Media Authenticity Methods in Practice: Capabilities, Limitations, and Directions
As synthetic media grows, verifying what’s real, and the origin of content, matters more than ever. Our latest report explores media integrity and authentication methods, their limits, and practical paths toward trustworthy provenance across images, audio, and video.
The post Media Authenticity Meth...
Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
arXiv:2602.16012v1 Announce Type: new
Abstract: Neural solvers have achieved impressive progress in addressing simple routing problems, particularly excelling in computational efficiency. However, their advantages under complex constraints remain nascent, for which current constraint-handling schem...
The Reasonable Effectiveness of Virtue Ethics in AI Alignment
Preface
This essay argues that rational people don’t have goals, and that rational AIs shouldn’t have goals. Human actions are rational not because we direct them at some final ‘goals,’ but because we align actions to practices[1]: networks of actions, action-dispositions, action-evaluation criteria...
Project Silica’s advances in glass storage technology
Project Silica introduces new techniques for encoding data in borosilicate glass, as described in the journal Nature. These advances lower media cost and simplify writing and reading systems while supporting 10,000-year data preservation.
The post Project Silica’s advances in glass storage technolog...
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
arXiv:2602.15159v1 Announce Type: new
Abstract: Learning from electronic health records (EHRs) time series is challenging due to irregular sam- pling, heterogeneous missingness, and the resulting sparsity of observations. Prior self-supervised meth- ods either impute before learning, represent miss...
Top 20 influential Chief AI Officers in the Silicon Valley area 2026
Silicon Valley continues to define the global AI agenda. In 2026, the region’s technology ecosystem is accelerating once again, home to multi-billion-dollar companies and many of the world’s most influential AI leaders. Are you ready?
Edge AI for start-ups: Why on-device intelligence is the future of MVPs
Startups no longer need massive cloud budgets to build intelligent products. By shifting AI from centralized servers to on-device processing, edge AI enables leaner, faster, and more privacy-conscious MVPs from day one.
How CVS Health continues to shape innovation in Boston
When people think about healthcare innovation in the US, Silicon Valley often gets the spotlight. But for decades, another ecosystem has been quietly getting on with the job of shaping the future of medicine and technology: Boston.
And right at the heart of that ecosystem sits CVS Health.
Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications
arXiv:2602.12338v1 Announce Type: new
Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications and computations, enabling efficient digital semantic- and goal-oriented communications in future wirele...
KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
arXiv:2602.11184v1 Announce Type: new
Abstract: Mixture of Experts (MoE) models have achieved great success by significantly improving performance while maintaining computational efficiency through sparse expert activation. However, their enormous parameter sizes and memory demands pose major chall...
Explaining AI Without Code: A User Study on Explainable AI
arXiv:2602.11159v1 Announce Type: new
Abstract: The increasing use of Machine Learning (ML) in sensitive domains such as healthcare, finance, and public policy has raised concerns about the transparency of automated decisions. Explainable AI (XAI) addresses this by clarifying how models generate pr...
On Decision-Valued Maps and Representational Dependence
arXiv:2602.11295v1 Announce Type: new
Abstract: A computational engine applied to different representations of the same data can produce different discrete outcomes, with some representations preserving the result and others changing it entirely. A decision-valued map records which representations ...
Faster Rates For Federated Variational Inequalities
In this paper, we study federated optimization for solving stochastic variational inequalities (VIs), a problem that has attracted growing attention in recent years. Despite substantial progress, a significant gap remains between existing convergence rates and the state-of-the-art bounds known for f...
arXiv:2602.10195v1 Announce Type: new
Abstract: A novel sequence architecture design is introduced, Versor, which uses Conformal Geometric Algebra (CGA) in place of the traditional fundamental non-linear operations to achieve structural generalization and significant performance improvements on a v...
Adaptive Optimization via Momentum on Variance-Normalized Gradients
arXiv:2602.10204v1 Announce Type: new
Abstract: We introduce MVN-Grad (Momentum on Variance-Normalized Gradients), an Adam-style optimizer that improves stability and performance by combining two complementary ideas: variance-based normalization and momentum applied after normalization. MVN-Grad sc...