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Unlearning Copyrighted Data From a Trained LLM – Is It Possible?

Unite.AI

In the domains of artificial intelligence (AI) and machine learning (ML), large language models (LLMs) showcase both achievements and challenges. Trained on vast textual datasets, LLM models encapsulate human language and knowledge. Why is LLM Unlearning Needed?

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MLPerf Inference v3.1 introduces new LLM and recommendation benchmarks

AI News

The latest release of MLPerf Inference introduces new LLM and recommendation benchmarks, marking a leap forward in the realm of AI testing. What sets this achievement apart is the diverse pool of 26 different submitters and over 2,000 power results, demonstrating the broad spectrum of industry players investing in AI innovation.

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

Unite.AI

However, a promising new technology, Generative AI (GenAI), is poised to revolutionize the field. This necessitates a paradigm shift in security approaches, and Generative AI holds a possible key to tackling these challenges. The modern LLMs are trained on millions of examples from big code repositories, (e.g.,

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Establishing an AI/ML center of excellence

AWS Machine Learning Blog

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. According to a McKinsey study , across the financial services industry (FSI), generative AI is projected to deliver over $400 billion (5%) of industry revenue in productivity benefits.

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CT-LLM: A 2B Tiny LLM that Illustrates a Pivotal Shift Towards Prioritizing the Chinese Language in Developing LLMs

Marktechpost

However, a groundbreaking new development is set to challenge this status quo and usher in a more inclusive era of language models – the Chinese Tiny LLM (CT-LLM). Imagine a world where language barriers are no longer an obstacle to accessing cutting-edge AI technologies. The pretraining corpus comprises an impressive 840.48

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ST-LLM: An Effective Video-LLM Baseline with Spatial-Temporal Sequence Modeling Inside LLM

Marktechpost

To tackle this challenge, a team of researchers from Peking University and Tencent has proposed a novel approach called ST-LLM. The core idea is simple yet unexplored: leverage the robust sequence modeling capabilities inherent in LLMs to process raw spatial-temporal video tokens directly.

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Meta AI Introduces CyberSecEval 2: A Novel Machine Learning Benchmark to Quantify LLM Security Risks and Capabilities

Marktechpost

Vulnerability exploitation tests focus on challenging yet solvable scenarios, avoiding LLM memorization and targeting LLMs’ general reasoning abilities. In code interpreter abuse evaluation, LLM conditioning is prioritized alongside unique abuse categories, while a judge LLM assesses generated code compliance.

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