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

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.

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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

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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Self Healing Machines: The Future Weapon to Fight Cyber Crime

 

Self Healing Machines: The Future Weapon to Fight Cyber Crime

Science and technology is the lifeblood of digital success. Connected devices, innovation trends and swift urbanization are transforming the economies for good. But, as it’s said, you have to bite the bitter with the sweet – digital dependency on shared infrastructure comes with its own cons.

“The more machines, the more critical our cyber-security problem becomes. Increased attacker sophistication means devices are now attacked at the deepest levels, including firmware and embedded software. In this new threat landscape, we cannot just rely on manual human intervention. We have to change the paradigm,” shares Boris Balacheff, Chief Technologist for Security Research and Innovation at HP.

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Self Healing Machine is the Answer

For that, conventional security devices won’t be enough – self-healing machines are the answer. They not only detect advanced cyber attacks but also shut off the system completely and restore it later without human intervention. Their response is quick.

As cyber criminals are on the rise, HP strives to reinvent device security to a great extent. For twenty years and more, HP Labs have been working on computer security. Its latest innovation drive is focused on bringing down cyber-resilience at hardware level. Just like the perpetrators employ newer tech capabilities, inventors of today’s security devices should also look up to artificial intelligence – in that respect, self-healing machines should never be only reactive but also proactive. The design and architecture of the machines should be as if they can immediately respond to attacks as well as fix their flaws then and there before someone else does.

Security Is In Focus

The prognosis of the World Economic Forum’s Global Centre for Cybersecurity and the UC Berkeley Center for Long Term Cybersecurity suggests that in the age of innovation and technology modification, security is at the fulcrum of future digital success. It needs combined effort and trust from law enforcement, public and private sector and the entire civil society. In order to build a secure and better cyberspace, we need to strike private-public partnership and work together.

To say the least, government and private players are coming together to meet several challenges transpiring from the intersection of security and innovation. Major breakthroughs in the field of personalized healthcare, 3D digital printing and AI are hitting new highs.

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Fortunately, forecasts say self-healing machines can prove useful across a wide range of operations. For example, they can reduce the load of supporting previous products that still relies on security updates. They can quickly predict malfunctions, even before the device starts showing anomalies. In fact, some of the IoT devices are already attached to vibration and ultrasonic sensors to make monitoring easy.

Conclusion

But, of course, self-healing machines can never be left alone to guard themselves – most of the companies will seek a human in the loop. Humans form an integral role in operating self-healing machines. “We need to continue to reinvent the security of the machines that we will depend upon for years to come,” shares Balacheff. “It’s our only way to win.”

DexLab Analytics offers state of the art artificial intelligence certification in Delhi NCR – the course infrastructure is well fed, student-friendly and follows a practical approach.

The blog has been sourced from ― www.wired.com/brandlab/2018/10/fighting-cybercrime-self-healing-machines
 

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How Artificial Intelligence Can Help Tackle Emotionally Charged Situations

How Artificial Intelligence Can Help Tackle Emotionally Charged Situations

An increasing number of jobs are incorporating artificial intelligence. But artificial intelligence applications tacking emotional problems is something rarely heard of.

Researches reveal that people who face workplace harassment don’t always report it to concerned authorities– fear of judgment and discomfort in recalling emotionally disturbing situations being among the many reasons. However, scientists believe that people shying away from human assistance might be able to open up in front of a tech.

Let’s look at some examples of artificial intelligence applications assisting humans in emotional situations.

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Spot:

Back in February 2018, Shaw and his partners who are software engineers by profession introduced Spot. This web-based chatbot is powered by artificial intelligence and helps people share and report painful incidents. The app incorporates expertise of psychologists as well as police personnel and has a robust interview technique ensuring recorded narratives are highly accurate. Moreover, the person interacting has the option to remain anonymous.

Spot is trained to gather information from the person’s initial description of the incident and respond to cues by posing specific questions, but never asking leading questions that might intimidate the user. Finally, a detailed and time-stamped PDF report is generated, which the user can choose to share or keep personal.

Advantages of artificially intelligent tools dealing with human emotions:

  • Apps are accessible 24/7
  • No prior appointment with HR is needed
  • Eliminate inconsistencies associated with human interactions
  • Help overcome a common human weakness– emotional memory recall
  • Machines can act more logically in situations where humans fail to think clearly.

