MAKING CITIES SMARTER WITH AI

The past few years have witnessed how AI is slowly and steadily transforming many sectors including business, transportation, healthcare and security among many others. Many such applications can be applied to enhance the development of cities into smart cities, as we call it today, especially since rapid urbanization is creating the need for smarter solutions.

So what are smart cities? – According to Bismart, a smart city is a city that uses technology to provide services and solve city problems. A smart city does things like improve transportation and accessibility, improve social services, promote sustainability, and give its citizens a voice.

What impact does AI have?

With internet and storage becoming easily available and accessible, there is a large amount of data available that can be used for purposes like marketing or security. The growth of big data and cheaper computing infrastructure have also enabled the explosion of artificial intelligence (AI), machine and self learning, in software applications supporting every aspect of life.

One significant application of AI in a smart city is video surveillance. For example, closed circuit television (CCTVs) can be used for facial recognition. A reporter was tracked down using AI in the Chinese city of Guiyang in less than ten minutes, on December 2017. On similar lines, police officers in Zhengzhou are using ‘SMART’ AI glasses, to recognize criminal suspects and finding civilians with fake IDs. Internet of things allows devices like CCTV cameras and sensors to share data, increasing the efficiency of security not only in public places but also in private households as well.

AI today, is also being used to solve traffic issues – like adjusting the way traffic lights are metered, or building or closing roads.

Once humans come up with a solution, AI can be used to implement it at a much faster rate. AI can then be used to model the results of proposed measures. This also allows for corner cases to be better understood beforehand. Ideas that might have taken years to prove out and materialize can now be done in a matter of minutes.

Major tech-giants are investing millions on automatic driving. Driverless cars are being tested on the streets of major cities and their commercial production is not far away.

City authorities can use AI to work through huge quantities of data to test and deploy new initiatives to cope with demands for parking as well.

AI is now being used in healthcare to diagnose disease and improve public health. Robotic surgeries are becoming more popular due to its accuracy.

It is also bringing forth the 4th industrial revolution, with the manufacturing industry being transformed through AI. The sector is entering its next phase – Industry 4.0 – which is driven by automation, Internet of things (IoT) and cloud computing. The big players are already investing millions in computer intelligence, so that they can save time, money and resources while maximizing their production.

With so many applications available to improve infrastructure, companies and governments are not afraid of investing huge amounts in this venture powered by AI. These investments will make spread opportunity and make cities more convenient and sustainable.

Cities today are being transformed by technology. The next wave of disruption will involve major automation and breakthroughs in widespread areas, all with the power of AI.

This blog was written by our Content Writing Intern – Rona Sara George. Click on the name to view her LinkedIn profile.

Author: Xaltius (Rona Sara George)

This content is not for distribution. Any use of the content without intimation to its owner will be considered as violation.

ARTIFICIAL INTELLIGENCE – TRANSFORMING HUMAN RESOURCE

The fourth industrial revolution is bringing forward transformation powered by artificial intelligence in many sectors. The Human Resource department is no less affected.  While AI cannot replace the HR department as a whole, it can certainly bring forth massive improvement. Experts point out that many innovative methods using AI can be adopted to minimize unnecessary work load, while maximizing employee selection and their efficiency.  Machines can takeover tasks that are tedious and time consuming. It can also bring transparency and accuracy to many processes that are usually subject to discrimination. Thus, it would help make the process better and take informed decisions.

Data management and analytics

The data collected by the HR department of the corporates can be effectively managed using AI. Face-recognition and other technologies that are capable of identifying gender and measuring employees’ psychological and emotional traits can be used and the data generated can be used for analytics. Each employee’s performance can be analyzed in depth so that their employees will have a clear picture on who to keep and who to let go. Evaluating the workforce can bring about smarter decisions that will lead to better performance results.

Analyzing such data can predict the future ROI, increase or reduce engagement levels of employees, solve problems pertaining to completion of projects and other unforeseen glitches that would normally go un-noticed by the human eye. It can also provide insights to employees on how to work more efficiently.

