<?xml version="1.0" encoding="UTF-8" ?><!-- generator=Zoho Sites --><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><atom:link href="https://www.rattusapps.com/blogs/tag/machinnelearning/feed" rel="self" type="application/rss+xml"/><title>Rattusapps - Cloud-based Warehouse Management System - Blogs #machinnelearning</title><description>Rattusapps - Cloud-based Warehouse Management System - Blogs #machinnelearning</description><link>https://www.rattusapps.com/blogs/tag/machinnelearning</link><lastBuildDate>Fri, 12 Dec 2025 20:59:20 +0530</lastBuildDate><generator>http://zoho.com/sites/</generator><item><title><![CDATA[The Pitfalls of Traditional Warehouses]]></title><link>https://www.rattusapps.com/blogs/post/traditionalwarehouse</link><description><![CDATA[<img align="left" hspace="5" src="https://www.rattusapps.comhttps://images.unsplash.com/photo-1601598852806-524f0060508e?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=Mnw0NTc5N3wwfDF8c2VhcmNofDEwfHx3YXJlaG91c2V8ZW58MHx8fHwxNjMwNjY2MzQ3&amp;ixlib=rb-1.2.1&amp;q=80&amp;w=1080"/>The recent boom of the e-commerce sector has propelled warehousing to the centre stage. It has exposed the loopholes that existed within the industry's fabric and perpetuated the need for digital transformation.]]></description><content:encoded><![CDATA[<div class="zpcontent-container blogpost-container "><div data-element-id="elm_MxmXZV-XSEyAvWKvGlLSAQ" data-element-type="section" class="zpsection "><style type="text/css"></style><div class="zpcontainer-fluid zpcontainer"><div data-element-id="elm_LdjB2936SQ6W9kvbnF6ghA" data-element-type="row" class="zprow zprow-container zpalign-items- zpjustify-content- " data-equal-column=""><style type="text/css"></style><div data-element-id="elm_dV8FfrdmThu_gDTXKR776g" data-element-type="column" class="zpelem-col zpcol-12 zpcol-md-12 zpcol-sm-12 zpalign-self- "><style type="text/css"></style><div data-element-id="elm_SKoigYvVTyaIDBOLEsDWOA" data-element-type="heading" class="zpelement zpelem-heading "><style></style><h2
 class="zpheading zpheading-align-center " data-editor="true"><span style="color:inherit;">The recent boom of the e-commerce sector has propelled warehousing to the centre stage. It has exposed the loopholes that existed within the industry's fabric and perpetuated the need for digital transformation. The following article tries to throw light on these shortcomings ang how they can be overcome with the help of tech-enabled support systems.</span></h2></div>
<div data-element-id="elm_CqOvg5ASRdORuV0Wb14AjA" data-element-type="text" class="zpelement zpelem-text "><style> [data-element-id="elm_CqOvg5ASRdORuV0Wb14AjA"].zpelem-text { border-radius:1px; } </style><div class="zptext zptext-align-center " data-editor="true"><div style="color:inherit;"><div style="color:inherit;"><p style="text-align:left;"><span style="font-size:20px;">With the exponential rise of the e-commerce platforms in recent years, the importance of warehouses has taken the centre stage in the supply chain network. From a layman’s perspective, a warehouse is nothing but a space where products and raw materials are stored before they are finally dispatched to manufacturers or consumers. However, those who are insiders in the industry know how warehouse is that significant cog in the wheel of the supply chain that keeps the balls rolling. Unless there is an optimized, efficient warehouse at the helm, the whole process of manufacturing and distribution would receive flak. The whole supply chain is dependent on the efficacy of warehouse that demands special attention in the 21st century.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">Since the sales velocity and the operational complexity have increased and multiple layers have been added to the supply chain network, warehouses across the world have gone for a digital overhauling. Warehouse management systems that monitor the end-to-end operations of warehouses, coupled with measures taken in favor of automation have changed the face of warehousing for good. However, there are managers who are either still cynical or nonchalant about strengthening their operations. This is mainly because either their business is too small to afford the digital boon or they are skeptical about the expenses they would incur. It must be noted that the fear of expenditure is nothing but a myth as properly implemented digital transformation always leads to handsome ROI in the due course of time and because of that even the small and medium business organizations are also taking the baton forward. Hence, in this article, we would try to highlight the limitations that a traditional warehouse would have that can be easily overcome with the sensible adaptation of digitalization.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">1.&nbsp; Accidents and Mishaps: Warehousing is a heavily labor-intensive process. A lot of workers serve the warehouse floor and they are susceptible to accidents. They need to handle items of various sizes in copious amounts. If they handle it manually, a lot of physical strain occurs that can dwindle their productivity. Additionally, the mental strain of recalling the exact locations of all items and pick-paths and accomplishing multiple targets in a stipulated deadline can be strenuous mentally. Moreover, improper handling of forklifts can be disastrous for the workers and can lead to fatal injuries. Warehouses that resort to automation processes employ AI/ML that can perform plenty of tasks at a greater speed with little or no human intervention, causing little threat of unfortunate occurrences.