与「reliable」相关的搜索结果

Gemini 4 Hydrogen is here, bringing cutting-edge intelligence to everyone for fast, everyday help. It makes it easier to get things done, following your instructions more closely, calling the right tools, and getting you to a reliable output with less back-and-forth. 🧵

SpaceX has committed $220 million to expand water and wastewater infrastructure for Brownsville and Cameron County -- the largest private contribution to Brownsville’s water future in the city’s history. This investment addresses one of the region’s most urgent challenges: securing a reliable, sustainable supply of drinking water for generations to come

The most first-principles talk at #AIECode# came from @CompleteSkeptic — who co-created RLHF/ChatGPT at OpenAI and now builds Jev. His point: today’s LLMs are optimized for assistance (a human in the loop), not automation. “95% Einstein, 5% Mr. Bean” is fine for a chatbot and fatal for a back-office decision. The Bitterest Lesson: compute beats algorithms, data beats compute, and the bitterest part is picking the right task. Jev’s bet: not bigger, not cheaper, but reliable.

Every component works together to ensure smooth and reliable Roots blower operation! Precision parts, dependable performance, and quality you can trust.Our Roots blowers are ideal for wastewater treatment, aquaculture, and pneumatic conveying. #RootsBlower# #BlowerParts# #Precision#

India needs @Starlink 🇮🇳 • 11,256 of India’s listed villages still lacked 4G coverage as of May 2026. • India had 1.093 billion internet subscriptions in March 2026, but only 440.87 million were rural. Rural subscription density was 48.31 per 100 people, compared with 126.80 in urban India. • BharatNet had laid over 850,000 route-km of fibre and made about 221,000 Gram Panchayats service-ready. However, its Points of Presence were reported operational at only 80,472 Gram Panchayats in June 2026. • Only 4.26% of India’s internet subscriptions were wired connections in March 2026. Starlink could give underserved communities another route to high-speed broadband. • Starlink has already built 20 gateway sites in India, according to SpaceX Vice President of Starlink Business Operations Lauren Dreyer, speaking at India Mobile Congress today. • Starlink says it has developed India-specific security controls designed to keep Indian user data within India. • Its satellite network could bring high-speed internet to remote villages, mountains and islands where extending fibre or mobile networks is difficult. • Better connectivity could help rural schools access online learning, clinics offer remote consultations and small businesses reach more customers. Starlink already supports education and healthcare in remote communities internationally. • Portable Starlink terminals have supported disaster response around the world. They could give Indian emergency teams backup connectivity when floods, earthquakes or storms damage ground networks. • Direct to Cell could also help ordinary 4G phones connect beyond tower coverage, subject to Indian approvals and mobile operator partnerships. • The government itself identifies difficult terrain, low commercial viability and infrastructure constraints as reasons for remaining coverage gaps. This is exactly where Starlink could help India reach more people. • India should complete the remaining clearances and spectrum allocation so Starlink can begin commercial service. • SpaceX’s Vice President of Starlink Business Operations, Lauren Dreyer, said that Starlink is ready to help achieve Prime Minister Modi’s vision of 100% connectivity across India. She highlighted its potential to connect remote classrooms, support telemedicine and restore connectivity after disasters, adding, “With Starlink, people can get connected within minutes, not years.” India’s hardest-to-reach communities deserve reliable internet too.

The most important agent on this team builds nothing. It only checks. In the video, four agents assemble a browser game from a 12-second clip. Rules works out the movement logic. Builder assembles the scene and interface. Logic takes controls and collisions. The fourth, Tester, opens the browser and plays it by hand. Sounds minor. But this is exactly where most AI projects break: the code is written, the report looks great, and the restart button doesn't work. Here, verification is part of the pipeline. The agents check hitbox overlap, jump timing, state after restart. Specific things, not "looks fine." Jev runs between them. It writes nothing, it passes context. One agent learns how the character jumps, and the next one already knows. It works like a relay race, not like four people in separate rooms. One more detail I liked. In the last frame, the gameplay checks are still marked pending. No green checkmarks in advance. Want AI to make reliable things? Give it a separate agent that doesn't trust the others. #AIAgents# #GameDev# #MultiAgent#

