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Data For Science
Technology, Information and Internet
New York, NY 386 followers
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About us
A weekly newsletter with the latest developments in Data Science and Machine Learning and Artificial Intelligence.
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http://www.data4sci.com
External link for Data For Science
- Industry
- Technology, Information and Internet
- Company size
- 1 employee
- Headquarters
- New York, NY
- Type
- Privately Held
- Founded
- 2019
Locations
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Primary
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New York, NY 10280, US
Employees at Data For Science
Updates
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[2603.21687] MIRAGE: The Illusion of Visual Understanding Worth a quick read if you work with vision-language models: MIRAGE argues that apparent “visual understanding” can be an illusion driven by shortcuts, and it’s a useful lens for evaluating benchmarks and model behavior. https://lnkd.in/eKgyihtM
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MIRAGE: The Illusion of Visual Understanding https://lnkd.in/eKgyihtM
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Safeguarding cryptocurrency by disclosing quantum vulnerabilities responsibly A practical look at how to handle quantum-related risks in crypto without causing unnecessary panic—focused on responsible disclosure and coordination. Useful context for anyone tracking post-quantum timelines and mitigation planning. https://lnkd.in/emz3sEgC
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[2603.14147] An Alternative Trajectory for Generative AI A thoughtful arXiv paper arguing for a different path for generative AI than the current scale-and-scrape trajectory. Useful if you’re tracking where the field could go next—technically and institutionally. https://lnkd.in/eJH_wpJB
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An Alternative Trajectory for Generative AI https://lnkd.in/eJH_wpJB
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[2603.26524] Mathematical methods and human thought in the age of AI Thoughtful arXiv essay on how AI is reshaping mathematical practice and, more broadly, how we think—useful if you’re trying to separate genuine insight from automated fluency. A quick read with good prompts for researchers and educators. https://lnkd.in/ekPXC5u5
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Mathematical methods and human thought in the age of AI https://lnkd.in/ekPXC5u5
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[2303.07103] Could a Large Language Model be Conscious? A clear, careful look at what it would even mean to call an LLM “conscious,” and which assumptions you’d need to defend. Useful for separating philosophical claims from testable questions about model behavior and architecture. https://lnkd.in/gTsHFQ99
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Could a Large Language Model be Conscious? https://lnkd.in/gTsHFQ99