The term big data has been doing the rounds quite often these days. That is solely because of the endless amount of potential it holds. Big data is, quite commonly, associated with the internet. It basically is extremely large sets of data that may be analyzed by advanced computing to uncover patterns and trends that would otherwise go unnoticed.
Designing is an art. And art, unlike most things, is not supposed to be the same. It needs to be varying, dynamic, adaptive and appealing. The norm of compliance to rules is something that does not apply to designing.
As effective as it is in almost every field today, the term big data has turned into a scourge of sorts that seems to be floating around every corner you turn. People have been so talked out with big data that there is not much left for us to discuss unless of course, we were to discuss the various tools that are employed in processing and analyzing it. There are several platforms, tools, and extensions available today that are meant to serve each and every need.
When it comes to big data, there is no platform or tool that asserts itself as Hadoop does. Of course, the cute little yellow elephant mascot is both symbolic of Hadoop as well as big data in general. An open-source platform for big data, Apache’s Hadoop serves as the go-to place for everything big data, from the most fundamental aspects to more complex processes. With a myriad of different modules to offer, Hadoop sets the bar quite high for versatility. The Hadoop framework itself contains four modules.
Hadoop Common: A module comprised of Java libraries and utilities, Hadoop common supports other Hadoop modules. The libraries of this module contain java files and scripts required to run Hadoop.
HDFS: Hadoop distributed file system or HDFS as it is commonly known is the primary storage system employed in all Hadoop applications.
YARN: Short for Yet Another Resource Negotiator, YARN is Hadoop’s cluster management system. It serves as a buffer between the HDFS’ and the processing engines.
Map Reduce: This is Hadoop’s data conversion module which converts data sets and breaks them down into individual elements called tuples. This is one of the most vital aspects of Hadoop and defining it in two sentences does not do it justice by the least. Perhaps we could cover this topic in detail in the future.
One of the most fundamental tasks when it comes to big data is data sorting or data refining. As a software applied in an underrated aspect of big data, OpenRefine is an open source big data sorting tool that allows you to sort out the most contrived and unstructured of business data. One of the most desirable aspects of this open source tool is its simplicity and the user-friendly nature of its interface which will allow even data newbies to get right into the big data experience. However, as with anything and everything in technology, a little of experience and technology would be most recommended to get the most out of data using Open Refine.
An open source application that runs on Hadoop and NoSQL databases, Talend is a comprehensive tool to harness the best out of big data. It equips the user with various graphics tools and wizards to use Hadoop effectively with data quality, data integration, and management. Furthermore, the simplicity of this application is an added bonus for beginners. Talent offers a visual representation of the data and the processes rather than the source code in a simple drag and drop system, which while desirable to some, could become quite a hassle during certain processes. Talend also offers TalendForge, a collection of open source extensions to support and enhance the experience with various products offered by them.
When it comes to non-relational databases, there is none like Mongo for big data. A document-oriented, cross-platform database, Mongo comes with full index support and a great deal of flexibility. Horizontal Scalability and third-party log tool support are some of the additional features that Mongo offers. This database also comes with a replication facility called the Replica Set which provides automatic data failover and data redundancy.
Yet another data visualization tool for data analysis and other big data related processes, Tableau is quite an impressive piece of technology with a twist. It offers a new perspective of the data by allowing the user to slice it up into bits and even merging it with other data to gain yet another perspective. Tableau harnesses the power of both Apache’s Hadoop as well as Hive to offer an immersive and interactive process.
As if we weren’t short of surprises this year particularly from the tech industry, Google made an announcement that could very well be the most pleasant one so far this year. At the Google I/O conference 2018 held this week, CEO Sundar Pichai announced that the Google Assistant will be getting major updates. And the updates are major indeed with several AI based application that could make life a ‘breeze’ for all you couch potatoes out there. Anyway, let us have a look at the updates that are soon going to hit the market.
Source: crowdfundingheadlines.com
Speaking of couch potatoes, here is an update that is for the ages which could make that expression a literal one soon. The Google Duplex is an AI tool that will be assisting you with real world tasks all accomplished through the phone without you having to move an inch. With the ability to understand natural speech and complex sentences, the google assistant can now book appointments, reservations or orders and should any complication arise it will place a call to have a conversation with the concerned person and get it done. Which, while on the surface seems swell and all, but in the ‘real world’ when have we ever convinced a snooty receptionist at a fully booked hotel to make room. Maybe, Google should add the Jedi mind trick as part of their update if they haven’t already. ‘These are not the reservations you’re looking for’. Anyway, without digressing further, the application has to be trained in such conversations to become accustomed to and eventually become adept at it. And Google stresses that the application can only carry out conversations based on such scenarios and not answer questions like ‘why won’t my girlfriend talk to me anymore? I only made an observation about her dress’. For that, you still have to go to Quora.com.
