The Question That Stalls Every Agent Project At some point in nearly every enterprise AI agent project, the conversation stops being about capability and starts being about access. The agent works, it can draft the email, resolve the ticket, pull the report, and then someone in the room, often from security, legal, or compliance, asks the question that ends the meeting: is it actually safe to give this thing access to our data? The honest answer is that the question, asked th

The Question That Gets Asked Too Late Most enterprises do not ask "can we test this agent first?" until after the rollout has already gone sideways: a customer-facing agent that confidently gave a wrong refund policy, an internal agent that took an action nobody authorized it to take, or a project that quietly consumed six months and a seven-figure budget before anyone could say with confidence whether it actually worked. By then the question has an expensive answer. The earl

The Question Every RAG Project Eventually Faces At some point in every retrieval-augmented generation (RAG) project, someone asks the same question: "How do we actually know this is working?" The demo always looks good: a few friendly questions, well-chosen documents, a confident answer. But a demo is not a system, and "it looked right when I tried it" is an anecdote, not an evaluation. That gap, between a demo that looked good and a system reliable enough for customers or em

Classification, which is the task of assigning objects to one of several predefined categories, is a pervasive problem that encompasses...

ABSTRACT Abstract In the last few years, deep learning has led to very good performance on a variety of problems, such as visual...

ABSTRACT Recommendation systems(RS)support users and developers of various computer and software systems to overcome information...

ABSTRACT As the complexity and volume of datasets have increased along with the capabilities of modular, open-source, easy-to-implement,...

ABSTRACT Due to the globalization trend and knowledge boost in the second millennium, multi-lingual translation has become a noteworthy...

ABSTRACT Autoencoders play a fundamental role in unsupervised learning and in deep architectures for transfer learning and other tasks....

ABSTRACT Deep Neural Networks (DNNs) are powerful models that have achieved excellent performance on difficult learning tasks. Although...

ABSTRACT Tremendous progress has been made in object recognition with deep convolutional neural networks (CNNs), thanks to the...

ABSTRACT The spread of COVID-19 across the world continues as efforts are being made from multi-dimension to curtail its spread and...

ABSTRACT With increasing amounts of data being generated by businesses and researchers there is a need for fast, accurate and robust...

ABSTRACT The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep...

ABSTRACT With the evolving behaviour of different types of social networking sites like Instagram, twitter, snap chat etc , the data...

ABSTRACT To facilitate future research in unsupervised induction of syntactic structure and to standardise best-practices, we propose a...