I mean, I get it. But seriously, do you honestly assume google won’t touch all the data they own on their platform? Even OpenAI used it hat time, just remember Mira murati in the interview when asked how they trained sora
DATA
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AI tool enables rapid screening for multiple systemic diseases using retinal photos
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“The [AI] tool presented here will enable rapid screening for multiple systemic diseases using retinal photographs, and it is a step forward in the evolution of oculomics from experimental research to real-world clinical practice.” —Editorial Team, @NatureMedicine
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Data Quality as the Foundation for AI Project Success
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47% of failed AI projects trace back to bad data. Not the model. Not the team. The foundation. Our 2026 State of Data Analysts report explains why ROI stays out of reach. Read it: https://
ow.ly/UiUH50Z1guU -
Hugging Face launches real-world open-source AI hardware stats
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What hardware actually powers open-source AI? Not benchmarks.
Not vendor marketing.
Real-world community usage. We’re launching @huggingface Hardware:
→ trending GPUs & CPUs
→ VRAM distribution
→ inference hardware trends
→ what the OSS AI ecosystem really runs on -
Closing the industrial data gap for AI operations
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Most industrial AI data was scraped from the internet, not from boats, cars, or plants actually running. That context gap is exactly what MQTT-based platforms like Coreflux are racing to close before AI can act on real operational data. #coreflux_ai pic.twitter.com/6FdXX05yZB
— Lucian Fogoros (@fogoros) 20 mai 2026Most industrial AI data was scraped from the internet, not from boats, cars, or plants actually running. That context gap is exactly what MQTT-based platforms like Coreflux are racing to close before AI can act on real operational data. #coreflux_ai
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Mathematical Methods in Data Science and Machine Learning
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Mathematical Methods in Data Science — Bridging Theory and Applications with Python: http://
amzn.to/4b7ZYQ4
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#ML #MachineLearning #DataScientist #DataScience #Mathematics #AI #Algorithms -
Who controls AI infrastructure and data? Dell AI Factory
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One of the biggest enterprise AI questions right now is simple: who controls the infrastructure and the data? That’s why this matters. Bringing @MistralAI models into the Dell AI Factory with NVIDIA gives enterprises more control over how they train, deploy, and scale AI without
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LandingAI Launches ADE Classify API for Intelligent Document Processing
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Stop parsing documents you don't need! LandingAI just released ADE Classify, a page-level classification API that sits before your parser. It labels every page in a document so you only parse what matters. The problem: Enterprise workflows get mixed bundles. A 50-page mortgage
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IndiaAI Launches Data Annotation Course for AI Skill Development
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Behind every AI model is annotated data. Data annotation is what helps AI understand the world. The IndiaAI Data Annotation Course introduces learners to the skills powering modern AI systems through hands-on learning and industry-focused training. Know more about IndiaAI Data
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Scaling AI from 80s to 2000s: Compute Not Enough
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Danny Hillis was scaling up AI with a massively parallel supercomputer in the 80s. In the 90s we had the data mining explosion, a.k.a. scaling up ML. In the 2000s we had the "big data" boom. And each time we noticed that no, compute etc. is not enough – you really need better