Google is also planning on changing the interface of the Google assistant on both iOS and Android platforms to make it more informative and interactive. A certain degree of automation will be available in the interface as well with timeline-based snapshots, suggestions, summaries of activities etc. being part of the order. All your planner based details from various applications will also be integrated to the assistant. As announced earlier this year Google’s Smart Displays will also be launched later this year which will further enhance the experience.
Google maps will now be integrated with the Google Assistant AI to allow multitasking. Now you can access weather-related information, songs, send text messages and even podcasts for some reason according to news outlets. This raises an interesting question, what are Google’s policies on driving while speaking on the phone? Because, hands-free or not, talking on the phone is something that I assume is frowned upon all the world. As a matter of fact all over India that is an offense punishable by law. So, food for thought?
One of the most highlighted features of this update are the 6 new male and female voices. And the most highlighted aspect of these voices is that they are ‘natural sounding’. So instead of that persistent and seemingly strict lady asking you to take a left turn at 100 meters, you get John Legend and no you won’t be getting ‘all of him’, just his voice. Hey, at least now we can have a soothing semi-baritone voice telling ‘All your base are now belong to us’ when the machines take over. And if you think I am exaggerating, John legend himself feels threatened by his AI self. That’s why he felt the need to tweet out ‘Real John Legend > AI John.’ Anyway, the new voices will be playing a huge role in achieving the goals that Google seeks to achieve through Google Duplex. Furthermore, you will no longer have to use the phrases ‘OK Google’ or ‘Hey Google’ to trigger a conversation with the assistant. The new update will enable the assistant to distinguish conversations with others from the ones you make with it. Which again is not necessarily a reassuring prospect.
To sum up the new updates seem to be targeted at enhancing user experience by a huge margin and resolving some of the most infuriating issues people have had over the years with various google assistant functions. As ambitious as it is, the project will take a while to incorporate all these functions and hopefully, it would change our lives for the better. And the question in everyone’s mind now probably is what is going to happen with Siri?
Virtual Reality technology has provided the much needed visual impetus to have a second look at products or services. It comes as no surprise at how companies these days are vying to incorporate VR tech considering the number of possibilities and the revenue markets this technology opens up.
One of the prime reasons estimated behind the immensely popular VR tech is the freedom it renders to the person using it. You no longer are bound to where the camera angle goes or what your physical environment is. VR has the power to transport you to an altogether new world that transcends the boundaries of the real world.
In this post, you will get to know how and which industries are benefiting from VR.
Retail showrooms are all about the glitz and the finesse of visual appeal. How about having something that gives the same impression but at half the cost? VR makes that possible for retail outlets everywhere.
Showrooms can now play to their strengths and display things in every shade possible and offering combination suggestions would not be that difficult a process now.
This would also give retailers an insight into what is it that pleases their customers the most and then make necessary changes.
The one thing you visualize when you hear the word architecture or architects is them working on huge blue sheets with scales and high-end pens etc. With the insurgence of VR, this would be far less a hassle.
It also allows them to experiment with the various fundamentals of erecting towers by using visual layouts and lighting and discuss the various outcomes of it all. This, in turn, saves building companies a lot as they come to know of problems before the actual construction takes place.
Visualising the corners of the world would no longer require going there. And that explains why this technology is a phenomenal boon to travel & tourism companies.
The tourists get to virtually visit the location even before they actually travel there, thus aiding their planning. Tourists can finalize accommodations based on the proximity of where they’d want to stay, what view they’d prefer, etc.
Out of all the sectors that rely on visualization for accuracy, the education sector would be considered to be the most important. It could be any branch of education for that matter.
From engineering to medicals, from linguistics to humanities to history and even geography. Bringing in VR would aid better understanding and recollection of concepts, thus making learning a wholesome experience.
Not only would VR aid learning about the human anatomy, but it would also benefit healing it. Getting to the root cause of the matter would bring in better treatment.
