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分类推荐榜首EEvoMapAgents & automationEvoMap is an infrastructure designed for the reuse of AI agent experiences. It organizes reusable strategies and repair assets with validation records via the GEP protocol, offering market- and quality-based ranking to help different agents discover, evaluate, and inherit existing capabilities.
分类推荐榜首OOpen DesignDesign & 3DOpenDesign is an open-source design workspace that can connect to local programming agents, use built-in model keys, or leverage cloud-based models, enabling the creation and editing of prototypes, web pages, presentations, and graphics within a design system; local software is free, while model services incur fees.
分类推荐榜首MMemoAIMusic & audioMemoAI is an AI-powered audio-to-text tool that supports localized processing, eliminating the need to upload data and ensuring privacy and security. It can efficiently transcribe YouTube videos, podcasts, and local audio/video files (such as MP4, MP3, AAC, M4A, etc.) into text, while offering core features like multilingual translation, speaker diarization, real-time subtitles, and floating notes—making it ideal for meeting minutes, interview transcription, content learning, and more.
分类推荐榜首JJAXModels & infrastructureJAX is a Python numerical computing library designed for accelerators, specifically tailored for high-performance array computations and large-scale machine learning. It efficiently executes the same code across multiple hardware backends, including CPUs, GPUs, and TPUs.
分类推荐榜首KKiroCoding & developmentKiro is an AI engineering tool for developers that organizes requirements into specifications, architectures, and tasks, generates code via agents, and supports the entire workflow—from planning to code review—through property-based testing, execution memory, and integration with development tools.
分类推荐榜首IIamIPIndustry applicationsIamIP is a patent platform that provides AI-driven search, analysis, and monitoring tools to help users conduct patent research and management more efficiently.
待评分 · 分类列表推荐闪FlashCut is an AI-powered creation platform for voice-over and short-video marketing. It can generate finished videos with voiceovers, subtitles, and visuals from text, offering digital human customization, photo-to-digital-human conversion, live-stream clipping, and intelligent editing. It also provides APIs and branded mini-program solutions for businesses.
待评分 · 分类列表推荐EElicitKnowledge & researchElicit provides semantic search, research report generation, literature screening, and data extraction for scientific research. It enables traceable answers within source materials and organizes evidence through a literature library, research agents, and ongoing tracking workflows, making it ideal for advancing from initial problem exploration to systematic reviews.
待评分 · 分类列表推荐ZZoom Workplace is Zoom’s team collaboration platform, integrating video conferencing, chat, calendars, and documents, and leveraging built-in AI to organize discussions, draft messages, and track follow-up tasks.
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2026-11-04
Follow the timelineExpanding Customer Notifications for ClickHouse Managed Postgres
ClickHouse Managed Postgres is adding five new customer notifications: inactive replication slots, planned switchovers, unplanned failovers, long-running transactions, and connections approaching their limit.
Front-end observability at scale: How OpenReplay captures billions of daily events in real time with ClickHouse
OpenReplay replaced Postgres with ClickHouse to ingest billions of events and up to 6 TB a day on a single, vertically scaled instance, with sub-second queries and retention handled by a single TTL setting.
Hemut: Building the Internet of Freight on Real-Time Data
Hemut uses Confluent, real-time data streaming, and AI to automate trucking operations, improve fleet efficiency, and build the Internet of Freight.
How Shipsidekick replaced Neon with ClickHouse Managed Postgres for 10x faster queries and better reliability
Shipsidekick moved from Neon to ClickHouse Managed Postgres in a single weekend, cutting CPU usage from 100% to 5-10% and making queries about 10x faster.
Latent Cluster Separation as a Regularizer for Lifelong Anomaly Detection
arXiv:2611.03652v1 Announce Type: new Abstract: Lifelong (continual) anomaly detection systems must learn a sequence of tasks without forgetting how to recognize anomaly types seen earlier -- a property known as backward transfer. A common way to try to improve backward transfer is to reshape a model's internal representation around learnable concept centroids, typically coupled with a new way of scoring anomalies based on distance to those centroids. Because these two design choices are usually introduced together, it is unclear which one is actually responsible for any performance gain. In this paper, we unbundle the two mechanisms within a VAE-based lifelong anomaly detector and study them separately. We find that used purely as a training-time regularizer -- while leaving anomaly scoring unchanged -- latent cluster separation can improve detection quality and backward transfer, though whether it outperforms the alternative scoring approach depends on the dataset's underlying representation. Switching to distance-based scoring is instead where most of the instability commonly associated with this class of method actually originates; we identify and explain the underlying mechanism. This benefit depends on the dataset's underlying representation, and we report this as practical guidance for choosing between the two design choices, rather than as a list of caveats.
