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line 40, column 0: content:encoded should not contain iframe tag (4 occurrences) [help]
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Source: https://datawider.com/feed/

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<title>Composable Commerce: The Future Of eCommerce</title>
<link>https://datawider.com/composable-commerce-the-future-of-ecommerce/</link>
<comments>https://datawider.com/composable-commerce-the-future-of-ecommerce/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Fri, 20 Oct 2023 06:12:16 +0000</pubDate>
<category><![CDATA[Business]]></category>
<guid isPermaLink="false">https://datawider.com/?p=738</guid>
<description><![CDATA[With technology developing at unprecedented rates, many find themselves racing to catch up on the latest and greatest. In the world of e-commerce, there’s one such advancement that has been making waves recently in retail circles: composable commerce. As a prominent up-and-coming modular approach, there’s a lot to learn about this modern technology and the [...]
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]]></description>
<content:encoded><![CDATA[With technology developing at unprecedented rates, many find themselves racing to catch up on the latest and greatest. In the world of e-commerce, there’s one such advancement that has been making waves recently in retail circles: composable commerce. As a prominent up-and-coming modular approach, there’s a lot to learn about this modern technology and the impact it’s having on the industry.
What is composable commerce? Defined as a component-based design approach, composable commerce provides companies the capability to build and run outstanding shopping experiences via enhanced flexibility and freedom within their eCommerce system. Brands utilizing such a system have the capacity to redefine their digital business strategies and add significant value to their customers’ overall experience. 
How so? Through a stronger emphasis on modular and adaptable approaches, composable commerce can offer brands the solutions needed to compete in an evolving market. These include greater flexibility when swapping out the various components of their tech stacks as well as enhanced agility to meet the ever-changing shifts in consumer needs and expectations. The result is an enriched ability to customize retail interactions for a value-added experience across channels.
There are three core traits that come together for a composable system. The first is that it should be cloud-native; in other words, your software runs in the cloud and benefits from tremendous autoscaling to manage online traffic peaks. Second, it must be component-based: This is the ability to add, replace and maintain modules independently. The third is that the system is tech-agnostic. This means it is not bound to one proprietary technology or programming language. A tech-agnostic system is vital as it provides the business complete freedom of engineering and application management. In addition to these benefits, composable commerce also offers infinite scale and improved adaptability to meet customer expectations of today and tomorrow.
These are just a few of the benefits offered by this emerging technological advancement. If you want to learn more about composable commerce, its benefits and how to implement it, please see the accompanying resource from commercetools.
<iframe src="https://drive.google.com/file/d/1QwMhSi2XGR_Z2S7Yt5pdyyQ1XCyyBrB5/preview" width="640" height="2100" allow="autoplay"></iframe>
Infographic created by commercetools, a <a href='https://commercetools.com/composable-commerce'>composable commerce platform<a/> company
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]]></content:encoded>
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<item>
<title>How Can Telematics Data Improve Freight Transportation?</title>
<link>https://datawider.com/how-can-telematics-data-improve-freight-transportation/</link>
<comments>https://datawider.com/how-can-telematics-data-improve-freight-transportation/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Wed, 28 Sep 2022 01:04:12 +0000</pubDate>
<category><![CDATA[Big Data]]></category>
<category><![CDATA[Technology]]></category>
<guid isPermaLink="false">http://datawider.com/?p=676</guid>
<description><![CDATA[In the old days, the only real metric for determining how well drivers did their jobs was how often they made their deliveries on time. Today, however, fleets have access to a lot more information. Tech professionals working in the freight and logistics sectors should all be aware of telematics and the many benefits the [...]
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]]></description>
<content:encoded><![CDATA[In the old days, the only real metric for determining how well drivers did their jobs was how often they made their deliveries on time. Today, however, fleets have access to a lot more information. Tech professionals working in the freight and logistics sectors should all be aware of telematics and the many benefits the technology can provide. With the data these systems collect, shippers can make better informed decisions about their drivers as well as their vehicles.
Telematics systems collect and process information from the vehicle at all times. This includes speed, location, acceleration, idle time, fuel consumption and more. That data is transmitted to a central server, where it can be accessed by the company for analysis. It gives managers, supervisors and tech pros exceptionally detailed insights into the performance of their fleets.
For example, driver behavior can be monitored to understand which employees are following safety precautions or meeting their projected arrival times. Knowing how soon each truck needs regularly scheduled maintenance can prevent breakdowns and increase productivity. Real-time updates on road conditions or traffic allow for routes to be adapted on the fly. Stolen equipment can be recovered thanks to GPS installed on each truck and trailer. Adjustments to fuel management can be implemented before inefficiencies cost the company too much.
Implementing telematics has the potential to improve freight transportation significantly, boosting revenue and lowering costs.
To learn more about how this technology can benefit the industry, take a look at the accompanying resource.
