Artificial Intelligence (AI)

[ad_1] ServiceNow has launched its Yokohama platform which introduces AI agents across various sectors to boost workflows and maximise end-to-end business impact. The Yokohama platform release features teams of preconfigured AI agents designed to deliver immediate productivity gains. These agents operate on a single, unified platform, ensuring seamless integration and coordination across different business functions. … Read more

[ad_1] In this tutorial, we’ll learn how to build an interactive multimodal image-captioning application using Google’s Colab platform, Salesforce’s powerful BLIP model, and Streamlit for an intuitive web interface. Multimodal models, which combine image and text processing capabilities, have become increasingly important in AI applications, enabling tasks like image captioning, visual question answering, and more. … Read more

[ad_1] The Qwen team at Alibaba has unveiled QwQ-32B, a 32 billion parameter AI model that demonstrates performance rivalling the much larger DeepSeek-R1. This breakthrough highlights the potential of scaling Reinforcement Learning (RL) on robust foundation models. The Qwen team have successfully integrated agent capabilities into the reasoning model, enabling it to think critically, utilise … Read more

[ad_1] Having worked with AI since 2018, I’m watching its slow but steady pick-up alongside the unstructured bandwagon-jumping with considerable interest. Now that the initial fear has subsided somewhat about a robotic takeover, discussion about the ethics that will surround the integration of AI into everyday business structures has taken its place.   A whole new … Read more

[ad_1] 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 … Read more

[ad_1] 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 … Read more

[ad_1] 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 … Read more

[ad_1] Image by Author   Airflow was created to resolve the complexity of managing multiple pipelines and workflows. Before the invention of Airflow, many organizations depended on cron jobs, custom scripts, and other inefficient means when faced with big data generated by millions of users frequently. These solutions became hard to maintain, inflexible, and lacked … Read more

[ad_1] Image by Author   Everybody is being told that they need to upskill, and the number one skill that many organisations are looking for at the moment is AI. One thing about learning skills related to AI is mathematics, statistics, and machine learning. But you also want to be knowledgeable about the sector, what … Read more

[ad_1] In the field of artificial intelligence, two persistent challenges remain. Many advanced language models require significant computational resources, which limits their use by smaller organizations and individual developers. Additionally, even when these models are available, their latency and size often make them unsuitable for deployment on everyday devices such as laptops or smartphones. There … Read more