AI

In a groundbreaking move, Aethir, a leader in decentralized GPU cloud computing, has unveiled AI Unbundled, an innovative alliance aimed at revolutionizing artificial intelligence (AI) within the Web3 ecosystem. This initiative is a confluence of key players across the decentralized infrastructure, blockchain networks, and venture capital landscape, including industry giants like Biconomy, Oasis Protocol Foundation,
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In a world where robotics often captivates the public’s imagination with striking performances—think dancing drones or karate-chopping automatons—it can be easy to overlook the underwhelming utility of these humanoid machines in everyday applications. Expert opinions, such as that of Fern, suggest that flashy exhibitions often distract from the essential question: How can humanoid robots contribute
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As the political landscape around immigration in the United States becomes increasingly contentious, the role of technology firms like Palantir in enforcing these policies warrants careful scrutiny. The recent $30 million award to Palantir for its enhancements to the ImmigrationOS case management system is a vivid illustration of how the government increasingly relies on private
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The landscape of artificial intelligence is undergoing a seismic transformation, characterized by the thrust into billion-parameter models which leverage vast computational power to develop intelligent agents capable of working autonomously and performing complex tasks. At the forefront of this revolution is NVIDIA, as its founder and CEO Jensen Huang delineated in his recent keynote at
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As businesses delve deeper into the realm of artificial intelligence, the advent of Enterprise Retrieval-Augmented Generation (RAG) is transforming how organizations approach data handling. In this rapidly evolving landscape, Cohere’s latest embedding model, Embed 4, emerges as a significant player, fueled by the immense buzz surrounding agentic AI technologies. What sets Embed 4 apart is
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In a compelling move toward advancing artificial intelligence capabilities, OpenAI has unveiled a groundbreaking suite of coding-focused models—dubbed GPT-4.1. As the competition within the tech industry heats up, with major players like Google and Anthropic pushing the envelope of AI utility, OpenAI positions itself at the forefront with these innovative models tailored for developers. But
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The quest to quantify intelligence has eluded scholars and technologists alike for decades. This challenge is particularly pronounced in the realm of artificial intelligence, where the metrics we employ often fall woefully short of capturing the true essence of an AI’s capabilities. Traditional evaluation methods, like standardized tests, can yield impressive scores, but these numbers
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The ascent of large language models (LLMs) in the world of artificial intelligence has been nothing short of remarkable. These expansive systems, boasting hundreds of billions of parameters, rely on intricate data connections refined through extensive training. While their size enables them to discern complex patterns and produce highly accurate outputs, this tremendous power comes
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