what_i_read_this_week_apr_30.json

{"byline":"","intro_md":"","items":[{"description":"https://www.mosaicml.com/blog/mpt-7b","entity":"bookmark","image_url":"","name":"Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs","url":"https://www.mosaicml.com/blog/mpt-7b"},{"description":"Structured and typehinted GPT responses in Python. Contribute to piercefreeman/gpt-json development by creating an account on GitHub.","entity":"bookmark","image_url":"https://opengraph.githubassets.com/86637bfb34d74a2920b7b600e6217acb8461a02a161a147111ccf29e7ea181ad/piercefreeman/gpt-json","name":"GitHub - piercefreeman/gpt-json: Structured and typehinted GPT responses in Python","url":"https://github.com/piercefreeman/gpt-json"},{"description":"Transformer-based models typically have a predefined bound to their inputlength, because of their need to potentially attend to every token in theinput. In this work, we propose Unlimiformer: a general approach that can wrapany existing pretrained encoder-decoder transformer, and offload the attentioncomputation across all layers to a single $k$-nearest-neighbor index; thisindex can be kept on either the GPU or CPU memory and queried in sub-lineartime. This way, we can index extremely long input sequences, while everyattention head in every decoder layer retrieves its top-$k$ keys, instead ofattending to every key. We demonstrate Unlimiformers's efficacy on severallong-document and multi-document summarization benchmarks, showing that it cansummarize even 350k token-long inputs from the BookSum dataset, without anyinput truncation at test time. Unlimiformer improves pretrained models such asBART and Longformer by extending them to unlimited inputs without additionallearned weights and without modifying their code. We make our code and modelspublicly available at https://github.com/abertsch72/unlimiformer .","entity":"bookmark","image_url":"https://static.arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png","name":"Unlimiformer: Long-Range Transformers with Unlimited Length Input","url":"https://arxiv.org/abs/2305.01625"},{"description":"https://wondercraft.ai/blog/learnings-from-1-month-of-ai-podcast","entity":"bookmark","image_url":"","name":"Wondercraft AI","url":"https://wondercraft.ai/blog/learnings-from-1-month-of-ai-podcast"},{"description":"The new YOLO-NAS architecture sets a new frontier for object detection tasks, offering the best accuracy and latency tradeoff performance.","entity":"bookmark","image_url":"https://deci.ai/wp-content/uploads/2023/05/YOLO-NAS-Launch-Technical-Blog2.jpg","name":"YOLO-NAS by Deci Achieves State-of-the-Art Performance on Object Detection Using Neural Architecture Search","url":"https://deci.ai/blog/yolo-nas-object-detection-foundation-model/"},{"description":"Explore how clear syntax can enable you to communicate intent to language models, and also help ensure that outputs are easy to parse","entity":"bookmark","image_url":"https://miro.medium.com/v2/resize:fit:1200/1*4q-D4si5XBmcPph7jhOcdA.png","name":"The Art of Prompt Design: Use Clear Syntax","url":"https://towardsdatascience.com/the-art-of-prompt-design-use-clear-syntax-4fc846c1ebd5"},{"description":"This blog discusses the usage of deep learning for recognizing UI components and introduces a correct method of using machine learning to solve various problems.","entity":"bookmark","image_url":"https://yqintl.alicdn.com/0866152984ebcbc972991f822f6348bf7ee21c6b.png","name":"How Do You Use Deep Learning to Identify UI Components?","url":"https://www.alibabacloud.com/blog/how-do-you-use-deep-learning-to-identify-ui-components_597859"},{"description":"Helping reduce hallucinations in LLMs with retrieval augmentation using vector databases.","entity":"bookmark","image_url":"https://www.pinecone.io/images/langchain-retrieval-augmentation-0.png","name":"Fixing Hallucination with Knowledge Bases | Pinecone","url":"https://www.pinecone.io/learn/langchain-retrieval-augmentation/"},{"description":"SemiAnalysis published something of a bombshell leaked document this morning: Google “We Have No Moat, And Neither Does OpenAI”. The source of the document is vague: The text below is …","entity":"bookmark","image_url":"https://static.simonwillison.net/static/2023/vicuna-chart.jpg","name":"Leaked Google document: “We Have No Moat, And Neither Does OpenAI”","url":"https://simonwillison.net/2023/May/4/no-moat/"},{"description":"Exploring the Unseen Capabilities of LLMs in Natural Language Processing. From text-to-code generation to full stack app creation, what's next?","entity":"bookmark","image_url":"","name":"Augmenting LLMs Beyond Basic Text Completion and Transformation","url":"https://blog.deepgram.com/augmenting-llms-beyond-basic-text-completion-and-transformation/"},{"description":"\"We needed it to be on the Daytona 500 side of the graph databases,\" LinkedIn Chief Architect for LIquid tells The New Stack.","entity":"bookmark","image_url":"https://cdn.thenewstack.io/media/2023/05/5a0f15d5-pexels-anthony-132477.jpg","name":"LinkedIn's Real-Time Graph Database Is LIquid","url":"https://thenewstack.io/linkedins-real-time-graph-database-is-liquid/"},{"description":"https://web.dev/import-maps-in-all-modern-browsers/","entity":"bookmark","image_url":"","name":"JavaScript import maps are now supported cross-browser","url":"https://web.dev/import-maps-in-all-modern-browsers/"},{"description":"[www.newsminimalist.com]","entity":"bookmark","image_url":"https://www.newsminimalist.com/opengraph-image.png?b6e6dd406cc97b87","name":"News Minimalist – Only significant news","url":"https://www.newsminimalist.com/"},{"description":"https://news.ycombinator.com/item?id=35798888","entity":"bookmark","image_url":"","name":"OpenLLaMA: An Open Reproduction of LLaMA | Hacker News","url":"https://news.ycombinator.com/item?id=35798888"},{"description":"https://gpt-index.readthedocs.io/en/latest/index.html","entity":"bookmark","image_url":"","name":"LlamaIndex 🦙 0.6.0","url":"https://gpt-index.readthedocs.io/en/latest/index.html"},{"description":"https://www.reddit.com/r/qyldgang","entity":"bookmark","image_url":"","name":"Between. $HYGW or $TLTW which one would you buy and hold forever? : r/qyldgang","url":"https://www.reddit.com/r/qyldgang/comments/135v4gc/between_hygw_or_tltw_which_one_would_you_buy_and/?utm_source=share&utm_medium=ios_app&utm_name=iossmf&utm_content=1&utm_term=15"},{"description":"The simplest, fastest repository for training/finetuning medium-sized GPTs. - nanoGPT/train.py at master · karpathy/nanoGPT","entity":"bookmark","image_url":"https://opengraph.githubassets.com/32e79ee7bfa1f9ebf4858ce954fe1408155b48f1b294e625c9701b2942873ed8/karpathy/nanoGPT","name":"nanoGPT/train.py at master · karpathy/nanoGPT","url":"https://github.com/karpathy/nanoGPT/blob/master/train.py"},{"description":"Searching for information using traditional keyword-based search systems can be frustrating. You type in a phrase and get back a list of results that has little to do with what you are looking for. It's like trying to find a needle in a haystack.In contrast, a semantic-based search system","entity":"bookmark","image_url":"https://txt.cohere.com/content/images/2023/05/rerank-blog-post.png","name":"Say Goodbye to Irrelevant Search Results: Cohere Rerank Is Here","url":"https://txt.cohere.com/rerank/"}],"last_updated":"May 5, 2023","subtitle":"","title":"what i read this week (apr 30)"}