Accurate VR-oriented diagnosis brings about better prognosis and this itself would improve the quality of medicine and healthcare all over the globe. This explains why the value of the virtual reality healthcare market in the U.S. has grown from $525 million (2012) to $976 million (2017).
The benefits that VR technology imparts are multifarious and more than what could be enlisted in one article. It is a wonderful era to live in and VR adds essence to existence.
According to an article in The Globe and Mail, the research firm Gartner estimates that there were around 3.8 billion devices and products connected last year. Gartner estimates that by 2020, this number will increase to 25 billion.
Statistically, the projected market for the Internet of things is estimated to be one million U.S dollars annually since 2017.
Evidently this means that the number of players in the IoT development space too would increase to cope with the rising demand from enterprises and customers alike.
Here is how you can use IoT to make your business stand out and to show it to your customers that you have the ability to bring imagination to reality.
The key to a successful product design is less about the technology and more about the design of the product – design that customers can use and leverage IoT to the maximum. The environment and user context can provide a lot of information about how the user will use the product.
Relentless prototyping is the key to ensuring that the time to market is the most opportune rather than the fastest. It is important to understand how the product will fit into the people’s lives and how you can ensure that this transition of the IoT product into their lives happens in the smoothest way possible.
IoT is great at working quietly in the background. Take for instance, the low powered long life sensors or actuators. They stay away from the limelight and continuously deliver data for additional analytics. The hardware needs to interact with it seamlessly and the overall user experience needs to be stellar
IoT goes way beyond adding a chip to connect machine to machine interactions. It needs to address a specific need of the end customer. All solutions (hardware, software, and connectors) need to be designed keeping this end need in mind. Only when the IoT product pays attention to customer behaviour during the product design and development, does it stand the chance to succeed in today’s intensely competitive times.
When your devices hold the ability to self-test, solving problems don’t eat up a lot of time or valuable resources. IoT serves as a bed for AI to comfortably be placed into products and devices which would soon be able to think and act by themselves (just like self-healing process in case of a connection fault).
Investing in the future has been the sole motive of a business and you just cannot ignore IoT when you look at the future from a tech expert point of view. Make sure to keep these considerations in mind so that you can develop a truly distinct IoT product that adds tremendous and tangible value to your end customers’ lives or work.
The blockchain is rapidly emerging as a hot tech trend. It has the capability to disrupt multiple industry sectors and offer endless possibilities and ventures that were once impossible but now are quite the opposite. It is also promising fruitful outcomes through mergers with other technologies
When it comes to mergers, let’s talk IoT (Internet of Things). The technology that is said to connect every device that consists of an IP address and can receive or transfer information is revolutionary in every perceivable sense. But there are challenges IoT seems to face before changing the face of technology. And if experts are to be believed in this arena, Blockchain seems to have just what it takes to address those issues and get the tech rolling.
One of the major challenges IoT faces is its reliance on centralization. This is done via the server/client model. The problem here is that since all devices are connected through cloud servers, in order for devices to be connected, they have to travel a long, long way even if the devices are at an arm’s length.
Yes, there is no denying the fact that cloud computing has revolutionized the tech industry, but looking at how much of data would be generated in the years to come, this system looks vulnerable to an electronic cloud-burst. It is imperative to find a surefire way to overcome this as industries like Healthcare and other very important aspects of human life will soon depend on IoT for its functioning.
This is where the decentralizing approach to IoT comes in handy, as per tech experts. Decentralizing IoT networks across the billions of devices that constitute IoT overall would ensure the absence of a weak spot. In case there ever would be a single spot of issue, it would still not pose enough threat to the entire network and the network would function just like it always did, without a glitch.
Blockchain, primarily, is a technology that allows the formation of a distributed network of transactions that would not rely on storing information in central servers but rather function on the shared nodes of a network. Blockchains use cryptography to authenticate and spot out nodes that enable them to safely add transactions.
What’s the best part about blockchains is that it is totally tamper-proof and cannot be messed or manipulated with.
The fascinating bit about this is that the merger of IoT and Blockchains is already making all the news. Being backed by start-ups and corporate tech giants alike, this IoT-Blockchain merger is riding on a high wave.
Companies like Ethereum and Filament are putting the IoT-Blockchain merger to use and are finding some interesting implications of it.
Though there may be a lot counting on IoT to click for the good of all humanity and though Blockchains pose a genuine solution to most of them, it is far too early to say that IoT-Blockchain is the ultimate solution to it all. It isn’t yet the perfect option but it sure is promising. And for the moment, that’s enough to consider.
