与「Seed」相关的搜索结果

Meta's deal to buy Manus got blocked, so I gave Meta's Muse a Manus 2.0-style launch film instead. Left: the official Manus film. Right: Claude Opus 5.5 + Seedance 2.5 from one URL. (Unofficial concept.) Want one for your product? Reply with your URL. First 5 are free.

Manus 2.0 的发布视频太火🔥了，你也想做一个吗？我给 @elonmusk 的Grok Bot做了一个。 - 左边：Manus 2.0 官方发布片。 - 右边：Grok Bot的 Manus 风格宣传片 使用Claude Opus 5.5 + Seedance 2.5，给到产品链接做能做出来。 想给你的产品也做一支？评论区留链接，我挑5个产品免费帮忙出 Launch Video。

Opus 5.5 非常优质的卡点 《凯尔经的秘密》原片配乐 这套的逻辑是 首先用MJ出图，把画风固定为凯尔经秘密风格 然后出视频， seedance出视频（但是太他妈贵） 先对整个画面的内容要有一个安排 然后来计划出一些首尾帧 然后有opus 5.5来控制整个节奏 把音乐的音轨拆成函数 再把对应的函数和视频拆开的每一帧 按照音乐的函数来控制画面播放 每一帧，都是时间的函数 这个能力是opus特别厉害的一个能力

The Manual, page 3: building a basket. Pick up to 18 assets: majors, xStocks, memecoins. Set the weights. Seed its liquidity with 10+ SOL, matched in its basket token. It starts as New, with a 7-day lock countdown. The day a coin on it graduates, it becomes Verified.

12/12｜BEAT RUSH：AI 舞者＋代码音游特效 英文、16:9、高能街机舞蹈：先用 Seedance 生成跳舞的动漫角色，再用代码制作节奏游戏画面和卡点效果。 需要：这一条明确要接 Seedance。Opus / Sonnet 负责策划、代码和合成；舞者视频由 Seedance 生成，还要准备音乐并对齐节拍。 12 条看下来，Prompt 定方向，实际成片还取决于素材、工具和后续迭代。 完整 Prompt： Create a high-energy arcade dance video in English and 16:9. Use Seedance to generate a dancing anime character, then use code to build the rhythm-game visuals and beat-synced effects.

8/12｜Creative Montage：展示剪辑和编码能力的混剪 素材丰富、不重复镜头，英文呈现，声音一直照顾到结尾，把重点放在后段更强的高潮。 需要：可用的视频/图片素材、剪辑合成和音频。Opus / Sonnet 可编排镜头、转场与代码动效；若素材不够，再考虑接 Seedance 等工具补镜头，原 Prompt 没有强制要求生成视频。 完整 Prompt： Create an impressive montage that shows off your editing and coding abilities. Use rich, varied material without repeating shots, with polished English presentation and sound through the ending. Focus the edit on the stronger climax in the later part.

2/12｜Emberkeep：游戏预告片 英文预告，面向 X；前两秒抓住注意力，精修画面，去掉底部进度条。 需要：游戏画面/素材、剪辑和音频。Opus / Sonnet 可负责策划、代码与剪辑编排；缺少镜头时可接 Seedance 等视频模型，音乐音效另备。原 Prompt 没指定视频模型，也没提供完整游戏设定。 完整 Prompt： Create a polished English trailer for an original game, made for sharing on X. Open with a striking hook in the first two seconds, make the visuals more refined, and remove the bottom progress bar. Generated music and sound effects are welcome.

Higgsfield is the most untold story in tech. $1BN in ARR in 18 months. Faster than everyone other than OpenAI and Anthropic. They spend $4M a month on models. They expect this to be $100K per person per month. They have 150 people working in a content machine. They will breed more millionaires than any other company in Kazakh history. For the first time, @alexmashrabov on the journey to $1BN in ARR. (below) 1. The Power of the Immigrant Founder Coming from Uzbekistan, Alex was pushed into competitive programming at age eight as his single path to reach the United States. For international founders, placing top in global competitions serves as the ultimate social elevator, instilling the relentless work ethic required to build breakout companies. 2. My Biggest Lessons in the Journey to Finding Product-Market Fit @higgsfield burned over $10 million of its $16 million seed round chasing hype and narrative rather than product quality. With under $5 million left, the team pivoted to product-led growth, solving camera control for creative directors, which immediately triggered organic hypergrowth without paid ads. 3. The 150-Person Content Team Powering Higgsfield's Billion in ARR Nearly half of Higgsfield's workforce consists of 150 in-house creative professionals producing tutorials, ads, and cinematic projects. Generating 90 minutes of TV-quality AI video requires 100 hours of raw output, proving human taste and curation remain the primary drivers of distribution. 4. We Spend $4 Million per Month on Models Higgsfield spends $4 million monthly on internal model usage, averaging $10,000 per employee so teams can freely vibe code and test workflows. Uncapped inference compute acts as a force multiplier, allowing top talent to discover breakthroughs at maximum velocity. 5. Why Chasing Benchmarks Is Bullshit and the Corporate Misalignment Occurring Public benchmarks have devolved into corporate psyops where lab researchers overfit test data to secure bonuses before job-hopping. Text-to-video benchmarks ignore real production workflows requiring 3,000-word prompts, proving direct customer iteration beats artificial leaderboards. 6. Why Team Sizes Won't Be Impacted as Much as People Think While AI handles over 60% of basic support requests, complex B2B environments cannot eliminate human teams. High product velocity constantly shifts rules and context, requiring smart, coordinated operators across legal and customer success. 7. Americans Are Way More Promiscuous When It Comes to Leaving Companies Silicon Valley workers routinely jump jobs every two years, prioritizing short-term trends over deep commitment. This transactional market gives international hubs an advantage, where cultural loyalty and team stability build compounding technical moats. (links in comments)

Crypto scams are getting smarter. 🔒 Never share your seed phrase 🎁 Real giveaways never ask for funds first 📱 Use official sources only ⚠️ Guaranteed returns are a red flag Stay informed. Stay skeptical. 👇