Tag: models
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The Register: AI hiring bias? Men with Anglo-Saxon names score lower in tech interviews
Source URL: https://www.theregister.com/2024/11/21/ai_hiring_test_bias/ Source: The Register Title: AI hiring bias? Men with Anglo-Saxon names score lower in tech interviews Feedly Summary: Study suggests hiding every Tom, Dick, and Harry’s personal info from HR bots In mock interviews for software engineering jobs, recent AI models that evaluated responses rated men less favorably – particularly those with…
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Simon Willison’s Weblog: A warning about tiktoken, BPE, and OpenAI models
Source URL: https://simonwillison.net/2024/Nov/21/a-warning-about-tiktoken/#atom-everything Source: Simon Willison’s Weblog Title: A warning about tiktoken, BPE, and OpenAI models Feedly Summary: A warning about tiktoken, BPE, and OpenAI models Tom MacWright warns that OpenAI’s tiktoken Python library has a surprising performance profile: it’s superlinear with the length of input, meaning someone could potentially denial-of-service you by sending you…
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Simon Willison’s Weblog: TextSynth Server
Source URL: https://simonwillison.net/2024/Nov/21/textsynth-server/ Source: Simon Willison’s Weblog Title: TextSynth Server Feedly Summary: TextSynth Server I’d missed this: Fabrice Bellard (yes, that Fabrice Bellard) has a project called TextSynth Server which he describes like this: ts_server is a web server proposing a REST API to large language models. They can be used for example for text…
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Simon Willison’s Weblog: Quoting Steven Johnson
Source URL: https://simonwillison.net/2024/Nov/21/steven-johnson/#atom-everything Source: Simon Willison’s Weblog Title: Quoting Steven Johnson Feedly Summary: When we started working on what became NotebookLM in the summer of 2022, we could fit about 1,500 words in the context window. Now we can fit up to 1.5 million words. (And using various other tricks, effectively fit 25 million words.)…
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OpenAI : Building smarter maps with GPT-4o vision fine-tuning
Source URL: https://openai.com/index/grab Source: OpenAI Title: Building smarter maps with GPT-4o vision fine-tuning Feedly Summary: Building smarter maps with GPT-4o vision fine-tuning AI Summary and Description: Yes Summary: The text discusses the integration and enhancement of mapping systems through the use of GPT-4 technology, particularly focusing on fine-tuning its vision capabilities. This is especially relevant…
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Hacker News: Niantic announces "Large Geospatial Model" trained on Pokémon Go player data
Source URL: https://nianticlabs.com/news/largegeospatialmodel/ Source: Hacker News Title: Niantic announces "Large Geospatial Model" trained on Pokémon Go player data Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the development of a Large Geospatial Model (LGM) by Niantic, which aims to enhance spatial intelligence through machine learning. It highlights the challenges faced by…
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Slashdot: DeepSeek’s First Reasoning Model R1-Lite-Preview Beats OpenAI o1 Performance
Source URL: https://slashdot.org/story/24/11/20/2129207/deepseeks-first-reasoning-model-r1-lite-preview-beats-openai-o1-performance?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: DeepSeek’s First Reasoning Model R1-Lite-Preview Beats OpenAI o1 Performance Feedly Summary: AI Summary and Description: Yes Summary: DeepSeek, a Chinese AI offshoot, has released a new reasoning-focused large language model, the R1-Lite-Preview, via its AI chatbot. This model demonstrates advanced reasoning capabilities and transparency in its processing, drawing attention…