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">2.&nbsp; Problem of Space: Warehouse is an expensive space and every inch of it counts. Since traditional warehousing is intensely manned, a lot of errors can crop up in the course of operations. One of them is faulty space utilization. Due to the miscalculations on the part of the executives, many times items are stashed wrongly which leads to stockpiling at one place and stock-out at another. Warehouse management system is a software solution that efficiently deals with this problem of space and helps in the seamlessness of operations.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">3.&nbsp; Wastage of Time: Traditional warehouses do not leverage resources and picking options optimally. Resultantly executives run extra distance empty-handed and a lot of fallow time creeps into operations. Warehouse management system generates the most useful pick-path for the workers and introduces various picking options like wave picking and batch picking. Additionally, through features such as task-interleaving, various operations are yoked together so that optimum results can be achieved. Workers just have to follow the instructions given by WMS and it frees them from the hassle of registering all the routes and locations mentally. The operational time that is freed up can be sensibly utilized in other constructive work such as getting trained and upgraded. Traditional warehouses with human planners have a tough time routing and re-routing paths that get completely eliminated in tech-savvy distribution centres.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">4.&nbsp; The Rut of Documentation: Warehousing is a process that entails a lot of documentation. Most of these documents are manually registered and maintained. This huge pile of documents can easily get misplaced or can be manhandled. The misplacement can not only lead to delays and demurrage, but also pilferage that can incur huge losses for the companies. Again a lot of useful time and resources get grossly wasted in locating the exact documents from the heaps of papers. Furthermore, an overt dependence on paper-based work can be detrimental to the sustainability missions of the companies. And it is a proven fact that the organizations that have clear eco-friendly objectives earn goodwill in the contemporary markets.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">5.&nbsp; Issues Related to Scanning: Most of the traditional warehouses do not have scanners to single out items and that can cost workers a lot of mental and physical strain. Even those warehouses that have barcode scanning systems harbor their own set of problems. Barcode scanners cannot scan items that are placed at a particular distance or have any other object hindering their view. Moreover, these scanners cannot scan multiple items at the same time and takes a lot of time in scanning all the consignments collectively. This wastage of precious working hours can be eradicated entirely with the smart application of Radio Frequency Identification Devices.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">6.&nbsp; Inventory Inaccuracy: The single biggest problem that traditional warehouses face is the complications that arise out of inaccuracy in knowing inventory level. Without a thorough grasp over the level of stock that a warehouse has, overstocking and stock-out are extremely common. In such scenarios, warehouse managers do not have a proper idea when their shelves would need replenishment. Concurrently, purchase orders are not served timely and then shelves go empty for days causing disruptive tremors across the entire supply chain. Moreover, without proper adherence to FEFO, FIFO rules, fast-moving products can get damaged. All such traditional warehouses conduct the annual audits of stocks manually and that causes shut down for a few days. However, in smart warehouses with efficacious inventory management systems, cycle counts are conducted at an intermittent period and that too simultaneously with the everyday operations, without causing breakage in the productive timeframe. </span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">7.&nbsp; J.I.T and Cross-Docking: This point can also be clubbed with the compromised warehouse spaces. E-commerce platforms have empowered consumers in such a way that they prefer same-day delivery or promptness in delivery to a greater length. Modern warehousing methodologies of just-in-time delivery or cross-docking completely corroborate to the efficiency in dealing with warehouse spaces. Without a competent workforce enabled by technology, this magnitude of proficiency would always remain elusive.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">8.