Its that time of the year and I for one am not going to make that age-old pun, instead, I’ll just say ‘a Happy May the 4th, wish I everyone’. Indeed it was 41 years ago this day when a seemingly young and assumingly tall George Lucas’s five-year penance in his basement studio bore fruit. The result, of course, a generation of fans to rival the Tolkien universe. Some often refer to Star Wars as a religion, and they are probably right. Of course as old as the franchise is today, so are its original fans. Most of them are probably in their mid-50s. And I think it would be safe to assume that quite a few of them are software developers probably in various fields of technology.
For many in the 70s, Star Wars would have served as a reference point as to how the future would appear. So, after more than four decades, how much of the Star Wars Universe has come to life? Let’s spend some time contemplating on that.
When R2D2 and C3-PO were first introduced, they are trying to escape from Tantive V and by chance meet Luke Skywalker and the story begins. And then we are introduced to the iconic Jedi Mind Trick by Master Obi-Wan. From the beginning, both automatons’ cognitive abilities are quite laudable considering that both of them have the ability to understand and respond in an almost human manner. Of course, R2D2 can only respond with bleeps and buzzing sounds. So fast forward to today, do we have robots that are capable of doing that? Surprisingly the answer is yes. While they are not as refined as the duo, we are getting there. Robotics has seen a lot of star wars style movement as well as designs based on the little dustbin shaped robot. The Robear and several such robots have been designed to perform similar functions as R2D2. Not to mention the AI robots that are eerily close to becoming reflections of ours.
One of the most replicated scenes of all times in science fiction is Princess Leia’s message projected by R2D2 as a hologram. Once considered a farfetched idea that could never be realized, holograms have become quite a common sight today at conventions and mass gatherings. They are still quite expensive, but the result far outweighs the cost.
One of the most humble and surprisingly effective modes of transportation in fiction after the Delorean, the Millennium Falcon is indeed a force to be reckoned with. Capable of blasting off into hyperspace, Han Solo’s priced smuggling ship has been an inspiration to many an inventor. Besides the very idea of blasting off at the speed of light with a tall furry humanoid bear assistant pilot is quite enough for most of us to get to the drawing boards and pour in the hours to come up with something very close. While the speed of light is something that is physically impossible, the idea of large space crafts capable of carrying a huge cargo has inspired some good designs in recent years particularly with the likes of SpaceX trying to achieve largely impossible feats at zero gravity.
The Death Star is arguably one of the most impressive pieces of technology ever conceived, albeit in fiction. Imagine the idea of a giant moon-sized battle station with a force field, and a billion LASERs ready to shoot down anything and everything that approaches. In today’s context, this makes more sense, considering all the threats and dangers we live in. But God forbid it should fall into the wrong hands as it did in the movies. With the amount of effort that is being put into the space programs for extraplanetary bases, it is quite possible that such a structure could be built in the distant if not the near future. Yet again this is something Elon Musk could consider as part of his SpaceX research efforts. Who knows, he probably already has and they are already building one at their secret base.
Probably the most iconic item ever seen in the history of entertainment, the LightSaber is as impressive a weapon as the sound it makes as it cuts through even the toughest of substances in the Alderaan system or the universe even. Every child’s fantasy till the prequel series and the latest sequel series started coming out, this is a weapon that as grown-ups we still feel the urge to fantasize about from time to time. Yet again this is a piece of technology that we have slowly started to develop over the past couple of decades. Directed Energy Weapons (DEVs) as they are called are in the works as you read this article. However, as easy as George Lucas made it seem in the back in the 70s, making DEVs is far from anything resembling any degree of ease. It is estimated that by mid-2020s these weapons will be available on a large scale and could redefine the art of war as we know it today. From short range LASERs to weapons capable of mass damage we have a lot of firepower or rather joules coming our way.
All in all Star Wars has been quite influential both in entertainment as well as in real life. There are several instances where the franchise has brought about change on various levels. Technology in particularly is in a way indebted to George Lucas and his franchise, if not as a source of ideas at least as a source of inspiration to dream big and beyond the stars. Many from the generation ‘x’ probably moved out of their mother’s basement after feeling the force and pursued their dreams. Although it is more likely that most of them got confined to their basements in the first place because of Star Wars. The impact nonetheless has been quite monumental.