Navigating through human emotions:

Ixy is another AI based app that aims to minimize anxiety in human chats by facilitating interactions over texts. It samples texts to help users understand how he/she is perceived by others.

Israeli enterprise Beyond Verbal has launched ‘’emotional analytics’’ software, which is a patented technology that measures the emotional factor of voice based on its modulation. This tech is employed in call centers so worker interactions can be fine-tuned as per customer needs. Other important uses of this software include examining employee morale and improving the working of AI virtual assistants by helping understand elements between lines of human conversations.

Yoram Levanon, the inventor of Beyond Verbal tech and its chief science officer, visualizes the development of applications more advanced than the ones described above, such as virtual assistants that can examine vocal biomarkers and predict a person’s emotional and physical state. He firmly believes that modern AI apps need to work in tandem with human emotions; that’s the key for AI to be complementary to human work and not its replacement.

To help, not replace humans:

Recently, there’s been a lot of unease and insecurities associated with AI. There’s fear that AI might eat into our human side and corrode human emotions. But the opposite of this is actually possible and these apps prove that point. Done correctly, machines can help us become better humans.

In today’s tech-driven society, the first step in unlocking the powers of modern equipment is enrolling for comprehensive Artificial Intelligence Certification Courses. From factory machinery, to chatbots, and now even human emotions, everything is forming inseparable bonds with AI. Join the leading artificial intelligence training institute in Gurgaon DexLab Analytics and begin a successful journey in this field. For course details, look up the brochure on DexLab’s website.

 

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Sell Yourself Well: Most Common Artificial Intelligence Interview Questions

Sell Yourself Well: Most Common Artificial Intelligence Interview Questions

Artificial Intelligence is seeping through our daily lives. Day by day, the robust technology is building a profound impact in the most beguiling ways, increasing the demand for AI professionals, blessed with the in-demand skills and expertise. No matter what, the future of AI seems to be all bright and beautiful.

This is why we are here to help you crack major AI job interview questions and guide your career through this fascinating field of science and technology. Go through the following questionnaire and showcase your knowledge, skill and talent. This will highlight how well you know the various nuances of AI and its implications.

What is Artificial Intelligence?

AI is the budding field of computer science and IT – which stresses on creating intelligent machines that imitate human brain’s cognitive abilities. It’s the simulation of human intelligence processed by machines using computer systems. Some of the notable AI activities are:

  • Speech recognition
  • Learning and planning
  • Problem-solving

What are the fields where AI is used?

Since its inception, AI is used across fields of extreme diversity, and some of them are mentioned below:

  • For customer support, including chatbots, sentiment analysis bots and humanoid support robots
  • In the linguistic field of processing natural language
  • Across IT fields, like computer software, sales prediction and analysis

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Highlight the advantages of Fuzzy Logic Systems.

Following are the key advantages of Fuzzy Logic System:

  • Easy to understand
  • Simple constructible logics
  • Takes in inaccurate, ill-mannered and malformed input data
  • Flexibility to include and delete the rules as per convenience in the FLS

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What is FOPL?

FOPL is the short form of First-order Predicate Logic, which is a compilation of formal systems, where the statement is divided into two sections: a subject and a predicate. The predicate has the power to determine or modify a subject’s characteristics.

What do you mean by Greedy Best First Search Algorithm?

This is an incredible algorithm method, where the node nearest to the goal expands first. f(n) = h(n) is the default explanation of nodes, and this process is largely applied in the subsequent levels, where priority queue comes into question.

Do you know the artificial key in AI?

An artificial key in AI is built by assigning a number to an individual record, when a standalone key goes missing.

What is an alternate key in AI?

All the candidate keys except primary keys are called alternate keys.

Mention the components of Robotics.

These are the following components, which we would require to build a robot:

  • Actuators
  • Pneumatic Air Muscles
  • Sensors
  • Power Supply
  • Electric Motors
  • Muscle Wires
  • Ultrasonic and Piezo Motors

Hope these general job-interview questions have helped you grasp the underlying features of AI and its applications. For more research in this specific area of interest, we recommend artificial intelligence certification in Delhi NCRDexLab Analytics is the go-to institute in this case.