&nbsp; Forecast and Analytics: One prime feature that WMS-enabled modern warehouses provide and traditional paper-based warehouses don’t is the privilege of business analytics. Business analytics is a powerful set of tools that analyses business trends in predictive and descriptive ways. These methods are extremely fruitful in presenting a strong business case. Additionally, they present a tentative forecast of the future trends that can help businesses stay afloat in times of disruptions and renders resilience to the fabric of the enterprise. This is an especially practical aspect of warehousing where customer demands have become exceedingly volatile and disruptions, both seasonal and unprecedented, have become the order of the day. The post-COVID scenario of uncertainty has cemented the need for formidable data analytics. In the traditional warehouses, where there is no scope of data curation, BI does not even exist in the whole purview. On the other hand, WMS stores individual data pertaining to manufacturers, sellers, product details, locations, shippers, and all the necessary stakeholders that create a huge pool of data that can be utilized to its hilt.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">9.&nbsp; Lack of Transparency: Traditional warehouses do not offer end-to-end visibility into their operations due to the lack of technical expertise. But in the modern day and age, stakeholders need complete transparency in the entire distribution cycle and thorough knowledge on the statuses of their consignment. The zilch of it takes away the reliability and credibility of the warehouses. Not only does WMS fulfills this age-appropriate need, but with the help of AR/VR tools, multiple parties would also be able to go through the entire process in the days to come.</span></p><p style="text-align:left;"><span style="font-size:20px;"><br></span></p><span style="font-size:20px;"></span><p style="text-align:left;"><span style="font-size:20px;">This discussion attempts to prove how traditional warehouses have started losing their sheen in the light of digital transformation and recurrent disruptions. Though a digital revamp may seem to burn a hole in the pocket, it is an extremely important and even a necessary facet of the modern supply chain. With the resurgent importance of warehousing operations, one would definitely not afford to lose sight of profitability. Spending on WMS, AI/ML, WCS etcetera are good investments. They reap the fruit of labor consistently and in their own sweet time. Thus, it is time to shrug off the slumber of indifference and adapt to the changes to keep up with the pace of time. Otherwise, obsolescence and redundancy loom large over businesses.</span></p></div></div></div>
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</div></div></div></div></div></div> ]]></content:encoded><pubDate>Fri, 03 Sep 2021 16:26:48 +0530</pubDate></item><item><title><![CDATA[AI/ML and the Quid Pro Quo]]></title><link>https://www.rattusapps.com/blogs/post/artificialintelligence</link><description><![CDATA[<img align="left" hspace="5" src="https://www.rattusapps.comhttps://images.unsplash.com/photo-1516110833967-0b5716ca1387?crop=entropy&amp;cs=tinysrgb&amp;fit=max&amp;fm=jpg&amp;ixid=Mnw0NTc5N3wwfDF8c2VhcmNofDExfHxhcnRpZmljaWFsJTIwaW50ZWxsaWdlbmNlfGVufDB8fHx8MTYyMjEwMDU2NA&amp;ixlib=rb-1.2.1&amp;q=80&amp;w=1080"/>Artificial Intelligence(AI) is an umbrella term that embeds multiple aspects in it! To keep the nomenclature simple, we need to understand its torn-down version i.e. Machine Learning(ML).]]></description><content:encoded><![CDATA[<div class="zpcontent-container blogpost-container "><div data-element-id="elm_HRIG9oCFTbmrGT4LloenuQ" data-element-type="section" class="zpsection "><style type="text/css"></style><div class="zpcontainer-fluid zpcontainer"><div data-element-id="elm_1kaqzRjSQKyBIGasoDVkaA" data-element-type="row" class="zprow zprow-container zpalign-items- zpjustify-content- " data-equal-column=""><style type="text/css"></style><div data-element-id="elm_FHN7aV39SDeOemznVLSqIA" data-element-type="column" class="zpelem-col zpcol-12 zpcol-md-12 zpcol-sm-12 zpalign-self- "><style type="text/css"></style><div data-element-id="elm_jaCzPDkqTY68ZQQsVKIjPA" data-element-type="heading" class="zpelement zpelem-heading "><style></style><h2
 class="zpheading zpheading-align-center " data-editor="true">The author of this article is Moinak Boral. He is currently posted as a Junior Associate with the Punjab National Bank. A graduate in mathematics from St. Xavier's College, Kolkata and M.Sc. in Mathematics and Computing from Banaras Hindu University, Moinak is a technophile. He also reposes interest in the ups and downs of the stock market and is a fitness enthusiast.</h2></div>
<div data-element-id="elm_rREZYN1kTfy3s0Uqf1RuRg" data-element-type="text" class="zpelement zpelem-text "><style> [data-element-id="elm_rREZYN1kTfy3s0Uqf1RuRg"].zpelem-text { border-radius:1px; } </style><div class="zptext zptext-align-center " data-editor="true"><p style="text-align:justify;"><span style="font-size:12pt;">Artificial Intelligence(AI) is an umbrella term that embeds multiple aspects in it! To keep the nomenclature simple, we need to understand its torn down version i.e. Machine Learning(ML). Before delving into the topic, we need to know in brief what human learning is and how it is related with computers. In cognitive science, learning is typically referred to as the process of gaining information through observation.&nbsp; In this context, the most obvious question that emerges is: 'Why do we need to learn at all?'.