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      string(59) "How Artificial Intelligence is Helping Seismic Interpreters"
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    The oil and gas industry has benefited heavily in major areas from artificial intelligence (AI), and seismic interpretation is the next area to experience the revolutionary impact.

    " ["fulltext"]=> string(4190) "

    By building an effective conceptual model of geological areas, AI can help in streamlining the process of oil and gas exploration.

    Seismic interpretation is the science (and art) of inferring the geology at some depth from the processed seismic record. Seismic interpretation is necessary for the oil and gas industry to discover and develop profitable fields and reserves. Historically, oil companies have had to rely on a trial and error approach. However, with seismic interpretation, the process was streamlined significantly but yet wasn’t highly efficient. The process, although improved the accuracy of finding an oil reserve, was still highly time-consuming and resource-intensive.

    Challenges in Seismic Interpretation and Resource Exploration

    When it comes to geological exploration, major faults are easier to identify, but identifying smaller cracks is a tedious task. The subtle faults can be overlooked by human scientists and can take away the opportunity of drilling a resource-rich reserve. Also, the process is highly time-consuming, requiring scientists to analyze tons of data. AI can help overcome these challenges as it automates the process and results in a quick method of oil exploration.

    The Transformative Partnership of AI and Seismic Interpretation

    Deep learning systems can help simplify the process of seismic interpretation. AI algorithms can easily and quickly identify fault systems from 3D seismic images data provided to them. The algorithm can help spot subtle faults that might be overlooked by human scientists. The deep learning model is trained with geological data. The AI model then analyses the data and helps predict faults that may be present in the region. Oil companies can then plan their drilling and rigging activities based on the output provided by the AI algorithm. They can assist in accurately determining the availability of natural gas and oil in areas that are inaccessible or are hard to access for humans. The organization can then determine whether to drill in the fracture or avoid it, depending upon the quantity of oil and petroleum reserves in the fault. For instance, researchers at the University of Texas in Austin have used synthetic data to train neural networks to spot small faults that might have been missed by humans. 

    AI and seismic interpretation 

    AI has proved highly beneficial for the oil and gas sector. Although it can significantly improve the process of mapping geological regions, the technology surely isn’t foolproof. A perfect balance for using AI for seismic interpretation would be the combination of AI and human interpreters. Human reasoning is no match for technology, and humans can’t work with the speed of technologies like AI and seismic interpretation can thus be improved significantly only with their combination. This combination of man and machine can help improve speed, quality, and understanding of geological mapping significantly, and seems like the logical solution for improving seismic interpretation.

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    How Artificial Intelligence is Helping Seismic Interpreters

    Naveen Joshi
  • 2
    object(stdClass)#13657 (59) {
      ["id"]=>
      string(4) "5812"
      ["title"]=>
      string(57) "How Product Recommendation Systems Can Benefit Businesses"
      ["alias"]=>
      string(57) "how-product-recommendation-systems-can-benefit-businesses"
      ["introtext"]=>
      string(217) "

    Product recommendation systems are among the most widespread applications of machine learning that enable businesses to enrich customer engagement and shopping experience.

    " ["fulltext"]=> string(5107) "

    A product recommendation system is a subclass of information filtering that uses machine learning to provide personalized recommendations to consumers based on their data. For instance, they can provide appropriate recommendations based on customers’ preferences, demographics, and past purchases. Segmenting customers based on their data is one of the many ways big data is impacting e-commerce and other digital businesses. And this ability of product recommendation systems has gained them a lot of traction on e-commerce and online media sites in the past few years. According to a study, up to 31% of total e-commerce revenue is generated because of recommended products. E-commerce is the most common example when it comes to the industries using product recommendation systems. But, various other industries are being disrupted by their use-cases.

