AI·The article dissects UPI's complex payment transaction architecture, detailing seven parties, NPCI's central role, and the shift from person-to-person to merchant payments.
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AI·Open-source models attract more traffic and earn most of the revenue, causing Anthropic's revenue to drop from dominance to a small fraction of the market.
AI·Alibaba's Lingbo released six embodied AI models from July 7-10, 2026, introducing 'Embodied Native' — a new paradigm that trains foundation models from scratch on physical-world data, interactions, and causal physics rather than migrating internet LLMs, with LingBot-VA 2.0 as the flagship VLA model achieving real-time 150Hz inference and strong generalization.
AI·MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction
AI·DeepSearch-World is a self-distillation framework for web search agents that uses self-generated experience for training in verifiable environments.
AI·Structured pruning method for sparsely-activated MoE models removes bad experts to address full expert bank memory bottleneck while preserving inference efficiency.
AI·Grounded Event Extraction from SEC 8-K filings uses a fine-grained taxonomy to overcome coarse SEC item codes for market-moving disclosures.
AI·The paper introduces a multi-cluster boundary learning method using MiniLM embeddings for detecting out-of-scope intents in human-machine interaction systems.
AI·The study applies LSTM and traditional models to analyze public sentiment on social media platforms like Twitter regarding real-time events and issues.
AI·The paper enriches Roy Harris's Integrationism theory with Barenholtz's Autogenerative Theory to address gaps in computational language approaches.
AI·ChatGPT Work is now an agent that takes action across apps and files, stays with projects for hours, and turns goals into finished work using GPT-5.6.
AI·WAIC event asks whether AI intelligence is enough without real action and judgment.
AI·Proactive memory agent introduced to combat behavioral state decay in long-horizon agents by actively surfacing scattered decision states.
AI·Dual Latent Memory in Vision-Language-Action models for robotic manipulation interleaves historical experience fluidly in the native latent embedding space, overcoming Markovian limitations in long-horizon tasks.
AI·LingBot-World 2.0 is an advanced world modeling system with four upgrades: unbounded interaction horizon, real-time 60 fps video support, diverse interactive actions and events, and multi-agent control for multi-player virtual environments.
AI·GPT-Live is a full-duplex voice model for natural real-time human-AI conversation that can listen while speaking and delegates complex reasoning to a backend frontier model.
AI·A sparse and truncated state-vector simulator for peaked quantum circuits predicts the most probable output bit string using only nonzero amplitudes with vectorized operations and optional GPU acceleration.
Pretrained video generative models are promising backbones for visuomotor control, but their imagined futures often drift from task intent and are not reliably action-conditional. As a result, these models can be difficult to use for planning or policy extraction. To address these limitations, we propose RoboTALES, a single-stage framework that learns task-aligned simulated futures and uses them to train robot policies. Our approach introduces two key innovations: (1) a hierarchical LLM-based p…
Single-stream diffusion transformer with a DeepSeek-V3-style sparse MoE (128 experts, top-8 routing, 1.4B active of 13B total). Six-reward RL post-training including a physical-plausibility reward, plus an action-to-video mode that predicts robot rollouts from action and hand-pose conditions. Weights, code, and a Diffusers/SGLang stack are open under the LingBot-Video name. Two things I would pus…
Accurate breast cancer classification from mammography requires effective integration of complementary information from craniocaudal (CC) and mediolateral oblique (MLO) views, which provide a more complete characterization of breast abnormalities. However, existing multi-view learning approaches typically rely on feature-level aggregation or single-stage cross-attention, which can entangle view-specific and shared representations and restrict interaction to limited network depths. To address th…
OpenAI and Molecule.one show how a near-autonomous AI chemist using GPT-5.4 improved a key drug-making reaction, advancing medicinal chemistry research.
Gemini 3.5 is built to help you execute complex, agentic workflows.
Our latest voice model has improved precision and lower latency to make voice interactions more fluid, natural and precise.
Human-Computer Interaction and Visualization
Google Research Blog·research.google··0.2human-computer interaction and visualizationmachine intelligence
Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules. This modularity exposes a large architectural design space, but current systems still rely on researcher intuition to choose where information is stored, how observations are processed, and how model calls are connected. Agent Architecture Search (AAS) automates such design for text-domain agents, but has not been systematically evaluated on perceptual embodied agents through s…
Zero-Shot Compositional Action Recognition (ZS-CAR) requires recognizing novel verb-object combinations composed of previously observed primitives. In this work, we tackle a key failure mode: models predict verbs via object-driven shortcuts (i.e., relying on the labeled object class) rather than temporal evidence. We argue that sparse compositional supervision and verb-object learning asymmetry can promote object-driven shortcut learning. Our analysis with proposed diagnostic metrics shows that…
We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named Entity Recognition (NER), or relation extraction. Rules are generated based on a task description and a set of labeled examples, then they are iteratively improved based both on additional examples and on human feedback overexisting rules. RuleChef can also be used to bootstrap rules using the observed input-output pairs from any existing model fo…