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Human body and mind are customised to carry certain activities which might be as simple and routine as walking down the street or doing the homework or it may be something very complex such as calculating the angle in which a rocket would be launched. To accomplish all these activities, we need to have some prior information on one or more things related to these task. As we keep learning, we tend to garner more experience and information related to the task. To elucidate the whole thing, we can cite the example of home assignment. With more knowledge we arm ourselves with the ability to do homework with less mistakes.&nbsp; Thus with more learning our efficacy in performing the tasks increases.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">There are mainly three types of human learning : learning under expert guidance, learning guided by knowledge gained from experts and learning by self. The readers might be wondering how does all these even correspond with our topic of discussion and the author probably tends to beat around the bush a little bit too much. But all the possible branches of knowledge in this world is linked with questions that we tend to overlook. It is only when we seek the answer, we learn in the process.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Hence, keeping strains with the three segments of learning process, we have to alight to this discussion: do inanimate objects like machines really learn? If so, then how do they learn?</span></p><p style="text-align:justify;"><span style="font-size:12pt;">If we go by a standalone, superficial answer then it’s a big No! Machines do not learn on their own but they do learn in the presence of a supervisor i.e. humans. If we be a bit more precise, learning is fed into machines under the direction of the human beings!</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">This essentially means that a machine can be considered to be gleaning learnings if it is able to gather experience by doing a certain task and improve its performance by doing the similar tasks in future.&nbsp; When we talk about experience, it simply alludes to the past data related to the task. This data is basically instilled as an input to the machine by some source.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Let us now understand this with a simple example.&nbsp; A machine has been given the task of image classification. In this context, let’s say that E is the collection of all the past data with images having&nbsp; <b><i>names</i></b> or assigned classes(for eg. Whether the image is of class cat or class dog or a class elephant etc.). We now consider a&nbsp; task of assigning a <i>moniker</i>&nbsp; to new <b><i>unlabelled</i></b> images(by unlabelled we mean that the random image should fall under some particular category which the computer will decide) and P is the collection of performance measure i.e. the percentage of images correctly classified. It means how aptly the computer finds out whether the image of a cat is the image of a cat and not of a dog. The more we feed the machine with inputs the more its performance in identifying random images increases.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Thus for every problem out there that needs to be solved there are three fundamental questions that should be clear: 'What’s the problem? ', 'Why does the problem need to be solved?', 'How would I solve the problem?'</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">You might be musing why we are even discussing ML? We were supposed to talk about AI!</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Well let me tell you that ML forms the basis of AI. In other words, </span><b><span style="font-size:12pt;">AI</span></b><span style="font-size:12pt;">&nbsp;is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas machine learning is an application or subset of&nbsp;<b>AI</b>&nbsp;that allows machines to learn from data without being programmed explicitly. </span></p><p style="text-align:justify;"><span style="font-size:12pt;">Let’s see some of the basic applications of Machine Learning. Apart from the example that we have discussed before here are some of the basic examples based on our day to day life that uses the ML algorithms.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">Speech Recognition</span></u></b><span style="font-size:12pt;">: In some search engines, we get a feature of assistance through voice. It comes under the subset of speech recognition and it is a popular application of machine learning.&nbsp;</span><span style="font-size:12pt;">Speech recognition is a process of converting voice instructions into text, and it is also known as 'speech to text', or 'computer speech recognition'. At present, machine learning algorithms are widely used by various applications. Many robotics developers&nbsp;are using speech recognition technology to follow the voice instructions.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">Traffic Prediction</span></u></b><span style="font-size:12pt;">: If we want to visit a new place, we take help of the navigation systems which show us the correct path with the shortest route and predicts the traffic conditions.</span></p><p style="text-align:justify;"><span style="font-size:12pt;">It predicts the traffic conditions too on the basis of the examination of data and can opine whether the traffic is smooth or is slow-moving or if the road is heavily congested. It is achieved with the help of two ways:</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">1.