I'd add that controlnet helps reign it in a bit
AI
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ArXiv Paper Withdrawal Raises Questions About Research Standards
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that's not what happens in this paper (also this is the first thing I've ever seen to be withdrawn from ArXiv, lol)
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OpenAI News Coverage and Regulatory Implications Analysis
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Like every other AI reporter, I’m also covering the @OpenAI news & related fallout. If you know stuff, have thoughts on the potential implications for companies beyond #openAI and/or ideas about how it could inform regulations, feel free to get in touch. (Signal is in my bio.)
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AI, IoT, and 5G Transform Workplace Opportunities and Efficiency
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#AI, #IoT, and #5G in the workplace will open up more opportunities than ever before. These new technologies have the power to make tasks faster, easier, cheaper, and more accurate than ever before. #FutureOfWork
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GroqChip Advantages and HPC Applications at Sorbonne University
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Join Ernesto Bonomi on Nov 22 at the @Sorbonne_Univ_ to hear about GroqChip™ advantages and use in the development of HPC applications from research to industry . #AI #DataAnalysis #HPC https://
scai.sorbonne-universite.fr/public/events/
view/7e264de87704e92cd47a/7
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NVIDIA Microsoft partnership launches AI foundry service Azure
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Our CEO Jensen Huang joined @Microsoft CEO Satya Nadella’s keynote at #MSIgnite to announce the companies’ expanding partnership and introduction of the NVIDIA AI foundry service on Microsoft @Azure
. Watch now: https://
nvda.ws/47I0JfH #AI -
OpenAI Reaffirms Developer Commitment Despite Uncertainty
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A note to @OpenAI developers : I wanted to express my appreciation for all the warm, thoughtful, and supportive messages I got and I’ve seen posted across the community. Despite a moment of uncertainty, our commitment to developers remained steadfast. In the meantime,
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Sony Leverages DataRobot AI on AWS to Accelerate Enterprise Value
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Sony Interactive Entertainment leverages DataRobot on @awscloud to accelerate time to value with AI. Next week at AWS re:Invent, we’re teaming up with Sony for a lighting session to share real-world insights into how DataRobot and AWS streamline processes, enhance
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Embedding to Text Reconstruction: Three-Step Technical Approach
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– step 1 can be implemented with any off-the-shelf embedder
– step 3 is solved with vec2text (
http://
github.com/jxmorris12/vec
2text
…)
– step 2 doesn't exist yet – some tasks might be solvable even with a simple embedding-to-embedding linear mapping if you're interested in trying this, DM me 🙂 -
Text Diffusion in Embedding Space for Sequence Tasks
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cool research idea for someone: text diffusion in embedding space solve any sequence-to-sequence task in three steps:
1. embed source sentence text
2. build diffusion model that maps input text embedding to target text embedding
3. invert to produce target text