Agent confidence on the technical frontier

Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial…

Source: MIT Technology Review

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The Lab Mistake That Might Revolutionize Computing

Today, you probably asked a question of a large language model, or accepted a connection suggestion on LinkedIn, or watched a recommended video on YouTube, or took a different route to work based on a traffic prediction from Google Maps. In other words, you probably…

Source: IEEE Spectrum

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The Download: metric weaknesses and AI elephant warnings

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The inevitable weakness of metrics There are plenty of useful things a metric can reveal. There are even more that it…

Source: MIT Technology Review

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On the Position Bias of On-Policy Distillation

arXiv:2606.22600v3 Announce Type: replace-cross Abstract: On-Policy Distillation (OPD) improves the learning efficiency of standard reinforcement learning through dense, token-level supervision from teachers. In the standard KL objective of OPD, token-level losses are uniformly averaged, implying equal weights for all tokens. However, we discover that not…

Source: cs.AI updates on arXiv.org

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The Remittance Blueprint: Data-driven Intelligence for Sri Lanka

arXiv:2606.28190v1 Announce Type: cross Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data analysis, stationarity corrected time-series modeling (ADF, Johansen, VAR/VECM), and supervised learning. Results reveal remittance inflows are primarily driven by…

Source: cs.AI updates on arXiv.org

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Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting

arXiv:2602.01588v3 Announce Type: replace-cross Abstract: Multimodal time series forecasting is crucial in real-world applications, where decisions depend on both numerical data and contextual signals. The core challenge is to effectively combine temporal numerical patterns with the context embedded in other modalities, such as text. While…

Source: cs.AI updates on arXiv.org

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ConlangCrafter Turns AI to Imagining Languages

There are over 7,000 natural languages today, but that doesn’t stop people from occasionally making up completely new ones. These constructed languages, or conlangs, include Dothraki, Klingon, and various Elvish languages. Now, an AI model called ConlangCrafter is also capable of generating new languages—and it…

Source: IEEE Spectrum

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