Automotive Security Best Practices

| November 22, 2017

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This paper is intended as an informative backgrounder and starting point for continued discussion and collaboration. The primary goal is to present the current state of automotive security, the main concerns, some use cases, and potential solutions. This is by no means an exhaustive review. This is the second version, incorporating comments from a variety of automotive and security researchers. Further comments are welcome, and the intent is an ongoing working paper as part of the Automotive Security Review Board (ASRB).

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Programming languages: Python and Java VS Code extensions get these new updates

Article | March 20, 2020

Microsoft has launched the March replace for its fashionable Python extension for Visible Studio Code (VS Code), its extensively used cross-platform code editor. It is also launched an replace for Java on VS Code with assist for the IDE extension, SolarLint. Probably the most notable change within the Python for VS Code replace is a brand new Microsoft-built Python debugger called debugpy, an implementation of the Debug Adapter Protocol for Python. The software permits builders to debug script recordsdata and modules from the command line, in addition to allow debugger logging. Till now, VS Code had built-in debugging assist for JavaScript, TypeScript, Node.js, and so forth, whereas extensions from the VS Code market enabled assist for different languages like Python, Go, C# and C++.

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AI and Marketing Automation: The Future of Content Creation

Article | July 23, 2021

The content market industry is growing rapidly. The US spent almost $10 billion on content in 2016. And with the merge of technology and content, this figure has multiplied several times. As a result, humans can concentrate on creativity while machines assist them in beautifying their work. The machines that we are going to talk about are AI-driven content marketing platforms for content creation, curation, and distribution. We will also let you know whether the world of writers is going to be extinguished or not! Content creation needs to be unique. There are numerous articles, blogs, listicles, etc., written on the same topic. So what do you need to do to make your content stand out? You might be thinking of SEO, personalization, target audience, and error-free content. But when all this is carried out manually, it turns out to be a daunting task. What if we tell you that the AI industry has revolutionized the content sector. Machines assist in content creation, curation, personalization, prediction, SEO analysis, keyword search, and everything you can think of. What is AI Content Creation? More than 2.5 quintillion bytes of data are created every day! Imagine the uniqueness your content needs to define to stay ahead in the race. The competition is unbelievable! This is where AI and automation meet content marketing. AI content creation helps to create, polish, personalize, distribute, and market user-centric content. AI uses predictive analysis, natural language process (NLP), natural language generation (NLG), and business intelligence to understand a buyer’s journey. AI helps in creating an efficient content strategy for the writers. It also assists them in using the right keywords and publishing on the right platforms. Moreover, content that is checked by the AI content creation algorithm has the least or no possibilities of errors. Below are the benefits of AI content creation and how it plays a significant role in shaping the future of content writing. Benefits of AI content creation Predictive Intelligence Predictive Intelligence is predicting the customer’s behavior and serving them precisely what they are looking for. It also helps the buyer to navigate to the things exclusive based on their browsing patterns. For example, if a customer is looking for casual shoes and has put the chosen ones in the cart, the AI-powered algorithm will suggest some socks to go with the shoes. The algorithm is designed so that based on the shoe size, color, and brand, it suggests the best pair of socks! And when this role is played in content creation, predictive intelligence suggests words, sentences, synonyms to create excellent content. When you have a process that foretells you the buyer’s journey, it becomes easy to create personalized content and yield the best results. Data-Driven Insights A study has proved that 90% of the customers get converted based on personalized AI content. AI-driven content marketing tools help gather all the customer's activity online and then give them the relevant suggestions. AI content creation tools compare your content with the competitor’s content and your previous works and performances. Based on that, it predicts the content to be framed. Finally, it recommends words and phrases to frame innovative, data-driven content. AI content creation helps in increasing your brand value and reach your target audience effortlessly. Chatbots for Customer Service Chatbots as customer service representatives are immensely successful. Chatbots are like a virtual friend that meets the customer. They not only provide information but also interact with the customers for fun. Chatbots are trained to have a conversation just like humans. They ask about feelings and then have a one-to-one conversation about ways to feel better. For example, when a chatbot is used to book a test drive for a car, it notes the personal details and saves the date for the concerned person and the customer on the calendar. That is pretty much robotic. But in the end, it tells you to have a pleasant drive and not to forget to wear your seatbelt! This is where it connects with the customer. Thus, chatbots can help promote content, navigate customers to the correct pages, and are more likely to fulfill the conversion