The Latin American Business Aviation Conference and Exhibition (LABACE) 2024 begins today, August 6, and runs through August 8. The event will take place at Congonhas Airport in São Paulo, Brazil, and is set to be a landmark occasion for the aviation industry. The 19th edition of LABACE, the largest business aviation event in Latin
AI and the Food and Beverage Industry: Trends and Innovations Artificial intelligence (AI) is transforming the food and beverage industry in profound and innovative ways. From production optimization to new product development, AI is becoming essential for companies that want to remain competitive and sustainable. Let’s explore the key areas where AI is making a
Artificial Intelligence (AI) has established itself as a crucial tool for various industries, and the food industry is no exception. The use of AI in this industry has the potential to revolutionize areas such as production, sales, marketing, and logistics. This article explores the benefits of AI in each of these areas, highlighting specific algorithms
We have been witnessing significant changes in some supermarket shelf products. Aiming not to raise prices for the customer, the industry is reducing the size of products while keeping the price close to the previous one or with some minor reduction. This practice is called “SHRINKFLATION.” Some cases have started to become the butt of
Neural networks, an artificial intelligence method inspired by the human brain’s architecture, teach computers how to process data and acquire knowledge through experience. This technique finds application in various tasks, including image recognition, voice and facial recognition, natural language processing, recommendation systems, data analysis, phenomena predictions, and more. Training a neural network can be complex
Use cases of artificial intelligence are exceptionally increasing, and machine learning models are everywhere, in the banking sector, education, health, and our homes. One of the major challenges we face in these projects is enhancing the model, and a key issue is its performance, as deployment makes little sense if the model is not accurate
Artificial Intelligence is changing the way companies work with data and automation, and one of the most effective ways to implement AI projects is through cloud computing. This enables companies to take advantage of AI advancements without the need to heavily invest in their own infrastructure. According to research by Gartner, global cloud services revenue
They say the world spins fast, faster and faster, right? Likewise, the business strategies that were thought for 10, 20 years ahead are no longer viable today, or at least are very risky. Of course, there are long-term strategies, but the trend in recent years, reinforced by the startup model, the Lean, agile vision, is
Machine Learning is one of the most promising areas of artificial intelligence and has revolutionized the way we handle data and make decisions. However, as with any field of research, there are challenges to be faced, and in this post, we will explore some of them. Insufficient Training Data This is a common problem in
For years, studies on strategies have aimed at a sustainable competitive advantage as the ideal strategy for growth and business perpetuation. Innovation has become essential. Recently, with the advent of AI transforming into a differentiated “workforce”, organizations have begun to reap significant results with its application. Engineering is not just about numbers and calculations, but