<iframe src="https://drive.google.com/file/d/1Q67HfFfmXVl8rTVszlq8ZhNe4wgB7376/preview" width="640" height="2150"></iframe>
Infographic created by
Track Your Truck, a <a href="https://www.trackyourtruck.com/gps-tracking- devices/">GPS vehicle tracking devices</a><a> provider</a>
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]]></content:encoded>
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<title>Differences Between Public, Private & Hybrid Cloud</title>
<link>https://datawider.com/differences-between-public-private-hybrid-cloud/</link>
<comments>https://datawider.com/differences-between-public-private-hybrid-cloud/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Wed, 28 Sep 2022 01:00:09 +0000</pubDate>
<category><![CDATA[Business]]></category>
<category><![CDATA[Technology]]></category>
<guid isPermaLink="false">http://datawider.com/?p=674</guid>
<description><![CDATA[Cloud computing has been one of the biggest developments in the world of information technology over the last decade. This innovation has made it possible for large quantities of data to be stored and secured without the need to manage a large-scale infrastructure. Although the most common perception of these systems involves remote server banks [...]
The post <a rel="nofollow" href="https://datawider.com/differences-between-public-private-hybrid-cloud/">Differences Between Public, Private & Hybrid Cloud</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
]]></description>
<content:encoded><![CDATA[Cloud computing has been one of the biggest developments in the world of information technology over the last decade. This innovation has made it possible for large quantities of data to be stored and secured without the need to manage a large-scale infrastructure. Although the most common perception of these systems involves remote server banks hosted in off-site locations, the truth is a little more complicated. Indeed, there are three main categories of cloud systems — public, private and hybrid. Each one brings its own unique set of advantages and drawbacks. If you’re a tech professional, it pays to know what these are so you can make the best-informed choice for your organization.
Public clouds are operated by third-party providers and shared by multiple organizations. They offer high scalability and cost effectiveness but fewer opportunities for customization. Private clouds are entirely in-house within a single enterprise and are not shared with anyone else. These provide more control and efficiency but tend to be much more expensive to operate. A hybrid cloud system combines the two, with both public and private servers contributing to the overall framework. They can be highly flexible and reliable but require a sizable investment and bring more complexity.
Moving your company’s data to the cloud can bring a wide range of benefits, but only if you know how to weigh the pros and cons of each model. To learn more about these three models, look at the accompanying resource for some details about what each has to offer. 
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width="640" height="2280" allow="autoplay"></iframe>
Infographic created by 
HotWire Networks, a <a href='https://www.hotwirenetworks.com/hosting'>web 
hosting</a> company
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]]></content:encoded>
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<title>AI’s Influence on Business Software</title>
<link>https://datawider.com/ais-influence-on-business-software/</link>
<comments>https://datawider.com/ais-influence-on-business-software/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Thu, 28 Jul 2022 09:24:44 +0000</pubDate>
<category><![CDATA[Artificial Intelligence (AI)]]></category>
<guid isPermaLink="false">http://datawider.com/?p=664</guid>
<description><![CDATA[It’s no secret that AI is having a profound impact on businesses of all sizes. But what may not be as well known is the extent to which AI is shaping the software that companies use to run their businesses. AI is increasingly becoming the brains behind business software, and its influence can be seen [...]
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]]></description>
<content:encoded><![CDATA[It’s no secret that AI is having a profound impact on businesses of all sizes. But what may not be as well known is the extent to which AI is shaping the software that companies use to run their businesses. AI is increasingly becoming the brains behind business software, and its influence can be seen in everything from marketing software to accounting software. Even in the testing of the software itself through <a href="https://testrigor.com/ai-in-software-testing/">AI in software test automation</a>.
Let us then explore the different areas of business where AI has made a difference through its influence on the software that runs a business in part, and then with regards to its testing.
<h2>Marketing</h2>
In <a href="https://www.forbes.com/sites/forbesagencycouncil/2019/08/21/how-artificial-intelligence-is-transforming-digital-marketing/?sh=2cedbdd721e1">marketing</a>, software and AI is being used to create more personalized campaigns and target ads more effectively. AI-powered accounting software is making it easier for businesses to track their finances and make better decisions about where to invest their money. And AI chatbots are becoming increasingly popular as a way for businesses to provide customer support.
<h2>Business Development</h2>
AI is also playing a role in the development of new business software. Many companies are using <a href="https://www.getsmartcoders.com/services/data-science/artificial-intelligence-services.php">Artificial Intelligence Services</a> to create software that can automate tasks and make employees more productive. This kind of intelligent technology is being used to create better predictive analytics tools, which can help businesses make better decisions about the future.
As AI continues to evolve, its influence on business software is only likely to grow. AI is quickly becoming the driving force behind the software that companies use to run their businesses. And as it gets smarter, so will the software that it powers.