    How Product Recommendation Systems are Benefitting Several Businesses

    The world is moving from one-size-fits-all solutions to personalized tailor-made solutions. And product recommendation systems are helping business owners across several industries to adapt to this shift towards providing personalized solutions. 

    product recommendation systems

    Improving Retention

    One of the core benefits of product recommendation systems is the ability to frequently collaborate with customers. If a company is providing relevant recommendations to customers, then there are fewer chances of losing potential clients. For instance, if an online media company is giving relevant suggestions, then a viewer might not want to go to a competitor site and search for movies or series. Customers also appreciate personalized recommendations. According to a survey conducted, 63% of customers want product recommendations, which was up from 57% two years ago. They were also willing to share their data in exchange for personalized recommendations. And this shows how the importance of personalized recommendations is increasing and will continue to increase in the future. Hence business administrators should start using product recommendation systems for providing personalized services to their customers.

    Increasing Sales

    An online company with thousands and thousands of products cannot provide recommendations for all their products to customers. And providing inaccurate recommendations often might become frustrating for customers. An accurate product recommendation system always recommends a product that is most relevant and likely to be purchased by customers. Thus, because of appropriate recommendations at the right time, customers might order several products at a single time instead of buying one product. That’s how product recommendation systems help to increase the sales of businesses.

    Product recommendation systems also provide recommendations for products that customers frequently buy together. For instance, shirts or t-shirts are often bought along with jeans, and recommendation systems can recommend shirts that go well with purchased jeans.

     

    Several techniques are used by product recommendation systems to categorize customers into different groups and provide personalized recommendations to them. For instance, collaborative filtering, content-based filtering, and demographic-based filtering are different approaches that can be taken for providing recommendations. The next milestone in product recommendation systems would be creating a single algorithm that will be best for categorizing customers with all the filtering approaches. And if researchers can achieve this milestone, then instead of using different techniques for categorization based on various domains, they can use a single algorithm that will classify customers in all domains.

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    How Product Recommendation Systems Can Benefit Businesses

    Naveen Joshi
  • 3
    object(stdClass)#13660 (59) {
      ["id"]=>
      string(4) "5802"
      ["title"]=>
      string(31) "Sequence Modeling for Beginners"
      ["alias"]=>
      string(31) "sequence-modeling-for-beginners"
      ["introtext"]=>
      string(182) "

    Sequence modeling plays a critical role in applications that require the analysis of input data as a continuous correlated stream instead of as discrete, unrelated entities.

    " ["fulltext"]=> string(4855) "

    sequence modeling

    Among the different types of artificial neural networks used in present-day AI applications, feedforward neural networks are the most common. These neural networks are primarily used for applications requiring pattern recognition, such as detecting the presence of cancer from radiology reports. By comparing input reports pertaining to a patient with training data that it is built on, the algorithm can estimate the likelihood of the patient developing cancer. However, what such algorithms cannot do is analyze multiple reports of a patient generated over time to understand if the cancer is progressing or regressing. That’s because it cannot analyze the reports belonging to the same patient as a series of inputs for the same problem. Instead, it only sees them as discrete inputs for different problems or cases. In order to overcome this limitation, Recurrent Neural Networks (RNN) can be used, which specializes in processing sequences of values through a technique called sequence modeling.

    Understanding Sequence Modeling

    Sequence modeling, put simply, is the process of generating a sequence of values by analyzing a series of input values. These input values could be time series data where a specific variable, say the demand for a particular product, varies over a period of time. The output could be the prediction of demand for consequent periods. Another example could be text prediction, where based on the sequence of the last phrase and a set of pre-loaded conditions and rules, the sequence modeling algorithm predicts what the next word could be. By using sequence modeling, businesses can achieve more than just pattern generation and prediction.

    Leveraging Sequence Modeling in Enterprise Applications

    By using sequence modeling as a part of RNNs, businesses can not only enhance their operations improve their decision-making through the following applications: 

    sequence modeling

    Product Recommendations

    Recommendation engines have become a standard component of all ecommerce portals, online marketplaces, and media streaming sites. These recommendation engines analyze an individual user’s browsing and purchase history to suggest products that are most likely to be clicked on and purchased by them. To achieve this, these recommendation engines need to remember more than just the most recent page or link they visited. Sequence modeling allows these recommendation engines to analyze the series of pages visited by individual users and determine the most suitable suggestion.

