Steve Taplin, a Forbes Councils Member, writes that despite 80% AI adoption, software delivery has not gotten faster because of an "AI validation gap" — the absence of evaluation, measurement or trust…
U.S. states are enacting AI mental health laws, with a federal version in the offing, according to a Forbes Innovation analysis by contributor Lance Eliot. Eliot writes that one approach would be a "f…
Nvidia co-founder and chief executive Jensen Huang said there is a "0% chance" AI destroys the world by 2030, dismissing warnings from former Anthropic researcher Jacob Coxon that AI could become "sup…
Top US and Chinese officials held talks in New York on Sunday to discuss an AI safety plan ahead of a Trump-Xi summit this week, according to BBC Technology. The meeting precedes the summit between Pr…
The Financial Times published an opinion piece arguing that agentic AI in finance requires a regulatory approach distinct from the UK Financial Conduct Authority's existing rule book, warning that app…
Researchers introduced Elastic Threshold Attention (ETA), an end-to-end trainable sparse attention architecture that predicts dynamic, contextual thresholds from query representations to speed up long…
Researchers introduced Bio-MF, a latent-free one-step MeanFlow framework for EEG-conditioned fNIRS generation, detailed in arXiv paper 2609.20904v1. On Dataset 1, EEG plus synthetic fNIRS improved acc…
Researchers introduced Stiefel-AdamW, a near drop-in replacement for the AdamW optimizer that constrains one factor of linear factorization blocks to the Stiefel manifold, according to arXiv paper 260…
Researchers introduced EnSol, an environment-aware probabilistic graph neural network for molecular solubility prediction, which achieved Spearman correlations of 0.876 on the SolProp benchmark and 0.…
A new arXiv paper (arXiv:2609.21126v1) proposes a decoupled, layerwise method for structurally sparsifying the fully connected layers of pretrained neural networks, extracting shallow two-layer subnet…
A new neural network model for identifying text content file types, especially source code, is approximately four times faster than Google's Magika and 28% smaller in size, according to an arXiv paper…
MIRCID, a framework comparing gene expression with inferred transcription factor activity and miRNA expression, infers 414 pan-cancer hub miRNAs from 977 L1000 landmark genes with a Pearson correlatio…
Researchers released FairLMs, a Python library that unifies fairness measurement and mitigation for language models through explicit declarations of model capabilities and input requirements, accordin…
A new arXiv paper (2609.21309v1) surveys and formalizes strategies for using lossless compression algorithms such as gzip as machine learning methods, via Normalized Compression Distance or the Minimu…
A new arXiv paper (2609.21327v1) introduces Deep-BQRL, a model-free distributional reinforcement-learning framework that extends buffered-quantile learning to neural function approximation, learning c…
A new arXiv paper (2609.21425v1) argues that zero-shot time-series forecasting should be governed as an evidence-access claim rather than a training-status condition, since a frozen language model pro…
A new arXiv paper (2609.21382v1) presents a generative sequence model for business process forecasting that uses marked temporal point processes to produce full predictive distributions over the next …
A new arXiv paper (2609.21656v1) extends the analysis of Joint-Embedding Predictive Architectures (JEPAs) beyond Euclidean assumptions, showing that Gaussian uniqueness is not a universal property of …
Researchers introduced IncentRL, a reinforcement learning framework that adds a Kullback-Leibler penalty between a specified outcome distribution and a preferred distribution to guide training while b…
Researchers developed Row-wise Matrix AdaGrad (Row-AdaGrad) and Column-wise Matrix AdaGrad (Column-AdaGrad), matrix-aware adaptive optimization methods derived from an Online Mirror Descent framework …