<h2>Automated Software Testing</h2>
Apart from AI software running many areas of business, it is also used in the process of checking software code. It is how the process is automated out of human control. A previous control that could potentially hamper its accuracy and most certainly drive up its cost.
Efficiency is what every business strives for and checking processes are no longer cost-effective to consider doing manually. Software testing or checking is one of these areas that has had to become automated to make it affordable. It is so important that it is carried out for efficiency and security reasons using the latest AI technology. It certainly encourages that it takes place.
<a href="http://datawider.com/software-testing/">AI-controlled software testing</a>, as opposed to that which was previously always manually controlled, helps businesses to save on wage bills and ensures that problematic errors in software coding are not missed by the checkers. The more errors detected at an earlier stage, the better for a business. It could be disastrous for a company to have errors that end up inconveniencing staff or customers. 
Inefficiency with software can result in lost business through lost reputations. Should a company’s software inconvenience anyone in the present, they are likely to look elsewhere in the future to do business. Staff morale can be lowered too when they just don’t have the tools to do the job. Firms with the best technology will attract the best candidates.
AI is continuing to have a profound influence on business software. AI-powered software can now do everything from automating simple tasks to making complex decisions for businesses. As AI continues to evolve, likely, even more, powerful and transformative applications of AI in business software will be developed. If you’re not already taking advantage of AI-powered software in your business, now is the time to start.
It is AI that is increasingly becoming the driving force behind business software and its influence is seen in all departments of a business. Even in the testing of the software itself, AI has made a difference. As AI continues to evolve, so too will the software it checks.
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]]></content:encoded>
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<title>DataOps vs. MLOps: Let’s Understand the Differences?</title>
<link>https://datawider.com/dataops-vs-mlops-lets-understand-the-differences/</link>
<comments>https://datawider.com/dataops-vs-mlops-lets-understand-the-differences/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Wed, 01 Jun 2022 10:47:27 +0000</pubDate>
<category><![CDATA[Big Data]]></category>
<category><![CDATA[Technology]]></category>
<guid isPermaLink="false">http://datawider.com/?p=651</guid>
<description><![CDATA[Data processing and model development is a core business operation today. The collection of crude data is just the first step of a fairly complex and extensive process. Companies need to classify data based on relevance and sensitivity. This data is then used to train AI software and improve its responsiveness. OPs are software combinations [...]
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]]></description>
<content:encoded><![CDATA[Data processing and model development is a core business operation today. The collection of crude data is just the first step of a fairly complex and extensive process. Companies need to classify data based on relevance and sensitivity. This data is then used to train AI software and improve its responsiveness. OPs are software combinations that are used to automate the data delivery process. 
Additionally, this software also integrates the data according to the prevailing workflow management and cloud storage. Agile principles have laid the foundation for DevOps, which aims to simplify the cross-stack integration process and data usage. Now, DataOps and MLOps are not focused on IT. Instead, they can have company-wide applications. In this article, we will lay down the differences between DataOps and MLOps.
<h2>Key requirements to deploy DataOps</h2>
DataOps ensures better collaboration across an organization. It extends the capability of DevOps methodology and eliminates the data storage across various departments. The major advantage that the DataOps methodology provides is that it democratizes data usage and makes it easily accessible to development teams and business teams. 
This democratization is achieved through seamless service portals and collaborative infrastructure. DataOps can enhance the capability of an organization by automating the data flow to the engineering, development, and operations teams. Additionally, this methodology also integrates tools and automation processes to improve data accessibility. 
To deploy this methodology, an organization should invest in an efficient data science platform. Such a platform can be used for data migration for open-source networks as well as vendors. 
DataOps methodology can be integrated with the organization’s commonly used frameworks and languages. It is also to be noted here that DataOps rely on automation in the IT sector within an organization to trigger certain tasks such as pipeline monitoring, quality assurance, etc. When the self-sufficiency of IT and business teams are improved, an organization automatically becomes more efficient. 
<h2>Key requirements to deploy MLOps</h2>
MLOps adoption is a bit more complex than DataOps adoption. It requires carefully planned steps and procedures across various departments. We must note here that MLOps require different stages to set off the machine learning model. 
The stages include IT and business goal identification, model development and training, data collection, data annotation, and final deployment. Post deployment,A there is also a requirement to have a system for proper maintenance of the model. MLOps trains data models by assigning the data from various pipelines. 
<a href="https://www.iguazio.com/mlops/">MLOPs solutions</a> mimic the task of extraction, transfer, and loading of master data management systems. The purpose of deploying MLOps is to streamline data flow and assure the quality of data that goes into processing. The primary objective of this methodology is to ensure business-wide collaboration and bridge the gap between various teams. 
