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When Graph AI Meets Generative AI: A New Era in Scientific Discovery

Unite.AI

In recent years, artificial intelligence (AI) has emerged as a key tool in scientific discovery, opening up new avenues for research and accelerating the pace of innovation. Among the various AI technologies, Graph AI and Generative AI are particularly useful for their potential to transform how scientists approach complex problems.

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AI trends in 2023: Graph Neural Networks

AssemblyAI

While AI systems like ChatGPT or Diffusion models for Generative AI have been in the limelight in the past months, Graph Neural Networks (GNN) have been rapidly advancing. And why do Graph Neural Networks matter in 2023? What is the current role of GNNs in the broader AI research landscape?

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Why Do Neural Networks Hallucinate (And What Are Experts Doing About It)?

Towards AI

They happen when an AI, like ChatGPT, generates responses that sound real but are actually wrong or misleading. This issue is especially common in large language models (LLMs), the neural networks that drive these AI tools. Generative AI relies on pattern matching, not real comprehension.

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Neural Processing Units (NPUs): The Driving Force Behind Next-Generation AI and Computing

Unite.AI

Just as GPUs once eclipsed CPUs for AI workloads , Neural Processing Units (NPUs) are set to challenge GPUs by delivering even faster, more efficient performanceespecially for generative AI , where massive real-time processing must happen at lightning speed and at lower cost.

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Generative AI versus Predictive AI

Marktechpost

Recently, two core branches that have become central in academic research and industrial applications are Generative AI and Predictive AI. This article will describe Generative AI and Predictive AI, drawing upon prominent academic papers. Ian Goodfellow et al.

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Hypernetwork Fields: Efficient Gradient-Driven Training for Scalable Neural Network Optimization

Marktechpost

Additionally, current approaches assume a one-to-one mapping between input samples and their corresponding optimized weights, overlooking the stochastic nature of neural network optimization. It uses a hypernetwork, which predicts the parameters of the task-specific network at any given optimization step based on an input condition.

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How to Become a Generative AI Engineer in 2025?

Towards AI

Last Updated on January 29, 2025 by Editorial Team Author(s): Vishwajeet Originally published on Towards AI. How to Become a Generative AI Engineer in 2025? From creating art and music to generating human-like text and designing virtual worlds, Generative AI is reshaping industries and opening up new possibilities.