AI
How can AI agents and developers find API and data services they can actually trust—especially when anyone can spin up fake identities to game the rankings? David Shi and Kevin Joo propose TraceRank for the x402 network, where services accept crypto payments for access. Instead of counting raw traffic,
AI
AI agents are getting good at coding and research, but they still struggle with long, domain-specific projects. Training them is hard: full-time human annotation is too costly, while pure trial-and-error rarely finds successful paths. Apollo is a new sampling framework that blends lightweight, asynchronous human guidance with strict action-level filtering.
AI
If your AI segments tumors, who is it serving—and who might it be failing? A new audit of the MAMA-MIA breast cancer segmentation dataset examines fairness not in classification, but in segmentation—the step that often feeds every downstream decision. * Researchers evaluated automated segmentation quality by age, ethnicity, and
AI
From doodle to design Imagine sketching a rough poster layout and instantly getting a polished version. That’s the promise of Sketch‑to‑Layout, a new approach that uses your sketch as the design guide. * How it works: A multimodal transformer takes your quick sketch plus content (text/images) and
AI
What's new Spiking Neural Networks (SNNs) mimic brain cells that communicate with brief spikes, not continuous signals. That makes them naturally energy-efficient and great at timing. * Surrogate-gradient training gets SNNs within 1-2% of standard ANN accuracy, converging by about 20 epochs with latency near 10 ms. * ANN-to-SNN conversion
AgenticAI
What is "Agentic AI" really? Sebastian Benthall and Andrew Clark argue it’s best seen as a software delivery mechanism—like SaaS—that lets an application work autonomously inside complex enterprises. * Applications first: Agentic AI systems should be judged as products, not as foundation models. * Validate with users: