A primer on digital twin technology


In the 21st century, the concept of a twin need not be confined to fraternal or identical--a twin can be digital too. Digital twins have caught the eyes of some of the biggest companies in the world--Amazon and Nvidia, for instance, both made announcements about new digital-twin initiatives within the last month--as well as those of specialists like infrastructure engineering software company Bentley Systems. The concept started gaining traction at the beginning of the century, and picked up steam in the early 2010s when the rise of IoT made digital twins more feasible. As of 2020, it was estimated to be a $3.1 billion market, per Markets and Markets, and projected to grow into a $48.2 billion industry by 2026. So...what is a digital twin?

Advance Trustworthy AI and ML, and Identify Best Practices for Scaling AI - AI Trends


Advancing trustworthy AI and machine learning to mitigate agency risk is a priority for the US Department of Energy (DOE), and identifying best practices for implementing AI at scale is a priority for the US General Services Administration (GSA). That's what attendees learned in two sessions at the AI World Government live and virtual event held in Alexandria, Va. last week. Pamela Isom, Director of the AI and Technology Office at the DOE, who spoke on Advancing Trustworthy AI and ML Techniques for Mitigating Agency Risks, has been involved in proliferating the use of AI across the agency for several years. With an emphasis on applied AI and data science, she oversees risk mitigation policies and standards and has been involved with applying AI to save lives, fight fraud, and strengthen the cybersecurity infrastructure. She emphasized the need for the AI project effort to be part of a strategic portfolio.

10 Python Code Snippets For Everyday Programming Problems - GeeksforGeeks


In recent years, the Python programming language has seen a huge user base. One of the reasons could be that it is easier to learn as compared to other object-oriented programming languages like Java, C, C#, JavaScript, and therefore more and more beginners who are entering the field of computer science are opting for Python. Another reason why the popularity of Python has shot up is that it is used in almost all domains of the IT industry, be it data science, machine learning, automation, web scraping, artificial intelligence, cyber-security, cloud computing, and what not! According to the recent developer survey, it is seen that Python is currently the second most loved programming language after JavaScript and will easily shoot up in the coming years. Demand for Python developers has significantly risen, especially in the past few months, and therefore learning Python could get you some really good career options.

How Artificial Intelligence Impacts Business Data Accuracy


Data accuracy is the most crucial part of the decision making in any business. An error that occurred in the process may cause you enough damages to crash you down. This is the core reason for the birth of data entry services or data processing services where businesses ask help to digitize and manage their data. Accurate data is a major component in the success of any firm, and no one is going to reject this fact. Artificial intelligence and automation are used currently to ensure that man-made mistakes are negligible and hence the accuracy is high in the database.

What We Still Need to Learn about AI in Marketing -- and Beyond


CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. A growing number of companies are turning to artificial intelligence to solve some of their most vexing problems. The promise of AI is that it can go through vast amounts of data and help people make better decisions. And one area where companies often search for profitable use cases for the technology is in marketing. It's harder than it looks. Data scientists at one consumer goods company recently used AI to improve the accuracy of the sales forecasting system. While they did get the system working better overall, it actually got worse at forecasting high margin products. And so the new, improved system actually lost money. Today's guest says that many leaders lean too heavily on AI and marketing without first thinking through how to interact with it.

Basic Probability Concepts for Data Science


Probability is one of the most common terminologies, not only in mathematics but also in the real world. We use the word probability frequently. About seven years ago, I was in my secondary level of education and got introduced to the term probability as a topic of mathematics. At that time, I had solved so many mathematical problems regarding probability. Unfortunately, it did not seem interesting to me.

Save $200 on a Shark robot vacuum at Walmart


SAVE $200: As of Dec. 6, the Shark EZ Robot Vacuum 913S is just $299 at Walmart -- that's $200 off its usual price. If you're looking for a robot vacuum that won't break the bank, this one leaves your floors sparkling and your wallet happy. Your guests will arrive sooner than you think for holiday celebrations -- and you surely don't want dirty floors to be the first thing they notice. Investing in a robot vacuum is an easy path to sparkling floors. Black Friday and Cyber Monday may have passed, but this deal still saves you an impressive $200 on the usual price tag. Ideal for newcomers to the smart home world, the Shark EZ Robot 913s is beginner-friendly with easily accessible smart features.

10 Google search tricks to help you find what you're looking for

USATODAY - Tech Top Stories

How often do you turn to Google? If you're focused on privacy, there are better options. Tap or click for alternatives to Google that work well without gathering so much of your data. Tap or click for reasons you should ditch Dr. Google. When it comes to finding what you want, some tricks make the job easy.

Can a Tiny AI Group Stand Up to Google?


It has amplified outrage on social media and struggled to flag hate speech. It has designated engineers as male and nurses as female when translating language. It has failed to recognize people with darker skin tones when matching faces. Systems powered by machine learning are amassing greater influence on human life, and while they work well most of the time, developers are constantly fixing mistakes like a game of whack-a-mole. That mean's AI's future impact is unpredictable. At best, it will likely continue to harm at least some people because it is often not trained properly; at worst, it will cause harm on a societal scale because its intended use isn't vetted -- think surveillance systems that use facial recognition and pattern matching.

Preparing the ImageNet dataset with TensorFlow


With its help, you can conveniently access a variety of datasets from many categories. However, ImageNet is an exception; it requires a manual setup. While there seem to be some instructions on achieving that, they are somewhat vague. As a result, it took me some time to prepare the dataset, but I ended up with a concise script. Before we do any preparation, we need to obtain the dataset.