Brandon Smock @deepsmock
Research Scientist, Machine Learning Seattle, WA Joined January 2018-
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An LLM’s understanding of text, built through modeling word relationships, might approximate real text and real word relationships very closely. But it’s not because an LLM understands the meaning of individual words. *This* meaning is essentially impossible for it to infer.
The consequence is that LLMs produce words without understanding any of their *individual* meanings.
Large language models, trained purely on text to predict the next word (token), are not taught the meaning of any individual word—nor do they learn it.
Kensho just released PubTables-v2 on Hugging Face The first large-scale dataset for multi-page table extraction with 135k+ cropped tables, 548k+ full-page tables, and 9k+ documents
More than 4 years after the release of PubTables-1M, PubTables-v2 is finally here! Among the highlights: this is the first dataset for document table extraction containing thousands of multi-page tables, some spanning up to 13 pages!
Announcing PubTables-v2: a first-of-its-kind large-scale dataset of 500k+ tables empowering end-to-end document AI. Annotates tables spanning multiple pages, unlocking deeper doc context for model training. Dive in and download: blog.kensho.com/introducing-pu… #DocumentAI #VLM #OpenData
This is achieved via prompting in natural language, which provides a way to interpolate new tasks in between tasks the model has previously seen. While still a shallow form of generalization, this has undoubtedly been a massive leap in the capabilities of these models.
In deep learning today generalization is powered by interpolation. Before LLMs, generalization was constrained to handling novel input for a single narrowly-defined task. The true breakthrough of LLMs in deep learning was to generalize beyond new inputs to entirely new *tasks*.
@tdietterich @ylecun @Michael_J_Black This is exactly how I remember it, as well. As someone who has always been a huge fan of Yann and his work, his consistent distortion and/or misunderstanding of the backlash to Galactica’s own overhyped claims has been painful to read.
Looking forward to #CVPR2024 in Seattle! If you’re attending, reach out and let’s grab ☕️. My team at Kensho is hiring a new grad MLE for visual document understanding. We don’t have a booth this year but if you track me down I have some free Kensho swag to hand out. 🧢✍️🛍️
Today we released the weights for three new pre-trained Table Transformer (TATR) models, for recognizing and extracting data from tables in unstructured documents. Check them out here: github.com/microsoft/tabl… #icdar2023
@rubenaros Gracias! I think you might be the first person to have discovered the updates coming soon to the main GitHub repository 🙂
@fchollet François, your clarity of thought and willingness to share in resistance to hype and groupthink is unmatched and immensely valuable. Thank you.
#PRESS Novo Nordisk and Microsoft collaborate to accelerate drug discovery and development using big data and artificial intelligence.
@fchollet Mine just arrived today, I’ll need a few days to read it first 😉
We are excited to announce our work “PubTables-1M: Towards comprehensive table extraction from unstructured documents” has been accepted at #CVPR2022! @RohithPesala Paper, code, and data are all publicly released: github.com/microsoft/tabl…
PubTables-1M: a large-scale dataset consisting of ~1 million tables from PubMed Central Open Access scientific articles. Can be used for training/evaluating machine learning models for the tasks of table detection, table structure recognition, and more. paperswithcode.com/dataset/pubtab…
ramie @yapramie
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Seth Ebner @_t_sne
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KIDS @KIDs66951395
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のぶ｜メディカ... @1n2Ml5SQK4WXO77
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WACV @wacv_official
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DailyPapers @HuggingPapers
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Andrew M. Dai @AndrewDai
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Docugami @docugami
599 Followers 124 Following Generative AI for Business Documents. Designed to provide immediate value for front-line business users and managers, across all segments.
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clem 🤗 @ClementDelangue
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LlamaIndex 🦙 @llama_index
122K Followers 39 Following Turn any doc into AI-ready context. The AI research lab for document parsing and extraction. Developer-first APIs. LlamaParse: https://t.co/yQGTiRSfFL
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Sara Hooker @sarahookr
65K Followers 12K Following Building intelligence that evolves @adaption_ai. Built @Cohere_Labs, @GoogleBrain, @GoogleDeepmind. ML Efficiency, Multimodal\lingual.
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18K Followers 1K Following Peter Lee retired as President, Microsoft Science. Today he advises on AI to health & life sci orgs, as well as to the Mercedes-AMG Petronas Formula One Team.
Sasha Luccioni, PhD �... @SashaMTL
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ICDAR2023 @icdar2023
183 Followers 0 Following The 17th International Conference on Document Analysis and Recognition. Held in San Jose, California, USA from August 21-26, 2023.
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