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A Discussion About Artificial Intelligence: Closer to Them

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A Discussion About Artificial Intelligence: Closer to Them

No need to introduce Artificial Intelligence nowadays, with the massive popularity that is shooting it forwards. Moreover, with the rigorous research and development from the technical giants and the best minds of the era at work on it, AI is progressing like never before.

Being the most mentioned technology in the present time, Artificial Intelligence, as we have checked it in the post A Discussion About Artificial Intelligence: Knowing AI Closely, has also surpassed both data and analytics, which are next in the race to emerge as the ultimate game-changer.

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Knowing AI

“AI is the science and engineering of making intelligent machines, especially intelligent computer programs” to quote the words of Alan Turing. But since the days the Turing, AI has come an inexplicably long and hard way to be known as what it is.

AI is the technology which will eventually be experienced as computers with brains. Artificial Intelligence is dreamed to be equipped with human-like intelligence, behavioural patterns similar to humans and with the ability to exude emotional responses just like we do.

We spotted a significant development when IBM hosted the first human-AI debate through its Project Debater in the last post and also named the three kinds of AI. Here we will know them in details.

Though AI is just taking its baby steps and would be subjected under countless shaping and reshaping, it is presently of 3 types, the classification of which is on the basis of the tasks they perform.

Artificial Narrow Intelligence (ANI)

Siri, Cortana, Alexa, Google Assistant, Google Translate and everything that surrounds us in our daily lives are grouped as ANI. This is perhaps the only kind of Artificial Intelligence that is successful and in perfect harmony with us in our digital world.

These AIs are primarily machine intelligence using Natural Language Processing (NLP). If you are interested in them, go for the peerless Natural Language Processing Course in Gurgaon right away. 

Artificial General Intelligence (AGI)

This type of AI is still not in existence. The Artificial General Intelligence are the AIs which will be almost as capable as humans in all the possible tasks. For this to be materialised, the human brain should be mapped correctly into an AI, which couldn’t be figured out till now. This is because we have not yet been successful in comprehending our brain and its actions completely. 

However, when this concept is realised and brought into existence, we should simply accept it straight away.

Deep Learning and AI using Python

Artificial Super Intelligence

This concept is still a possibility in the remote future. This is assumed to be in a time when the AIs would be more capable than their human creators. Everything including the comprehension of the human expressions, emotions, dreams and the cognition of them, should then be a child’s play for the AIs of this kind.

This may also construe that the ASI would be excelling us even in the circumstances that we fail, or are too fickle or fragile to handle. Spine-chilling isn’t it?

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A Discussion About Artificial Intelligence: Knowing AI Closely

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A Discussion About Artificial Intelligence: Knowing AI Closely

You must be aware of the term “AI” which is the acronym of Artificial Intelligence. In fact, it is the technology dominating the present time globally.

According to a survey conducted among 3,000 CIOs, Artificial Intelligence turns out to be the most mentioned technology and sweeps up, seizing the top spot, ahead of data and analytics, which seems to be strongly catching up.

AI is developing firm grounds and is believed to be the technology with the most human interactions in the near future. Therefore, if you can enroll for the best Artificial Intelligence Certification in Delhi NCR.

What is AI?

Robots are artificially structured, programmed entities, designed to carry out an array of tasks.

When the programmers are successful in embedding brains into robots, thus, they move about possessing an intelligence like humans, behavioural patterns, feelings and emotions similar to that of humans, the robots are then said to have Artificial Intelligence engineered in them.

AI and its Progress

Within a couple of years, AI has shown marked progress, where it has reportedly taken giant and promising leaps. Artificial Intelligence has shown the potential to mimic most of the tasks that only humans know to do exclusively, including debating, which was possible by the extensive research and development under the hands of IBM.

The Project Debater, conducted by the organization, made the human-AI debate possible. This would strive to aid the decision-makers make more informed decisions.

AI can presently perform a variety of tasks, including the ability to debate. The Artificial Intelligence is literally in its initial stages. Eventually, the AI would be subjected to multifarious moulding in the forthcoming years, to be the sole companion of the humans and even outmatch humans in certain jobs which require utmost precision and consistency.

Data Science Machine Learning Certification

On the basis of the jobs that the Artificial Intelligence can carry out, they are divided into three different types. These are the Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI).

Thus, being one with the Artificial Intelligence technology and catching up with the latest trends in it is really essential. If you have been in the same domain and want to brush up on your skills, and also achieve quality certification, then, hurry up and avail the finest Artificial Intelligence Training Institute in Gurgaon with its convenient and comprehensive courses.

Though the humans are believed to be the only beings who can exhibit their emotions and act accordingly, comprehend the feelings of their kind and take judicious decisions in real time, keeping them humane all along, they miserable fail at several junctures. Does this mean that the AI would be capitalizing on those and behave more like humans?

 


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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.

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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

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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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Self Healing Machines: The Future Weapon to Fight Cyber Crime

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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

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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

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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 NCR – DexLab 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

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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

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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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