Open AI News: Fine-Tuning and Customized Models
OpenAI Broadens the Horizons of Artificial Intelligence with Fine-Tuning Improvements and the Development of Customized Models to Meet Specific User Needs.
Insights, ideas, and inspiration: dive into our blog to discover the latest advances in artificial intelligence.
Speak with an AI Expert →OpenAI Broadens the Horizons of Artificial Intelligence with Fine-Tuning Improvements and the Development of Customized Models to Meet Specific User Needs.
Generative AI is transforming the sales sector by boosting the productivity of sales professionals, saving them an average of 4.5 hours per week. It automates repetitive tasks and enhances customer interactions, while also requiring new skills. However, data security and human oversight remain critical for building trust. The adoption of AI follows two stages: rapid integration of tools, followed by optimization based on data quality. This technology becomes a strategic partner, enriching the role of sales professionals without replacing them.
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L'intelligence artificielle est un levier clé pour innover et optimiser les processus en entreprise. Pourtant, beaucoup hésitent à se lancer, pensant qu'il faut d'importantes ressources et des équipes spécialisées. Cet article explore l'intérêt de mettre en place un laboratoire IA interne, une approche agile et accessible qui permet de tester des solutions, lancer des projets pilotes et renforcer la culture IA et data. Découvrez pourquoi et comment structurer efficacement un laboratoire IA pour transformer vos opérations tout en minimisant les risques et les coûts.
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The new OpenAI models, o3 and o4-mini, mark a breakthrough: AI is no longer content with responding, it reasons and acts independently. These advances make it possible to deal with complex business issues from end to end — financial modeling, anomaly detection, opportunity scoring, logistics simulations — without human supervision. Thanks to their integration via API, these AIs are transforming business tools.
Cette étude fournit aux décideurs des données stratégiques et des perspectives clés sur ce secteur en rapide évolution.
According to Gartner, 85% of data projects fail, often due to a lack of a clear objective, poorly exploited data, or a lack of buy-in from business teams. To succeed, it is essential to define a specific business need, to structure and clean the data beforehand, and to involve the teams from the start. The tool must be integrated into existing processes and evolve with the company to ensure a lasting impact.