5/ The team released open catalogs so any researcher can pick targets for follow-up with ground telescopes and ESA's upcoming PLATO mission. AI is no longer just assisting astronomers. It is becoming the primary discovery engine for mapping the galaxy's planetary architecture.
MACHINE LEARNING
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RAVEN AI Pipeline Validates 118 Planets from TESS Mission Data
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3/ Enter RAVEN: an AI pipeline trained on hundreds of thousands of simulated planets and fake signals. It detects, vets, and confirms candidates in one go. Result: 118 validated planets, 31 brand new, and over 2,000 strong candidates from TESS mission data.
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AI Discovers 100+ Hidden Planets in NASA Star Data
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1/ Holy: Astronomers just pointed an AI at NASA data from 2.2 million stars. It found over 100 hidden planets, including worlds so extreme they shouldn't even exist according to current theory. I love it. Lets break it down and explain what it means :
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Retracted AI Education Paper Prompts Discussion of Meta-Analyses
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My surprise here seems warranted, this paper was retracted (There are other peer-reviewed meta-analyses of the impact of AI on education finding positive effects, like: https://
researchgate.net/publication/38
7110151_The_effects_of_GenAI_on_learning_performance_A_meta-analysis_study
… though the best evidence of AI helping is from RCTs of interventions with AI tutors) -
Skills Needed to Successfully Program with AI
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What skills do people need to successfully program with #AI?
by Christoph Elhardt @TechXplore_com Learn more: https://
bit.ly/3QyG6zj #ArtificialIntelligence #ML #MachineLearning -
SHAPE Method Rewards Reasoning Progress Over Verbosity in LLMs
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What if LLMs could reason smarter, not just longer? Researchers from Huawei Taylor Lab, Peking University, and Shanghai University of Finance and Economics introduce SHAPE. The method rewards actual progress in reasoning — not verbosity — by using a two-level system: a
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Models Become Components: What Turns Agents Into Systems
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My biggest takeaway: Models are becoming components, not products. What matters now is the system around them: → runtimes
→ memory
→ tool access
→ orchestration
→ secure execution environments That is what turns a model into an agent, and an agent into something the -
Proposing real-world benchmarks for medical AI models
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We need more real-world benchmarks for models. Saying that a model scored "87.4% on the MMLU AQuA-RAT" is useless for anyone who's not a researcher. How about we test for: -ER diagnosis (accuracy + time)
-Radiology reads (scan → diagnosis)
-ICU management (decisions → -
Gemini’s Performance Floor Drops Consistently on Bad Runs
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The floor dropping that hard on bad runs is Gemini's specific problem and it's been consistent across versions.
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Brain Decoding from MEG Signals Using Deep Learning for Semantic Language
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A Coding Implementation of Brain Decoding from MEG Signals Using NeuralSet and Deep Learning for Predicting Semantic Language! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang