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7 Everyday Applications of AI

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7 Everyday Applications of AI

If you Google searched for “artificial intelligence” and somehow came across this article, you just made use of artificial intelligence. Or, if you hailed a cab through an app like Uber or Ola, you just made use of artificial intelligence. The science of AI is all around us, in the smallest aspects of our lives. We take a look at how AI impacts our everyday lives in amazing ways.

Google Maps and Ride-Hailing Applications

Till only recently GPS (Satellite-based navigation) was guiding us through. But now artificial intelligence has come in to revolutionize the game, enabling systems like Google Maps to know exact directions, the optimal route and even road barriers and traffic congestion. Cab hailing apps have also made use of this technology.

Face Detection and Recognition

Making use of virtual filters when taking pictures and using face ID to unlock phones are two of the applications of AI in everyday lives. The former uses face detection and the latter uses face recognition. Smart machines are taught to identify facial coordinates in pictures of faces to enable face detection and recognition features.

Text Editors or Autocorrect

When we type out something onto a word document, inbuilt auto-correct tools begin perusing our script for spelling mistakes or grammatical anomalies.

Artificially intelligent algorithms also use machine learning, deep learning, and natural language processing to identify incorrect usage of language and suggest corrections.

Search and Recommendation Algorithms

Smart recommendations systems, that power our music applications and ecommerce websites, learn user behavior and interests from online activities.

“The personalized experience is made possible by continuous training. The data is collected at the frontend (from the user), stored as big data and analyzed through machine learning and deep learning. It is then able to predict your preferences by recommendations that keep you entertained without having to search any further,” a report says.

Chatbots

Answering questions can be time consuming, especially if they are coming from a customer. Chatbots are taught to impersonate the conversational styles of human beings through NLP (Natural Language Processing) so they can answer customer queries and take and track orders. They will give the impression of a customer representative when, in fact, they are just another example of artificial intelligence.

Digital Assistants

The latest digital assistants are well acquainted with human language and incorporate advanced NLP and ML. “They understand complex command inputs and give satisfactory outputs. They have adaptive capabilities that can analyze your preferences, schedules, and habits. This allows them to systemize, organize and plan things for you in the form of reminders, prompts and schedules.”

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Social Media

Various social media applications are using the support of AI to control problems like cyber crime, cyber bullying, and hate speech. “AI algorithms can spot and swiftly take down posts containing hate speech a lot faster than humans could. This is made possible through their ability to identify hate keywords, phrases, and symbols in different languages. These have been fed into the system, which has the additional capability to add neologisms to its dictionary. The neural network architecture of deep learning is an important component of this process.”

So, you see how AI had come to influence more aspects of our lives than we could have imagined. This essay was brought to you by DexLab Analytics. DexLab Analytics is a premiere artificial intelligence training institute in Gurgaon.

 


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How AI Is Facilitating Digital Marketing

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How AI Is Facilitating Digital Marketing

Artificial Intelligence has transformed the world of digital marketing by making it ultra intelligent and intuitive. Almost every platform used by the digital marketer is powered by some form of AI or an AI-powered machine learning model.

If we were to define what AI marketing is, according to a report by Forbes, it is a method of leveraging technology to improve the customer journey. It can also be used to boost the return on investment (ROI) of marketing campaigns.

How AI Works In Marketing Strategies

AI plays a very important role in eliminating guesswork when it comes to customer interactions online like in email marketing. Big Data Analytics, machine learning and other related processes gain insights into target audience behaviour. “With these insights, you can create more effective customer touch points.”

Moreover, it is gradually automating processes that were once dependent on human beings. Content generation, PPC ads, and even web design and video marketing are all possible applications for AI marketing.

Marketing Campaigns

AI, in the world of digital marketing, can streamline and optimize marketing campaigns. “It can also eliminate the risk of human error”. It acts as a support system to shore up efforts born out of human ingenuity with its data driven reports and analyses.

While AI might be able to launch a marketing campaign all on its own, human attributes like empathy, compassion and the art of storytelling are still needed to shape up the soul of an online marketing campaign.

