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AI·Terraform enables safe and predictable creation, change, and improvement of infrastructure through declarative configuration files shared as code.
AI·SQLite strict tables enforce column types to prevent datatype errors like inserting text into integer columns, allowing only standard types or ANY for flexibility, but cannot be added to existing tables and require SQLite 3.37+.
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.
AI·GitHub trending page for the Ansible repository describes Ansible as a simple IT automation platform for deploying and maintaining applications and systems.
AI·OpenAI's GPT-5.6 limited preview, reportedly requiring White House approval, was abruptly released without permission after 10 days, with the government clarifying no approval is needed and labeling the cooperation 'voluntary'.
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·Anthropic's J-space analysis of Claude reveals a small subset of internal representations forming a functional global workspace for flexible reasoning, but the paper explicitly states this has no bearing on AI consciousness and clarifies the core of AI alignment research.
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·Zhipu AI founder Tang Jie releases internal letter after 'GLM Moment' success, announcing focus on long-horizon tasks, autonomous agents, and self-evolving AI beyond coding and reasoning.
AI·Meta plans to mass-produce its own Iris AI chip by September, DeepSeek and Zhipu AI are developing custom inference chips, and OpenAI unveiled Jalapeño, signaling a shift from NVIDIA GPU reliance to full-stack model + chip + cloud strategies.
AI·2025 saw multiple AI companionship app closures including Woebot (150M users, clinical tool shut down due to unsustainable economics) and Dot AI (vision divergence, funds exhausted), with global closures in at least five products and domestic in eight; survivors like Replika (post-data deletion), Character.AI (Google talent acquisition), and China's Xin Bing (ice) lost users amid regulatory scrutiny and high inference costs, revealing unsustainable business models lacking self-reinforcing revenue.
AI·Sources say China's DeepSeek is developing its own AI chip, potentially advancing domestic AI hardware capabilities amid global tensions.
AI·Power semiconductor manufacturers are rapidly expanding capacity amid high demand from EVs, AI data centers, and power grids, while low-end supply exceeds demand.
AI·Upstart PhD founder of Eaglewing Zhiwei completes third funding round in three months for a bio-inspired flapping-wing robot that learns to understand and drive fluid dynamics via self-developed simulation engine.
AI·llama.cpp build b9966 fixes regex recompilations for -sm tensor mode, caching patterns per tensor to reduce CPU overhead on decode threads.
AI·AI is tested in real disaster simulations like fires, evacuations, and crowds to assess decision-making, collaboration, and survival ability rather than human-like appearance.
AI·A user shares benchmarks of dual RTX 3090 and Titan RTX cards running llama.cpp with Qwen3.6-27B at 180k context, comparing tensor and pipeline parallel modes for PCIe transfer efficiency.
AI·The author benches a quad 5060Ti setup for Qwen3.6-27B code generation using MTP, reporting 608 tokens/s prefill and 52.2 tokens/s decode at 256k context on a cost-effective build.
AI·Quantum Computing China has completed its first 100,000-card cluster, achieving national full-stack computing power support for the ten-thousand-card era and successfully running over 300 applications.
AI·OpenAI attributes a complete proof of the 50-year-old Cycle Double Cover Conjecture (every bridgeless graph has a cycle double cover) to GPT-5.6 Sol Ultra, which completed the 3-page PDF in under an hour using 64 parallel sub-agents guided by a 700-character public prompt.
AI·Cloudwise, marketed as Hong Kong's first AGI stock, saw a 41% single-day plunge on unlock day; frequent equity raises and project-based revenue reveal ongoing losses, long receivables, and lack of self-sustaining API/token model.
AI·VultronRetriever family of models is released on Hugging Face, topping MTEB leaderboard classes including VultronRetrieverPrime-8B as global #1, with offline iPhone Q&A and embedding demo.
AI·LLM-as-judge scores fluctuate across evaluators even with fixed candidate responses, treating the issue as measurement validity. Across four datasets, scaling Qwen3 from 1.7B to 32B parameters yields only limited adjacent gains, while MiniMax M2-to-M2.7 API upgrades show none; stronger judges reduce but do not eliminate position and verbosity biases, with repeated juries offering little benefit under correlated errors.
AI·This position paper reviews LLM-driven formal theorem provers and argues that current systems function mainly as solvers for well-defined problems, not as research agents capable of discovering new theorems or resolving open conjectures at the frontier. It identifies key limitations in datasets, exploration, tools, and collaboration and proposes a roadmap for AI4Math systems to support genuine mathematical research.
AI·Across five instruction-tuned LLMs, ordinary answer-confidence separates correct from wrong answers on answerable questions but fails to distinguish unanswerable questions (e.g., false-premise ones in CREPE), while a linear probe on hidden states performs the opposite, revealing two distinct abstention axes that remain separable even at 14B scale.
AI·DominoTree is a training-free best-first tree draft builder for speculative decoding that scores each candidate node by re-applying Domino's GRU-based causal correction along its specific root-to-node path. It restricts per-node correction to top-M candidates for efficiency and delivers up to 6.6x speedup with the highest mean accept length of any tested method.
AI·MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction
AI·ICDAR 2026 HIPE-OCRepair competition evaluated LLM-assisted post-correction of noisy OCR from 17th-20th century multilingual (EN/FR/DE) historical newspapers and books. Four teams used zero-shot to fine-tuning approaches; results show significant error reduction but recurring over-correction on low-noise inputs, with a public dataset and evaluation framework released.