The hiring process

Talent acquisition is one of the major areas where AI can be a blessing. An analysis of the resumes can put forward the best candidate for the job, with the algorithm giving importance to the factors that the company wants. Focusing on performance, culture and career-alignment analysis, AI can quickly identify whether or not a candidate is a good fit. AI will also be devoid of the biases based on race, gender or other factors that usually influence the process.

Replacing Administrative Tasks

Repetitive recruiting tasks such as sourcing resumes, scheduling interviews and providing feedback can be replaced by machines, giving the officials time to work on other matters. Conversational interfaces can be used instead of emails for communication. Chatbots can be used to answer real-time questions raised by either the employees or the customers.

AI can never replace this human driven sector completely, which places so much importance on personal relationships. AI will most likely never replace processes which involve connecting with top talent, providing a more personalized interview experience and establishing training and mentoring programs. In lieu of the above, Ben Peterson from BambooHR say that “increasing speed, quality and efficiency without sacrificing meaningful communication and relationships seem to be the right balance leading to the best possible outcome.”

This blog was written by our Content Writing Intern – Rona Sara George. Click on the name to view her LinkedIn profile.

Author: Xaltius (Rona Sara George)

This content is not for distribution. Any use of the content without intimation to its owner will be considered as violation.

RISE OF CONVERSATIONAL AI

Up until two years ago, chatbots were hailed as the next big trend. Thousands of chatbots flocked the market as they are relatively easy to build and could be controlled by a predefined flow. However, this trend began to wane when the chatbot could meet complex customer demands. It could only work for completing simpler commands like ordering or booking something.

Conversational AI was sought out in order to deal conversations that require a level of comprehension and cognition that goes far beyond the predefined flow of today’s chatbots. This is a form of Artificial Intelligence that allows people to communicate with applications, websites and devices in everyday, humanlike natural language via voice, text, touch or gesture input. Ram Menon, CEO of Awaamo, writes that “these platforms offer more than a natural language interface (NLI): they demonstrate true advancements in combining a variety of emerging technologies — everything from speech synthesis to natural language understanding (NLU) to cognitive and machine learning technologies — and are capable of replacing humans in a variety of tasks.”

Understanding the customer is the key.  Using advanced AI-driven conversational platforms such as Teneo, can result not only in an increase in customer satisfaction, but in the actionable data that conversational interfaces generate. Such conversational chatbots can understand the context and the sentiment behind the conversation. When conversational AI solution integrates with back-end data and third-party databases, a deeper personalization can take place. It also needs to be capable of creating detailed analysis of the chat logs in real-time to feedback into the conversation, improve and maintain the system and deliver actionable insights to the business.

The benefits of using Intelligent Conversational Interface

Intelligent conversational interfaces are the simplest way for businesses to interact with devices, services, customers, suppliers and employees everywhere. There are lots of companies that provide AI-driven conversational platforms specifically focused on high impact use cases, including IBM’s Watson and KAI.

Analysts predict rapid and sustained growth of Virtual Digital Assistants in the coming years. This growth underlines the strongly defined benefits that both consumers and enterprises see in conversational AI.

Giving the customers the best experience and analyzing the data garnered can increase the profits of the company.  Businesses can also cut down on costs by using AI-driven chatbots for automating many tasks such as customer service. As cost benefits continue to pile up, the trend will accelerate in 2018.

This blog was written by our Content Writing Intern – Rona Sara George. Click on the name to view her LinkedIn profile.

Author: Xaltius (Rona Sara George)

This content is not for distribution. Any use of the content without intimation to its owner will be considered as violation.

INDUSTRY 4.0 AND AI

There are many factors that spike up the production costs of a company. In manufacturing, ongoing maintenance of production line machinery and equipment represents a major expense, having a crucial impact on the bottom line of any asset-reliant production operation. Manufacturing companies are finding it increasingly harder to maintain high levels of quality. Bringing out the best product takes time as well as large human resources. But all that is set to change.