By deploying the MLOps methodology, organizations can ensure monitoring and proper governance of machine learning projects. To deploy MLOps, IT teams must create an efficient machine learning lifecycle conforming to the industry standards. Additionally, the IT department must also take note of regulatory guidelines for sensitive data handling. Also, a well-defined machine learning tracking system should be in place to minimize errors in production.
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]]></content:encoded>
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<title>Dream Engine – The Best Place to Find Space For TV Commercial Production</title>
<link>https://datawider.com/dream-engine-the-best-place-to-find-space-for-tv-commercial-production/</link>
<comments>https://datawider.com/dream-engine-the-best-place-to-find-space-for-tv-commercial-production/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Thu, 26 May 2022 03:48:00 +0000</pubDate>
<category><![CDATA[Business]]></category>
<category><![CDATA[Technology]]></category>
<guid isPermaLink="false">http://datawider.com/?p=648</guid>
<description><![CDATA[Are you looking for a place to produce your television commercial production in Melbourne? Look no further than Dream Engine. We are the best place to find space for TV production. With our studios and crew, you can create a high-quality commercial that will get your message out to the world. What is TV commercial [...]
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]]></description>
<content:encoded><![CDATA[Are you looking for a place to produce your <a href="https://www.dreamengine.com.au/video-production-services/television-production-melbourne/">television commercial production in Melbourne</a>? Look no further than Dream Engine. We are the best place to find space for TV production. With our studios and crew, you can create a high-quality commercial that will get your message out to the world. 
<h2>What is TV commercial production?</h2>
TV commercial production is the process of creating a television commercial. Television commercials are short, 15 or 30 seconds, and air during commercial breaks on TV shows. 
They are a form of advertising, and their purpose is to promote a product, service, or brand. Ad agencies produce TV commercials on behalf of their clients. The first step in tv commercial production is to develop an idea or concept for the ad. The agency’s creative team usually does this.
Once the idea is okay by the client, the next step is to produce the commercial. This involves hiring a production company, cast and crew, and shooting the commercial. After the commercial shot, It’s edited and then aired on television.
<h2>Is Dream Engine the best place to find space for TV commercials?</h2>
At Dream Engine, we specialise in making branded videos that tell your story and connect with your audience. Our experienced corporate video production team has a proven track record. We are best at producing high-quality, engaging content that gets results. 
We help brands find their voice and create engaging videos that showcase you in a positive light. With our marketing platform, clients can reach their target audience in a way that engages and inspires them. Contact <a href="https://www.dreamengine.com.au/">Dream Engine</a> today to learn more about how we can help you get the most out of your TV commercial space.
When it comes to TV commercials, Dream engine is the best production company in Melbourne. There are many reasons why this is so, but here are the top 5:
✔ We have a friendly, engaging tone of voice that will keep your viewers hooked 
We create compelling branded videos that help you deliver your internal communications strategy. Our friendly, engaging tone of voice keeps your viewers hooked. Our experienced team knows how to create videos that achieve your objectives. Even if you want to get your employees more involved or improve how they talk to each other, we can help.
✔ Our team has years of experience in TV commercial production, so you can be sure your ad will look and sound great
When it comes to creating a TV commercial that looks and sounds great, our team has the experience you need. We’ve been in the business of producing high-quality video content for years. Our crew has produced TV commercials, web videos, and more. We know how to create a commercial that engages viewers and leaves a lasting impression. 
We know how to shoot and edit, so we can give you a finished product that you’ll be proud to show off. So, if you’re looking for a team that can produce a top-notch TV commercial, look no further than ours. We’re ready to put our experience to work for you.
✔ We have a range of affordable packages to suit any budget
In selecting a communications partner, the cost is a decision issue. We offer a range of affordable packages to suit any budget. Whether you need marketing or internal communications support, we provide a low-cost solution. 
The client’s project will be done on time and under budget as we deal with some of the best production companies. So if you’re looking for quality communications at an affordable price, give us a call today. We’ll be happy to discuss your needs and tailor a suitable package for you. 
 ✔ Our team is passionate about creating high-quality videos that engage and entertain viewers
Our conference videos can be produced through online distribution in mind. We make them engaging and entertaining to capture the audience’s attention. We also produce videos for advertising space on websites and social media platforms. Unlike conference videos, video commercials must be compelling to be efficient. Our crew enjoys creating high-quality videos that entertain and engage viewers. We are always seeking new methods to attract viewers.
✔ We work closely with our clients to ensure that their vision for the commercial is realised
As a video production company, Dream Engine knows that a commercial is more than a video. It’s an opportunity to tell your story and connect with your audience on a deeper level. That’s why we work with our clients to guarantee we fulfil their commercial goal. From concept creation to final video production, we’re with you every step of the way. 
We also offer website video clips and training videos to help you get the most out of your video project. We can help you develop an engaging and effective ad to promote your business or sell a product.