Content Generation And Curation

“At present, content marketing has ballooned into a global industry. It’s so prevalent that some refer to it as the only type of marketing.” Moreover, AI powered content marketing strategies are also becoming a rage.

AI can be used potentially for both curating and generating content. Already, companies are using AI for automated content generation at a basic level. But in the long run, “AI could generate viable topics for writers, or even develop initial drafts of content based on certain parameters”.

Digital Advertising

AI is also gradually transforming the way businesses advertise. In fact, today’s digital advertising strategies all have a basic level of AI powered models processing them.

AI works with the help of algorithms in its systems. “These systems operate autonomously, placing the right kinds of ads in front of the right kinds of people based on complex algorithms and big data.” This feature service is known as “programmatic advertising.”

Chatbots

Chatbots have become the latest game changer when it comes to the marketing industry. They are the first interface customers encounter on many websites today, giving the website a human touch, excelling at answering customers’ frequently asked questions.

“The key fascination with chatbots is the impact they can have on the customer experience. For some businesses, there aren’t enough employees or hours in the day to answer customer queries quickly. Chatbots allow customers to help themselves.”

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Behavior Analysis And Predictive Analytics

More and more companies are beginning to hire data scientists and programmers for their marketing departments. There “are so many data sets (on the Internet) that humans alone can’t possibly hope to analyze them all.”

“Using machine learning and big data analysis, AI is able to provide businesses with deep insights into their customer(s’ behaviour). Not only will businesses be able to hyper-personalize interactions, but…they’ll also be able to predict future customer behaviours based on the data collected.”

For more information on AI powered systems, do peruse the DexLab Analytics website today. DexLab Analytics is a premiere institute that offers artificial intelligence certification in Delhi NCR.

 


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How AI is used in Banking

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How AI is used in Banking

Artificial Intelligence has revolutionized the banking sector, transforming back end processes into faster mechanisms, making money transfers safer and back-end operations more efficient.

From fraud detection to customer service chatbots, AI is powering several banking wings. Here is a list of operations AI has been facilitating in banks across the world.

Customer Support & Front Office

Millennials have rendered brick and mortar banks dispensable. According to Business Insider, 40 per cent of this generation does not use the services extended in physical bank offices.

AI has come to the rescue, however, by powering chatbots and voice assistants in most major financial institutions. Kasisto, for example, is one such neo-banking institution that has been using AI to the hilt.

“Kasisto’s major contribution is its conversational AI platform, KAI, which banks can use to build their own chatbots and virtual assistants. It’s rooted in AI reasoning and natural-language understanding and generation, which means it can handle sophisticated questions about finance management that other bank customer-service digital assistants…can’t”, says a report.

Kasisto has supported and shored up AI assistants for several reputed banking institutions including the UAE-based digital bank Liv., DBS Bank, Standard Chartered Bank and TD.

“The bank’s KAI-based bot walks customers through how to make international transfers, block credit card charges and transfer you to human help when the bot hits a wall.”

Fraud Protection & Middle Office

Artificial Intelligence has truly transformed “middle office functions” – where banks manage risk and protect themselves from bad actors. These functions include fraud detection, anti-money laundering initiatives and customer identity verification.

“And sometimes that means incorporating AI into legacy, rules-based anti-fraud platforms. But some the most innovative and secure countermeasures are other, from-the-ground-up models, built by companies like the ones below.”

“Up to $2 trillion is laundered every year — or five percent of the global GDP, according to UN estimates.” The sheer number of investigations across the globe, coupled with the complexity of data and reliance on human involvement makes anti-money laundering (AML) difficult work.

AML processes also cost a lot. Ayasdi’s AI-powered AML incorporates three key advancements: “intelligent segmentation, or optimizing the data-sifting process to produce the fewest number of false positives; an advanced alert system, which auto-categorizes alert priorities; and advanced transaction monitoring, which uses machine learning to spot suspicious anomalies”.

