Instinct’s powerful AI assistant is raising privacy and security concerns
Early testers are raving about what Instinct can do, but some say the AI assistant’s sweeping access, broad terms and ability to act on users’ behalf come with uncomfortable trade-offs
Data Intelligence: Building Your Competitive Advantage in the Era of AI
To keep pace with modern business, data strategy is shifting toward more autonomous real-time systems that deliver intelligence at the moment decisions are made. Driven by agentic AI, modern data teams are moving beyond simply looking at what happened. Now they’re automating complex workflows that a...
Valor, Point72 back General Intuition at $6B valuation as AI startup pushes into robotics
General Intuition, the startup building a foundation model that trains generalized AI agents how to move through space and time, is in talks to raise at a $6 billion pre-money valuation from new investors including Valor Ventures, Point72 Ventures, Seven Seven Six.
To generate intelligence at scale, AI factories run continuously, and their economics are defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime. That requires AI infrastructure designed and built as a full factory, not a collection of individual acc...
With Groq 3 LPX in Full Production, NVIDIA Extends Vera Rubin Inference for Agents
The next era of AI inference won’t be defined by a single breakthrough chip, network or system. It’ll be defined by how every layer of the AI factory works together. That’s why NVIDIA is extending Vera Rubin NVL72 with fast token generation for agentic systems. Announced today, the NVIDIA Vera Rubin...
Up to 30x More Work Per Watt: NVIDIA Vera Rubin NVL72 Sets a New Efficiency Standard for AI Agents
According to OpenRouter data, agentic AI workloads consume 15x more tokens than a simple chat request. Why? Consider what happens when an AI agent researches a company for an investment decision. The agent queries financial databases, searches news and filings, invokes a sub-agent to run peer compa...
Most LLM inference runtimes have no idea a physical deadline exists. This one refuses admission rather than miss a 33ms robot control cycle, evicts KV cache by meaning instead of age, and is written entirely in hand-written CUDA — no cuBLAS, no libtorch.
The post Can an LLM Forget the Right Things? ...
Generalist AI Releases GEN-1.5: A Robot Foundation Model That Learns New Tasks From One 3–12 Second Demo
Generalist AI has released GEN-1.5, a robot foundation model that learns a new physical task from a single demonstration. Drop 3–12 seconds of sensorimotor data into its 30-second context window, and the robot performs the task. No gradient updates, no fine-tuning, no task-specific programming. Acro...
Google Research Introduces ME-POIs: A Mobility-Informed Framework that Adds “How a Place Is Used” to Text-Based POI Embeddings
framework that folds aggregate human movement into text-based place embeddings. Language models describe what a place is; they miss how it is used. ME-POIs encodes each visit as a contextualized vector and aligns it with one learnable prototype per POI through contrastive learning, then transfers vi...
Speculative Decoding on CPUs: Nearly 4x Faster Token Generation with DFlash
Speculative decoding can turn underused CPU compute into faster token generation, without changing the model's output. In our vLLM tests, DFlash delivered 3.92x the autoregressive throughput with Qwen3.5-9B on Intel Xeon 6 at concurrency 1. We break down where the speedup comes from, explain the acc...
Integrating Agentic AI with Existing Machine Learning Pipelines
In this article, you will learn how to combine a classical machine learning pipeline with an agentic AI system to build a hybrid, autonomous customer...
AI Agents Don’t Need More Context — They Need Typed Context
AI agents don’t just have a context problem—they have a context typing problem. When instructions, memory, retrieved evidence, and tool outputs are flattened into one string, their semantic boundaries can disappear. I built a lightweight, zero-dependency Python runtime that keeps those boundaries ex...
Bankruptcy Prediction via Hybrid Resampling and Stacking Ensemble Techniques with Explainable Artificial Intelligence (XAI)-Driven Analysis
arXiv:2608.20343v1 Announce Type: new
Abstract: This study develops and evaluates a bankruptcy prediction framework that integrates consensus-based feature selection, hybrid resampling, stacking ensembles, and explainable artificial intelligence to improve minority-class detection in severely imbal...
From Thermal Preference Prediction to Adaptive Thermal Intervention: A Reinforcement Learning Approach Using Physiological and Environmental Sensing
arXiv:2608.20423v1 Announce Type: new
Abstract: Personalised thermal comfort is essential for occupant wellbeing and for the development of more responsive building-control strategies, yet conventional Heating, Ventilation, and Air Conditioning (HVAC) systems rely on static setpoints and population...
SDAD: Spec-Driven Agentic Development for the AI-Native SDLC
arXiv:2608.20341v1 Announce Type: new
Abstract: Frontier coding agents backed by large language models with context windows from hundreds of thousands to millions of tokens are restructuring the Software Development Life Cycle (SDLC). Rich context handling and multi-step reasoning now allow substan...
PrimeAgentOrchestrator: Memory-Primed Agent Spawning for Personal AI Infrastructure
arXiv:2608.20342v1 Announce Type: new
Abstract: Large language model (LLM) coding agents start each session with an empty context window, discarding accumulated knowledge from prior work. We present PrimeAgentOrchestrator (PAO), a system that spawns new instances of Claude Code -- Anthropic's termi...
Truth Lies Deep: Countering Semantic Camouflage via Latent Intent Verification
arXiv:2608.20378v1 Announce Type: new
Abstract: Safety alignment in Large Language Models (LLMs) is often superficial, relying on refusal mechanisms that trigger only at the final stages of generation without erasing the foundational knowledge of harmful concepts acquired during pretraining. This s...
A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications
arXiv:2608.20379v1 Announce Type: new
Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agentic frameworks that orchestrate perception, memory, and decision-making around powerful LLM backbon...
Scientific Data Analysis with LabPlot in Python: Signal Processing, Spectral Peak Fitting, Visualization, and Batch Automation
In this tutorial, we explore a LabPlot-inspired scientific data analysis workflow in Python while preserving the structure and terminology of LabPlot’s aspect tree, analysis kernels, plotting system, and project model. We build reusable components to import tabular data, compute descriptive statisti...