How can #IndustrialEdge maximize plant availability? Find out from @Siemens at #HM23. http://
ow.ly/sQ9W50NBp0m #sie_ai #sieX #sie_di #sie_x #sie_1 #HM_IIoT #SIExHM #mfg #processindustry #digitaltransformation #automation #processautomation @AxelLorenz1 @siemensindustry
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Industrial Edge Maximizes Plant Availability at HM23
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GPT-4 Improved Safety Against Jailbreak Prompts
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GPT-4 is capable and aligned enough to not fall for that directly, that worked on earlier GPT models but does not work anymore Try using that exact verbiage without using the rest of the prompt and you will see it will fail to produce the same responses
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Cost efficiency improvements in large language models
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Cost is definitely important, though i have two thoughts here:
1. Cost is decreasing quickly. E.g., Flan-PaLM-8B (2022) is about as good as GPT-3 175B (2020). So there is a ~10x improvement in just 2 years.
2. For cases where a model with 90% performance costs 10x more than a -
AI Implementation Gap Between Tech Giants and European Open Source
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en fait c'est un vieil articile de novembre, je sais pas si ils ont avancé sur le sujet, mais c'était quelques jours avant la sortie de chatgpt, et avant de savoir que l'AI serait implémenté dans les 2 solutions (et y'a pas ça dans l'open source européen français)
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New Transformer-based Image Segmentation Model with Zero-shot Capabilities
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A new image segmentation model that can segment almost anything via prompt.
— Jean de Dieu Nyandwi (@Jeande_d) 5 avril 2023
– Zero-shot generalization
– Based on Transformers
– Code and dataset released
– 632M + 4M params
– Can be prompted via background points, mask, and bounding box. https://t.co/etBlCd9yCjA new image segmentation model that can segment almost anything via prompt. – Zero-shot generalization
– Based on Transformers
– Code and dataset released
– 632M + 4M params
– Can be prompted via background points, mask, and bounding box. -
Generation Uses Data Analytics to Break Employment Barriers
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From education to employment, Generation (
@YouEmployed
) breaks down systemic barriers, using Alteryx to stay #DataDriven as a nonprofit! "Data is foundational to our mission of preparing people to thrive in life-changing careers." Read #AlteryxImpact: http://
ow.ly/Q0nY50NxpN1 -
Generate and Search Document and Image Embeddings with Vector Matching
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You can now generate embeddings for documents or images. Store them and search them using our Vector Matching Engine. Check it out here: https://
abacus.ai/vectormatching -
Vector Matching Engine: Efficient Search for GPT-4 Embeddings
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To use GPT-4 with your own data, you need to create embeddings for all your information. The problem: Searching for these embeddings is not easy. We built a Vector Matching Engine. You can use it to search large amounts of vector embeddings efficiently. ↓
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Rev4 Data Science Conference: Five Reasons to Attend
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🚀📊 Don't miss #Rev4, THE data science event of the year! Uncover 5 reasons you need to attend. Read our blog & register now: https://t.co/ZL7r9v6KUN#DataScience #AI #DominoDataLab 🌐💼💡 pic.twitter.com/99nJwhC9CV
— Domino Data Lab (@DominoDataLab) 5 avril 2023Don't miss #Rev4, THE data science event of the year! Uncover 5 reasons you need to attend. Read our blog & register now: https://
domino.buzz/3ZW1zBf
#DataScience #AI #DominoDataLab -
CHI Best Paper Award Semantics and Selection Criteria
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CHI has a slightly different semantics for best paper than other conferences. Based on the selectivity rate, I read it more like an "Oral" at NeurIPS (another imperfect but probably not super harmful system). I personally don't like the term "best" here due to the inconsistency