AI Transformation

Construction About to Move 100 Years Forward

The construction industry is "on the brink of a major transformation thanks to recent advances in artificial intelligence (AI) and machine learning." After years of relative stagnation, integrating AI into key processes is poised to boost productivity, reduce waste, and take construction to new levels of speed and precision. ECONews

How to Embrace AI in a Tech-averse Construction Industry

Across industries, AI has already shown its ability to provide users with competitive advantages. AI can be used in various capacities to improve efficiency, reduce costs, and advance innovation. Many early AI use cases have emerged in the construction sector (historically a slow tech adopter), including improving safety and risk management on job sites, processing documents and resource allocation planning and powering autonomous equipment.

Boost for Project Product Selection

AI-driven Approach to Product Selection

A significant hurdle construction firms face is the laborious process of identifying suitable products and materials for each project’s unique requirements. Manually comparing design specifications across thousands of manufacturer websites is a cumbersome process that consumes valuable time and has a high likelihood of error. However, AI and associated technologies can considerably reduce the time spent on product selection and quoting. MSN  

Construction Market Activity

AFCOM: AI Boom Fueling Data Center Construction, Design Innovation

Rapid growth in the artificial intelligence and wider digital services industries is fueling demand for new data center developments while stimulating innovation in data center design and technical innovation, according to AFCOM's latest State of the Data Center Report. DataCenter Knowledge 01/31/24

Eight Themes That Will Shape the Data Center Industry in 2024

The AI boom will ripple through the digital infrastructure sector, impacting the availability of space, the supply chain, pricing, cooling, power and design. Data Center Frontier

Better Concrete

Study: Forecasting Strength of Preplaced Aggregate Concrete Using Machine Learning

This study emphasizes enhancing comprehension of PAC compressive strength using machine learning models. Thirteen models are evaluated with 261 data points and eleven input variables. 

AI Challenge: Huge Energy Demands

Artificial Intelligence’s ‘Insatiable’ Energy Needs Not Sustainable, Arm CEO Says

AI models such as OpenAI's ChatGPT "are just insatiable in terms of their thirst' for electricity," ARM CEO Haas says. “The more information they gather, the smarter they are, but the more information they gather to get smarter, the more power it takes.” Without greater efficiency, "by the end of the decade, AI data centers could consume as much as 20 to 25 percent of U.S. power requirements." Today, it's approximately 4 percent. "That's hardly very sustainable." Wall Street Journal 

Big Tech’s Latest Obsession Is Finding Enough Energy

How much electricity will be required to power the exponential increase in data centers worldwide is unclear. But most everyone agrees that the data centers needed to advance AI will require so much power that they could strain the power grid and stymie the transition to cleaner energy sources. Wall Street Journal

Generative AI Beyond the Hype

Generative AI Isn’t Ubiquitous in the Business World—at Least Not Yet

ChatGPT and other forms of generative artificial intelligence have experienced meteoric growth, but many businesses are hesitant to rush headlong into the technology. 
Wall Street Journal 

Artificial Intelligence ‘Explainability’ Is Overrated

While the desire for AI explainability is understandable, its importance is often overstated. The term itself is ill-defined—what criteria exactly makes a system explainable remains unclear. More importantly, a lack of explainability does not necessarily make an AI system unreliable or unsafe. Forbes