NTN applies AI and machine learning to accelerate bearing design, cut analysis time and reduce engineering workload.
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
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Machine learning lends a helping 'hand' to prosthetics
Holding an egg requires a gentle touch. Squeeze too hard, and you'll make a mess. Opening a water bottle, on the other hand, ...
In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...
AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...
As organizations plan for 2026, a clear structural shift is emerging in how technical talent is valued and deployed. Amid this shift, Interview Kickstart has introduced an advanced machine learning ...
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Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
In 1854, London was struck by a devastating cholera outbreak. Public authorities responded using the best tools and scientific understanding available at the time.Disease was widely believed to spread ...
Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
AI makes work faster, but the advantage comes from learning enterprises that sense, decide, and adapt more quickly — turning speed and insight into real results.
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