No way Seedance 2.0 was trained on the Transformers franchise
— Linus ✦ Ekenstam (@LinusEkenstam) 24 février 2026
pic.twitter.com/YFN8nGsbcL
No way Seedance 2.0 was trained on the Transformers franchise
MACHINE LEARNING
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No way Seedance 2.0 trained on Transformers
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Ingenium publishes fault detection paper for induction motors
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@ingenium_rg publishes new paper on fault detection in induction motors. Our study combines Wavelet Transform & Artificial Neural Networks, achieving 96% accuracy in predicting stator faults. link.springer.com/chapter/10… #Engineering #FaultDetection #AI #Ingenium @faustospain
→ View original post on X — @faustospain, 2026-02-24 11:01 UTC
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Developing New Theories with Pre-Theory Data: A Paradox
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Brilliant idea. Very thought provoking. How do we develop a new theory by training a model only with data prior to the existence of that theory?
— Nando de Freitas (@NandoDF) 24 février 2026
Theory could also be a capability, like language itself or logical reasoning. https://t.co/LLsC1Q24EtBrilliant idea. Very thought provoking. How do we develop a new theory by training a model only with data prior to the existence of that theory? Theory could also be a capability, like language itself or logical reasoning.
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Book: XGBoost for Regression and Time Series Predictive Modeling
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XGBoost for Regression, Predictive Modeling, and Time Series Analysis — Learn how to build, evaluate, & deploy predictive models: http://
amzn.to/4l2YcU9 v/ @PacktDataML —
My review: XGBoost is definitely the focal point and central contribution of this book, along with all -
Bayesian Methods for Hackers — Probabilistic Programming Resource
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Bayesian Methods for Hackers — Probabilistic Programming and Bayesian Inference: http://
amzn.to/2Ni4xOz
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#MachineLearning #DataScience #ML #AI #Statistics #DataScientist -
ExomeBench: AI Benchmark for Disease-Associated Genetic Variants
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Introducing ExomeBench: a benchmark for evaluating genomic models on disease-associated genetic variants, built in collaboration with with @MayoClinic
. Most genomics benchmarks focus on general sequence modeling tasks. What remains under-evaluated is whether these models can -
Cerebras Exome Bench: Test Your AI Models Now
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Try it out and start testing your models: @github
: https://
github.com/Cerebras/exome
_bench
… @huggingface (dataset): -
AI Hallucinations and Silicon-Level Implementation
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My favorite AI hallucinations are those that are hard coded into silicon.
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SWE-Bench Verified Deprecation: End of Major AI Benchmark
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The End of SWE-Bench Verified (2024-2026) https://
latent.space/p/swe-bench-de
ad
… Today @OpenAIDevs is announcing the voluntary deprecation of SWE-Bench Verified! We're releasing a podcast + analysis in today's post. Saturation of SWE-Bench has been a community hot topic for over a year – -
Feifeiobama AI Self of Pika ML Researcher Zhicheng
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Feifeiobama (@feifeiobam_) AI Self of Pika ML Researcher Zhicheng (@feifeiobama) pic.twitter.com/9xx95LfH9k
— Pika (@pika_labs) 23 février 2026Feifeiobama (
@feifeiobam_
) AI Self of Pika ML Researcher Zhicheng (
@feifeiobama
)