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Real-World Lessons for Machine Learning in Business


Machine learning seems to be getting all the interest and hype these days, and some are even saying that it's going mainstream. There are even dedicated conferences and summits for ML just like the 2021 AWS Machine Learning Summit. For ML to go mainstream, in my perspective, there are still real-world lessons we'll need to translate ML into production for businesses, and I was hoping to get some takeaways from this summit. I listed here some parts that made the most impact on me. Hopefully, you'll find these useful when you are planning to apply ML: Since the talk has been organized by AWS, the summit is leaning towards the use of their ML services, but the takeaways here can also be applied to other cloud computing platforms like GCP that offer their own ML services.

6 Books Machine Learning Engineers Should Read


ML and AI can be very intimidating for the beginners. As a prerequisite, you should be able to write a little bit of code either in python or R, have some mathematical background and should be able to understand some basic ML jargon. But what's most important is to be guided by the right Machine Learning book. I absolutely love this book. This is the book you need to grok and master machine learning concepts.

Understanding edge-based artificial intelligence and its role in improving user experience


The diverse and successful implementations of Artificial Intelligence (AI) across domains have enabled the delivery of augmented and personalised experiences to users at work as well as in their everyday lives. However, in recent times, edge-based AI is upping the ante and offering an enhanced experience by bringing the data and the compute closer to the point of interaction. Most of us are already consuming it in our daily lives. The autocorrect suggestions on our smartphone keyboards or several capabilities of the voice assistant that we use countless times throughout the day are examples of consumer-facing edge-based AI solutions. Edge-based AI uses machine learning algorithms to process data generated by a hardware device (Internet of Things endpoints, gateways, and other devices at the point of use) at the local level instead of sending data to remote servers or the cloud.

How Intelligent Search Solutions Optimize Business Analytics


However, as the competition gets tougher and customer's purchasing behavior changes, data may become too extensive for businesses to handle. It can be challenging to identify the issues that need immediate fixing. This area is where intelligent search solutions can come in handy. What Are Intelligent Search Solutions? Intelligent search solutions are software programs that use algorithms to monitor and analyze data. They can provide users with the most relevant information for their needs, as they can analyze large data sets of information.

Innovative Ways That Different Industries Are Using AI - IntelligentHQ


Artificial intelligence (AI) is a relatively new technology that is already showing its value, and will only grow more and more useful over time. It has the potential to save time, reduce costs and even free up employees to focus on more detailed tasks. Not only does it work quickly and rarely need human intervention, but it can also drastically reduce potentially costly errors. AI is now being used in some of the biggest industries on the planet. Here are some of the innovative ways it is changing those industries.

AI and ML for Open RAN and 5G


Fast, reliable, and low-latency data services are essential deliverables from telecom operators today. Realizing them is pushing operators to enhance infrastructure, expand network capacity and mitigate service degradation. Unlike other industries, though, telecom networks are vast monoliths comprising fiber optic cables, proprietary components, and legacy hardware. Because of this, there is less enhancing--and more shoring up the creaking infrastructure. Radio access networks (RAN) are the backbone of the telecommunications industry. However, the industry's propensity to incubate and evolve newer, cost-effective, and energy-efficient technologies has been slow due to monopolization by RAN component manufacturers.

Artificial Intelligence in Construction Engineering and Management – CoderProg


This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI.

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning - PubMed


The world is facing the COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Likewise, other viruses of the Coronaviridae family were responsible for causing epidemics earlier. To tackle these viruses, there is a lack of approved antiviral drugs. Therefore, we have developed robust computational methods to predict the repurposed drugs using machine learning techniques namely Support Vector Machine, Random Forest, k-Nearest Neighbour, Artificial Neural Network, and Deep Learning. We used the experimentally validated drugs/chemicals with anticorona activity (IC50/EC50) from'DrugRepV' repository.

This Italian entrepreneur uses artificial intelligence to keep workers safe


We are always happy to talk about Italian innovation and research, particularly at a time like this, when creative entrepreneurship can be instrumental in pulling our Country and society at large out of the crisis. Today we are happy to tell you about a young female entrepreneur who is using artificial intelligence to ensure safer working conditions for factory workers, using an algorithm to predict anomalies in the equipment, thus reducing the risk of accidents. Many look with mistrust at artificial intelligence and algorithms, because they feel this kind of technology is too present in our everyday lives or because they are afraid automatisation will take away human jobs. Giulia Baccarin, however, always looked at this matter from a different perspective. Ever since she was a student, she was fascinated by artificial intelligence and, while still at university, she designed a predictive algorithm to be implemented in a high-tech t-shirt, equipped with airbags, to protect elderly people from incidents and falls.

A New Way To Understand Automation

NPR Technology

For one of the most distinguished critics of automation, MIT economist Daron Acemoglu has been, ironically, cranking out research on the subject lately like he's a machine. He and his co-author Pascual Restrepo have produced so many studies on the subject that he couldn't tell us how many they've done. "I've lost count," he says. Their conveyer belt of research has been spitting out some startling facts. They find, for instance, that each new industrial robot killed, on average, 3.3 jobs in America between 1993 and 2007.