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AI will not be reliable if it is not representative
Representativeness cannot be incorporated once a system is finished. It begins by defining what problem will be solved, what data will be used, and who participates in the decisions that will determine its operation.
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Semantics and Artificial Intelligence: emerging business models and future challenges
Semantics represents a critical field of innovation in the development of modern Artificial Intelligence. Beyond processing data, the ability to understand the deep meaning of language and concepts opens new frontiers for technological and business transformation. The Challenge of Semantic Understanding: Current artificial intelligence models have…
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Emotional Management of AI-Based Innovations
AI promises to revolutionize business, but its adoption is often hampered by psychological and organizational barriers. “How can we overcome this resistance and maximize the potential of AI?” is a question frequently asked by the leadership of most organizations. The answer lies in neuromanagement, a discipline that studies…
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Evolution and Perspectives of Generative Artificial Intelligence
The term Artificial Intelligence, henceforth AI, was coined in the 1960s by computer scientist and mathematician John McCarthy, considered one of the "fathers of AI," who, along with Claude Shannon, Marvin Minsky, and Nat Rochester, gave the world's first conference on AI in 1956…
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The resurgence of the Humanities in the age of Artificial Intelligence
I am writing these lines from the Ortega-Marañón Foundation in Madrid, sitting in the very space where José Ortega y Gasset used to stroll and develop part of his philosophical thought. The emotion I feel reflecting on the future of the Humanities from this place steeped in intellectual history is difficult to describe. The walls of this building…
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Against All Odds
The role of women in society has historically been made invisible, but our leadership has always existed, marking milestones throughout time. In a sector like technology, often perceived as cutting-edge and even distant for many, it is essential to remember that female leadership is neither an exception nor something…
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LoRAs in generative AI: a revolution in image creation
Introduction Fine-tuning generative AI models is one of the most promising areas of deep learning. Thanks to techniques like fine-tuning and LoRA (low-range adaptation), it is now possible to customize existing models to suit specific use cases without the need for expensive hardware. This article…
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GenAI and the New Era of Payment Methods
The payments industry is experiencing a slowdown in mature markets, where the global industry is projected to reach $2.3 trillion by 2028, with an annual growth rate of 51%. This figure is lower than the 91% growth recorded in the last five years, when the market reached $1.8 trillion in…
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Pioneering and relevant women for the birth of Generative AI and their contribution to this technology
Generative artificial intelligence is a type of artificial intelligence that uses neural networks and algorithms to generate original content from deep learning models trained by analyzing existing datasets, simulating the learning processes and decision-making of the human brain. Technological development since…
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Introducing Women in genAI
The Generative AI Association's commitment to society, to the evolution of generative AI and its integration into an increasingly connected community, where female engineering graduates in the 2021-2022 academic year represented 28.31% of the workforce, and the presence of ICT specialists in companies in 2023 was approximately 16.41%, and…