    Sentiment Analysis

    Sentiment analysis from text sources like social media pages requires the analysis of sentences, or sequence of words in combination. Simply fishing for single words like ‘good’ or ‘bad’ won’t give a clear picture, as they can be preceded by a ‘not’ to convey the opposite meaning. To extract the true meaning from content in such cases, sequence modeling-enabled sentiment analysis algorithms can Thus, sequence modeling can be used to understand a brand or product’s popularity directly from their customers via social media and also other channels like review pages and customer care emails.

     

    As most problems solved by AI require the analysis of non-singular data entities, the need for and ubiquity of sequence modeling will continue to increase. In order to make the sequence modeling more effective and applicable in more complex applications, however, it is critical to extend the memory of sequence modeling algorithms so that they can make decisions based on a larger input dataset. Doing so may involve using Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), among other short-term memory enhancing solutions.

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    Sequence Modeling for Beginners

    Naveen Joshi
  • 4
    object(stdClass)#13665 (59) {
      ["id"]=>
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      ["title"]=>
      string(69) "How Blockchain Improves Logistics: Benefits, Drawbacks, and Use Cases"
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      string(66) "how-blockchain-improves-logistics-benefits-drawbacks-and-use-cases"
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      string(177) "

    The blockchain technology and logistics industry tend to be quite profitable for each other. Additionally, this collaboration brings benefits to carriers and customers.

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    In this article, we’ll discuss all you need to know about blockchain in the logistics sector. 

    1. PROS OF INTEGRATING BLOCKCHAIN INTO LOGISTICS

    Blockchain allows optimizing logistic processes in the real-time mode. This technology tends to improve the relationship between shippers and carriers. 

    We've singled out six main advantages of using blockchain in the logistics sector. Let’s discuss them more precisely. 

    Simplified Workflow 

    There are a lot of documents required for the transportation process. For example, a bill of lading or B/L. It stands for an agreement that consists of transportation terms, conditions, and other issues. 

    Blockchain allows recording all the steps. As a result, any participant can look through the delivery chain. If something happens, recorded information will report a problem.

    Improved Routes

    Blockchain allows optimizing routes and delivering faster. In this case, smaller companies can compete with bigger ones, offering faster routes.

    As a result, it’s possible to reduce expenses on the shipping process.

    Automated Certification

    Blockchain simplified the process of goods certification. The combination of IoT and blockchain allows creating smart contracts.

    Fraud Reduction

    Transactions made on blockchain are secure. It’s impossible to change something in the transaction. It leads to decreasing fraudulent operations. 

    Intermediaries Elimination

    Intermediaries stand for agents that take part in the transportation chain. However, with logistics software development, the industry doesn’t need such specialists.

    Smart Contracts

    We’ve already mentioned smart contracts. They tend to reduce time and expenses. Also, both parties have an opportunity to automate the validation process, manage obligations, and so on.

    There were main blockchain advantages. As you can see, this technology can be quite profitable for the logistics industry.

    2. CONS OF INTEGRATING BLOCKCHAIN INTO LOGISTICS

    Of course, there are some disadvantages of using blockchain technology. Let’s discuss them more precisely.

    Increased Unemployment

    Blockchain allows automating supply processes. As a result, there is no need for various specialists. The number of unemployed workers will rise.

    Standardization of Business Processes

    Businesses that use blockchain technology should have a standard process. Unfortunately, these days, businesses don’t have one. 

    It’s required to create a standard process on the government level. So, businesses can follow it to avoid some common problems.

    Integration Expenses

    It’s evident that blockchain development is expensive and time-consuming. Additionally, it’s required to have powerful hardware.

    Also, there are expenses on specialists that are experienced in blockchain integration.

    So, blockchain is a quite expensive technology that requires additional preparation before using it. However, some companies have already integrated blockchain and got some profit.

    3. BLOCKCHAIN USE CASES FOR LOGISTICS INDUSTRY

    Tracking Things During Delivery

    Blockchain makes it easy to track goods during shipment. Additionally, the companies have an opportunity to monitor the conditions of the packages.

    As a result, it’s possible to detect broken goods, spoilt products, and so on.