 
The blog has been sourced from — www.janbasktraining.com/blog/artificial-intelligence-interview-questions
 

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DexLab Analytics Partnered With DU for Vishleshan’18

DexLab Analytics Partnered With DU for Visheshan’18

DexLab Analytics in association with Department of Business Economics, Delhi University proudly presented Vishleshan’18, an analytics conclave to nurture budding talent pool. Each year, Delhi University organizes an annual competition, where in data enthusiasts get an opportunity to showcase their analytical capabilities and complex problem-solving skills. This year, DexLab Analytics shared the platform with the esteemed institutional body under DU – and we can’t feel more obliged!

Our sincere gratitude and good wishes rests with the Department of Business Economics, University of Delhi; they recognized our efforts towards the data analytics community and shared interest in collaborating with us, which was indeed an honorable moment for us.

Now, coming to the event details, Analytics Conclave – Vishleshan’18 was segregated into two rounds. The first round also known as the elimination round comprised of an online quiz session, candidates were required candidates to be well-versed in all verticals of analytics. The second round was a lot more challenging, because here selected teams were allotted a case study each. In this round, DexLab Analytics played a crucial role – the seasoned consultants actively participated in structuring these all-encompassing case studies.

The case studies were all in sync with this year’s theme ‘AI and Machine Learning: Transforming Decision Making’, which means bagging the winner title was no mean feat. Various teams, all from notable institutes and in accordance to eligibility criteria (only post-graduates or MBA students allowed) participated in the contest. Out of them, only 5 teams were finally selected to present their case studies in front of a distinguished panel of judges at the DU campus on 8th September 2018.

Artificial intelligence and machine learning are driving the technology realm. Not only are they the pioneers of effective decision-making processes but also engines of faster and cheaper predictions for all big and small companies. Next to the US, India is deemed to be biggest hub of artificial intelligence, thus it’s time for prestigious Indian educational institutes, like Delhi University to start training the bright young minds for the next big boom of AI and machine learning. And that’s exactly what they were found doing.

However, as it’s said, teamwork divides the task and multiplies the success – the organizers of Vishleshan’18 approached DexLab Analytics, a leading data analytics training institute in Gurgaon, Delhi NCR. Together, they believed they would better analyze the data acumen of the participants and foster a symbiotic association for more knowledge sharing in the future.

Perhaps, not surprisingly, DexLab Analytics has created a place of its own, in the niche analytics industry. Comprehensive in-demand skill training courses are crafted keeping in mind the students’ requirements and industry demands. Moreover, the consultants who bring in considerable domain experience in the related field are all experienced and loaded with expertise. Together with you, this institute can be considered as a center of excellence in the big data analytics domain!

 

For a more detailed report, click the link below:

www.prlog.org/12728482-dexlab-analytics-is-case-study-partner-for-analytics-conclave-vishleshan-18.html  

 

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Forecasting Earthquake Aftershocks with Artificial Intelligence

Forecasting Earthquake Aftershocks with Artificial Intelligence

Recently, a study where a huge number of earthquakes were analyzed using machine-learning models, fared better at indicating the regions affected by aftershocks than traditional methods of analyzing the same.

This study puts forward new ways of analyzing how ground stress, which is caused by a massive seismic activity like earthquake, trigger aftershocks that follow. Researchers believe that this advancement in aftershock detection can open up fresh avenues for assessing seismic risks.

Phoebe DeVries, a seismologist at Harvard, believes this new research to be a demonstration of the immense opportunities that machine learning has in this field.

Contrary to the general idea that aftershocks aren’t as damaging as the main earthquake, they can actually be more devastating. As an example consider the 7.1 magnitude earthquake that shook Christchurch area in New Zealand in September 2010. It didn’t take lives but the 6.3 magnitude aftershock that occurred over 5 months later caused massive damage and took 185 lives.

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Standard Method

Currently, the problem lies not in predicting the magnitude of aftershocks; rather seismologists find it difficult to forecast the spots where the aftershocks will hit. The traditional method used for aftershock forecasting involves calculating changes in stress of nearby rocks that’s produced by the main earthquake and using these calculations to find out the likelihood of aftershocks striking a particular area. This stress-failure process is good for defining after-shock patterns, but sometimes it fails to generate correct results.

There’s a lot of data available on previous earthquakes. DeVries and her group has used this data and applied it in machine learning models to create better predictions.