If you’re looking for TV commercial production in Melbourne, Dream Engine should be your first and only stop. We have years of experience and a team of talented professionals. We can help you create a commercial that will not only grab attention but also convert viewers into customers. Contact us today to get started!
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<title>Advancements in Robotics Everyone Should Know About</title>
<link>https://datawider.com/advancements-in-robotics-everyone-should-know-about/</link>
<comments>https://datawider.com/advancements-in-robotics-everyone-should-know-about/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Sat, 14 May 2022 03:40:32 +0000</pubDate>
<category><![CDATA[Artificial Intelligence (AI)]]></category>
<category><![CDATA[Technology]]></category>
<guid isPermaLink="false">http://datawider.com/?p=643</guid>
<description><![CDATA[Robotics has been thought of as purely science fiction for a long time. Since the days of Philip K. Dick, robots have been the stuff of dreams. They were an imagination, something we’d never fully accomplish. This turned out to be untrue. Not only has the field of robotics become a reality, but there have [...]
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]]></description>
<content:encoded><![CDATA[Robotics has been thought of as purely science fiction for a long time. Since the days of Philip K. Dick, robots have been the stuff of dreams. They were an imagination, something we’d never fully accomplish. This turned out to be untrue.
Not only has the field of robotics become a reality, but there have also been quite a few advancements in the industry. Whether you are interested in robots that clean the floor or are waiting for the world to be crawling with machine individuals, below are the advancements in robotics everyone should know about.
<h2>Artificial Intelligence (AI)</h2>
You probably already know about artificial intelligence (AI). You’ve probably seen the movie AI, but do you really understand it? AI describes the capacity of machines to learn by themselves, adapt to their surroundings, and make complex decisions. Of course, technology is integral to the field of robotics.
<a href="http://datawider.com/what-is-artificial-intelligence-ai-in-business/">Robot vacuums</a> were some of the first machines to use AI in their products. Now, as robotics evolves and the technology gets better, AI is becoming much more useful to create effective robots. AI will change a lot in human civilization, but robotics is certainly one of the areas that is most impacted by the technology. The ability for machines to learn on their own will change everything.
<h2>Teleoperation</h2>
Another hugely impactful aspect of robotics is teleoperation. <a href="https://www.sarcos.com/products/guardian-xt/">Teleoperated robots</a> are a great advancement in technology. Now, humans can control robots remotely. Whether the people are using robots to do work in dangerous areas or are just having some fun controlling a machine, teleoperation has changed the way we think about technology, machinery, and robotics in general.
The ability to control robots from safety can change the way that we get things done and work with machines. Teleoperation and robotics are a game-changing advancement for so many people. Now, people can operate a robot from far away. This opens the doors to all kinds of opportunities. Teleoperated robots are the stuff of the future.
<h2>Automation</h2>
Automation is when a machine operates on its own. It isn’t quite learning like AI, but instead it has all the information it needs to move forward or continue the task. Automation is being used in all kinds of ways. For example, self-driving cars use automation and image-capture technology to know where the other cars are on the road.
This technology isn’t just useful for cars; robots can use automation to perform specific tasks. Whether a robot is cleaning the floor, taking out the trash, or solving complex math problems, robotics is forever changed by automation. It creates the opportunity for <a href="https://www.bbvaopenmind.com/en/articles/a-decade-of-transformation-in-robotics/">machines to facilitate human life</a> and make our day-to-day existence easier. Automation is central to the improvements of technology. It will continue to change our world. As human life evolves, technology will make our lives easier and more convenient.
<h2>Robotic Enhancements</h2>
One thing that people didn’t anticipate when they were fantasizing about robots was just how much they would be able to enhance the human body. You don’t need a full-scale walking and talking robot to take advantage of all that robotics has to offer. There are body suits, robotic arms, and gloves.
You can use the enhancements to protect yourself in a dangerous work environment. When you’re working in heat, with sharp objects, or with hazardous chemicals, robotic enhancements can protect your body. Furthermore, they can make your body stronger. You will be able to lift more and increase your endurance. Robotics is enhancing human lives in other ways than just fulfilling tasks. 
Robotics is a field that continues to change. For some people, it has moved slowly. But robotics has advanced quickly. Robots are now reaching the ideas of science fiction. The field has evolved with the rest of technology.
Robotics is now a player in the conversation around modern tech and the future of human life. Whether you are interested in robotics as a field or are dreading the day machines walk among us, there is no stopping the evolution of robotics. The future is up in the air, but one thing is for sure. Machines will become more efficient, with the ability to teach themselves new things, move around more effectively, and facilitate our daily lives. It’s inevitable.