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Lending And Risk Management

“AI holds real promise for more equitable credit underwriting — as long as practitioners remain diligent about fine-tuning the algorithms. 

Beyond credit scoring and lending, AI has also influenced the way banks assess and manage risk and how they build and interpret contracts.”

Denying credit to persons because of a class or racial bias is something that ails the banking industry across the world. ZestFinance’s“AI-based software purportedly generates fairer models, essentially by downgrading credit data that it has “learned” results in unfair decisions”.

For more on this, do peruse the DexLab Analytics website. DexLab Analytics is the premiere most artificial intelligence training institute in Gurgaon.

 


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How AI is Helping Tackle Climate Change

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How AI is Helping Tackle Climate Change

While the spread of the COVID-19 pandemic has become a bane for economies across the world, slowing down or bringing to a halt markets and trade, the series of lockdowns declared by states has had a positive impact on the environment.

According to China’s Ministry of Ecology and Environment, data recorded between January and March 2020 reflects an 84.5 per cent increase in days with good air quality in 337 cities, and satellite data from the United States National Aeronautics and Space Administration shows a decline in nitrogen dioxide over China.

This piece of news is certainly welcome. Climate change is one of the biggest crises ailing our world today, with scientists and stakeholders worried. However, technological advancements like those in the field of Artificial Intelligence are to a large extant helping tackle the crisis of climate change. Here is how.

Improved climate predictions

At the intersection of data science and climate science is the piece of technology called climate informatics.

It includes areas like“improving prediction of extreme events such as hurricanes, paleoclimatology, like reconstructing past climate conditions using data collected from things like ice cores, climate downscaling, or using large-scale models to predict weather on a hyper-local level, and the socio-economic impacts of weather and climate.”

AI can also uncover new insights from the massive amounts of complex climate simulations generated “by the field of climate modeling, which has come a long way since the first system was created at Princeton in the 1960s.”

Better predictions can help officials make informed climate policy, allow governments to prepare for change, and potentially uncover areas that could reverse some effects of climate change.

Revealing the effects of extreme weather

AI is helping scientists reveal to common persons the effects of extreme weather conditions so they can work towards reversing the effects.

“To make it (the effects) more realistic for more people, researchers from Montreal Institute for Learning Algorithms (MILA), Microsoft, and ConscientAI Labs used GANs, a type of AI, to simulate what homes are likely to look like after being damaged by rising sea levels and more intense storms.”

This was done to inculcate in people habits that are eco-friendly and ecologically sustainable.

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Measuring sources of carbon

By monitoring coal plant emissions with satellite imagery, Carbon Tracker, an independent financial think-tank, can use the data it gathers to convince the finance industry that carbon plants aren’t profitable.

“A grant from Google is expanding the nonprofit’s satellite imagery efforts to include gas-powered plants’ emissions and get a better sense of where air pollution is coming from.”

AI can help make analysis of power plants images automated to get regular updates on emissions. “It also introduces new ways to measure a plant’s impact, by crunching numbers of nearby infrastructure and electricity use. That’s handy for gas-powered plants that don’t have the easy-to-measure plumes that coal-powered plants have.”

For more on AI and its algorithms or related sciences, do peruse the DexLab Analytics website today. DexLab Analytics is a premiere artificial intelligence training institute in Gurgaon, India.

 


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Application of AI in 8 Business Functions

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Application of AI in 8 Business Functions

Artificial Intelligence has made advancements in various sectors of the economy. But it has not yet taken the business world by storm. Business leaders, however, are excited about implementing AI in their companies’ business functions to start reaping its benefits. Here is a list of ways in which AI and machine learning will impact business functions across the globe.

Marketing

AI can assist in working out business strategies as well as implementing them. “Already AI sorts customers according to interest or demography, can target ads to them based on browsing history, powers recommendation engines, and is a critical tool to give customers what they want exactly when they want it,” says a report. Also, AI is being used as a marketing tool in the form of chatbots. These chatbotshelp solve problems, suggest products or services, and support sales. Artificial intelligence also helps marketers build and make adjustments to marketing campaigns according to consumer behavior analyzed accurately by AI systems.

