Category: Artificial intelligence

Google NotebookLM is a fantastic free artificial intelligence tool created by Google, designed to help students and professionals manage, analyze and create content from their documents. Unlike other chatbots, this tool relies solely on the sources the user provides, which reduces errors and ensures greater accuracy. Its features include summaries, glossaries, quizzes, analysis of media files and the ability to collaborate in real time. Since it is integrated with Google Workspace, it is perfect for improving productivity, study and daily work.

Conversational artificial intelligence is becoming a strategic ally for retailers, improving customer experience and optimizing sales operations. We explore the key benefits that conversational solutions offer both to customers, such as through personalized and immediate assistance, and to retailers, through improved engagement, automation and data collection. We also understand the key steps to effectively implement conversational AI within a retail operation, with a focus on integration with existing systems such as CRM, e-commerce, and marketing platforms.

Conversational artificial intelligence is revolutionizing the retail world, offering new tools to improve the customer experience, optimize internal processes and increase sales. We explore the main use cases of conversational AI in retail, analyzing how chatbots, virtual assistants and voice interfaces are becoming strategic resources for consumer interaction, sales support and service personalization.

Computer vision is transforming many industries through its ability to automatically and intelligently interpret and analyze images. This article provides an overview of the main applications of this technology in five key areas: transportation, healthcare, manufacturing, retail and agriculture. Through concrete examples, it illustrates how artificial intelligence-based solutions are refining processes, improving safety, optimizing efficiency and becoming an integral part of our daily lives.

Computer vision is a discipline of artificial intelligence that enables computers to “see” and interpret images and videos, simulating human visual ability. We discover the basic principles of computer vision, clarifying the difference between the technical concept and broader computer vision. We also understand the goal of visual recognition and how machines actually perceive the world today through sensors and algorithms. Finally, we explore the main benefits of computer vision.

Artificial intelligence is revolutionizing the agricultural sector, offering new solutions to address challenges related to sustainability, efficiency and food security. AI can play a key role in managing the agricultural information cycle, supporting more informed and timely decisions through advanced data analysis. In addition, AI can help optimize agricultural processes by improving productivity, environmental monitoring and resource management. Along with the benefits, there are still technical, economic and social challenges that hinder its large-scale adoption. Will these challenges be overcome and will we arrive at more resilient and sustainable models?

In recent years, we are witnessing a real revolution in the way we grow, process and consume food. Central to this change is the application of artificial intelligence. From the ability to predict weather conditions with greater accuracy to the ability to monitor the status of crops in real time, artificial intelligence is becoming a valuable ally for the entire agri-food sector.Let’s find out the benefits that these technologies can improve food quality, reduce waste, and make the entire agri-food sector more sustainable and efficient.

LLMs are increasingly present in our daily lives: they answer questions, generate texts, summarize information and much more. But despite their amazing ability to deal with natural language, these models have limitations: they can “make up” facts, confuse concepts or lack access to up-to-date or reliable knowledge. And this is where knowledge graphs come in. These structures organize information in a precise and relational way, allowing LLMs to draw on well-organized and verifiable data. We explore how knowledge graphs can become a key ally in improving the accuracy, transparency and reliability of language models, helping them “really know” what they are talking about.

Nowadays we hear all the time about artificial intelligence and, in particular, about large language models, known as Large Language Models or LLMs. These tools, the most famous of which is ChatGPT, are capable of understanding and generating text in a surprisingly natural way and are finding applications in so many areas, from automatic writing to scientific research. One of the most promising uses in recent years is the generation and curation of knowledge graphs, a graph representation of information of interest, where concepts and relationships between them are linked in a structured way with semantic meaning.

Persuade people to take an action, buy a product or access a service (in other words, respond to a “call to action”), making Programmatic Advertising, Marketing Automation and Customer Care even more effective. This is what Artificial Intelligence is and what it is used for in Marketing.