Bob Violino

2 months ago | lemondeinformatique.fr | Bob Violino

2025 sera probablement l'année de l'IA agentique et de nombreuses entreprises cherchent à trouver des cas d'utilisation à valeur ajoutée. D'où la question qu'elles se posent d'emblée : quels sont les processus opérationnels qui se prêtent réellement à l'IA agentique ? Le cabinet de conseil Deloitte prévoit qu'en 2025, 25% des entreprises qui utilisent l'IA générative lanceront des projets pilotes ou des prototypes d'IA agentique, et que ce chiffre passera à 50% en 2027.

2 months ago | cio.com | Bob Violino

From downplaying data management to underestimating the importance of measuring outcomes, too many AI projects suffer from key strategic oversights and mistakes.

2 months ago | cnbc.com | Bob Violino

Companies including PepsiCo, Intel and Qualcomm are part of a new business alliance working on breakthroughs in what is known as the Ambient Internet of Things (IoT), a class of IoT devices that can ditch the need for a battery and primarily be powered by harvesting ambient energy. Ambient IoT will allow more battery-less things to be interconnected, using power from radio waves, light, motion, heat, or any other viable ambient energy source, according to the recently formed Ambient IoT Alliance.

Mar 3, 2025 | businessandamerica.com | Bob Violino

Pricing of UEM platforms has remained relatively stable, outside of nominal increases as a result of global inflation, Cipolla says. “Many vendors have simplified their licensing models by creating bundled tiers,” he says. Hochmuth, on the other hand, says prices might actually be declining on an application service provider (ASP) level for basic UEM/mobile device management (MDM) functions.

Feb 28, 2025 | computerworld.es | Bob Violino

Problemas de rendimiento y escalabilidadConforme el uso del aprendizaje automático crece con el tiempo surge otro problema: la escalabilidad es otro problema. Si los sistemas no son capaces de mantener su rendimiento y eficiencia cuando se trata de conjuntos de datos significativamente más grandes, una mayor complejidad y mayores demandas computacionales, es probable que los resultados no sean aceptables.