Tag: model deployment

  • Slashdot: Google Shifts Gemini App Team To DeepMind

    Source URL: https://tech.slashdot.org/story/24/10/17/2310259/google-shifts-gemini-app-team-to-deepmind?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google Shifts Gemini App Team To DeepMind Feedly Summary: AI Summary and Description: Yes Summary: Google is consolidating its AI efforts by moving the team behind the Gemini app to DeepMind, aiming to enhance model deployment and feedback loops in AI development. This strategic shift reflects Google’s commitment to…

  • Hacker News: AI PCs Aren’t Good at AI: The CPU Beats the NPU

    Source URL: https://github.com/usefulsensors/qc_npu_benchmark Source: Hacker News Title: AI PCs Aren’t Good at AI: The CPU Beats the NPU Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text presents a benchmarking analysis of Qualcomm’s Neural Processing Unit (NPU) performance on Microsoft Surface tablets, highlighting a significant discrepancy between claimed and actual processing speeds for…

  • Hacker News: Run Llama locally with only PyTorch on CPU

    Source URL: https://github.com/anordin95/run-llama-locally Source: Hacker News Title: Run Llama locally with only PyTorch on CPU Feedly Summary: Comments AI Summary and Description: Yes Summary: The text provides detailed instructions and insights on running the Llama large language model (LLM) locally with minimal dependencies. It discusses the architecture, dependencies, and performance considerations while using variations of…

  • Hacker News: AMD Inference

    Source URL: https://github.com/slashml/amd_inference Source: Hacker News Title: AMD Inference Feedly Summary: Comments AI Summary and Description: Yes Summary: The text describes a Docker-based inference engine designed to run Large Language Models (LLMs) on AMD GPUs, with an emphasis on usability with Hugging Face models. It provides guidance on setup, execution, and customization, making it a…

  • OpenAI : o1 System Card

    Source URL: https://openai.com/index/openai-o1-system-card Source: OpenAI Title: o1 System Card Feedly Summary: This report outlines the safety work carried out prior to releasing GPT-4o including external red teaming, frontier risk evaluations according to our Preparedness Framework, and an overview of the mitigations we built in to address key risk areas. AI Summary and Description: Yes Summary:…

  • Slashdot: OpenAI Releases o1, Its First Model With ‘Reasoning’ Abilities

    Source URL: https://tech.slashdot.org/story/24/09/12/1717221/openai-releases-o1-its-first-model-with-reasoning-abilities?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: OpenAI Releases o1, Its First Model With ‘Reasoning’ Abilities Feedly Summary: AI Summary and Description: Yes Summary: OpenAI’s launch of the “o1” AI model showcases significant enhancements in reasoning and problem-solving, targeting complex tasks in science, coding, and math. However, these advancements come with increased operational costs and limitations,…

  • Cloud Blog: Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024

    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-named-a-leader-in-forrester-wave-for-ai-platforms/ Source: Cloud Blog Title: Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024 Feedly Summary: Today, we are excited to announce that Google is a Leader in The Forrester Wave™: AI/ML Platforms, Q3 2024, tying for the highest score of all vendors evaluated in the Strategy category. At Google…

  • Simon Willison’s Weblog: Quoting Magic AI

    Source URL: https://simonwillison.net/2024/Aug/30/magic-ai/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Magic AI Feedly Summary: We have recently trained our first 100M token context model: LTM-2-mini. 100M tokens equals ~10 million lines of code or ~750 novels. For each decoded token, LTM-2-mini’s sequence-dimension algorithm is roughly 1000x cheaper than the attention mechanism in Llama 3.1 405B for…

  • Hacker News: 80% of AI Projects Crash and Burn, Billions Wasted Says Rand Report

    Source URL: https://salesforcedevops.net/index.php/2024/08/19/ai-apocalypse/ Source: Hacker News Title: 80% of AI Projects Crash and Burn, Billions Wasted Says Rand Report Feedly Summary: Comments AI Summary and Description: Yes Summary: The RAND Corporation report reveals that over 80% of AI projects fail, highlighting the critical role of leadership understanding, data quality, and infrastructure in successful AI implementation.…