<span style="font-size:7pt;">&nbsp; </span>Realtime&nbsp;<b></b>location&nbsp;of the vehicle amassed through sensors</span></p><p style="text-align:justify;"><span style="font-size:12pt;">2.<span style="font-size:7pt;">&nbsp; </span>Data on the average time taken&nbsp;on the previous days at the same time.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Everyone who is using these navigation systems is helping this app in making it better. It takes information from the user and sends back to its database to improve the performance.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">Product Recommendations:&nbsp; </span></u></b><span style="font-size:12pt;">Machine learning is widely used by various e-commerce and entertainment companies&nbsp; for the sake of product&nbsp; recommendation to the user. Whenever we search for some product on the apps or websites of these online retailers, we start getting an advertisement for the same product while surfing internet on the same browser and this is because of machine learning.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">Information pertaining to the user interest is collected using various machine learning algorithms and helps suggest the product as per customer interest.&nbsp;</span><span style="font-size:12pt;">Similarly, when we use digital streaming platforms, we get to see some recommendations for entertainment series, movies et al and this is also done with the help of machine learning.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">Automatic Language translation: </span></u></b><span style="font-size:12pt;">&nbsp;Nowadays, if we visit a new place and we are not aware of the language then we would not feel lost and helpless. Machine learning helps us in transcending this human barrier by converting the text into languages that we know. The technology behind the automatic translation is a sequence-to-sequence learning algorithm, which is used with image recognition and translates the text from one language to another.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">Self Driving Cars:&nbsp;</span></u></b><span style="font-size:12pt;">One of the most exciting applications of machine learning is self-driving cars. Machine learning plays a very significant role in bringing this marvel of science to being. One of the most popular car manufacturing companies in the world is working on self-driving car. It is using unsupervised learning method to train the car models to detect people and objects while driving.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">●<span style="font-size:7pt;">&nbsp; </span></span><b><u><span style="font-size:12pt;">ML in Supply Chain:&nbsp; </span></u></b><span style="font-size:12pt;">&nbsp;Supply chain, being a heavily data reliant industry, has many applications of machine learning. Some of the uses and benefits&nbsp; of how ML can impact the Supply Chain Industry are as follows:</span></p><p style="text-align:justify;margin-left:36pt;"><span style="font-size:12pt;">&nbsp;</span></p><p style="text-align:justify;"><span style="font-size:12pt;">1.<span style="font-size:7pt;">&nbsp; </span>AI/ML is implemented in the warehouses to optimise pick-path routes through voice recognition devices and robotic channels such as automatic guided vehicles and autonomous mobile robots. These mechanized models are fed with navigation systems and sensors that help in onboarding and seamless functioning within the warehouses. Other mechanized vehicles like GTP, carousels, conveyors, vertical lifts, forklifts help reduce errors in warehouse movement and amp up productivity and profitability.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">2.<span style="font-size:7pt;">&nbsp; </span>AI works towards optimisation of product flow in the supply chain through inventory control. Stockout or overstocking or staffing are the challenges that logistics industries meet on a daily basis. These sophisticated and innovative technologies render accuracy in inventory management and thus business performances are also achieved well.</span></p><p style="text-align:justify;"><span style="font-size:12pt;"><br></span></p><p style="text-align:justify;"><span style="font-size:12pt;">3.<span style="font-size:7pt;">&nbsp; </span>Machine learning helps derive actionable insights, allowing for quick problem solving and continual improvement.</span></p><p style="text-align:justify;"><span style="font-size:12pt;">&nbsp;</span></p><p style="text-align:justify;margin-bottom:0.0001pt;"><span style="font-size:12pt;">As the conclusion to this article that tried to capture the essence of this much-debated, much-discussed grain of learning that what we see is just the beginning of a colossal digital revolution. In the&nbsp; coming years ML/AI is going to automate nearly each and every human task.&nbsp; </span><span style="font-size:12pt;">Machine Learning is going to open up unparalleled opportunities for organizations enabling automation, efficiency, and innovation thereby making our lives much easier than ever before.</span></p><p style="text-align:justify;margin-left:108pt;"><span style="font-size:12pt;">&nbsp;</span></p><p><span style="color:inherit;"></span></p><p style="text-align:justify;"><span style="font-size:12pt;">&nbsp;</span></p></div>
</div></div></div></div></div></div> ]]></content:encoded><pubDate>Thu, 27 May 2021 13:10:24 +0530</pubDate></item></channel></rss>