The post <a rel="nofollow" href="https://datawider.com/advancements-in-robotics-everyone-should-know-about/">Advancements in Robotics Everyone Should Know About</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
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<title>The Power Of Data Analytics For Non-Profits</title>
<link>https://datawider.com/the-power-of-data-analytics-for-non-profits/</link>
<comments>https://datawider.com/the-power-of-data-analytics-for-non-profits/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Thu, 24 Mar 2022 14:44:21 +0000</pubDate>
<category><![CDATA[Big Data]]></category>
<category><![CDATA[Business]]></category>
<guid isPermaLink="false">http://datawider.com/?p=634</guid>
<description><![CDATA[Countless businesses large and small have embraced data analytics as a foundational element of their decision-making process. The reason for this is simple — harnessing data effectively means making better choices and more money. However, improving profitability isn’t the only reason why big data matters, which is why non-profit organizations (NPOs) also should take advantage [...]
The post <a rel="nofollow" href="https://datawider.com/the-power-of-data-analytics-for-non-profits/">The Power Of Data Analytics For Non-Profits</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
]]></description>
<content:encoded><![CDATA[Countless businesses large and small have embraced data analytics as a foundational element of their decision-making process. The reason for this is simple — harnessing data effectively means making better choices and more money. However, improving profitability isn’t the only reason why big data matters, which is why non-profit organizations (NPOs) also should take advantage of it. 
If anything, data and IT professionals at non-profits should be more interested in reaping the benefits that data analytics can provide. With limited resources and large populations of people depending on their services, non-profit institutions such as public school districts and charities need to squeeze as much value from every last dollar they spend. 
These processes provide them with streamlined budget forecasting, greater recruitment and retention capabilities, and enhanced outreach — among other benefits. In essence, the use of data in this fashion enables these organizations to work smarter, not harder. 
<h2>Analytical Strategies That Work Best for Non-Profits</h2>
There are four main types of data analytics that have been found to provide non-profit groups with the greatest value. These are: 
 – Predictive: This uses trends found in data to predict future outcomes. 
– Diagnostic: Used to find connections between variables to provide insight into why something happened, this technique often troubleshoots initiatives after the fact. 
– Descriptive: Normally used to compare performance between different periods of time, this format provides a detailed look into matters. 
– Prescriptive: Machine learning gives this strategy the capability to forecast outcomes and suggest courses of action that may be the most successful. 
<h2>How Using Data Can Benefit Your NPO</h2>
There are numerous ways in which your organization may be able to realize smoother operations and greater success through the application of one or more of these techniques. For instance, it can help you gain a better handle on how you spend funds by recognizing areas where greater efficiency could be achieved. 
It also has the potential to optimize your fundraising by identifying areas of opportunity that may not have been as obvious without it. You also can take advantage of it to help you recruit and retain volunteers more effectively by spotting those who would be the best candidates based on their prior involvement. 
As a data or IT professional, you don’t need to be concerned about the bottom line to realize how much advanced data analytics can do for you. Even non-profits are taking advantage of everything these models have to offer, and so can yours. To learn more about the benefits they can provide, take a look at the accompanying resource.
<iframe src="https://drive.google.com/file/d/1GpdhAY2purN6KumUAcSilzFNHrhV7zlV/preview" width="640" height="2500" allow="autoplay"></iframe>
Infographic created by Sylogist, a <a href='https://www.sylogist.com/serenic-navigator/'>fund accounting software<a/> company
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<title>Before Jumping into Machine Learning, Do These Very Human Things First</title>
<link>https://datawider.com/before-jumping-into-machine-learning-do-these-very-human-things-first/</link>
<comments>https://datawider.com/before-jumping-into-machine-learning-do-these-very-human-things-first/#respond</comments>
<dc:creator><![CDATA[Data Wider]]></dc:creator>
<pubDate>Wed, 19 Jan 2022 07:52:56 +0000</pubDate>
<category><![CDATA[Artificial Intelligence (AI)]]></category>
<guid isPermaLink="false">http://datawider.com/?p=624</guid>
<description><![CDATA[Machine learning is one of the most exciting aspects of modern computing. It is one of the top reasons to major in computer science. Companies will pay massive bounties for programmers who are skilled in the area. You will make an executive’s salary from the firs day you enter the field. Your stock options will [...]
The post <a rel="nofollow" href="https://datawider.com/before-jumping-into-machine-learning-do-these-very-human-things-first/">Before Jumping into Machine Learning, Do These Very Human Things First</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
]]></description>
<content:encoded><![CDATA[Machine learning is one of the most exciting aspects of modern computing. It is one of the top reasons to major in computer science. Companies will pay massive bounties for programmers who are skilled in the area. You will make an executive’s salary from the firs day you enter the field. Your stock options will set you up for life. Moreover, you will be scouted while you are still in college. And like top college athletes, companies will entice you to go pro even before you finish your degree. It hardly gets better than that as a career direction.
