January, 2021 - Vinova

ReactJS Vs. VueJS | Front-end JS Frameworks Comparison

by vinova | 2 Jan 2021 | mobileapp

April 01, 2020 If someone asks, which framework will you select for development in 2020, what will be your answer?Clearly you have two main choices to select from: React.Js and Vue.Js! But, what if you need to select one? Well, the battle between the two most popular frameworks React Js and Vue.Js is real. It is indeed very difficult to manifest which overrules the other. However, we have tried to distinguish between the two frameworks here. Please Read this blog…. It is needless to say, Javascript has won millions of hearts and big Giants are grabbing their share using this technology. But, adding more to the popularity of it are the two most talked Javascript frameworks, React.Js and Vue.Js. Developers are embracing this declarative, and component-based process of designing the applications using the magical frameworks. Both of the frameworks are popularly known for the easy learning curve and higher performances. However, in order to stay abreast of the competitors, you need to select any one framework out of these two. Therefore, after getting thorough analysis from our experts, we have discussed the key differences between the two frameworks Vue.Js vs React.Js in this blog. Have a look and select the best fit for your application development. A major part of the software development companies is using these influential frameworks namely React.Js and Vue.Js. Let’s have a better understanding of the frameworks here. React.Js: React is an open-source Javascript library that is developed by Facebook. React development enables developers to create reusable and attractive UI components. It is best used to , and native applications because it allows developers to...

Tiny Machine Learning: The Next AI Revolution | by Matthew Stewart, PhD Researcher | Oct, 2020 | Towards Data Science

by vinova | 1 Jan 2021 | Cyber Security

Over the past decade, we have witnessed the size of machine learning algorithms grow exponentially due to improvements in processor speeds and the advent of big data. Initially, models were small enough to run on local machines using one or more cores within the central processing unit (CPU). Shortly after, computation using graphics processing units (GPUs) became necessary to handle larger datasets and became more readily available due to introduction of cloud-based services such as SaaS platforms (e.g., Google Colaboratory) and IaaS (e.g., Amazon EC2 Instances). At this time, algorithms could still be run on single machines. More recently, we have seen the development of specialized application-specific integrated circuits (ASICs) tensor processing units (TPUs) which can pack the power of ~8 GPUs. These devices have been augmented with the ability to distribute learning across multiple systems in an attempt to grow larger and larger models. This came to a head recently with the release of the GPT-3 algorithm (released in May 2020), boasting a network architecture containing a staggering 175 billion neurons — more than double the number present in the human brain (~85 billion). This is more than 10x the number of neurons than the next-largest neural network ever created, Turing-NLG (released in February 2020, containing ~17.5 billion parameters). Some estimates claim that the model cost around $10 million dollars to train and used approximately 3 GWh of electricity (approximately the output of three nuclear power plants for an hour). While the achievements of GPT-3 and Turing-NLG are laudable, naturally, this has led to some in the industry to criticize the increasingly large carbon footprint of the AI...

ReactJS Vs. VueJS | Front-end JS Frameworks Comparison

Tiny Machine Learning: The Next AI Revolution | by Matthew Stewart, PhD Researcher | Oct, 2020 | Towards Data Science

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