AI·XALPHA is a memory-driven AI quant researcher that uses multi-source research memory integrating external financial reports and prior discovery feedback, with Macro Brain for theme planning and archetype selection, Micro Brain for hypothesis-to-code translation and tri-alignment verification, and Cross Brain for feedback consolidation, enabling closed-loop continuous alpha discovery that outperforms baselines on CSI300.
AI·The paper introduces Hallucination Self-Play, a bootstrapping approach that uses an evolved generator to reinforce a detector for identifying faithfulness hallucinations in LLMs.
AI·The paper introduces a graph-based framework to quantify uncertainty, coherence, and robustness in LLM reasoning, addressing gaps in decoding strategies like Self-Consistency that only check final-answer agreement.
AI·Researchers developed SQZ-Qwen-ASR-1.7B for MLC-SLM 2026 Task 1, combining a modular speaker diarization front-end (VAD, CAMPPlus embeddings, spectral clustering, RTTM segmentation) with Qwen3-ASR-1.7B adapted via full supervised fine-tuning, LoRA on TTS-generated synthetic speech, and GRPO reinforcement learning for lower tcpMER (23.70 on dev set, 17.97 on eval set).
AI·The paper proposes UltraX, a method for refining large-scale pre-training data using adaptive programmatic editing to improve LLM quality when scaling data yields diminishing returns.
AI·Achieves 50-54 tok/s for Qwen3 30B A3B float8 on 16GB RTX 5060 Ti using custom CUDA/C++.
AI·A $100 setup using three NVIDIA P102 cards delivers 20 GB VRAM and 448 GB/s memory bandwidth, sufficient for three concurrent LLM users with high context and better speeds than costlier lower-VRAM cards.
AI·DeepSearch-World is a self-distillation framework for web search agents that uses self-generated experience for training in verifiable environments.
AI·The paper identifies a failure mode in critic-free RL methods for LLMs where implausible tokens receive uniform credit, and proposes tail-aware credit calibration to improve reinforcement learning.
AI·The paper empirically assesses the reliability of Gemini models as audio judges for full-duplex voice agents by scoring stereo waveforms, validated against human calibration.
AI·The paper proposes an agentic tool-making pipeline that compiles repeated SOP steps into validated versioned tools to reduce latency and improve reliability in production LLM agents.
AI·Holographic Neural PCFG induces latent constituency trees from raw text using holographic memory and neural rule scoring for unsupervised parsing.
AI·Prompt Compression via Activation Aggregation compresses task-relevant prompt information into a single activation vector for re-injection into the model.
AI·Structured pruning method for sparsely-activated MoE models removes bad experts to address full expert bank memory bottleneck while preserving inference efficiency.
AI·36kr AI, a Chinese tech startup, is discussed for updates on AI chip developments, highlighting advancements in AI capabilities and recent changes in industry organization.
AI·COALA enhances contextualized SLMs for multi-entity ASR via contrastive regularizer and biasing score estimation to handle domain-specific entities robustly.
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 paper probes internal representations of Eternis-Forecaster 8B for forecasting, training a representation-pooling method to assess calibration and faithfulness of internal CoT reasoning.
AI·COBART uses a bidirectional auto-regressive transformer for optimized ad headline generation with multi-objective control over quality and CTR.
AI·TypeProbe recovers type representations from hidden states of pretrained code models using parallel Java and Python datasets.
AI·Best-of-N TTS evaluation is confounded by ASR family alignment, where verifier quality depends on the judging ASR model family.
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·Questions costs and viability of aftermarket SXM2 boards for two V100 GPUs, comparing to consumer GPU setups.
AI·Reports EPYC 9374F CCD benchmarks using ik_llama.cpp; finds limited decoding gains vs older 9135 at low thread counts.
AI·User questions whether to withdraw from ACL ARR and resubmit to a workshop after mediocre 2.5-3 scores on an Interpretability-track EMNLP paper.
Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models struggle with long-term stability. We propose LongE2V, a novel approach that leverages pre-trained video diffusion priors to jointly handle event-based video reconstruction, prediction, and frame interpolation. By fine-tuning a foundational video model, our approach achieves high data efficiency and superior perceptual quality. We introduce Auto…
The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operating everyday tools and assisting users in real-world environments. However, existing benchmarks struggle to evaluate such agents effectively, as they often rely on sandboxed environments and single-turn evaluation paradigms. Moreover, their scenario-based task taxonomies mix multiple model capabilities within the same task category, making it dif…
Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properties, often neglecting the influence of disease context on target behavior and therapeutic outcomes. To address this gap, we introduce DrugGen-2, a novel generative model that designs small molecules conditioned on both disease ontology and target protein sequences. DrugGen-2 was developed by fine-tuning a pre-trained GPT-2 model on a curated datase…
Hi everyone, A year ago I began pre-training language models exclusively on 1800’s London data. Recently I have completed my largest dataset ever, containing 40B tokens or 160GB of 1800-1875 english data from England and the United States. I will soon train a 2B parameter model on it, but for now I’ve trained a 500M parameter evaluation model on a 5B token sample. I have also fine tuned the eval …
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