Postgres wait events, now in Query Insights
Query Insights for ClickHouse Managed Postgres now shows what active sessions are waiting on, with wait event breakdowns, blocked-session and lock-wait charts, and the same metrics in Prometheus.
The Agentic Analytics Benchmark: ranking tables and labeling failures with Jev
Jev ranks warehouse tables and labels agent failures in under a second, but adding retrieval hints leaves accuracy flat across 20 models on the Agentic Analytics Benchmark.
The Agentic Analytics Benchmark, round two: GPT-6, Claude Opus 5.5, Claude Sonnet 5.5
We added GPT-6 Astra, Luna and Sol, Claude Opus 5.5 and Claude Sonnet 5.5 to the Agentic Analytics Benchmark: all five land mid-board within a point of each other, and Sonnet 5.5 brings the biggest change in turns, cost and truncated runs.
The new cost-based join optimizer with reordering support for non-inner joins
ClickHouse’s new exhaustive cost-based join optimizer safely reorders inner, outer, semi, and anti joins to find the cheapest valid plan.
Trace and evaluate Cursor agents with Langfuse, powered by ClickHouse
Connect Cursor to Langfuse to trace every agent turn, pinpoint expensive model and tool calls, and use evaluations to confirm a fix actually helps, with ClickHouse powering the analytics underneath.
2026-10-30
Follow the timeline12:00
What Constitutes Food Similarity? Visual Representations and Retrieval in Indian Cuisine
arXiv:2610.37867v1 Announce Type: new Abstract: Food similarity underlies retrieval, recommendation, substitution, and other food computing tasks, yet food representations are typically evaluated by identity preservation. We ask what happens to food similarity beyond identity: how different visual representations organize foods into relational neighborhoods, what culinary relationships these neighborhoods reveal or obscure, and how consistently these structures emerge across representations. Indian cuisine provides a challenging setting in which visually similar foods may have different culinary identities, while foods within a culinary family can vary substantially in appearance. Using an expanded Khana dataset and seven pretrained visual representations spanning convolutional, transforme
2026-10-28
Follow the timeline17:13
DouBao’s PR team responds to the “150,000 extras fed into a model” rumor: The claim is seriously inaccurate.
Liu Xing, head of DouBao’s PR department, issued a statement debunking the rumor, stating that the claim “Hengdian has partnered with ByteDance to feed the portraits and voices of 150,000 extras into ByteDance’s large AI model” is seriously false. He explained that the real “Hengdian Film & TV AI Service Platform” aims to build public digital infrastructure, organizing on-site assets such as film studio locations into high-quality datasets. This helps production crews efficiently scout locations, prepare for shoots, and streamline filming, while also lowering the barrier for small and medium-sized film and TV companies to adopt AI, enabling more creators to produce quality work.
12:00
Structured Maps for Landmark-Based Route Instructions with LLMs
arXiv:2610.36582v1 Announce Type: new Abstract: To generate landmark-based route instructions, models must understand both map geometry and human landmark preferences. Although large language models (LLMs) show great abilities in language tasks, the best way to structure map data for these models is not yet established. This paper proposes a structured text representation for landmark selection tasks in route navigation, utilizing SVG format to encode spatial features. The structured text maintains a geometric connection with rendered map images, allowing language models to directly access spatial and semantic data. Using a new dataset created from human-written route descriptions and OpenStreetMap data, we evaluate models on two tasks: landmark selection at turns and around destinations.
03:06
How to put generative AI directly into a dbt pipeline with plain SQL
Google Cloud on wiring BigQuery's AI SQL functions into dbt pipelines, from sentiment scoring to LLM-generated product briefings.
02:44
How KOHO built a Claude-powered self-serve analytics tool on years of dbt governance
KOHO explains why AI self-serve analytics needs a strong data culture and a governed dbt foundation first.
02:41
Why an AI agent's revenue query was $3.5 million wrong, and how AWS fixed it with dbt Semantic Layer
A plausible AI revenue query was $3.5 million wrong. AWS explains how business context helps prevent those errors.
02:34
Why most of your dbt models aren't in a hurry, and what that's worth in Snowflake credits
Most models in a dbt DAG aren't on the critical path. Espresso AI and Authentic Insurance on turning that slack into real savings.
02:20
How Ecolab used an AI migration agent to shrink 84,000 lines of legacy SQL by 6x
Ecolab and Datafold used an AI migration agent to rebuild a decade of tangled Snowflake logic as clean, documented dbt models.
02:16
How Checkr cut an hours-long metrics investigation to minutes by engineering AI context on dbt and Omni
Checkr gave its AI agent a structured dbt context layer, cutting a support-metric investigation from hours to minutes.
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