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I Used AI for Everything for 30 Days. Here’s What Nobody Told Me.
I let artificial intelligence help me work, write, plan, learn, and make decisions for an entire month. By Day 30, the biggest surprise Continue reading on Medium »
KVBoost: Chunk-Level Key-Value Cache Reuse with Deviation-Guided Recomputation for Efficient Large Language Model Inference
arXiv:2608.21362v1 Announce Type: new Abstract: Transformer-based large language models (LLMs) incur high prefill latency because key-value (KV) tensors must be recomputed for each request. Existing prefix-caching systems reduce this cost but require prompts to share a leading contiguous prefix, limiting effectiveness when shared content appears at arbitrary positions. We present KVBoost, a chunk-level KV cache reuse system for HuggingFace-compatible decoder models that enables reuse regardless of content position. KVBoost introduces a dual-hash keying scheme that separates positional identity (prefix hash) from content identity (content hash), supporting both exact and approximate cache matches. To address attention boundary errors from independently cached chunks, KVBoost employs two repair strategies: SelectiveRecompute, which re-encodes boundary regions, and CacheBlendRecompute, which identifies and recomputes high-deviation tokens after a probe pass. The system further incorporate
AIREP: A Protocol for Per-Decision Evidence in AI Runtime Governance
arXiv:2608.21363v1 Announce Type: new Abstract: A protocol is presented for recording the governance decisions of automated AI runtimes. When a runtime releases, blocks, defers, redacts, or escalates an individual output, AIREP records that decision as a single signed object that any party can check offline, independent of the runtime that produced it. A record carries the decision as one of a closed set of verbs under a stated policy basis, references its input, output, and evidence by hash rather than by value, and declares both what its evidence covers and what it does not. Records form a SHA-256 hash chain that binds each record to its position, so that tampering and gaps are detectable by recomputation. Vendor-, model-, and domain-specific content is confined to a single optional namespace, and a mechanical neutrality test keeps the shared format free of it. A reference implementation and a two-language conformance kit are described. Some implementation issues are considered, and
Multimodal-Language-Model-Driven Interaction and Companionship for Service Robots in Elderly-Care Facilities
arXiv:2608.21387v1 Announce Type: new Abstract: Service robots are increasingly deployed in elderly-care facilities to alleviate caregiver workload and enhance the quality of daily care. However, most existing studies focus on isolated service functions and lack integrated capabilities for continuous companionship, natural interaction, and safety monitoring. In this paper, we present an intelligent companion robot system that unifies active visual human-following, real-time LLM-driven speech interaction for intent understanding and task execution, and VLM-based safety monitoring for fall detection and abnormal posture assessment. The perception layer ensures robust human tracking and uses an active gimbal to maintain the user in view during occlusions or abrupt movements. At the interaction layer, a Large Language Model interprets spoken requests and maps them to robot actions, enabling escorting and semantic navigation. Simultaneously, a VLM-based safety agent continuously analyzes vi
RoboShape: Information-Theoretic Point Cloud Representations for Privacy-Aware Robot Perception
arXiv:2608.21380v1 Announce Type: new Abstract: With the increased adoption of robotic agents operating in human environments by scanning and sharing 3D representations (e.g., for fleet learning, cloud-based planning, or collaborative mapping), collected point clouds reveal not just the objects in a scene but also sensitive spatial context, such as room function or information that occupants never consented to disclose. Traditional point cloud encoders offer no principled control over this: either all is preserved, or none. Hence, we introduce RoboShape, an information theory guided compression head following the frozen {\tt Sonata} encoder. We project voxel-level embeddings using the Donsker-Varadhan formulation of mutual information (MI). Specifically, we maximize the MI between embeddings and object-level understanding while minimizing it for private attributes. RoboShape leads to 87.5\% smaller embeddings that retain 98.7\% of object classification utility while collapsing sensitiv
Why Robot Deployment Hours Matter More Than Viral Demos
Some of the most impressive robotics videos today only last a few minutes. A humanoid might fold clothes, organize objects, work in a Continue reading on Medium »
Why I Wrote 38,000 Lines of Code Instead of Paying $80/Year to [enter fitness app here]
The economics of on-device AI, the hidden cloud GPU tax, and why a calorie tracker shouldn t cost more per month than it costs forever.Continue reading on Medium »
India’s Airbound bags $37M to take on trucks with rocket-like drones
Airbound's ultra-lightweight approach to drone delivery has attracted backing from Greenoaks, DoorDash, and Silicon Valley investor Lachy Groom.
Your Company Does Not Need More AI Tools. It Needs a Path from Pilot to Production.
After years of working on digital products and enterprise systems, I keep seeing the same problem: companies are excited about AI, but Continue reading on Medium »
Ilya’s List #22 and #23, Part 4: The Overall Transformer Architecture
Hello all you Sutskevites.Continue reading on Ilya Sutskever’s 30 Foundational Papers of AI, Explained »
Situational Awareness, star AI hedge fund that nearly imploded, now being probed by the SEC
The AI hedge fund went from "the talk of Wall Street" to "subject of federal subpoenas" faster than you can say "diversify your portfolio."
AMT: Carrying Alan Mathison Turing’s Name Into a Modern Pulse‑Driven Operating System
In the history of computing, certain ideas never lose their relevance.Continue reading on Medium »