Introducing – The Fourth Industrial Revolution

The fourth industrial revolution, powered by technology is remolding the industrial sector, helping businesses achieve more profits and more efficiency. It has had a massive impact on the manufacturing sector. The sector is entering its next phase – Industry 4.0 – which is driven by automation, Internet of things and cloud computing. The big players are already investing millions in computer intelligence, so that they can save time, money and resources while maximizing their production. The Manufacturer’s Annual Manufacturing Report 2018 found that 92% of senior manufacturing executives believe that ‘Smart Factory’ digital technologies – including Artificial Intelligence – will enable them to increase their productivity levels and empower staff to work smarter.

How is the Manufacturing Sector using Artificial Intelligence?

Through computer vision, machines can be powered to pay attention to the tiniest of details, far beyond a man’s potential. Landing.ai, a startup formed by Silicon Valley veteran Andrew Ng, has developed machine-vision tools to find microscopic defects in products such as circuit boards, using a machine-learning algorithm trained on remarkably small volumes of sample images. If it spots a problem or defect, it sends an immediate alert, an AI process known as “automated issue identification.”

Artificial intelligence can also be used to monitor the whole process of manufacturing. Siemens, one of the leading manufacturing companies on the planet, did just that. They embarked on a digitalization strategy of which one of the major goals was Overall Equipment Efficiency. In late 2017, the company announced the latest version of its IoT operating system, MindSphere. Physical machines can be connected to Mindsphere cloud environment, enabling it to build the application that visualizes the various metrics that plant managers need to monitor in 2018. It also gives the resources needed to build an industrial IoT system in a fraction of the time it would take to set up a physical environment.

General Electrics is yet another leader in the manufacturing sector that has adopted the ai strategy. In 2015 GE launched its Brilliant Manufacturing Suite for customers, which it had been field testing in its own factories. The system takes a holistic approach of tracking and processing everything in the manufacturing process to find possible issues before they emerge and to detect inefficiencies. GE claims it improved equipment effectiveness at this facility by 18 percent.

It is powered by Predix, their industrial internet of things platform. In the manufacturing space, Predix can use sensors to automatically capture every step of the process and monitor each piece of complex equipment. You can view a short video of how its done here.

Another application of Ai is the use of generative design. Designers or engineers input design goals into generative design software, along with parameters such as materials, manufacturing methods, and cost constraints. Software explores all the possible permutations of a solution, quickly generating design alternatives. It tests and learns from each iteration what works and what doesn’t. From the many solutions that are put forward, the designers or engineers filter and select the outcomes that best meet their needs. This can lead to major reductions in cost, development time, material consumption and product weight. Airplane manufacturer Airbus used generative design to reimagine an interior partition for its A320 aircrafts and came up with an intricate design that ultimately shaved off 45 percent (30kg) of the weight off the part.

Such applications bring down labor costs, reduce product defects, shorten unplanned downtimes, improve transition times and increase production speed. It all comes down to an optimal manufacturing performance. If manufacturers do not invest in the long term and ignore advancing technologies, then their profits would be affected, as prices of products as well as the raw materials would only go up. However, it is not late yet as the field artificial intelligence is constantly evolving.

This blog was written by our Content Writing Intern – Rona Sara George. Click on the name to view her LinkedIn profile.

Author: Xaltius (Rona Sara George)

This content is not for distribution. Any use of the content without intimation to its owner will be considered as violation.

{R BOOTCAMP}

R is a tool which has been used over a long period of time and still continues to be used by both students and industries in the fields of statistics and data science. R continues to be important because of its versatality in these fields, especially in data exploration.

Xaltius conducted an R Bootcamp for the students of Yale-NUS to prepare them for their internal hackathon, Datathon. More than a 150 students were trained on R over the span of three workshops.

Through this R bootcamp, the students learnt how to do the following:

  • Webscraping using various R libraries and cleaning the scraped data.
  • Relational data cleaning and exploration through Exploratory data analysis.
  • Data Visualization using ggplots and plotly.
  • How business questions should be asked and given data how to approach the solution?

The students learnt the above through intensive hands-on during the sessions and self-practice. We received tremendous positive feedback and response from Yale-NUS for taking up these sessions.

If you are interested conduct such workshops and talks for your institution or be part of one, please get in touch with us.

Page 3 of 1112345...10...Last »