Experimental News Clipping Site

Tag: large language model

  • Hacker News: AI Search Engineer at Activeloop (YC S18): Build Multi-Modal Enterprise Search

    —

    by

    system automation
    in

    Source URL: https://www.workatastartup.com/jobs/68254 Source: Hacker News Title: AI Search Engineer at Activeloop (YC S18): Build Multi-Modal Enterprise Search Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces Activeloop’s innovative API and platform that focuses on multi-modal AI dataset management, specifically designed for large-scale model training and retrieval optimization. This is particularly relevant…

  • Hacker News: Large Language Models as Markov Chains

    —

    by

    system automation
    in

    Source URL: https://arxiv.org/abs/2410.02724 Source: Hacker News Title: Large Language Models as Markov Chains Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a theoretical analysis of large language models (LLMs) by framing them as equivalent to Markov chains. This approach may unveil new insights into LLM performance, pre-training, and generalization, which are…

  • Hacker News: Controlling AI’s Growing Energy Needs

    —

    by

    system automation
    in

    Source URL: https://cacm.acm.org/news/controlling-ais-growing-energy-needs/ Source: Hacker News Title: Controlling AI’s Growing Energy Needs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The provided text highlights the significant energy demands associated with training large AI models, particularly large language models (LLMs) like ChatGPT-3. It discusses the exponential growth in energy consumption for AI model training, the…

  • Hacker News: Sei AI (YC W22) Is Hiring an AI/ML Engineer with LLM Exposure

    —

    by

    system automation
    in

    Source URL: https://www.ycombinator.com/companies/sei/jobs/TYbKqi0-ai-ml-llm-engineer Source: Hacker News Title: Sei AI (YC W22) Is Hiring an AI/ML Engineer with LLM Exposure Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces Sei, an AI-driven regulatory compliance platform actively recruiting AI/ML engineers to enhance its technological abilities and support its rapid growth. The focus on developing…

  • Simon Willison’s Weblog: Quoting Menlo Ventures

    —

    by

    system automation
    in

    Source URL: https://simonwillison.net/2024/Nov/29/menlo-ventures/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Menlo Ventures Feedly Summary: Among closed-source models, OpenAI’s early mover advantage has eroded somewhat, with enterprise market share dropping from 50% to 34%. The primary beneficiary has been Anthropic,* which doubled its enterprise presence from 12% to 24% as some enterprises switched from GPT-4 to Claude…

  • Hacker News: CleaR: Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Labels

    —

    by

    system automation
    in

    Source URL: https://arxiv.org/abs/2411.00873 Source: Hacker News Title: CleaR: Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Labels Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses a novel approach to Parameter-Efficient Fine-Tuning (PEFT) designed to enhance model performance when working with noisy labeled data. This research is particularly relevant for professionals in AI,…

  • Simon Willison’s Weblog: Quoting Andrej Karpathy

    —

    by

    system automation
    in

    Source URL: https://simonwillison.net/2024/Nov/29/andrej-karpathy/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Andrej Karpathy Feedly Summary: People have too inflated sense of what it means to “ask an AI" about something. The AI are language models trained basically by imitation on data from human labelers. Instead of the mysticism of "asking an AI", think of it more as…

  • Simon Willison’s Weblog: LLM Flowbreaking

    —

    by

    system automation
    in

    Source URL: https://simonwillison.net/2024/Nov/29/llm-flowbreaking/#atom-everything Source: Simon Willison’s Weblog Title: LLM Flowbreaking Feedly Summary: LLM Flowbreaking Gadi Evron from Knostic: We propose that LLM Flowbreaking, following jailbreaking and prompt injection, joins as the third on the growing list of LLM attack types. Flowbreaking is less about whether prompt or response guardrails can be bypassed, and more about…

  • Schneier on Security: Race Condition Attacks against LLMs

    —

    by

    system automation
    in

    Source URL: https://www.schneier.com/blog/archives/2024/11/race-condition-attacks-against-llms.html Source: Schneier on Security Title: Race Condition Attacks against LLMs Feedly Summary: These are two attacks against the system components surrounding LLMs: We propose that LLM Flowbreaking, following jailbreaking and prompt injection, joins as the third on the growing list of LLM attack types. Flowbreaking is less about whether prompt or response…

  • Hacker News: An Intuitive Explanation of Sparse Autoencoders for LLM Interpretability

    —

    by

    system automation
    in

    Source URL: https://adamkarvonen.github.io/machine_learning/2024/06/11/sae-intuitions.html Source: Hacker News Title: An Intuitive Explanation of Sparse Autoencoders for LLM Interpretability Feedly Summary: Comments AI Summary and Description: Yes **Summary**: The text discusses Sparse Autoencoders (SAEs) and their significance in interpreting machine learning models, particularly large language models (LLMs). It explains how SAEs can provide insights into the functioning of…