Unite.AI

JUNE 25, 2023

In a pioneering effort to further enhance AI capabilities, researchers from UCLA and the United States Army Research Laboratory have unveiled a unique approach that marries physics-awareness with data-driven techniques in AI-powered computer vision technologies.

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Unite.AI

FEBRUARY 10, 2025

Neetu Pathak , Co-Founder and CEO of Skymel , leads the company in revolutionizing AI inference with its innovative NeuroSplit technology. Alongside CTO Sushant Tripathy, she drives Skymels mission to enhance AI application performance while reducing computational costs.

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Unite.AI

DECEMBER 9, 2024

I recently came across HARPA AI , and I was impressed with its capabilities. In this HARPA AI review, I'll discuss the pros and cons, what it is, who it's best for, and its key features. Then, I'll show you how I used some of HARPA AI's tools to streamline my online workflow! What is HARPA AI? and Gemini. and Gemini.

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IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Machine learning is a subset of AI. What is artificial intelligence (AI)?

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Unite.AI

FEBRUARY 16, 2024

Artificial Intelligence (AI) is everywhere. From smart assistants to self-driving cars , AI systems are transforming our lives and businesses. But what if there was an AI that could do more than perform specific tasks? What if there was a type of AI that could learn and think like a human or even surpass human intelligence?

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O'Reilly Media

NOVEMBER 19, 2024

One popular term encountered in generative AI practice is retrieval-augmented generation (RAG). What’s old becomes new again: Substitute the term “notebook” with “blackboard” and “graph-based agent” with “control shell” to return to the blackboard system architectures for AI from the 1970s–1980s. Does GraphRAG improve results?

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Marktechpost

JUNE 29, 2024

In the contemporary landscape of scientific research, the transformative potential of AI has become increasingly evident. This is particularly true when applying scalable AI systems to high-performance computing (HPC) platforms. Scaling AI systems involves both model-based and data-based parallelism.

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