But slow your roll for a hot minute. The reason the career is so exciting is that machine learning paired with artificial intelligence is the new infrastructure for all computing endeavors going forward. It is the framework that will undergird everything from social media algorithms to government policy. No aspect of life, including medicine and healthcare, is excluded. <a href="http://datawider.com/machine-learning-everything-you-need-to-know-about-machine-learning/">Everything you need to know about machine learning</a> cannot fit into a single article. There are a lot of technical aspects of it that will take years of study to unravel. But there is also a human component that many in the field fail to consider. Here are three:
<h2>More Than Math</h2>
To be clear, there is a lot of math in computer science. There are excellent tools that can help you <a href="https://www.proprep.com/georgia-state-university/math/math-2212">study for calculus</a>. Just remember that there is a big difference between coding a simple Android app and mastering computer science. You don’t need to know anything about machine learning to code an app. In fact, you don’t really need to know that much about programming. But for machine learning, there is a rather steep human learning curve.
Before getting into the field, you need to know the human cost of machine learning. It is not for no reason that you will be paid all that money. It will take a great deal of study and dedication. Even after you have started your first job, the study doesn’t end. It never ends. The computer science industry is demanding and calls for lifetime learners. There will be new standards, new methods, and new programming languages. What you learn in school will be a foundation for what is to come. It will not be the end of the knowledge you need, but the beginning. Be sure you are ready for that level of dedication.
<h2>Beware of Bias</h2>
Humans are terribly biased when it comes to just about everything. We cannot separate our biases from other aspects of our lives. Machines have the potential to do better. But they will only do better if we remove our biases from the teaching process. It has been shown time and again that there is <a href="https://sitn.hms.harvard.edu/flash/2020/racial-discrimination-in-face-recognition-technology/">racial discrimination in facial recognition technology</a>. At the heart of the problem is the racial inequity in the field of computer science.
Early facial recognition was based on caucasian faces. Computers got very good at recognizing caucasion faces. But they were very bad at recognizing non-caucation faces. Female faces were poorly recognized for much the same reasons. This did not initially stop law enforcement agencies around the world from deploying the bias-laden tech. More recent efforts are doing better. But we still have a long way to go. You have to remember that you are not just manipulating ones and zeros. You are affecting human lives that deserve systems free from human bias.
<h2>Machines Cannot Replace Humans</h2>
There are many jobs that machines can do more efficiently than humans. But the goal should never be to replace humans. It should be to empower humans to reach their maximum potential. Many corporations are only interested in machine learning as a means of replacing all those expensive and troublesome humans. If that is the goal toward which you are working, just remember that the computers could theoretically learn enough to replace you. Such a dystopic approach serves no one. Be sure to advance the technology in a way that empowers rather than replaces.
There is no denying the exciting potential that will be unleashed with the development of machine learning. Just remember that machine learning is a very human affair. It requires human dedication, the subjugation of human bias, and the desire to empower humans rather than render them obsolete.
The post <a rel="nofollow" href="https://datawider.com/before-jumping-into-machine-learning-do-these-very-human-things-first/">Before Jumping into Machine Learning, Do These Very Human Things First</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
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<title>Machine Learning – Everything You Need To Know About Machine Learning</title>
<link>https://datawider.com/machine-learning-everything-you-need-to-know-about-machine-learning/</link>
<comments>https://datawider.com/machine-learning-everything-you-need-to-know-about-machine-learning/#respond</comments>
<dc:creator><![CDATA[Vatsal Ghiya]]></dc:creator>
<pubDate>Fri, 03 Sep 2021 13:47:24 +0000</pubDate>
<category><![CDATA[Artificial Intelligence (AI)]]></category>
<guid isPermaLink="false">http://datawider.com/?p=599</guid>
<description><![CDATA[Machine learning has probably the most mixed definitions and interpretations in the world. What arrived as a buzzword a few years ago continues to baffle a lot of people thanks to the way it’s been portrayed and presented. If you look at pop culture, machine learning – coupled with Artificial Intelligence (AI) – is always [...]
The post <a rel="nofollow" href="https://datawider.com/machine-learning-everything-you-need-to-know-about-machine-learning/">Machine Learning – Everything You Need To Know About Machine Learning</a> appeared first on <a rel="nofollow" href="https://datawider.com">DataWider</a>.
]]></description>
<content:encoded><![CDATA[Machine learning has probably the most mixed definitions and interpretations in the world. What arrived as a buzzword a few years ago continues to baffle a lot of people thanks to the way it’s been portrayed and presented. 
If you look at pop culture, machine learning – coupled with Artificial Intelligence (AI) – is always shown as an agent of doom. They are projected as entities created by mad scientists, trying to take over the world to show their dominance and superiority. Even some of the classic movies like 2001: A Space Odyssey showed AI as the reason for how the movie eventually unfolds. 
