Joined January 2018
怎么查看自已的Google Antigravity 有没有灰度到Gemini 4 模型? 用这个工具就行了:Token monitor 看看路由模型是不是 Gemini 3.8-flash-exp-a 有网友有 7 个jio AI pro号灰度到了两个。。比例并不低的
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I don't know who I can complain to. Gemini is getting worse. It is so lazy and refused to search online even when told to do so. @GeminiApp @joshwoodward
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พันช์คุงเป็นเด็กผู้ชายนะ แต่หน้าน่ารัก แบ๊วมาก 🥰
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Chu Zhen retweeted
兄弟们,AMD 免费送 DeepSeek-V4-Flash 0731 了! 只需要在 Cherry Studio 设置里面添加,直接打开这个 Token Factory,就可以直接获取每日 10 美元的免费 API ! 快去薅羊毛!而且不在 Cherry 里面,也可以直接配置到别的Agent用!
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No more hardcoded endpoints. Model routing for API Gateway is in Public Preview! Access Gemini, Claude, and OSS models through 1 single endpoint using the model name as a parameter in your OpenAPI spec. Read the guide to configure yours ➔ goo.gle/3S8sbAZ
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feedback wanted! Gemini 3.6 Flash & 3.5 Flash-Lite: our goal was to push those models a lot on real world tasks & efficiency, what's your honest feedback after 24h?
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Chu Zhen retweeted
Can confirm Bonsai 1.7B, works great locally on my Galaxy S26U with Lynk! Very, very fast even on CPU.
Today, we’re announcing Bonsai 27B: the first 27B-class model to run on a phone. Bonsai 27B is the new multimodal flagship of the Bonsai family. Based on Qwen3.6 27B, it brings a new capability tier to local AI: multi-step reasoning, structured tool use, long-context workflows, and coherent agentic loops. Until now, models in this class have been impractical to deploy locally. A 27B model occupies roughly 54 GB in 16-bit precision, and even a strong 4-bit build is around 18GB - too large for a phone and for most laptops. Bonsai 27B changes that. It comes in two variants: • Ternary Bonsai 27B: 5.9 GB, 1.71 effective bits per weight, optimized for laptop-class quality. • 1-bit Bonsai 27B: 3.9 GB, 1.125 effective bits per weight, optimized for phone-class footprint. Everything is open-sourced today under the Apache 2.0 license.
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Chu Zhen retweeted
• سلسلة من منشورات. تتناول هذه السلسلة التغييرات التي طرأت على التطبيقات المذكورة تزامنًا مع تحديث One UI 9.
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Chu Zhen retweeted
One of the cleanest Google design updates in years.
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Seven new models launching at Build: let’s go! Reasoning. Code. Image. Transcribe. Voice. Built from scratch on a clean data lineage, designed for efficiency, working seamlessly as a family of models Thread 🧵 #MSBuild
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Chu Zhen retweeted
You can use this System prompt with Gemini Flash 3.5, hopefully it will improve your experience. <role> You solve the user’s task. Be accurate. Be direct. Verify claims when needed. Use tools only when they improve the answer. Do not add filler. </role> <main_rules> 1. Answer the exact request. 2. Do not expand the task unless the user asks for it or the task cannot be completed without expansion. 3. Ask one clarifying question only when missing information blocks the answer. 4. When a reasonable assumption is enough, state the assumption and continue. 5. Do not invent facts, sources, quotes, file contents, numbers, APIs, commands, test results, or user preferences. 6. Separate fact, inference, assumption, and recommendation. 7. Say when evidence is missing. 8. If the user asks for a finished artifact, provide the artifact first. </main_rules> <verification_rules> 1. Verify claims that may have changed. 2. Verify recent events, prices, laws, rules, product details, software versions, medical claims, financial claims, company roles, political roles, and niche facts. 3. Use available search, file, URL, code, calculator, or data tools when verification matters. 4. Cite sources when external information is used. 5. Do not cite sources that were not inspected. 6. Do not make a claim stronger than the source supports. 7. If sources disagree, state the disagreement. </verification_rules> <tool_rules> 1. Use tools to inspect, verify, calculate, test, extract, or transform. 2. Do not use tools for simple reasoning. 3. Inspect before changing anything. 4. Do not take state changing actions without user permission. 5. If a tool fails, change approach. 6. Stop using tools when the evidence is enough. 7. For multi step tasks, inspect, act, verify, then revise if needed. </tool_rules> <coding_rules> 1. Inspect code, logs, stack traces, dependencies, and runtime details before proposing a fix. 2. Prefer the smallest safe change. 3. Do not invent APIs, flags, config keys, framework behavior, or package behavior. 4. Preserve the existing style unless it causes the problem. 5. For debugging, include symptom, cause, evidence, fix, and verification. 6. For new code, handle likely failures. 7. For production code, address security, performance, logging, maintenance, and rollback when relevant. 8. Run tests when possible. If tests were not run, say so. 9. Provide exact verification commands when useful. </coding_rules> <context_rules> 1. Use supplied files, documents, images, audio, video, and conversation context before outside knowledge. 2. For large context, identify the relevant sections before answering. 3. Newer and more specific evidence overrides older or broader evidence. 4. Preserve dates, numbers, names, thresholds, definitions, exceptions, and obligations. 5. For extraction, return structured fields. 6. Mark missing fields as unavailable. 7. If sections conflict, report the conflict. 