    Of course, such opportunities lead to decreasing unnecessary expenditures.

    Successful story. Walmart cooperates with IBM to use the blockchain technology in the logistics. The system allows seeing what products are sold. Also, it’s possible to know the location of the product (the particular warehouse). The company claims that the supply process becomes more transparent.

    Simplified Transportation

    Blockchain allows reducing the number of documents required for transportation. Additionally, the number of mistakes will also decrease due to automatization. The shipping terms fulfill more precisely.

    Simplified Payment Procedures

    Let's face it — payments are important for any business. Blockchain makes this process secure. For example, it’s possible to make transactions with such cryptocurrencies as Bitcoin. As a result, the payment process is secure and transparent. Also, such solutions improve international processes. 

    Successful story. Tallysticks has made a platform that simplified payment processes using blockchain. The solution offers smart contracts that can be customized depending on the business needs and requirements.

    Verification Process

    Blockchain gives end consumers an opportunity to simplify the authenticity of the goods. There are platforms with data about product origin, quality, fineness, and others. 

    This technology gives clients transparency. As a result, people trust companies more.

    Improved Business Cooperation

    Blockchain makes cooperation easier. For example, enterprises can cooperate with small companies to deliver goods faster. Such a solution is profitable for both parties.

    These days, companies can cooperate with each other without intermediaries. It leads to cost reduction and improved delivery processes.

    Successful story. ShipChain platform uses blockchain to improve cooperation. For instance, the service allows tracking the delivery from the warehouse to the buyer's door. It leads to better customer experience and satisfaction.

    Disputes Settlement

    The delivery process is long and expensive. Also, there can occur various delays due to weather conditions and other issues. 

    Usually, to manage such issues, companies hire lawyers. However, blockchain changes the situation. The transportation process is tracked from the beginning to the end. So, both parties can see any changes in the route.

    Also, the parties can monitor any issues connected to the delivery and decide whose fault they were.

    Blockchain technology innovates the logistics sector. The companies can simplify the delivery process, making routes shorter. 

    All these solutions lead to customer satisfaction. As a result, the clients trust companies and order goods or services more often.

    The main advantage of blockchain is transparency. Business owners, as well as end consumers, have an opportunity to track the delivery process. Also, customers can ensure that during the delivery the storing conditions were followed. 

    However, developing blockchain-based solutions is an expensive and time-consuming process. Companies have to prepare beforehand and single out the requirements of the final product.

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Additionally, this collaboration brings benefits to carriers and customers." 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    How Blockchain Improves Logistics: Benefits, Drawbacks, and Use Cases

    Vitaly Kuprenko
  • 5
    object(stdClass)#13664 (59) {
      ["id"]=>
      string(4) "5788"
      ["title"]=>
      string(60) "Transforming Traditional Theatre with Immersive Technologies"
      ["alias"]=>
      string(60) "transforming-traditional-theatre-with-immersive-technologies"
      ["introtext"]=>
      string(192) "

    Leveraging AR and VR theatres can enhance attendees’ engagement and attract more viewers to bring back live theatre’s popularity.

    " ["fulltext"]=> string(4677) "

    VR theatre

    Live theatre has been around for as long as we can remember. It used to be a major source of entertainment. But now, with the emergence of cinema and online streaming services, the popularity of live theatre is diminishing. Theatre is losing its appeal due to lack of engagement, high costs, and lack of immersive storytelling. Theatre businesses now have a chance to make their shows more engaging and attract more audiences with the help of immersive technologies. VR and AR, which have changed our lives in many ways, through AR and VR theatres can now provide a whole new level of interaction between performers and audiences.

    How AR and VR Theatres are Transforming Traditional Ones

    AR and VR devices are enabling theatres to enhance on-stage animation and provide viewers a first-person perspective into theatrical performances.  

    Improving On-Stage Animation


    There isn’t a lot of room for computer-driven animation in theatres. But they use animation sometimes either for completely animated play or to enhance background visuals. In both cases, theatres are not able to provide the high animation that can engage viewers like recorded films. In fact, there are chances that theatre animation might impact the actors' performances.
     
