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Navicat 和 DBeaver 真的可以考虑卸载了，国内团队做出的这个 AI 数据库神器简直在乱杀。 OtterMind / Chat2DB 是一个在 GitHub 上爆火的 AI 驱动型多数据库客户端，斩获了 2.7 万+ Star。它把大模型能力直接塞进了数据库 GUI 里，彻底打破了打工人写复杂 SQL 的门槛。无论是 MySQL、PostgreSQL、Oracle 还是 ClickHouse，全都能拿捏。 核心卖点： 人话变 SQL：零基础输入需求，AI 自动帮你写完超长复杂查询。 SQL 逆向翻译：看不懂别人留下的屎山代码？AI 一秒翻译成白话文。 性能一键诊断：慢查询自动提示优化方案，不用天天麻烦 DBA。 多端全平台：支持 Win/Mac/Linux 客户端及 Web 部署。 主流全兼容：兼容 MySQL、Oracle、PG、SQLite、ClickHouse 等数十种数据库。 🔗 GitHub：

Tomorrow will be my last day at Google after 27 years, and watching it grow from 25 people to 190,000+ has been an amazing journey. Below is a note I shared with many people internally at Google today. An excerpt is: It has been an absolute pleasure to work with you and to help build some of the most widely used and impactful products of all time. As a kid, I dreamed of helping build software that would be used by many people, and Google now has thirteen products used by more than a billion people (amazing!). Our work has had a tremendous impact in the world, and I have been lucky enough to collaborate and form friendships with many colleagues that I deeply admire, respect, and enjoy. It still brings me joy every time I see people out in the world using our products to find information, handle email, translate documents, watch videos, learn new things, navigate and understand the physical world, browse the web, use their phone, run large-scale computations on our infrastructure, ride in an autonomous vehicle, or perform complex tasks with the help of our AI systems. I hope you all share this sense of joy, because it is a shared accomplishment! Thank you to all of my colleagues at Google over many years! Now I'm excited to go start @DiscoLoopAI with my longtime friends and colleagues @Sanjay_Ghemawat, @OriolVinyalsML, and @quocleix. (Updated post: slightly redacted to not have some personal info)

Grok Build keeps getting smarter.....this update expands Auto mode, gives developers more control over Bash permissions, speeds up /btw, and makes long conversations easier to navigate Release Notes: v0.2.119 Features: • Always allow for bash commands now lets you edit a free-form glob pattern instead of only word-prefix scopes. • Long responses now show a clickable arrow that jumps back to the start of the answer. • Auto mode now auto-approves more common read-only git commands and harmless file appends. • Plan previews now show Mermaid diagram buttons (Open Image, Copy Image Path, Copy Source). Bug Fixes: • Gateway connections now detect and recover from dead sockets more reliably. • Question cards now let you Tab through answers instead of losing focus to the scrollback. • Resume picker no longer tries to load a session from pasted garbage when you press Enter. • Background task completion messages no longer grow unbounded when the task produced a huge log. • Plan viewer scrollbar now responds to clicks on the border column and renders without dark stripes in • Expired external auth provider credentials now correctly trigger the interactive sign-in flow instead of a silent 401 loop. Performance: • /btw side questions now reuse the parent session’s cached prefix for faster responses. • Doctor and tmux-backed startup are now faster when no live tmux processes remain.

Havi Nguyen grew up managing Medicaid for her family while working at her parents’ nail salon. Now the Abby Care founder is helping others navigate America’s byzantine health care programs by using her AI-powered app to become paid caregivers. #BillionDollarStartups#

OpenAI continues to innovate on odd interface patterns. Today, a button in the primary navigation view acts as a toggle or segmented control to swap out the entire child content of the view??

A humanoid robot is fundamentally an embodied AI system. While motors, actuators, batteries, and sensors provide the body, neural intelligence provides the mind. Without neural computation, a humanoid is simply an advanced machine. With it, the robot becomes capable of adapting to unpredictable environments, understanding language, recognizing objects, planning tasks, and continuously improving through experience. This shift positions "Humanoid Neural" as a foundational concept within the robotics ecosystem. Neural Intelligence is the Core of Future Humanoids. Modern humanoids rely on neural-network-based systems to perform nearly every cognitive function. These include: Visual perception Speech recognition Language understanding Object identification Human pose estimation Motion planning Reinforcement learning Dexterous manipulation Long-term memory Decision making Navigation Emotional recognition Social interaction As robots become more capable, nearly every subsystem transitions from traditional programming toward learned neural models. This makes "neural" less of a niche AI term and more of an umbrella for robot intelligence. A Broad and Scalable Brand One of the strongest characteristics of is that it is not confined to a single product category. #Languageunderstanding# #neuralnetwork# #socialinteraction# #neuralntelligence# #smarthumanoids# #iq#

The future of humanoids isn't just mechanical—it's neural. A humanoid robot is an embodied AI system. Motors, sensors, and actuators provide the body, but neural intelligence provides the mind. Neural models power vision, speech, language, navigation, manipulation, planning, memory, decision-making, and continuous learning. As robotics evolves, nearly every cognitive subsystem is becoming neural-first. That's why represents more than a niche—it's a foundational concept for the next generation of intelligent robotics. #HumanoidRobots# #EmbodiedAI# #PhysicalAI# #NeuralNetworks# #ArtificialIntelligence# #Robotics# #MachineLearning# #DeepLearning# #RobotLearning# #ReinforcementLearning# #ComputerVision# #GenerativeAI# #AIResearch# #Automation# #FutureOfAI#

best blogs of the week (so insightful that i read at least twice) Coding Agent: How @cognition reduces Devin's token cost by harnessing: How @cursor_ai builds complex projects with low redundancy through swarm: How @claudeai Code designs context for new model-driven agents: Robots: @MistralAI SOTA visual navigation model: Vision models: @GoogleDeepMind unveils the source of creativity for diffusion models:

Converting flat satellite maps into fully interactive 3D digital twins used to take weeks of manual 3D modeling and GIS engineering Now, a single tool can process geospatial satellite data and reconstruct the complete 3D geometry of any building on Earth in seconds Here is how the spatial extraction actually works: First, you select a structure on a standard satellite map. The software reads the footprint, elevation data, and height boundaries Next, it automatically generates a volumetric 3D wireframe mesh, rendering the physical layout in real time From there, you can apply a cross-section slice to cut through individual floors, revealing subterranean basements and foundation depth Finally, you can drop into a first-person view to physically navigate interior corridors, stairwells, and room layouts This bridges the gap between static geospatial map data and immersive 3D spatial simulation for architecture, urban planning, and spatial analysis