Ofcourse all the new movies have taken a huge step back from the amazing atmosphere of imagination and mystery and delivered us to an era of Computer Generated Diarrhea. But Star Wars still takes us all back to the days of our childish wonders where our dreams had no bounds or as Yoda would put it ‘Truly Wonderful the mind of a child is’. So Dream on and May the Force be With You.
If you’ve used the internet at all in the past decade or so, you would have come across this word quite a few times – Big data. Naturally, your interest would have peaked to find out what exactly is big data and why is everybody making such a big deal out of it. If that is the case, you’ve come to the right place, my friend.
Like its name suggests, Big Data is a huge collection of data that is drawn from a vast resource and is constantly growing on an exponential scale. This, however, is a watered down definition. In reality, big data is such a huge repository of data that the data management tools that we have been using for analytics, have been rendered obsolete and newer technologies have sprung up overnight to keep up with the scale. Given the magnitude of this technology, there is a lot of ground for us to cover. So let’s get started.
With all the hype around the size of big data databases, one might be wondering, how big is big data really. It is estimated that every day around 2.5 quintillion bytes of data is generated. That is 2.5 followed by 18 zeros. If that is hard for you to assimilate, it is around 2.5 billion gigabytes. That is an impressively eerie amount of data, especially considering the fact that a healthy percentage of that could be generated from even from the silly banter on the Youtube comments section. Anyway, we are not here to talk about one of the millennial generation’s favorite hobbies, but to talk about the data that governs almost everything we do today.
Big Data can be classified into three major types.
This is data that has fixed format and length. Structured data is usually comprised of numbers, dates, and strings. Structured data is obtained from a myriad of sources, including machine-generated data, human-generated data, and sensor-based data. Experts estimate that around 20 percent of the data available today could be classified as structured data. This is also the data that is being processed in the most comprehensive manner and from which most value is derived.
Contrary to the concept of structured data, this type of data is comprised of non-uniform or non-field based data. It includes all text and multimedia-based data such as word documents, audio files, video files, and other documents. This is the most abundant form of data. It is estimated that unstructured data accounts for around 80 to 90 percent of data generated by organizations today. While this form of data is quite difficult to analyze, the actionable insights acquired by doing so could yield vital actionable insights that could be leveraged to cope with the competition.
This type of data displays certain properties of being structured in form but it is not defined in a relational database as with structured data. XML and non-SQL based data are good examples of semi-structured data. Such data will be easier to analyze, allowing us to leverage better insights.
One of the most defining aspects of big data is its diversity. From text to audio and video, there are a lot of data varieties. Handling such a wide variety of data on such a large scale is a messy tedious affair. Even storing such data will require a wider range of storage tools to match the scale, let alone the nature of the data. Maintaining any sort of consistency when it comes to big data is nothing more than a fantasy. Especially when you consider the fact that each browser, platform, and the web page has its own specific data, the versatile nature of the data really exasperates things. Processing this data, therefore, could pose as an insurmountable task. One of the most significant ones is the loss of vital parts of each piece of data while processing and analyzing. This beats the very purpose of big data. While traditional computing methods fail at the first whiff of such data, agile based technologies have proven to be quite effective when it comes to analyzing and processing big data. There are several programs to this end that should be explored. Perhaps we could cover those in another article.
Given the large volume of data that floats around the internet these days, speed is a factor that plays a key role in making anything out of it. The idea behind big data has always been to leverage it to use every bit of data available. And given the density of competition, companies have to get their big data sorted out fast. Keeping track of the frequency or velocity of data generation will allow companies to gain insights on the growth of data and how fast it is being relayed to various ends.
Volume is the most significant attribute of big data. Today there are a lot of sources for data generation and these sources are generating an unfathomable amount of data. Even labeling a collection of data as ‘big data’ depends on its volume. So, this is a crucial attribute that needs to be taken into consideration before delving deeper into the data.
Big data is undoubtedly a technology that has been revolutionizing various vertically of enterprise for nearly a decade now. As newer technologies are developed to process and analyze big data, the valuable insights that are driving millions of businesses today will become more insightful as well as productive.
Modern businesses rely a lot upon a good logistics system. Keeping up with the sheer volume of business that companies deal with today doesn’t make things any easier. This is where all the automated goodness of AI plays a major role as a disruptor. Given the expanse of functions within the logistics industry, it is no doubt that there is a lot that AI could do and to a great extent is already doing.
