Google DeepMind has shattered conventional boundaries in robotics AI with the unveiling of Gemini Robotics, a suite of models built upon the formidable foundation of Gemini 2.0. This isn’t just an incremental upgrade; it’s a paradigm shift, propelling AI from the digital realm into the tangible world with unprecedented “embodied reasoning” capabilities. Gemini Robotics: Bridging… →
Cohere For AI has just dropped a bombshell: Aya Vision, a open-weights vision model that’s about to redefine multilingual and multimodal communication. Prepare for a seismic shift as we shatter language barriers and unlock the true potential of AI across the globe! Smashing the Multilingual Multimodal Divide! Let’s face it, AI has been speaking with… →
In today’s digital landscape, interacting with a wide variety of software and operating systems can often be a tedious and error-prone experience. Many users face challenges when navigating through complex interfaces and performing routine tasks that demand precision and adaptability. Existing automation tools frequently fall short in adapting to subtle interface changes or learning from… →
Recent advancements in embedding models have focused on transforming general-purpose text representations for diverse applications like semantic similarity, clustering, and classification. Traditional embedding models, such as Universal Sentence Encoder and Sentence-T5, aimed to provide generic text representations, but recent research highlights their limitations in generalisation. Consequently, integrating LLMs has revolutionised embedding model development through two… →
Emotion recognition from video involves many nuanced challenges. Models that depend exclusively on either visual or audio signals often miss the intricate interplay between these modalities, leading to misinterpretations of emotional content. A key difficulty is reliably combining visual cues—such as facial expressions or body language—with auditory signals like tone or intonation. Many existing systems… →
Long-horizon robotic manipulation tasks are a serious challenge for reinforcement learning, caused mainly by sparse rewards, high-dimensional action-state spaces, and the challenge of designing useful reward functions. Conventional reinforcement learning is not well-suited to handle efficient exploration since the lack of feedback hinders learning optimal policies. This issue is significant in robotic control tasks of… →
In this tutorial, we implement a Bilingual Chat Assistant powered by Arcee’s Meraj-Mini model, which is deployed seamlessly on Google Colab using T4 GPU. This tutorial showcases the capabilities of open-source language models while providing a practical, hands-on experience in deploying state-of-the-art AI solutions within the constraints of free cloud resources. We’ll utilise a powerful… →
Large language models (LLMs) models primarily depend on their internal knowledge, which can be inadequate when handling real-time or knowledge-intensive questions. This limitation often leads to inaccurate responses or hallucinations, making it essential to enhance LLMs with external search capabilities. By leveraging reinforcement learning, researchers are actively working on methods to improve these models’ ability… →