Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.
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How FOMO Is Turning AI Into a Cybersecurity Nightmare
Every CEO I meet thinks their AI strategy is simple: implement tools, boost productivity, and stay competitive. The reality ...
Booked big gains in silver miners and now stepping aside as silver’s parabolic rally risks a 20–30% pullback. Click for this ...
In 2025, misconceptions about AI flourished as people struggled to make sense of the rapid development and adoption of the ...
anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...
Morning Overview on MSN
Math team solves cellular 'noise' puzzle, unlocking better treatments
Cells live in a world of chaos, constantly buffeted by random molecular jolts that can derail even the most carefully tuned ...
Children and parked cars are color-coded on a monitor inside a Mercedes-Benz S-Class during an autonomous driving and AI demonstration in Immendingen, Germany on July 17, 2018. In 2025, misconceptions ...
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Morning Overview on MSNOpinion
After 40 years, Sebestyen’s theorem breaks past old math limits
For four decades, a quiet boundary in pure mathematics kept a powerful theorem locked inside the safe world of finite quantities. Now a new result known as Sebestyen’s theorem has pushed that boundary ...
This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
Abstract: A two-terminal memristor device is a promising digital memory for its high integration density, substantially lower energy consumption compared to CMOS, and scalability below 10 nm. However, ...
Objectives This study assessed whether a previously developed Monte Carlo simulation model can be reused for evaluating various strategies to minimise time-to-treatment in southwest Netherlands for ...
Abstract: Neural networks (NNs) are effective machine learning models that require significant hardware and energy consumption in their computing process. To implement NNs, stochastic computing (SC) ...
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