Sales

AI improves sales functions by improving forecasting, predicting customer needs, and improving communication.

Research and Development

AI can help analyze a large amount of information in industries like healthcare, pharmaceuticals, finance, and more. It can help us research problems and find solutions to them efficiently and accurately. “AI can automate many tasks, but it will also open the door to novel discoveries, ways of improving products and services as well as accomplishing tasks. Artificial intelligence helps R&D activities be more strategic and effective.”

IT Operations

Also known as AIOps, AI for IT operations is the application of AI and machine learning to IT operations in an organization. “AI is commonly used for IT system log file error analysis, with IT systems management functions as well as to automate many routine processes.”AI helps alert the IT team so they can fix problems before the IT systems crash. AIOps helps the IT component of businesses improve system performance and services.

Human Resources

AI can help human resource acquisition by effectively scouting for talented workers and prospective hires. “AI can help human resources departments with data-based decision-making and make candidate screening and the recruitment process easier. Chatbots can also be used to answer many common questions about company policies and benefits.”

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Contact Centers and Customer Experience

The contact centers of an organization serve as important points of data collection “that can be used to learn more about customers, predict customer intent, and improve the “next best action” for the customer for better customer engagement.” The unstructured data collected from contact centers can also be studies and analyzed by machine learning systems to uncover customer trends and then improve products and services. Also, AI helps improve customer experience by offering loyalty points to customers and recommending what they can shop for according to their preferences.

Manufacturing

Companies like Heineken use data analytics at every stage of the manufacturing process from the supply chain to tracking inventory on store shelves. “Predictive intelligence can not only anticipate demand and ramp production up or down, but sensors on equipment can predict maintenance needs. AI helps flag areas of concern in the manufacturing process before costly issues erupt.”

Accounting and Finance

Human finance professionals will be freed of repetitive tasks so they can focus on more serious activities while the use of AI in accounting will reduce errors. “AI is also able to provide real-time status of financial matters to organizations because it can monitor communication through natural language processing.”

To know more, do peruse the DexLab Analytics website. DexLab Analytics is a premiere artificial intelligence training institute in Gurgaon.


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CoCalc and Juno Help You Master Data Science on Mobile Phones, Here’s How!

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CoCalc and Juno Help You Master Data Science on Mobile Phones, Here’s How!

Innovation has been at the heart of data science evolution. Cutting-edge technology advancements are found influencing data science training and learning mediums. Besides conventional channels, such as desktops and laptops, there’s now a new way to master machine learning coding systems, i.e. through mobile phones. A robust combination of tools is now at your service to help you code and monitor complex machine learning frameworks using mobile phones.

Take a look at these two tools; they are perfect tools for completing random machine learning tasks.

CoCalc

It is a pioneering web app that hosts coding environments amidst the cloud. It is a sophisticated online work domain that helps you perform mathematical calculations in the cloud. Later, you can share your projects even successfully.

CoCalc is primarily student-friendly software. It is crafted for students’ training modules and machine learning training programs. Thus, it comes loaded with a slew of potent data science packages, including Pandas, and all this makes it easier to develop Jupyter notebooks.

A lot of teachers are found using CoCalc to design courses. People can even chat using CoCalc, which further enhances collaboration on projects and improves the overall learning experience. What’s more, its customer service is also quite responsive. Their team of experts is always a step ahead to assist you.

2

Juno

The notable iPhone app helps user code in CoCalc on any mobile devices. In fact, Juno is specially designed for mobile and boasts of superb keyboard support. It tackles multi-screen multitasking challenges and provides support to Python code completion.

Quite interestingly, Juno is largely free for users. That makes it more suitable for mastering demographic. The experts have tried their best to make the free versions of Juno as interactive and fun as possible – engage with introductory notebooks available on Python, Matplotlib, Jupyter, SciPy and NumPy without shelling any extra penny. They not only keep things interesting but also feel good on the pocket.