Neural Networking

Data related to over 131,000 main and after tremors were analyzed by scientists. It included some of the most destructive earthquakes, like the 9.1 magnitude quake that shook Japan in 2011. Employing this massive data set, neural networks were trained and these modeled a grid of cells that surrounded every main tremor location at a distance of 5 kilometers. Neural networks were given the signal that an earthquake had occurred and also fed in data related to the changes in stress at the centre of each grid cell. Following this, the neural networks were asked to give the probability of each cell generating aftershocks.

After testing this method for 30,000 main shocks and aftershock events, it was concluded that the neural networks forecasted the after tremor locations more accurately as compared to the stress-failure method. The networks treated each cell as an individual problem instead of calculating the overall effect of stress on the rocks. Furthermore, the ML models also implied some physical changes that occur in the ground due to the main shock and other important parameters that researchers don’t normally consider in seismic studies. One of them is the stress changes that occur in certain materials, like metals.

To conclude, it can be said that this new study is a motivating step forward in the study of seismic activities. AI and ML are breaking new grounds in every field of study. Understandably, Artificial Intelligence courses are all the rage among students wanting to leap forward in their careers. If data, numbers and forecasts interest you then this artificial intelligence certification in Delhi NCR should definitely be considered.

 

Reference: https://www.nature.com/articles/d41586-018-06091-z

 

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7 Leading Sectors in India That Need an AI & Analytics Makeover

7 Leading Sectors in India That Need an AI & Analytics Makeover

Advancements in the field of data analytics and artificial intelligence are fuelling innovation in every nation around the world. India too is showing keen interest in AI. This year, the government has doubled the amount invested in the innovation program Digital India which drives advances in machine learning, AI and 3-D printing.

The signs of increased activity in AI research and development are showing in different areas. Here are the topmost sectors of India that are in dire need of AI and data science revolution:

FINANCE

According to reports by PricewaterhouseCoopers, financial bodies and payment regulators deal with billions of dollars in transactions through ATMs, credit cards, e-commerce transactions, etc. When human expertise is combined with advanced analytical methods and machine learning algorithms, fraudulent transactions can be flagged the moment they occur. This leaves less room for human errors. Considering the recent discoveries about major frauds in reputed banks in India, this approach seems more like a necessity.

Image source: American Banker

 

AGRICULTURE

Although 40% of the Indian population works in the agricultural sector, revenues from this sector make up only 16% of the total GDP. The agricultural industry needs advanced data analytics techniques for the prediction of annual, quarterly or monthly yields; analyzing weather reports are observing the best time to sow; estimating the market price of different products so that the most profitable crop can be cultivated, etc. AI powered sensors can measure the temperature and moisture level of soil. With the help of such data farmers can identify the best time to plant and harvest crops and make efficient use of fertilizers.

Image source: Inventiva

HEALTHCARE

According to the Indian constitution, each and every citizen is supposed to get free healthcare. And government hospitals do provide that to people below poverty line. Nonetheless, 81% of the doctors work for private hospitals and nearly 60% hospitals in India are private (According to Wikipedia). The root cause for this is that government hospitals are overpopulated. People who can afford healthcare services from a private hospital prefer to be treated there. Data science can play a pivotal role in managing the growing demand for healthcare services by strengthening the current infrastructure. It can help by predicting how many days a patient is likely to be admitted and find out the proper allotment of beds. AI fine tunes medical predictions and helps selecting a proper line of treatment.

Image source: wxpress

CRIME PREDICTION

Considering the number of security threats and extremist attacks India has faced in the past, there’s urgent need to develop efficient methods that can neutralize such threats and maintain proper law and order. AI and ML can step in to ease the burden of security personnel. A welcome development is the collaboration between Israeli company Cortica and Best Group. Massive amounts of data from CCTV cameras across the nation are being analyzed to anticipate crime and take action before it happens. Streaming data is scrutinized for behavioral anomalies, which are considered as warning signs for a person who commits a violent crime. The aim of the Indian authorities is improving safely in roads, stations, bus stops and other public places.

Image source: Digital Trends

From the paragraphs above it is evident that AI and data analytics has immense scope to improve these major sectors in India. While you look forward to these developments also follow DexLab Analytics, which is a leading data analyst training institute in Delhi. For data analyst certification, get in touch with DexLab’s industry experts.

