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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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Meet SemiKong: The World’s First Open-Source Semiconductor-Focused LLM

Marktechpost

This growing concern has prompted companies to explore AI as a viable solution for capturing, scaling, and leveraging expert knowledge. These challenges highlight the limitations of traditional methods and emphasize the necessity of tailored AI solutions. Dont Forget to join our 60k+ ML SubReddit.

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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

Similar to how a customer service team maintains a bank of carefully crafted answers to frequently asked questions (FAQs), our solution first checks if a users question matches curated and verified responses before letting the LLM generate a new answer. No LLM invocation needed, response in less than 1 second.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning Blog

Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Rigorous testing allows us to understand an LLMs capabilities, limitations, and potential biases, and provide actionable feedback to identify and mitigate risk.

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Hugging Face Releases Picotron: A Tiny Framework that Solves LLM Training 4D Parallelization

Marktechpost

Hugging Face Releases Picotron: A New Approach to LLM Training Hugging Face has introduced Picotron, a lightweight framework that offers a simpler way to handle LLM training. Conclusion Picotron represents a step forward in LLM training frameworks, addressing long-standing challenges associated with 4D parallelization.

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TrueFoundry Secures $19 Million Series A Funding to Revolutionize AI Deployment

Unite.AI

TrueFoundry , a pioneering AI deployment and scaling platform, has successfully raised $19 million in Series A funding. The exponential rise of generative AI has brought new challenges for enterprises looking to deploy machine learning models at scale.

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LLM continuous self-instruct fine-tuning framework powered by a compound AI system on Amazon SageMaker

AWS Machine Learning Blog

Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. You can use supervised fine-tuning (SFT) and instruction tuning to train the LLM to perform better on specific tasks using human-annotated datasets and instructions.

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