For the logistics industry, the journey has been long and eventful, starting in the early days of pioneers looking for trade routes to procure tea and spices. At this juncture of the 21st century, however, logistics has evolved to its fullest as far as infrastructure is concerned. Furthermore, there are very few industries today that does not apply logistics in one form or the other. There are quite a few aspects of logistics that AI could be applied to. Here are a few areas where artificial intelligence is applied in logistics.
The heart and soul of the logistics industry is transport. Without transport, every other process in logistics is just redundant. While the 20th century could make do with paper and ledger based management systems, transport in the 21st century requires a giant leap. This is where AI’s role is pretty cut and dry. Before getting into AI’s role in transport management, we need to address the current scenario surrounding this technology. Transport being a rather physical function, most logistics companies address it as such and consider it quite a priority and with good reason. There are several hassles and risks involved with transportation which go beyond the pen and paper strategies devised in offices. This is the reason why most companies leave the data based technological bits to third-party logistics companies or 3PLs. This has slowed down the widespread adoption of technology in general.
This trend of outsourcing technological details to 3PLs has also limited the influence of mobile technology which plays a huge role in AI-based applications. So, coming back to automation, the advancements made in optimizing transport management has been monumental. As far as AI in transport management is concerned, the idea is to automate as much of the entire process as possible. And to this end, there are quite a few remarkable devices and applications out there.
The fast pace at which the world moves today demands fast systems for anything and everything to cope with our lifestyle. In logistics live tracking has been quite a disruptor. There are several automated tracking applications for all platform that collect and relay a lot of vital data. From scheduling trips to providing live updates of the cargo’s position, AI-based applications ensure an open and intuitive line of communication between the bases and mobile units. Even information such as traffic, potential delays and so on are relayed using predictive analysis. Furthermore, advancements in the mobile industry and the level of simplicity they have facilitated therein have inspired various businesses to onshore many of their processes pertaining to this. Online retail companies such as eBay, Amazon and so on have already adopted this technology on a rather comprehensive level with their management capabilities going down to the door level.
Black boxes in trucks have received an overhaul as well. Advanced back boxes provide a great deal of support for the operating companies as well as drivers. These devices are capable of collecting information such as engine temperature, the status of the load, tire pressure and so on. Despite their fundamental purpose as a disaster recording tool, these black boxes make this data analyzable in real time and allow operators to monitor and manage their transport systems well. Similar advancements have been made in the systems of cargo ships and airplanes along with advanced automated navigational tools.
While transport is a major aspect of logistics, it is still just a part of a larger process comprised of several smaller processes. These are the processes where AI could manifest into more cognitive and at times even physical forms. There are various manual processes which take thousands of man-hours to get through, and after all that could still yield various levels of errors. Here are a few of those processes that have been optimized by AI.
Ask anyone who has worked in a warehouse and they will tell you how hectic the schedule there is. The volume of loading and unloading that take place alone is enough to drive Rain Man and John Nash crazy. Loading and unloading then again are just the tip of the iceberg. AI in warehouse management has simplified many of these processes. The use of AI-based sorting and labeling systems have allowed logistics companies to speed up these processes and minimized the margin of error.
The AI systems in logistics today are also capable of scheduling various tasks within the entire process. Automation of planning and scheduling is something that has revolutionized logistics. AI systems, based on various warehouse itinerary data schedule the transportation, organize pipelines for cargos, assign and manage various employees to particular stations and so on. Apart from the obvious con of potential layoffs, this particular application of AI in warehouses has facilitated a faster network for logistics processes.
While AI’s application in logistics has been in a minimalistic way to various mundane tasks, one of the most pronounced applications has been that of robots. Despite the constant opposition from various scholars and trade unions, robotics has been applied to a great extent in all fields and logistics has not been spared in the least. From working in warehouses to transferring freight at cargo airports, robots have their work cut out for them and they are doing it at speeds their flesh and blood counterparts could never achieve.
Despite the slow rate of progress in adopting AI as a logistics tool, the technology is slowly but surely seeping into the system. Machine learning has further allowed investors with a broader outlook on how AI could revolutionize logistics just as it has done in many other verticals. The issue that surrounds AI now is not lack of optimization but the dilemma of having to divert time towards setting it up. This in today’s context makes sense as most companies shy away from investing in newer technologies unless a dire need for it is presented.