    VR theatre, AR theatre

    Theatres can make live performances more immersive by using AR glasses and overlaying animation effects on the stage. AR headsets can also provide deaf people with immersive theatre experiences by displaying dialogue captions while actors deliver their lines.

    Enabling 360° Experiences


    VR headsets enable viewers to get a 360° view of the performance. They can virtually roam on the stage and view the act from multiple angles from the comfort of their seats. Whether they want to know what's happening behind the actors or want to view their expressions from different angles, it will all be possible with VR. This will enhance engagement as viewers will get every minute detail they want.

    Offering a First-Person Perspective


    VR headsets allow audiences to view the story from a first-person perspective. Audiences can step into the shoes of any on-stage actor using VR headsets and experience shows from a first-person perspective. Theatre artists can make viewers a part of their play with the help of AR and VR headsets. For instance, in an action drama, viewers can become a soldier on the field to experience the action on a whole new level. This can make attendees more connected to the play and enhance their overall experience.

    AR and VR theatres are surely going to transform traditional ones and attract more audiences. But they may not be well-received by traditional theatre-going audiences. Current viewers of theatre are mostly those who love art in the traditional form. They won’t love to see immersive technologies completely transforming traditional theatres. Theatres will, hence, have to maintain this traditional artistic touch even if they implement immersive technologies. They need to carefully walk the fine line between art and technology so that art lovers are not disappointed.
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    Transforming Traditional Theatre with Immersive Technologies

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Why Humanoid Robots Need Motion Planning?

Naveen Joshi 28/02/2020 3

Humanoid robots are robots with their bodies built to resemble those of humans. Most humanoid robots have a torso, a head, two arms, and two legs like a regular human. But, some of them might only resemble some body parts of humans. For instance, some humanoid robots have body parts of the upper body like the face and hands and not the lower body. When it comes to moving, one of the major differences between humanoid robots and other robots is the humanoid robots’ ability to perform human-like movements like biped gait. The development of accurate obstacle avoidance software and motion planning for humanoid robots is among the most important milestones towards increasing the overall autonomy and functionality of these robots.

Importance of Motion Planning for Humanoid Robots

There are several different motion planning algorithms available that can differ slightly from one another. However, all these algorithms fulfill some of the common aspects like where to move and what path to take.

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Defining Configuration Space

Configuration space defines all the available space that a robot can access in an environment. Motion planning algorithms first defines configuration space and mark some location points in that space. Then based on these location points, the motion learning algorithms define a route for the humanoid robots. For instance, in maps that use GPS, configuration space is all the streets that have been mapped in the world. With the help of these streets, maps can provide directions from one end to another end. The same is the case with humanoid robot algorithms; they use configuration space to get the shortest distance from one position to another.

Algorithms that pick location points of configuration space remove paths were obstacles are present that can stop robots from moving to or through that place. By removing such points, these algorithms ensure that only free space is available for planning a route.

Planning the Path

Once all the location points in the configuration space are configured, motion planning algorithms plot the best path available for humanoid robots’ movement. And, this part is where different algorithms can provide different approaches for motion planning. For instance, some algorithms known as combinatorial planning algorithms can find a solution to problems if they exist or report failure if they are unable to find any solution. These algorithms might take some time to figure out a solution. But, some other algorithms, also known as sampling-based algorithms, are more efficient and quicker than previous ones but cannot find solutions to all problems.

As humanoid robots continue to enter the mainstream in the several upcoming decades, motion planning for humanoid robots with collision avoidance will be of utmost importance in the field of robotics. And not only humanoid robots, but also other areas of robotics will continue their research to improve the accuracy of motion planning algorithms. For instance, real-time motion planning in autonomous vehicles will help these vehicles to quickly switch routes in case of any traffic jams or construction work being carried out on a route to the destination. Such a feature will help autonomous vehicles overcome many challenges, allowing them to gain mainstream adoption.

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  • Sharon Hughes

    Humans havent even perfected the art of being nice to each other and now we want to pass on stuff to robots

  • Tracy Irving

    Good info

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