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. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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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

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 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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NVIDIA

MAY 29, 2024

Editor’s note: This post is part of the AI Decoded series , which demystifies AI by making the technology more accessible, and showcases new hardware, software, tools and accelerations for GeForce RTX PC and RTX workstation users. Generative AI is enabling new capabilities for Windows applications and games.

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Unite.AI

AUGUST 22, 2023

Sean Mullaney is the Chief Technology Officer at Algolia , an end-to-end, AI-powered search and discovery platform. Sean is a former Stripe and Google executive with a background in scaling engineering organizations, developing AI-powered Search and Discovery tools, and growing API-first solutions globally.

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O'Reilly Media

NOVEMBER 19, 2024

One popular term encountered in generative AI practice is retrieval-augmented generation (RAG). One more embellishment is to use a graph neural network (GNN) trained on the documents. tend to dislike using an AI application as a “black box” solution, which magically handles work that may need human oversight.

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