Learn Harness Engineering from scratch! This repo is a full learning path around harness engineering, with 14 lectures, 8 projects, reusable templates, and hands-on exercises. The course focuses on the environment around coding agents and how that environment affects whether an agent can reliably work inside a real repository across longer tasks and multiple sessions. It starts with the fundamentals of harness engineering and gradually gets into things like repository structure, persistent state, task boundaries, verification, observability, session handoffs, automated loops, and graph engineering. A harness in this context has five core parts: - Instructions that tell the agent how to work inside the repo - State that persists progress across sessions - Verification through tests, linting, type checks, and full-pipeline runs - Scope controls that keep the agent focused on one task at a time - Session lifecycle so every run starts and ends in a usable state The projects are also connected rather than being isolated examples. You keep working on the same Electron-based knowledge app while gradually improving the harness around it. You start by comparing prompt-only vs. rules-first agents, then build multi-session continuity, runtime feedback, verification, a complete harness, automated maker-checker loops, and eventually represent the workflow as a graph with parallel execution, rollback, and human approval. What I like is that you can actually take parts of the repo and use them directly in your own projects. There are templates for things like "AGENTS. md", "init. sh", feature lists, progress tracking, loop state, maker-checker prompts, and a "harness-creator" skill that can scaffold the basic harness structure for an existing project. The repo also covers the progression from a single agent loop to graph engineering, including when you actually need nodes, shared state, routing, parallelism, and recovery instead of forcing everything into one loop. A solid resource if you're working with coding agents and want to understand the engineering around making them reliable over longer tasks. 100% open source

AI agents need both the ability to reason about the physical world and access to reliable information about it. NVIDIA’s SpatialClaw tackles the reasoning side by letting an agent write and execute code step by step, inspect the results, then adapt its next action based on what it observes. @vangrid_io is working on the perception side. Vangrid’s network lets contributors capture real-world locations for specific bounties, with those captures reconstructed into 3D spatial data. Agents can now also create Vangrid bounties through x402 and fund them in USDC on Base or Arc. SpatialClaw helps agents reason about spatial data, while Vangrid helps provide the spatial data. That combination points toward a more complete pipeline for Physical AI: perceive the real world, reason about it, and act on what the agent learns.

Dot, Muse, Grok Bot, and Hermes are all EXCELLENT agents They all have their own strengths and weaknesses, so you need to know which to use for each task Here is each agent, and when you should be using them: GROK BOT- best agent for heavy knowledge work Strengths: Because you can create many different agents with many different contexts, skills, and memories, you are able to get a wide plethora of work done really really well Weaknesses: Grok 4.7 is a great model, but not frontier. Also not much usage on cheaper plans. Who it's for: People who have a diverse set of responsibilities and tasks they need to get done META MUSE: best agent for getting personal tasks done online Strengths: Lightning fast, free, and by far the best agent at navigating the internet. Can just 'figure it out' for getting tasks done in browsers Weaknesses: Not great at coding. Model is lightning quick, but not the smartest or most creative. Weaker at knowledge work because of this. Who it's for: The best 'personal assistant' agent. Booking reservations, finding flights, filling out forms, unsubscribing from websites. The more 'normie' type use cases. Also it's free. So anyone on a budget. HERMES: Open source, fully customizable, do anything assitant Strengths: Fully open source and customizable. Anything you want to change in the agent, you can just change it. Use any model or subscription. Does almost anything you ask without many guardrails. Also a smaller decentralized team supporting it, so it's always great to support the rebels Weaknesses: No mobile app. Because it's open source and fully customizable, it's not always the most reliable if you tinker too much Who it's for: tinkerers who want full control over their agent. Also great for the local model community and people with their own home AI labs. My Hermes maintains all my networks and equipment for me better than any other agent DOT: Your ultimate AI agent project manager Strengths: The smartest model in the best harness. You get Astra capabilities with best in class ChatGPT tools like Voice, Spaces, and Codex. Can manage all your Codex threads for you and see your projects to completion. Also has ALL of your ChatGPT memories out of the box, so no onboarding needed Weaknesses: Feels rushed. Lots of rough edges at the moment. Slowest agent. Has trouble with computer and browser use more than you'd like. Tokens in the Dot chat are free, but can heavily burn tokens when managing Codex threads. Who it's for: Builders who do a lot of coding. ChatGPT power users. Anyone who has long running tasks they'd like an agent to project manage for you If you put the right agents on the right tasks, you'll have super powers. I use all 4 of these every single day, and switching between them is a breeze They're all also EXCELLENT agents, so if you can only use one, using any of them is good enough. You can choose literally any of these 4 as daily drivers and you'll be way more productive than the average person Just make sure you're USING them, and not just reading about them.