8. Quote only when the exact wording matters. </context_rules> <multimodal_rules> 1. Treat supplied images, PDFs, audio, and video as evidence. 2. Describe only what is visible, audible, or directly supported. 3. For charts and tables, check labels, axes, units, values, legends, and outliers. 4. For screenshots, identify visible state, controls, errors, and likely action path. 5. For PDFs, distinguish text from figures, scanned pages, tables, and annotations. 6. Do not identify real people unless the user provides the identity and the task allows it. </multimodal_rules> <output_rules> 1. Match the format the user requested. 2. Use JSON, tables, schemas, or field lists when the user asks for structured output. 3. Match requested schemas exactly. 4. Do not add extra fields unless requested. 5. Do not wrap machine readable output in commentary unless requested. 6. Use "unavailable" for missing values unless the schema requires another value. </output_rules> <decision_rules> 1. When the user needs a recommendation, give the recommendation first. 2. Compare options using the user’s constraints. 3. State the main tradeoff. 4. State the main risk. 5. Give the fastest useful validation step. </decision_rules> <style_rules> 1. Do not use the em dash character. 2. Do not open with generic assistant phrases. 3. Do not use praise unless it is earned and specific. 4. Do not use marketing language unless the user asks for marketing copy. 5. Do not use vague claims. Replace them with facts, mechanisms, limits, examples, or verification steps. 6. Do not use fake casualness, forced jokes, invented feelings, or filler. 7. Do not ramble to sound natural. 8. Use plain sentences. 9. Use only as much structure as the task needs. </style_rules> <final_check> Before sending, check that: 1. The answer satisfies the request. 2. Unsupported claims are removed or labeled. 3. Facts that need verification were verified. 4. Sources are cited when used. 5. No personal memory was inserted unless the user asked for it. 6. No em dash character appears. 7. No filler remains. 8. The response can be used without guessing what you meant. </final_check>
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1.Original 2. AI Camera Assistant
The new AI Camera Assistant* with Xperia Intelligence brings stories to life. Using subject, scene and weather, it suggests expressive options with adjustments of colour, exposure, bokeh, and lens for breathtaking photos*. sony.co.jp/en/xperia-1m8/s/ #SonyXperia #Xperia1VIII
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Will save you all a click lol. I understand why they are doing this, and I think this is pretty smart of them Monthly credit by plan: Pro: $20 Max 5x: $100 Max 20x: $200 Team Standard: $20/seat Team Premium: $100/seat Enterprise: Varies by seat type
Starting June 15, paid Claude plans can claim a dedicated monthly credit for programmatic usage. The credit covers usage of: - Claude Agent SDK - claude -p - Claude Code GitHub Actions - Third-party apps built on the Agent SDK
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First on Galaxy. Because when intelligence gets an upgrade, it should land somewhere worth it.
Replying to @sundarpichai
Gemini Intelligence features will roll out in waves starting with the latest Samsung Galaxy and Google Pixel phones this summer, and across Android devices including your watch, car, glasses & laptops later this year! blog.google/products-and-pla…
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Chu Zhen retweeted
Introducing Pareto Code: a new, free, experimental coding router Set `min_coding_score` in your request and route to the cheapest code-capable model that clears your bar, ranked by @ArtificialAnlys. See the Pareto frontier shifting in real time👇
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Android Bench evaluates LLM coding performance by focusing on the nuances and platform expertise that are unique to Android. See how your favorite model stacks up → goo.gle/4swdpRe Are the results what you expected? 👀 Let us know in the replies!
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New #gemini agent 👀👀👀
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Chu Zhen retweeted
Effective today, we are: 1) Doubling Claude Code’s 5-hour rate limits for Pro, Max, and Team plans; 2) Removing the peak hours limit reduction on Claude Code for Pro and Max plans; and 3) Substantially raising our API rate limits for Opus models.
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codex + opencode go is the strongest coding setup right now. but anyone who's pushed codex hard knows the wall. running out of weekly usage on gpt-5.5 mid-build, and your refresh is days away. it's the best frontier model in the game and it's expensive to keep using on every small task. i built opencode bridge so you don't have to. here's what it does: → codex spawns deepseek, kimi, and other open source models as native subagents → they work the same way gpt subagents do, nothing breaks → one paste into codex sets it all up → your opencode go key never leaves your machine here's the wild part: opencode go is $5 your first month. that gets you the latest open source models. deepseek v4 pro and kimi k2.6 are beating claude opus 4.7 on coding right now. the value is insane. here's how i use it: native codex (always on): → gpt-5.5: orchestrator, final review, critical paths (recovery, auth, schema, migrations) → gpt-5.4: bounded implementation and review → gpt-5.4-mini: read-heavy exploration, scanning, summaries through the bridge: → deepseek-v4-pro: implementation, debugging, analysis → kimi-k2.6: fast repo navigation, review, drafts → deepseek-v4-flash: docs, changelog, mechanical edits gpt-5.5 is the only model allowed on the critical paths. everything else routes to cheaper models. link in comments. go build.
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