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Software Tools Every Engineer Should Know How To Use



Software Tools Every Engineer Should Know How To Use

Software tools are a necessary part of an engineer’s toolkit.

While there are many different types of software tools, some of the most common ones include CAD (computer-aided design) software, simulation software, and analysis software.

Each type of software has its own unique set of capabilities and can be used for different purposes. For example, CAD software is often used for creating and modifying designs, while simulation software can be used for testing and verifying designs. Analysis software, on the other hand, is typically used for evaluating data and performing calculations. 


No matter what type of engineering you’re involved in, there are certain software tools that you should know how to use. In this article, we’ll take a closer look at some of the most commonly used software tools and discuss how they can be used to help you achieve your engineering goals.

Data Analysis Software

Data analysis software helps users visualize and analyze their data. It has many features, including the ability to create custom graphs and charts, as well as export data to other software programs. The most popular data analysis software programs are Pasco and Microsoft Excel. They both have a variety of features that can be used for data analysis, and many users are familiar with them. Though both programs can be difficult to learn at first, they are worth the time investment. The main difference between the two programs is that Pasco is geared more towards scientific data analysis while Microsoft Excel is better suited for business data analysis.

CAD Software

CAD software is one of the most common types of software used by engineers. It allows you to create and modify designs using a computer. There are many different CAD programs available, but some of the most popular ones include Autodesk Inventor, Sledworks, and CATIA. The type of CAD software you use will depend on the type of engineering you do. For example, if you are an electrical engineer, you may want to use a program that specializes in creating electrical designs. If you are just starting out with CAD software, it is important to choose a program that is easy to learn and use. Inventor is a good choice for beginners because it has a simple user interface and teaches you the basics of CAD design.

Finite Element Analysis Software

Finite element analysis (FEA) is a type of software that is used to analyze the strength and stability of structures or objects. It can be used to predict how a structure will behave under different loads and conditions. FEA software is used in a variety of industries, including aerospace, automotive, and manufacturing.


There are many different FEA software programs available, and each one has its own set of features and capabilities. It is important to select the right software for the task at hand. Some factors to consider when choosing FEA software include the type of analysis that needs to be performed, the size and complexity of the model, and the computing resources available.


Vaadin is a Java web application framework that helps developers create high-quality user interfaces for their web applications. It is a complete platform that includes a wide variety of tools and features, making it one of the most popular choices for web development. Some of the features that make Vaadin so popular include its ability to create responsive user interfaces, its intuitive drag-and-drop interface builder, and its wide range of components. In addition, Vaadin also offers a variety of other features such as internationalization, security, and performance optimization.


An Integrated Development Environment (IDE) is a software application that provides comprehensive facilities for software development. An IDE typically consists of a code editor, build automation tools, and a debugger. The code editor is the primary tool used to write source code. It provides features such as syntax highlighting, automatic indentation, and code completion. The build automation tools automate the process of compiling and deploying software. The debugger allows developers to step through code, set breakpoints, and inspect the values of variables. There are many different IDEs available, each with its own set of features. Some popular IDEs include Eclipse, Visual Studio, and IntelliJ IDEA. Eclipse is a popular open-source IDE that is widely used in the Java community. It provides comprehensive support for Java development, including syntax highlighting, code completion, debugging, and refactoring.

Software tools are an important part of an engineer’s toolkit. These tools can help you with everything from engineering design to simulation and analysis. Of course, there are many other software tools that engineers might need to use, depending on their specific field of work. But the tools we have discussed here are a good starting point for anyone looking to get started in engineering. With these tools, you will be able to tackle most engineering challenges you encounter.

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Einstein, Empathy and AI



Einstein, Empathy and AI

Albert Einstein once said: “The ideals that have lighted my way, and time after time have given me new courage to face life cheerfully, have been Kindness, Beauty and Truth.”

Kindness, beauty and truth. You don’t often hear these words in the digital world. How do we integrate these life essentials in technologies like artificial intelligence (AI), machine learning, edge computing, internet of things (IoT) and data at scale? Technology, after all, makes things less personal, right?

One company is working hard to disprove this assumption. Not only that, they have a direct tie to Einstein himself.

A hundred years after Einstein shared his views about human existence, NVIDIA is on a path to connecting kindness, beauty and truth with AI as it explores the human qualities of inference, context and nuance in supportive technologies. As for the famous scientist with the wild white hair, NVIDIA has proven he was right about his prediction of gravitational waves, which can now be seen by astronomers for the first time at the Laser Interferometer Gravitational-wave Observatory (LIGO).

This makes sense. After all, NVIDIA has powered 352 out of 500 of the world’s supercomputers.

