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Image Generated with DALL·E 3 NLP, or Natural Language Processing, is a field within Artificial Intelligence that focuses on the interaction between human language and…
The deep learning revolution in computer vision has shifted from manually crafted features to data-driven approaches, highlighting the potential of reducing feature biases. This paradigm shift…
One of the main challenges in current multimodal language models (LMs) is their inability to utilize visual aids for reasoning processes. Unlike humans, who draw and…
It is abundantly clear today that the procurement team or function of any business needs to play a strategic role rather than an operational role.Procurement teams…
Topological Deep Learning (TDL) advances beyond traditional GNNs by modeling complex multi-way relationships, unlike GNNs that only capture pairwise interactions. This capability is critical for understanding…
In machine learning, differential privacy (DP) and selective classification (SC) are essential for safeguarding sensitive data. DP adds noise to preserve individual privacy while maintaining data…
Initially, when ChatGPT just appeared, we used simple prompts to get answers to our questions. Then, we encountered issues with hallucinations and began using RAG (Retrieval…
Integrating Responsible AI practices into LLMOps15 min read·19 hours agoAbstract. While we see growing adoption of both LLMOps & Responsible AI practices in Gen AI implementations,…
Machine unlearning is a cutting-edge area in artificial intelligence that focuses on efficiently erasing the influence of specific training data from a trained model. This field…
A major weakness of current robotic manipulation policies is their inability to generalize beyond their training data. While these policies, trained for specific skills or language…