However, if you want to savour the benefits of Juno Pro that connects you to an arbitrary Jupyter server, you have to make a one-time purchase and use it on all your devices.

Power of Combination

Surely, an effective combination of these two abovementioned tools comes as a soothing balm in the life of working professionals. They are the ones who need to be constantly on the go. Now, with these powerful tools at the tap of their fingers, they can work on myriad data science assignments while being at home or travelling.

However, as a downturn, coding on mobile is not as easy as it seems to be. Mobile devices are not highly configured to support rapid content creation. As a result, they take more time finishing an assignment as compared to laptops and desktops.

But, of course, if you are an adult learner, Juno and CoCalc are sure-fire ways to make progress along the bustling field of artificial intelligence and machine learning. In case, you want to learn more about AI, opt for an encompassing artificial intelligence certification in Delhi NCR.

 

The blog has been sourced from ― www.analyticsindiamag.com/learn-data-science-on-your-mobile-phone-with-these-tools

 

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Advancement in Genomics with Artificial Intelligence

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Advancement in Genomics with Artificial Intelligence

Artificial Intelligence is raging hot, and the healthcare industry is not left behind. Reports suggest AI will help the healthcare industry generate $6.7 billion in revenue. In healthcare, genomics is one of the most notable areas that have evolved significantly after the rise of AI. Involving processes like gene editing and sequencing, genomics is largely performed in agriculture, customized medicine industry and animal husbandry.

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Researchers have long been conducting DNA analysis. However, their initiatives used to be stalled midway because of several challenges – such as the massive size of the genome, high cost, regulatory factors, prediction norms and technology limitations. On top of that, a vast amount of data on genes and genomes further added up to the problem of ostentatiously large amount of patient data. 

Fortunately, today, researchers are better off using machine learning for genomics – they can now perform gene synthesis, construct precision and personalized medicines and understand the genetic makeup of each orgasm amongst others.

Major Development Highlights

  • Elevation Project by Microsoft grabbed eyeballs when its researchers collaborated with a set of biologists from UC Berkeley to assist in gene editing using AI. They decided to combine their efforts and increase efficiency and accuracy of CRISPR technology – which is basically a gene-editing tool for resulting in genetic improvements.

Together, they also launched Elevation, which uses Machine Learning technology to forecast effectively the off-target effects that take place during the process, thus increasing the efficiency of the entire process.

  • Nvidia and Scripps Research Translational Institute (SRTI) improvised their operations for developing deep learning tools and methods. They aim to process and analyze genomic and digital medical sensor data that would increase the use of AI and prevent the spread of diseases, promote health and streamline a host of biomedical research measures.
  • Google released DeepVariant – it is a cutting-edge deep learning model designed to analyze genetic succession. Last year, they devised a new version DeepVariant v0.6, which features brand new accuracy developments that helps get a more accurate picture of an entire genome.
  • Deep Genomics, a budding startup in Canada is found leveraging artificial intelligence to decipher genome and ascertain the most suitable drug therapies based on DNA found on the cell. The company specializes in the field of personalized medicines.

Genomics in India

Following the footsteps of its global partners, India too is slowly maneuvering into the space of AI-powered genomics – several startups, like Artivatic Data Labs are building power in this new field with radical innovations. Another Chennai-based startup, Orbuculum is leveraging AI to predict debilitating diseases and optimize disease diagnosis.

End Note

Major breakthroughs are happening in the new world of genomics. But, of course, understanding human genome and developing genomic medicines is beyond the human capabilities. Often, it needs analysis of millions and millions of data and performs several repetitive tasks for which AI seem to be the most feasible solution. Undeniably, advancements in AI and ML technology have resulted in a comprehensive understanding of genomics – they are the best way to interpret and proceed on genomic data.

FYI: DexLab Analytics is a top-notch artificial intelligence training institute in Gurgaon. It offers excellent in-demand skill training for students, professionals and anyone who is interested in data.

 

The blog has been sourced from ― www.analyticsindiamag.com/when-artificial-intelligence-meets-genomics

 

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