NVIDIA has long been known for gaming technologies – it invented the graphics processing unit (GPU) in 1999, triggering the steep growth of the gaming market (much to the chagrin of many parents everywhere) with superior computer graphics and intuitive AI.

Chances are you’ve touched NVIDIA’s tech some time along your day today. Since its launch in 1993, it has been the “AI engine” for thousands of companies, including Google, Microsoft, Amazon, Meta, Alibaba, Tencent, Pinterest, PayPal, Snap and Spotify. The full-stack computer company fuels data center-scale computing solutions with the help of some 20,000 employees in more than 50 countries.


GPU-powered AI solutions impact critical insights needed for businesses to make better decisions, improve customer service and reduce fraud. The technology is particularly impactful in financial services where around 80% of firms are using artificial intelligence to improve services. NVIDIA’s State of AI in Financial Services 2022 Trends Report reveals that 8 of 10 financial firms are using AI to reduce the estimated $5 trillion in global fraud each year and that conversational AI is being used to mimic customer service representatives in self-service chatbots and call center virtual agents by many banks. AI-led recommendation systems are delivering hyper-personalized experiences to bank customers by giving personalized recommendations.

Conversational AI, however, is where GPU technology can make a significant difference. To date, it has often been seen as deeply flawed by many people, myself included.

Tell me if this sounds familiar. You call a company hoping to resolve an issue. Its AI-driven customer service agent answers in a monotone voice. Soon thereafter, the exchange goes off the rails. You’re asking if they have a product in stock and the agent is asking if you want to make a return. Finally, you request a live agent. I’ve gotten lost in the digital loop of big companies when connecting with a real human being is akin to hitting the jackpot.

What’s missing? From moment one, it’s empathy.

Just to be on the same page, Merriam Webster defines empathy as “the action of understanding, being aware of, being sensitive to, and vicariously experiencing the feelings, thoughts, and experience of another.”

Feeling understood by another is the point of NVIDIA’s article “May AI Help You? Square Takes Edge Off Conversational AI With GPUs”, which explores AI’s unique potential for going beyond the facts, entering the realm of “sympathetic listening.”

As more companies adopt conversational AI, empathy plays a larger role in the customer experience – and, ultimately, growth factors like profitability, customer retention and brand equity. According to Zendesk, 81% of consumers say a positive customer service increases the chances of them making another purchase. AI is more than taking care of business. Customers want to feel good about the exchange and not like a “number.” They want a kinder, more memorable touch point that resolves their real problem and makes them feel “seen.”

Can digital assistants and digital agents get us there?


With the help of NVIDIA, the popular payment platform Square is making progress. You could say NVIDIA invented one of AI’s greatest solutions – the GPU. The company’s article points out that Square’s tech team “started training AI models at Eloquent on single NVIDIA GPUs running CUDA (a programming interface) in desktop PCs.” Eloquent is an NLP startup acquired by Square in 2019. In addition to the GPU enabled desktop stations, large model training jobs were run on NVIDIA GPUs in the AWS cloud service.  The results were impressive on both training and inference fronts. In particular, Square found “inference jobs on average-size models run twice as fast on GPUs than CPUs. Inference on large models such as RoBERTa run 10x faster on the AWS GPU service than on CPUs.”

Progress? Listen to this: Merritt writes that “Square Assistant can understand and provide help for 75 percent of customer’s questions, and it’s reducing appointment no-shows by 10 percent.”

Trust takes so much time to build. One poor experience breaks it immediately. In an ideal world, our conversations with others are fluid as long as the level of service meets our satisfaction. When an experience falls short, the ramifications interrupt our perception of a brand or worse.

Like New Year’s Eve 2021 when I made a large payment to my house remodeler via check. I sent the check a week ahead to ensure it can be processed before the end of the year. My bank texted me to confirm my identity. I verified that the payment was legit. More than an hour later and seven – SEVEN – transfers from one digital assistant to another and then to a live agent later, the issue was finally resolved. By that time, however, it was already the new year.  As a small business owner, that one day delay had implications on taxes and a supplier’s revenue. 

Many consider Einstein as a great scientist, but I think of him as a great thinker. He understood the power of the human touch. In one essay, he wrote: “When we survey our lives and endeavors we soon observe that almost the whole of our actions and desires are bound up with the existence of other human beings.”

When AI understands the nuances of language, we will have taken the next big leap. Intuitive, empathetic AI is upon us. The question is: will it inspire greater kindness, beauty and truth for those who use it?

Explore NVIDIA’s AI solutions and enterprise-level AI platforms driving the future of financial services. 

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