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Google AI Proposes MathWriting: Transforming Handwritten Mathematical Expression Recognition with Extensive Human-Written and Synthetic Dataset Integration and Enhanced Model Training

Marktechpost

Comprising 230k human-written and 400k synthetic samples, it surpasses offline HME datasets like IM2LATEX-100K. The MathWriting dataset comprises 253k human-written expressions and 6k isolated symbols for training, validation, and testing, alongside 396k synthetic expressions.

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Researchers from the University of Pennsylvania and Vector Institute Introduce DataDreamer: An Open-Source Python Library that Allows Researchers to Write Simple Code to Implement Powerful LLM Workflow

Marktechpost

The deployment of large language models (LLMs) has become central to many applications, from synthetic data generation to fine-tuning models for specific tasks. The methodology behind DataDreamer integrates features that address common challenges in LLM research, such as the need for synthetic data generation and the fine-tuning of models.

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Can Synthetic Clinical Text Generation Revolutionize Clinical NLP Tasks? Meet ClinGen: An AI Model that Involves Clinical Knowledge Extraction and Context-Informed LLM Prompting

Marktechpost

Creating synthetic training data with LLMs is a potential technique to address these issues as it uses LLMs’ capabilities in a resource- and privacy-conscious way. In general machine learning, one of the most common study areas is synthetic data creation using foundation models.

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Researchers at Purdue University Propose GTX: A Transactional Graph Data System for HTAP Workloads

Marktechpost

Researchers from Purdue University have introduced GTX to address the challenge of handling large-scale graphs with high throughput read-write transactions while maintaining competitive graph analytics. In contrast, the proposed data system GTX is a latch-free write-optimized transactional graph data system.

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Will LLM and Generative AI Solve a 20-Year-Old Problem in Application Security?

Unite.AI

While effective in simple cases, these methods struggle to address the creative ways developers write code and configure systems. The Magic of LLM in Security Generative AI is an advancement over older models used in machine learning algorithms that were great at classifying or clustering data based on trained learning of synthetic samples.

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Generative AI use cases for the enterprise

IBM Journey to AI blog

The result will be unusable if a user prompts the model to write a factual news article. Code generation : Software developers and programmers use generative AI to write code. With readily available synthetic data sets, companies can rapidly iterate on AI models, test new features and bring solutions to market faster.

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WellSaid Labs AI Voice Generator Review (October 2023)

Unite.AI

WellSaid Labs is an advanced AI voice generator that turns text into voiceovers in seconds, offering over 50 high-quality synthetic voices. Its high-quality synthetic voices can help create engaging and professional training materials that effectively convey information to employees.

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