Edge-Computing

TL;DR Most multi‑agent LLM frameworks still rely on a central organizer that becomes expensive, rigid, and a single point of failure. Symphony proposes a fully decentralized runtime—a capability ledger, a beacon‑based selection protocol, and weighted Chain‑of‑Thought (CoT) voting—to coordinate lightweight 7B‑class models on consumer GPUs. In benchmarks (BBH, AMC), Symphony outperforms centralized baselines like AutoGen and CrewAI, narrowing the gap across model quality and adding fault tolerance with ~negligible orchestration overhead. ...

In the race to conquer time-series classification, most modern models have sprinted toward deeper Transformers and wider convolutional architectures. But what if the real breakthrough came not from complexity—but from symmetry? Enter PRISM (Per-channel Resolution-Informed Symmetric Module), a model that merges classical signal processing wisdom with deep learning, and in doing so, delivers a stunning blow to overparameterized AI. PRISM’s central idea is refreshingly simple: instead of building a massive model to learn everything from scratch, start by decomposing the signal like a physicist would—using symmetric FIR filters at multiple temporal resolutions, applied independently per channel. Like a prism splitting light into distinct wavelengths, PRISM separates time-series data into spectral components that are clean, diverse, and informative. ...

If you’ve ever tried to run a powerful AI model on a modest device—say, a drone, a farm robot, or even a Raspberry Pi—you’ve likely hit the wall of hardware limitations. Today’s most accurate models are big, bloated, and brittle when it comes to efficiency. Enter knowledge grafting, a refreshingly biological metaphor for a novel compression technique that doesn’t just trim the fat—it transfers the muscle. Rethinking Compression: Not What to Cut, But What to Keep Traditional model optimization methods—quantization, pruning, and distillation—all try to make the best of a difficult trade-off: shrinking the model while limiting the damage to performance. These methods often fall short, especially when you push compression past 5–6x. ...