next ai
By any measure, 2023 was an amazing year for AI. Large language Models (LLMs) and their chatbot applications stole the show, but there were advances across a broad swath of uses. These include image, video and voice generation.
The combination of these digital technologies have led to new use cases and business models, even to the point where digital humans are becoming commonplace, replacing actual humans as influencers and newscasters.
Importantly, 2023 was the year when large numbers of people started to use and adopt AI intentionally as part of their daily work. Rapid AI innovation has fueled future predictions, as well, including everything from friendly home robots to artificial general intelligence (AGI) within a decade. That said, progress is never a straight line and challenges could sidetrack some of these predicted advances.
As AI increasingly weaves into the fabric of our daily lives and work, it begs the question: What can we expect next?”
While digital advancements continue to astonish, the physical realm of AI — particularly robotics — is not far behind in capturing our imagination. LLMs could provide the missing piece, essentially a brain, particularly when combined with image recognition capabilities through camera vision. With these technologies, robots could more readily understand and respond to requests and perceive the world around them.
In the Robot Report, Nvidia’s VP of robots and edge computing Deepu Talla said that LLMs will enable robots to better understand human instructions, learn from one another and comprehend their environments.
One way to improve robot performance is to use multiple models. MIT’s Improbable AI Lab, a group within the Computer Science and Artificial Intelligence Laboratory (CSAIL), for instance, has developed a framework that makes use of three different foundation models each tuned for specific tasks such as language, vision and action.
Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.
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