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Tag: demo

  • The Register: UK tax collector inks £366M in ERP deals to get systems into cloud

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    Source URL: https://www.theregister.com/2024/11/18/uk_tax_collector_awards_366/ Source: The Register Title: UK tax collector inks £366M in ERP deals to get systems into cloud Feedly Summary: SAP and Deloitte winners in transition from legacy software to SaaS, which includes housing and transport ministries The UK’s tax collector has awarded contracts worth up to £366 million ($461 million) in an…

  • Slashdot: Google, Microsoft Are Spending Massively on AI, Quarterly Earnings Show

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    Source URL: https://tech.slashdot.org/story/24/11/18/0022217/google-microsoft-are-spending-massively-on-ai-quarterly-earnings-show?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google, Microsoft Are Spending Massively on AI, Quarterly Earnings Show Feedly Summary: AI Summary and Description: Yes **Summary:** The text discusses Alphabet and Microsoft’s significant financial performance and growth driven by their investments in AI technology. Both companies have reported increased revenues, partly due to the demand for AI…

  • Hacker News: You could have designed state of the art positional encoding

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    Source URL: https://fleetwood.dev/posts/you-could-have-designed-SOTA-positional-encoding Source: Hacker News Title: You could have designed state of the art positional encoding Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the evolution of positional encoding in transformer models, specifically focusing on Rotary Positional Encoding (RoPE) as utilized in modern language models like Llama 3.2. It explains…

  • Simon Willison’s Weblog: LLM 0.18

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    Source URL: https://simonwillison.net/2024/Nov/17/llm-018/#atom-everything Source: Simon Willison’s Weblog Title: LLM 0.18 Feedly Summary: LLM 0.18 New release of LLM. The big new feature is asynchronous model support – you can now use supported models in async Python code like this: import llm model = llm.get_async_model(“gpt-4o") async for chunk in model.prompt( "Five surprising names for a pet…

  • Hacker News: All-in-one embedding model for interleaved text, images, and screenshots

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    Source URL: https://blog.voyageai.com/2024/11/12/voyage-multimodal-3/ Source: Hacker News Title: All-in-one embedding model for interleaved text, images, and screenshots Feedly Summary: Comments AI Summary and Description: Yes Summary: The text announces the release of voyage-multimodal-3, a cutting-edge multimodal embedding model that enhances the capability of semantic search and retrieval tasks involving both text and images. Its ability to…

  • Slashdot: What Happened After Google Retrofitted Memory Safety Onto Its C++ Codebase?

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    Source URL: https://tech.slashdot.org/story/24/11/16/0630218/what-happened-after-google-retrofitted-memory-safety-onto-its-c-codebase Source: Slashdot Title: What Happened After Google Retrofitted Memory Safety Onto Its C++ Codebase? Feedly Summary: AI Summary and Description: Yes Summary: Google’s transition to Safe Coding and memory-safe languages aims to enhance security within its extensive C++ codebase, notably in critical products like Chrome and its various services. By integrating hardened…

  • Hacker News: SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks

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    Source URL: https://arxiv.org/abs/2310.03684 Source: Hacker News Title: SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks Feedly Summary: Comments AI Summary and Description: Yes Summary: This text presents “SmoothLLM,” an innovative algorithm designed to enhance the security of Large Language Models (LLMs) against jailbreaking attacks, which manipulate models into producing undesirable content. The proposal highlights a…

  • Hacker News: Don’t Look Twice: Faster Video Transformers with Run-Length Tokenization

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    Source URL: https://rccchoudhury.github.io/rlt/ Source: Hacker News Title: Don’t Look Twice: Faster Video Transformers with Run-Length Tokenization Feedly Summary: Comments AI Summary and Description: Yes Summary: The text presents a novel approach called Run-Length Tokenization (RLT) aimed at optimizing video transformers by eliminating redundant tokens. This content-aware method results in substantial speed improvements for training and…

  • Simon Willison’s Weblog: NuExtract 1.5

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    Source URL: https://simonwillison.net/2024/Nov/16/nuextract-15/#atom-everything Source: Simon Willison’s Weblog Title: NuExtract 1.5 Feedly Summary: NuExtract 1.5 Structured extraction – where an LLM helps turn unstructured text (or image content) into structured data – remains one of the most directly useful applications of LLMs. NuExtract is a family of small models directly trained for this purpose, and released…