Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer Hardware
arXiv:2608.00008v1 Announce Type: new
Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, the energy costs on consumer hardware remain poorly characterized, as most benchmarks focus solely on ac...
CoT-Core: Accelerating LLM Evaluation via CoT-Aware Coreset Selection
arXiv:2608.00014v1 Announce Type: new
Abstract: Evaluating Large Language Models (LLMs) incurs prohibitive computational overhead during continuous development processes. While coreset selection accelerates evaluation, existing methods either suffer from a severe ``cold start'' bottleneck requiring...
Genspark Open Sources GenOffice: A Free, Ad-Free AI Office Suite for macOS and Windows with Docs, Sheets, Slides, PDF
Genspark has open sourced GenOffice under the Apache License 2.0. It is an AI-native office suite for macOS and Windows, covering Docs, Sheets, Slides and PDF as five Electron apps over one shared engine layer. The notable engineering claim is a byte-preserving round trip: only edited paragraphs are...
Open-Weight Models Aren’t Enough. We Need Truly Open Source AI Models for Science and Society.
As Chinese AI closes the capability gap, Washington and Silicon Valley debate open-weight models. Stanford HAI's James Landay says it's the right conversation framed the wrong way.
AI Weekly Issue #518: The White House finished its AI safety framework. It's secret.
Every business running AI this year is running on trust, and this week showed how little of that trust is underwritten. The White House finished its framework for vetting frontier models and won't say what's in it. The law still has no answer for an AI agent that breaks into a company on its own, wh...
Evaluating Multimodal Vision Models with Moonshot PerceptionBench Using Robust Data Loading and Automated Judging
In this tutorial, we design an end-to-end evaluation workflow for PerceptionBench. This multimodal benchmark measures fine-grained visual perception capabilities across tasks such as OCR, counting, localization, contextual reasoning, comparison, depth understanding, and hallucination detection. We b...
AWS is helping vibe-coding startup Superblocks, and the implications are big
AWS now allows vibe coding tool Superblocks to be embedded into the private clouds of AWS customers. It's another step towards decoupling apps from models.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Humanoid robots usually elicit more cringe than awe: They stumble, kick children, and despite advances are still worse at using their hands than my toddler. It’s ...
House spending records show OpenAI's ChatGPT dominates paid AI use on Capitol Hill, with congressional offices relying on the chatbot to draft memos, summarize legislation, and assist constituent communications.
Prompt, Context, Loop: The Three Engineering Layers Every RAG System Is Built On
Enterprise Document Intelligence [Vol.1 #M2] - Every RAG system is built in three engineering layers stacked on one LLM call: prompt (the call itself), context (what fills the model’s window), loop (when the next call fires and when it stops). Knowing which layer you are standing on is half of build...
Read about MiniMax's own architecture, and see how it runs a real task against the actual API. Learn the pieces of the MiniMax story that weren't covered in the launch post.
Orchard: An open framework for scalable agentic AI
Orchard is an open-source framework for the research community to train and evaluate AI agents across task types. It reduces complexity while supporting strong performance from smaller models by enabling researchers to reuse the same infrastructure.
The post Orchard: An open framework for scalable a...
This chapter is divided into nine parts; they are: • Reading Logits from a Model • Greedy Decoding • Temperature Sampling • Top-$k$ Sampling • Nucleus Sampling • Repetition Penalties • Beam Search • Stop Conditions • Structured Output Constraints The model returns a vector of logits for every positi...
How use Claude to craft an outstanding resume that lands offers
The post How Claude Help Me Build My $200k+ ML Resume appeared first on Towards Data Science.
Alibaba Qwen Releases Qwen3.8-Max: A 2.4 Trillion Parameter MoE Model and the Most Capable One in the Qwen Family to Date
Alibaba's Qwen team moved Qwen3.8-Max from preview to general availability, with published per-token pricing and open weights due next week. The 2.4T parameter MoE model accepts text, image and video input across a 1M-token context. No benchmark table has been published.
The post Alibaba Qwen Releas...
Cogent AI Team Releases VR-1: A Frontier Cyber Reasoning Model That Composes and Verifies Enterprise Attack Paths
Cogent AI team released Cogent VR-1, a reasoning model post-trained specifically for cybersecurity rather than picking up cyber capability as a side effect of general coding strength. It ships with two companions: IntrusionBench, a benchmark that scores agents on completed enterprise intrusions, and...
How we built a realtime system for responsive voice AI in six months
GPT-Live enables continuous voice interaction with AI, using a turnless speech model and low-latency architecture for faster, more natural conversations.
Topology-Aware Data Movement for Disaggregated GPU Inference
arXiv:2607.28633v1 Announce Type: new
Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate GPU pools, the KV cache must be transferred between them. For a 70B model this is 2.6 GB per request,...
Sensitivity Analysis of GRU, LSTM and Transformer Encoder in Classification of Automated Driving Systems
arXiv:2607.28665v1 Announce Type: new
Abstract: Automated driving systems (ADSs) are becoming ubiquitous. Future Software Defined Vehicles (SDVs) may be able to run multiple ADSs, both native and aftermarket such as Comma.ai's Openpilot. Monitoring systems to independently verify which automated dr...
Guarantees on Dynamical System Distinguishability for LLM Token Generation
arXiv:2607.28667v1 Announce Type: new
Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a black-box dynamical system (DS) and comparing prediction residuals of two DSs. Despite the empirical ...
LARA: Lightweight Adapters in the Residual Stream for Composable Adaptation and Alignment
arXiv:2607.28669v1 Announce Type: new
Abstract: We present LARA (Lightweight Additive Residual Adaptation), a method for efficient adaptation that operates in the residual stream of a frozen model rather than in its weights. Where LoRA adds an update of low rank to weight matrices, LARA reads the h...