If you look up the internet, on the other hand, you will find tons of marketing pieces and sponsored posts that will sort of give you an idea of what machine learning is but again move on to promoting their products or services. 
We felt there was a void that needed to be filled and this post exactly stems from the same reason. This is an educational piece on what machine learning is so at the end, you have a basic understanding of what the concept is and how it works. This will ensure you have the right knowledge you need to decide if you need machine learning modules for your next business idea and have conversations with companies or investors you’re trying to reach out to. 
<h2>What Is Machine Learning?</h2>
Without getting into jargon and definitions, let’s understand that machine learning is all about making machines learn processes to let them autonomously perform tasks and actions. This is done through artificial intelligence, so machines develop systems in them that will let them mimic humans and take decisions and actions by themselves. 
For machine learning to be accurate, systems have to be fed massive volumes of data. Consider machine learning similar to an infant, who is learning what an orange is for the first time. You show them images after images on what an orange is (and what isn’t as well) until they learn to differentiate and precisely identify autonomously. Machine learning involves the same process but on a whole different volume, scale and stake. 
Today, machine learning is everywhere. If your search engine completed your search query it’s due to machine learning and predictive analytics. From your navigational systems in your phone to Netflix recommending what to watch next, there’s machine learning in everything you touch. 
<h2>Why Is It Required?</h2>
Now, concepts like machine learning and artificial intelligence aren’t new. They’ve been under discussion and development since the 1950s. However, they’ve been practically feasible only since the last decade – after the data boom. 
When we cracked the concept of Big Data and uncovered new ways to store and process large amounts of <a href="https://www.shaip.com/blog/the-only-guide-on-ai-training-data-you-will-need-in-2021/">AI training data</a> and machine learning automatically became practically more achievable. 
Thanks to this, we can now accomplish more than we actually could with machines by our side. Over decades, we’ve been doing tons of work manually and that was time-consuming. Today, we let the machines take care of complex processes that require intricate calculations, estimations and predictions, leaving the inference and optimization parts to humans. 
This has been the reason for some drastic changes and innovations in the last few years. In short, we need machine learning to further push our capabilities as humans and explore uncharted areas in diverse fields. 
One crucial example is the development of a vaccine for Covid-19. Thanks to AI and its applications in clinical trials, drug research and simulations, we were able to crack the code within months and make way for mass production and distribution. 
<h2>How Do We Get Machines To Learn?</h2>
Though machine learning sounds fancy and ambitious, it’s complex. Imagine getting a machine made up of a few circuits, a board, a chip and a couple of sensors to learn something and accomplish crucial tasks. But that’s where it gets interesting as well. 
Algorithms are the fulcrum of machine learning models. In simple terms, they are conditions or instructions that clearly define, solve or perform a specific computation. With this understanding, let’s further understand that machines can be made to learn using three distinct concepts: 
Supervised learning – where you train a system with tons of AI Training Data to help it recognize or learn something. For instance, showing a module thousands of images of dogs to make it understand what a dog is. 
 – Unsupervised learning – where models develop algorithms of their own to process data and learn autonomously through clustering or regression techniques. For instance, you could throw in datasets of both dogs and cats and machines would differentiate the two. 
 – Reinforcement learning – where rewards and penalties are assigned for arriving at right and wrong solutions respectively. This optimizes machines for better performance with every computation. 
Apart from these, there are advanced concepts like neural networks – part of deep learning – where models mimic the working of a brain to mimic humans. Let’s not go there now. 
<h2>Challenges and Limitations of Machine Learning</h2>
The efficiency of <a href="http://datawider.com/get-to-know-machine-learning-technology/">machine learning models</a> completely depends on how they are trained and for this, they need tons of AI training data. This by itself is a big challenge considering there wouldn’t be much relevant and contextual datasets available across all market segments, industries, and demographics to train a specific AI model to serve a distinct purpose. 
Even if the challenge of the volume of right datasets is tackled, the next struggle is eliminating any inherent bias that could have automatically crept in either among datasets or algorithms. Bias skews results and could cause machine learning models to fail big time. 
The initial success of models after feeding a minimal volume of datasets is never a celebratory moment as real tests for machines arrive only when large volumes of AI Training data are fed. For companies that are awaiting funding or <a href="http://datawider.com/what-is-artificial-intelligence-ai-in-business/">entering new market segments</a>, this will always be a struggle they need to find effective solutions for. 
<h2>Wrapping Up</h2>
Despite these challenges, businesses around the world come up with interesting and creative ways to generate datasets and optimize their machine learning models for precision and accuracy. 
Otherwise, we wouldn’t have some of the most revolutionary products and services available in the market today. 
And as science reveals, we are only scratching the surface of what we call Narrow AI. If we could do so much at this point, let’s only imagine the possibilities when we crack the code for Artificial Super Intelligence.
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