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Image Recognition Has an Income Problem

Flipboard

Image recognition neural networks are only as good as the data they’re trained on. But a set of training data released today by machine learning benchmarking organization MLCommons makes the image recognition neural network ResNet more than 50 percent more accurate. You can see the problem below. It’s terrible.

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Yariv Fishman, Chief Product Officer at Deep Instinct – Interview Series

Unite.AI

Unlike ML, DL is built on neural networks, enabling it to self-learn and train on raw data. We saw a 64% increase in zero-day attacks in 2023 compared to 2022, and we released Deep Instinct’s Artificial Neural Network Assistant (DIANNA) to combat this growing trend. Enterprise zero-day vulnerabilities are on the rise.

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ZipNN: A New Lossless Compression Method Tailored to Neural Networks

Marktechpost

Researchers from IBM Research, Tel Aviv University, Boston University, MIT, and Dartmouth College have proposed ZipNN, a lossless compression technique specifically designed for neural networks. ZipNN can compress neural network models by up to 33%, with some instances showing reductions exceeding 50% of the original model size.

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Using Neural Networks with Pytorch to Predict Fail of Automatic Recovery

Towards AI

The next step is to define the neural network. I won’t go into the details for this function since it is not the objective of the article df = QueryAthena("""select * from table """).run_query()df.describe() df_minority = df_t[df_t[df_t.columns[-1]]>0.5]df_minority_upsampled import torch.nn

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The Power of Self-Managed Content

Unite.AI

Self-managed content refers to the use of AI and neural networks to simplify and strengthen the content creation process via smart tagging, metadata templates, and modular content. Role of AI and neural networks in self-management of digital assets Metadata is key in the success of self-managing content.

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Read graphs, diagrams, tables, and scanned pages using multimodal prompts in Amazon Bedrock

AWS Machine Learning Blog

Name a product and extract metadata to generate a tagline and description In the field of marketing and product development, coming up with a perfect product name and creative promotional content can be challenging. The image was generated using the Stability AI (SDXL 1.0) model on Amazon Bedrock.

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The Plagiarism Problem: How Generative AI Models Reproduce Copyrighted Content

Unite.AI

How Neural Networks Absorb Training Data Modern AI systems like GPT-3 are trained through a process called transfer learning. Overall, evidence indicates plagiarism is an inherent issue in large neural network models that requires vigilance and safeguards. Record metadata like licenses, tags, creators, etc.