Tag: natural language

  • Slashdot: If You Want Your Company’s Stock To Go Up, Hire Wonkier IT People

    Source URL: https://tech.slashdot.org/story/24/10/22/1448225/if-you-want-your-companys-stock-to-go-up-hire-wonkier-it-people?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: If You Want Your Company’s Stock To Go Up, Hire Wonkier IT People Feedly Summary: AI Summary and Description: Yes Summary: The findings from Barclays research indicate that companies focusing on hiring specialized AI talent are yielding superior stock market returns. This trend underlines the significance of targeted recruitment…

  • Hacker News: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges

    Source URL: https://arxiv.org/abs/2408.13296 Source: Hacker News Title: Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges Feedly Summary: Comments AI Summary and Description: Yes Summary: This guide extensively covers the fine-tuning of Large Language Models (LLMs), detailing methodologies, techniques, and practical applications. Its relevance to AI and LLM security professionals is underscored by discussions…

  • Hacker News: Rabbit raises additional $10M to launch first AI hardware to replace appbased OS

    Source URL: https://www.rabbit.tech/newsroom/rabbit-raises-additional-10m Source: Hacker News Title: Rabbit raises additional $10M to launch first AI hardware to replace appbased OS Feedly Summary: Comments AI Summary and Description: Yes Summary: Rabbit Inc., an AI startup, has secured an additional $10 million in funding to launch its new AI hardware and operating system, rabbit OS, which employs…

  • Cloud Blog: We tested Intel’s AMX CPU accelerator for AI. Here’s what we learned

    Source URL: https://cloud.google.com/blog/products/identity-security/we-tested-intels-amx-cpu-accelerator-for-ai-heres-what-we-learned/ Source: Cloud Blog Title: We tested Intel’s AMX CPU accelerator for AI. Here’s what we learned Feedly Summary: At Google Cloud, we believe that cloud computing will increasingly shift to private, encrypted services where users can be confident that their software and data are not being exposed to unauthorized actors. In support…

  • Hacker News: VPTQ: Extreme low-bit Quantization for real LLMs

    Source URL: https://github.com/microsoft/VPTQ Source: Hacker News Title: VPTQ: Extreme low-bit Quantization for real LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses a novel technique called Vector Post-Training Quantization (VPTQ) designed for compressing Large Language Models (LLMs) to extremely low bit-widths (under 2 bits) without compromising accuracy. This innovative method can…

  • Docker: Announcing IBM Granite AI Models Now Available on Docker Hub

    Source URL: https://www.docker.com/blog/announcing-ibm-granite-ai-models-now-available-on-docker-hub/ Source: Docker Title: Announcing IBM Granite AI Models Now Available on Docker Hub Feedly Summary: IBM’s Granite AI models, optimized for business applications, are now available on Docker Hub, making it easier for developers to deploy, scale, and customize AI-powered apps. AI Summary and Description: Yes Summary: The announcement regarding IBM’s Granite…

  • Hacker News: Use Prolog to improve LLM’s reasoning

    Source URL: https://shchegrikovich.substack.com/p/use-prolog-to-improve-llms-reasoning Source: Hacker News Title: Use Prolog to improve LLM’s reasoning Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the limitations of Large Language Models (LLMs) in reasoning tasks and introduces innovative methods to enhance their performance using Prolog as an intermediate programming language. These advancements leverage neurosymbolic approaches…

  • Simon Willison’s Weblog: Quoting François Chollet

    Source URL: https://simonwillison.net/2024/Oct/16/francois-chollet/ Source: Simon Willison’s Weblog Title: Quoting François Chollet Feedly Summary: A common misconception about Transformers is to believe that they’re a sequence-processing architecture. They’re not. They’re a set-processing architecture. Transformers are 100% order-agnostic (which was the big innovation compared to RNNs, back in late 2016 — you compute the full matrix of…

  • Hacker News: DeepSeek: Advancing theorem proving in LLMs through large-scale synthetic data

    Source URL: https://arxiv.org/abs/2405.14333 Source: Hacker News Title: DeepSeek: Advancing theorem proving in LLMs through large-scale synthetic data Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper introduces DeepSeek-Prover, an innovative approach that leverages large-scale synthetic data to improve the capabilities of large language models (LLMs) in formal theorem proving. It highlights the challenges…