goal. Examples of AI Content Creation Applications Twinword Twinword is one of the examples of AI-powered keyword research tools. It speeds up the keyword research process and provides the most curated list of LSI, long-tail, short-tail keywords. It understands the customer’s intent and provides you with the target keywords. Articoloo It is one of the Automated AI Content tools used to write articles, blogs, and other relevant content. It has been said to deliver content with the most competitive keywords and a proper understanding of the industry dynamics. In addition, it creates high-quality content which is almost 90% unique. Grammarly The AI-powered tool does more than grammar checks. It checks your article's tone and gives you options to improve or change words, sentences, length, etc., according to the audience. It frames sentences, gives synonyms, and also creates your writing graph. It shows how your writing has evolved with time and keeps on assisting to improve your writing. This is one AI tool that has been widely used by writers and is a proven success. MarketMuse This tool analyses your content and makes it ready for the competitive market. It minutely analyses your content for SEO and content research and gives appropriate suggestions for keywords and content optimization. It also has a keen eye on keyword intensity. Thus, it is the best tool to automate content marketing and keep you ahead of the race! Onespot This tool provides excellent AI Content and User Experiences across multiple platforms. It tracks the buyer’s journey, analyses the user’s behavior on your website, and then automates a personalized experience for the customer. In addition, it generates e-mails and newsletters for the customers for an enriched experience. All the content generation is very personalized and connects readily with the target audience! These are some of the content creation services for optimization, creation, and keyword research. But there is a plethora of AI in content marketing and automated tools for content creation to choose from! Will AI replace human writers? No. AI content creation is still in the infancy phase. It can create newsletters, small articles, or emails but not valuable content like humans. However, there are AI content creation tools that are said to write almost 800 articles in a year. So if you are looking only at content generation, then yes, AI performs a better job than humans. But can machines feel and express the emotions that humans do? No matter how many trillions of words they have fed themselves, expressing emotions with the right words is still a human thing. Likewise, there are stats to prove that humans tend to take action when they feel emotionally connected. And we all know machines are practical beings! So as long as humans are social and emotional, there is no way that AI and automation can replace writers now or in the long run. It can assist humans in writing better quality, personalized and well-researched content, but never replace them. If you still have second doubts, think, did the invention of smartphones with excellent cameras, photo studios, or design studio apps like Adobe photoshop replace photographers? So relax, use AI and automation to minimize your efforts, gather data, and give you a piece of structured and well-researched content. Then use your creativity skills and enhance them by giving the human touch because that is what only a human brain can do! Frequently Asked Questions What is AI in content creation? AI is automated Insights in content creation. It helps optimize the written content according to the target audience. It uses Natural Language Generation (NLG) to create content and narratives. In addition, it can automate repetitive tasks. Once AI creates the content, a human writer can enhance and personalize it accordingly. How does AI help in content creation? AI provides an in-depth analysis of the content, website, and target audience. Based on this research, creates and suggests changes in the content. This in-depth research of AI helps deliver valuable and personalized content to the target audience with the right set of keywords. How do you automate content creation? Content creation can be automated with the use of automation tools. These tools recommend the topic, keyword, and tone of the article to be written. In addition, they assist the writer with the correct grammar, synonyms, and keyword predictions. If it is a technical article, the automated tool can write the entire article with no errors. Examples of such tools are Articoolo, Grammarly, Onespot, etc. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What is AI in content creation?", "acceptedAnswer": { "@type": "Answer", "text": "AI is automated Insights in content creation. It helps optimize the written content according to the target audience. It uses Natural Language Generation (NLG) to create content and narratives. In addition, it can automate repetitive tasks. Once AI creates the content, a human writer can enhance and personalize it accordingly." } },{ "@type": "Question", "name": "How does AI help in content creation?", "acceptedAnswer": { "@type": "Answer", "text": "AI provides an in-depth analysis of the content, website, and target audience. Based on this research, creates and suggests changes in the content. This in-depth research of AI helps deliver valuable and personalized content to the target audience with the right set of keywords." } },{ "@type": "Question", "name": "How do you automate content creation?", "acceptedAnswer": { "@type": "Answer", "text": "Content creation can be automated with the use of automation tools. These tools recommend the topic, keyword, and tone of the article to be written. In addition, they assist the writer with the correct grammar, synonyms, and keyword predictions. If it is a technical article, the automated tool can write the entire article with no errors. Examples of such tools are Articoolo, Grammarly, Onespot, etc." } }] }

