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
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
Have you ever wondered how machines manage to make complex decisions and predictions? The field of artificial intelligence is truly fascinating, but it often faces a significant challenge: how can we trust a model whose processes are opaque and hard to understand? Machine learning systems are still, for the most part, black boxes that, although
The Chat GPT (Generative Pre-trained Transformer) is a natural language model developed by OpenAI that has revolutionized the way companies conduct their digital marketing strategies and planning. This model uses a large-scale neural network to predict and generate text automatically, learning from a vast dataset of textual data. Chat GPT can be used for various
Frequently, a controversy related to the result of Google’s query correction suggestion algorithm, the famous “Did you mean it”, regains the spotlight on social networks. The controversy revolves around the fact that the algorithm suggests a correction of the word “coronation” to “corruption” when accompanied by the term “Lula”, and another correction when associated with
Automation in industry has changed the way companies produce, and the introduction of collaborative robots and artificial intelligence (AI) into production lines is one of the main reasons for this increase. These technologies are transforming the way companies produce, ensuring more efficiency and precision in the execution of tasks. Collaborative robots are designed to work
Rodrigo Silva, our brilliant developer, has just released a new article that sheds light on how Artificial Intelligence is reshaping the way we code and optimize processes.
The AI gold rush has begun. Leaders understand that AI is a critical strategic differentiator to stand out in the market, and companies from different industries are starting their adoption journey. However, according to the “Gartner 2022 AI in Organizations” survey, only 53% of AI projects go into production. At Hop, that number is closer
In a competitive market like e-commerce, Artificial Intelligence (AI) is already transforming the market and helping to create personalized shopping experiences for consumers. With the help of AIs, it is possible to collect and analyze a large amount of data about consumer behavior, such as their purchasing preferences, browsing history and interactions with the website
