several companies got together to address the hindrances and share their views on AI in e-commerce. The director of one of the companies says that AI applications is based on data and bringing out the best insights requires specialized softwares. Most of the time one AI model cannot serve all purposes .The introduction of machine learning here to spot patterns would be beneficial.Another application of AI was an app that allowed users to photograph an item and search for it in the companies database. Often data protection laws make it difficult to gain access to data . On the other hand,data might be available in plenty but companies dont know what questions should they seek to answer.Read more about the challenges and implementations of AI at: https://deepsense.ai/shadows-of-customers-on-the-wall-key-takeaways-from-the-ai-in-e-commerce-business-breakfast/?u

 

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Public-Private partnerships in exploring the applications of AI.

The AI World Government,a three-day forum that started on June 24th, gathered leaders in the government,academic and industrial sectors to exchange views on the challenges and possible benefits of AI in the automation. According to leading companies such as Gartner and McKinsey,AI has cognitive abilities,and tends to imitate human performance by learning, understanding complexities, predicting and providing solutions.Intelligence and defence government agencies are heavily relying on AI for its application and growth in the areas of healthcare, transport, commerce and administration. It is clear that the government is investing heavily and wants to explore the capabilities of AI .The methodology of developing tools and applications of AI came across as a public-private partnership supported by investment which is looking at combining human and computer power.

Read more at: https://www.aitrends.com/ai-in-government/government-an-integral-partner-for-exploring-ai/

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Data Management made less perturbing with Data Catalogs.

Big businesses have huge repositories of data.Each company is in the race to draw more value from this data so that they are not competed out.Data is unorganized,metadata initiatives have been falling and unearthing and extraction of data has become more difficult. Data protection regulations have exacerbated the problems.Lack of data management, renders data inefficient. IO Tahoe has published on Data Catalogs-a metadata management tool as a solution to this problem. The speed of AI coupled with human learning will help companies to overcome challenges of data management.There are several kinds of data catalogues and this report is a guide on which will be best for your company.

Read more at: https://insidebigdata.com/2019/06/18/ai-driven-data-catalogs-right-business/

 

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NEURAL NETWORKS: UNFOLDING THE BLACK BOX

The most powerful algorithms extensively used in the field of deep learning are neural networks. Here we focus on the artificial neural networks which are nothing but the computing system based on the structure of human brain. It is a type of machine learning which is used for detecting patterns in unstructured data. A lot of business applications today depend on neural networks to solve various complicated problems. However companies use neural networks in various ways. For instance, as explained by LinkedIn’s Deepak Agarwal, neural networks are used in LinkedIn along with text classifiers to detect spams. Neural networks are widely used in activities like marketing, finance, operations management, insurance etc. Thus the capabilities of artificial neural networks are inexhaustible. Read more at: https://www.cmswire.com/digital-experience/what-is-a-neural-network-and-how-are-businesses-using-it/

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