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THE FUTURE IS BOTH AUTOMATED AND INTELLIGENT

Article | June 2, 2021

Intelligent Automation (IA) is one of the trending buzzwords of our times. What makes automation smart? Is it new? Why the renewed focus? Bill Gates believed automation to be a double-edged sword when he said: “Automation applied to an efficient operation will magnify the efficiency. … Automation applied to an inefficient operation will magnify the inefficiency.” IA lies at the intersection of robotics, artificial intelligence (AI) and business process management (BPM). But before you think HAL from 2001: A Space Odyssey, J.A.R.V.I.S. from Iron Man or Terminator 2: Judgment Day scenarios, first, a little context. IA is not new; automated manual processes have been in existence since the dawn of the Industrial Revolution. It enabled speeding up go-to-market, reduced errors and improved efficiencies. Over time, automation made its way into software development, quality assurance processes, manufacturing, finance, health care and all aspects of daily life. “Intelligent” automation backed by robotics, AI and BPM creates smarter business processes and workflows that can incrementally think, learn and adapt as they go — for instance, processing millions of documents and applications in a day, finding errors and suggesting fixes or recommendations. What Intelligent Automation Does, Humans Can’t IA enables the automation of knowledge work by mimicking human workers’ capabilities. It includes four main capabilities: vision, execution, language, and thinking and learning. Each of these capabilities combines different technologies that are used as stand-alone or in combination to complement each other. One oft-quoted IA example is fraud detection and prevention in the BFSI sector. Robotic process automation (RPA) optimizes the speed and accuracy of the fraud identification process. Since RPA can go through months’ worth of data in a matter of hours and throws up exceptions, teams cannot keep up with the speed and scale needed to resolve the issues flagged. However, speed and efficiency are of the essence where fraud management is concerned. The answer lies in AI and BPM coupled with RPA. IA can streamline the process end-to-end. Pascal Bornet notes in his book, Intelligent Automation, that IA can help improve the overall automation rate to nearly 80%, and it can help improve the time to solve a fraud incident and obtain clients’ refunds by 50%. While RPA provides excellent benefits and quick solutions, cognitive technologies offer long-term value for businesses, employees and customers. IA And Digital Transformation IA adoption is growing swiftly across the enterprise, being fast adopted by more than 50% of the world’s largest companies. Its benefits are relevant to the majority of business processes. For example: • Industrial systems that sense and adapt based on rules. • Chatbots that learn from customer interactions to improve engagement. • Sales and marketing systems that predict buyer journeys and identify leads The Future Of Work: Bitter Or Better There is much speculation when it comes to IA and the future of work. The main contention is that robots will take away jobs from humans. My argument is that, while it will cause role changes, it doesn’t necessarily mean job losses. The Industrial Revolution helped automate “blue-collar” jobs in manufacturing and agriculture. Similarly, IA will automate many white-collar jobs that are tedious and tiring. A recent IBM report shows that 90% of executives in firms where IA is being used believe it creates higher-value work for employees. So, no, we will not be living in a dystopic world controlled by bots running amok! IA means better roles, the elimination of laborious tasks and improvements in employee well-being. The Promise Of The Better Life In 2018 alone, over $5 trillion (6% of global GDP) was lost due to fraud. Medical errors in the U.S. incur an estimated economic value of almost $1 trillion — and 86% of those mistakes are administrative. A 2017 Medliminal Healthcare Solutions study found that 80% of U.S. medical billings contain at least minor errors — creating unnecessary annual health care spending of $68 billion. The World Economic Forum cited an ILO report that “estimates that the annual cost to the global economy from accidents and work-related diseases alone is a staggering $3 trillion.” Now, let us imagine we can save $5 trillion globally through the deployment of IA. It means: • Global budgets allocated to education could more than double. • Global healthcare budgets could be increased by more than 70%. • Environmental investments could be multiplied almost twentyfold. Transitioning To Intelligent Automation However, adopting IA is not like flipping a switch. There are some key steps an organization must experience in its bid to be automating intelligently. • Planning. For the successful adoption of IA, business leaders must understand the relationship between people and machines. Enterprises must plan so as not to disrupt other parts of the business and integrate IA seamlessly into the existing programs. Instead of adopting IA across the processes, identify where it delivers the most value. Automating broken processes will not fix the problem. IA will only reap rewards on stable and mature processes • Change management. IA is not easy to implement. There will be a great deal of resistance to adopting IA in your organizations. Designing a change management strategy, an execution road map, an enterprise operating model and key metrics for ROI will help your cause. Invite key stakeholders from the outset to ensure buy-in and train your employees to work in collaboration with IA. • Governance framework. Establishing a governance framework helps determine who will watch the watchmen. The bigger the role of IA in your organization, the more critical governance becomes. Designing a framework will help you monitor performance as well as define exceptions and errors. It is a recipe for disaster if you don’t have a command and control center to ensure IA is making the right choices. Even more reason for humans with industry expertise to still “have their jobs” and excel at them. Future Of Intelligent Automation The future of IA will direct businesses to a more adaptive model that is beneficial for business leaders to uncover higher value and employees to do more satisfactory and creative roles. Preparing for an intelligent future means adapting our technology, skills and education to fit the future of the workforce. What are we waiting for? Disclaimer – This article was 1st published on Forbes.comEnable GingerCannot connect to Ginger Check your internet connection or reload the browserDisable in this text fieldRephraseRephrase current sentenceEdit in Ginger

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Researchers use Artificial Intelligence to predict drug response in lung cancer therapies

Article | March 22, 2020

Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease. The researchers at Columbia University's Irving Medical Center analysed CT images from 92 patients receiving drug agent nivolumab in two trials; 50 patients receiving docetaxel in one trial, and 46 patients receiving gefitinib in one trial. To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment.

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