Reference:

www.brookings.edu/blog/techtank/2018/05/17/artificial-intelligence-and-data-analytics-in-india

www.analyticsvidhya.com/blog/2018/08/top-7-sectors-where-data-science-can-transform-india-with-free-datasets

 

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AI is enhancing careers: How can you gain advantage in this AI-era?

Artificial intelligence has a significant impact on our lives. Several AI powered automation tools are already in use such as customer service applications and voice-powered assistants, like Apple’s Siri and Amazon’s Alexa. Adoption of AI will benefit the business by improving the quality and consistency of work. Based on a discussion between Forbes Agency council members, we have listed the ways in which artificial intelligence can help workers improve their career.

  1. More valuable insights

AI will bring positive changes in the job of PR professionals. AI technology will take over manual jobs such as news monitoring, researching, reporting and making media lists. AI based predictive analytics will help PR professionals make better market predictions. They will reduce manual workload and help in strategic and creative thinking.

  1. Replace mundane tasks

AI, automation and machine learning will replace daily low-quality cognitive tasks such as scheduling calendar invites, daily food ordering, determining whether to answer/review/delete emails based on facts. They will eventually aid in quality tasks such as identifying connections, analyzing correlation and drawing inferences.

  1. Act as concierge

Popularity of Alexa, Watson, and Einstein suggest that consumers will expect tech to provide concierge services in the future. As AI techs evolve post their purchase, it will anticipate an individual’s daily tasks and provide highly personal recommendations.

  1. Make marketing smarter

AI will enable companies develop stronger relationships with their customers. IBM’s Watson and other cognitive technology will help analyze unstructured text, audio, images and video. AI’s ability to perceive and process personality, tone and feelings will help deliver better personal recommendations. It will help companies carry out conversations using chatbots.

  1. Automate customer support

The availability of chatbots round the clock will save a lot of time. They answer customer questions, give recommendations and guide customers to the next step. They will reduce the workload of customer support systems. Bots can draw insights on the needs, engagements and emotions of customers.

  1. Unleash the full potential of your mind

Workers will be spared from carrying out mundane tasks. They will have the time to focus on productive tasks, which require problem-solving skills and creativity.

  1. On-the–fly video editing

AI will eventually edit videos in real time.  Real- time user engagement will perform multiple instantaneous tasks such as changing sound effects on the fly.

  1. Create jobs and assimilate workflow

AI will interfere with regular workflow but in return it will create new jobs. It will help integrate the workforce. Humans will be instrumental in helping the AI work in harmony with the employees.

  1. Improve future strategies

Humans will always be a part of the PR industry, as they are crucial in maintaining a healthy customer relationship. The data that is collected through AI will enable making more informed decisions for the future. AI will help companies stay abreast of information related to their competitors through better media monitoring.

  1. Shrink 40 hours of analysis to 4 minutes

Manual analysis is very time consuming. The future of marketing efficiency lies in automation tools that will drastically reduce the time taken to analyze data and form strategies.

  1. Productivity even during commute

AI has made automated driving a reality. Driving in autopilot mode greatly reduces driver fatigue and can affect productivity during commute, especially to and from work.

  1. Improve brand engagement

AI can help devise customized experiences in real time. It interprets customer interactions and instantly creates customized content.

  1. Make routine processes easier

Entrepreneurs describe AI as the ultimate efficiency driver. The day to day tasks can be entrusted to digital hands, which enable human hands to be more productive. AI driven technology is benefitting manufacturing processes as well as advertising platforms.

  1. Give edge in competition

Businesses using AI will have a competitive edge over their clients. This is because AI implementation replaces manual processes of sorting complex data, drawing key insights and chalking out an action plan. AI improves decision-making, ROI, operational competence and cost savings.

AI related employment opportunities are on the rise. Compared to the demand, there is a lack in the number of professionals proficient in AI. It is predicted that by 2020, 20 percent of companies will need their workers to monitor and direct neural networks. About 2 million jobs in the cyber security sector are about to go vacant in the coming years.

So it is absolutely imperative to future-proof your career for the imminent AI era. Broaden your skill set and increase your proficiency by taking professional training in Machine Learning, Business Analytics and Data Science. Get an edge in your career by joining the Data science and machine learning certification course offered by Dexlab Analytics- a premier institute offering multiple courses on data science.

Interested in a career in Data Analyst?

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