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How to Become a Generative AI Engineer in 2025?

Towards AI

Video Generation: AI can generate realistic video content, including deepfakes and animations. Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

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Top BERT Applications You Should Know About

Marktechpost

Models like GPT, BERT, and PaLM are getting popular for all the good reasons. The well-known model BERT, which stands for Bidirectional Encoder Representations from Transformers, has a number of amazing applications. Recent research investigates the potential of BERT for text summarization.

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UC Berkeley Researchers Propose CRATE: A Novel White-Box Transformer for Efficient Data Compression and Sparsification in Deep Learning

Marktechpost

The practical success of deep learning in processing and modeling large amounts of high-dimensional and multi-modal data has grown exponentially in recent years. They believe the proposed computational paradigm shows tremendous promise in connecting deep learning theory and practice from a unified viewpoint of data compression.

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AI News Weekly - Issue #343: Summer Fiction Reads about AI - Jul 27th 2023

AI Weekly

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation.

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Can Transformer Blocks Be Simplified Without Compromising Efficiency? This AI Paper from ETH Zurich Explores the Balance Between Design Complexity and Performance

Marktechpost

The motivation for simplification arises from the complexity of modern neural network architectures and the gap between theory and practice in deep learning. The study conducted experiments on autoregressive decoder-only and BERT encoder-only models to assess the performance of the simplified transformers.

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Frontiers of Foundation Models for Time Series

ODSC - Open Data Science

In a compelling talk at ODSC West 2024 , Yan Liu, PhD , a leading machine learning expert and professor at the University of Southern California (USC), shared her vision for how GPT-inspired architectures could revolutionize how we model, understand, and act on complex time series data acrossdomains. The result?

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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning Blog

of nodes with text-features MAG 484,511,504 7,520,311,838 4/4 28,679,392 1,313,781,772 240,955,156 We benchmark two main LM-GNN methods in GraphStorm: pre-trained BERT+GNN, a baseline method that is widely adopted, and fine-tuned BERT+GNN, introduced by GraphStorm developers in 2022. Dataset Num. of nodes Num. of edges Num.

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