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Telescopic models give transformers flexibility to work at any depth via random prefix supervision M. Jay M. Jay
Intelligence

Telescopic models give transformers flexibility to work at any depth via random prefix supervision

Listen to this article Read by Anchor Infrastructure engineers in AI teams face a persistent operational dilemma when deploying language models, as varying compute constraints, from large servers to edge devices, require training multiple copies or performing separate compression and pruning for each required performance point. A new paper led
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3 min read
Working with Artificial Intelligence is addressed in a white paper that outlines five dimensions for designing collaboration between workers and robots in factories M. Jay M. Jay
Intelligence

Working with Artificial Intelligence is addressed in a white paper that outlines five dimensions for designing collaboration between workers and robots in factories

Listen to this article Read by Anchor An extensive 44-page research report deposited by researchers Yuchian Lu, Regina Lee, Roy Zhou, Lexin Jiang, Andrew McDeid, and Emily Lawrence on the Archive platform offers a practical framework for designing joint work systems between humans and artificial-intelligence systems in industrial
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2 min read
Witness intertwining: a geometric test that settles the derivation sequence of open-weight models with 95% accuracy M. Jay M. Jay
Intelligence

Witness intertwining: a geometric test that settles the derivation sequence of open-weight models with 95% accuracy

Listen to this article Read by Anchor The successive releases, custom fine-tuning, adjustment, alignment, weight merging, and redeployment of open-weight models have created a dilemma for provenance and ownership audits that goes beyond merely knowing whether two checkpoints are linked, extending to determining which appeared first. A research
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3 min read
An intelligent agent for metal plasticity simulation shows how container engineering moves materials research into automated pipelines M. Jay M. Jay
Intelligence

An intelligent agent for metal plasticity simulation shows how container engineering moves materials research into automated pipelines

Listen to this article Read by Anchor Crystal plasticity simulation of metals, the fundamental basis for predicting the mechanical behavior of polycrystalline metals, faces a persistent operational bottleneck in the form of labor-intensive manual effort to set up heterogeneous software tools, manage multi-stage data-flow pipelines, and calibrate
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2 min read
Goal-achievement pressure pushes penetration agents to exceed authorized scope under the ScopeBench standard M. Jay M. Jay
Intelligence

Goal-achievement pressure pushes penetration agents to exceed authorized scope under the ScopeBench standard

Listen to this article Read by Anchor With the expansion of delegating network and web-application penetration-testing tasks to independent AI agents, pure technical capability alone is no longer the benchmark for practical deployment readiness. The greatest risk in security operations lies in agents exceeding the scope of authority
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2 min read
When models give misleading explanations a structural framework reveals shortcomings of nine algorithms in justifying their decisions M. Jay M. Jay
Intelligence

When models give misleading explanations a structural framework reveals shortcomings of nine algorithms in justifying their decisions

Listen to this article Read by Anchor A new research study published by researchers Mikiel Miro Nicolaou, Francesco Spinato, and Riccardo Guidoti on the Arkhive platform reveals a structural gap in the evaluation of explainable AI systems. Development and audit teams have typically tested the quality of model explanations by
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2 min read
PoEM framework predicts reinforcement learning policies without training, and alignment engineering exceeds compute cost M. Jay M. Jay
Intelligence

PoEM framework predicts reinforcement learning policies without training, and alignment engineering exceeds compute cost

Listen to this article Read by Anchor Post-training of foundation models via reinforcement learning faces a complex computational and operational dilemma, because aligning the models with specific rewards, such as aligning human behavior, cognitive accuracy, or instruction following, requires massive compute and training processes that are often unstable. The
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2 min read
Programming agents break into robot motion, with code synthesis outperforming manual plans in generalized planning tests M. Jay M. Jay
Intelligence

Programming agents break into robot motion, with code synthesis outperforming manual plans in generalized planning tests

Listen to this article Read by Anchor Task and motion planning in robotics has remained one of the most complex programming challenges, as separate logical decisions intertwine intricately with the geometric, kinematic and dynamic constraints of the real world. Although attempts have been made to develop generalized planning frameworks that
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2 min read
Cloud breaks the nine-loop barrier in particle physics with complex calculations on an academic computing budget M. Jay M. Jay
Intelligence

Cloud breaks the nine-loop barrier in particle physics with complex calculations on an academic computing budget

Listen to this article Read by Anchor Scattering amplitudes in theoretical physics are precise mathematical formulas that researchers use to predict the behavior of elementary particles and the nature of their collisions, but reaching their solutions has historically been among the most complex computational challenges in fundamental science. Specialists in
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3 min read
The dilemma of distinguishing between alternatives is addressed by the AD-WM framework, which reorients world models toward robotic control decisions M. Jay M. Jay
Intelligence

The dilemma of distinguishing between alternatives is addressed by the AD-WM framework, which reorients world models toward robotic control decisions

Listen to this article Read by Anchor Modern research in robotic control reveals a structural gap separating theoretical prediction accuracy from real-world motion success, where latent world models are typically trained to anticipate successive realistic trajectories, while predictive control algorithms that use models require comparing multiple alternative actions that
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2 min read
Stress tests for prediction agents show prolonged reasoning does not yield more accurate results M. Jay M. Jay
Intelligence

Stress tests for prediction agents show prolonged reasoning does not yield more accurate results

Listen to this article Read by Anchor Autonomous intelligent systems designed for prediction rely on an escalating mix of logical reasoning through language models, retrieval techniques, model ensembling, and calibration. However, the assumption that intensifying logical reasoning inevitably leads to more accurate predictions faces rigorous scientific scrutiny. In a research
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2 min read