Créer un compteSe connecter

Recherches récentes

Aucune recherche récente

Options de recherche

Disponible uniquement lorsque vous êtes connecté.
pouet.chapril.org est l'un des nombreux serveurs Mastodon indépendants que vous pouvez utiliser pour participer au fédiverse.
Chapril https://www.chapril.org est un projet de l'April https://www.april.org

Administré par :

Statistiques du serveur :

1,1K
comptes actifs

pouet.chapril.org: À proposAnnuaire des profilsPolitique de confidentialité

Mastodon: À proposTélécharger l’applicationRaccourcis clavierVoir le code sourcev4.3.7

#neuralnetworks

6 messages5 participants0 message aujourd’hui
Public
Calin Sandu

Hugging Face Transformers is a leading open-source library designed to simplify the use and development of transformer-based models, which have become foundational in natural language processing (NLP) and beyond. This library enables developers to leverage state-of-the-art models for tasks such as text classification, machine translation, question answering, and even computer vision and audio processing.

ml-nn.eu/a1/75.html

ml-nn.euHugging Face Transformers OverviewMachine Learning & Neural Networks Blog
#Programming#MachineLearning#NeuralNetworks
Public
Calin Sandu

Markov Decision Processes

MDPs are mathematical frameworks used to model decision-making in environments where outcomes are partly random and partly under the control of a decision maker. They are widely used in various fields, including artificial intelligence, robotics, economics, and operations research, to optimize decisions over time.

ml-nn.eu/a1/49.html

ml-nn.euMarkov Decision Processes (MDPs)Machine Learning & Neural Networks Blog
#Programming#MachineLearning#NeuralNetworks
Public
Calin Sandu

Pruning in Neural Networks: A Comprehensive Overview

Pruning is a critical technique in the field of neural networks, aimed at optimizing model performance, reducing computational complexity, and improving efficiency. As neural networks have grown in size and complexity, particularly with the advent of deep learning, the need for techniques to manage and streamline these models has become increasingly important.

ml-nn.eu/a1/77.html

ml-nn.euPruning in Neural Networks: A Comprehensive OverviewMachine Learning & Neural Networks Blog
#Programming#MachineLearning#NeuralNetworks
Public
Calin Sandu

Why Are AI Models Not Truly Intelligent?

Artificial Intelligence has advanced significantly, transforming industries and reshaping how we interact with technology. Despite these impressive capabilities, AI models remain fundamentally different from human intelligence. They excel at pattern recognition and data processing but lack the deeper cognitive and emotional faculties that define true intelligence...

ml-nn.eu/a1/82.html

ml-nn.euWhy Are AI Models Not Truly Intelligent?Machine Learning & Neural Networks Blog
#Programming#MachineLearning#NeuralNetworks
Public
Miguel Afonso Caetano

Tell me about it...

"Artificial intelligence (AI) systems with human-level reasoning are unlikely to be achieved through the approach and technology that have dominated the current boom in AI, according to a survey of hundreds of people working in the field.

More than three-quarters of respondents said that enlarging current AI systems ― an approach that has been hugely successful in enhancing their performance over the past few years ― is unlikely to lead to what is known as artificial general intelligence (AGI). An even higher proportion said that neural networks, the fundamental technology behind generative AI, alone probably cannot match or surpass human intelligence. And the very pursuit of these capabilities also provokes scepticism: less than one-quarter of respondents said that achieving AGI should be the core mission of the AI research community.

"I don’t know if reaching human-level intelligence is the right goal,” says Francesca Rossi, an AI researcher at IBM in Yorktown Heights, New York, who spearheaded the survey in her role as president of the Association for the Advancement of Artificial Intelligence (AAAI) in Washington DC. “AI should support human growth, learning and improvement, not replace us.”

The survey results were unveiled in Philadelphia, Pennsylvania, on Saturday at the annual meeting of the AAAI. They include responses from more than 475 AAAI members, 67% of them academics."

nature.com/articles/d41586-025

www.nature.comHow AI can achieve human-level intelligence: researchers call for change in tackA survey finds that most respondents are sceptical that the technology underpinning large-language models is sufficient for artificial general intelligence.
#AI#GenerativeAI#AGI
ExplorerFlux en direct
À propos