earshot v0.3 is out!
added:
- a library of 201 sounds, all made with code
- earshot kit can create a whole sound kit
- earshot sfx times a sound to the exact frame (improved)
plus earshot is now used in cinetic (skill for creating motion design)
will continue improving it!
Procrastination has met its match. ChatGPT is now in Word.
You can add ChatGPT to Microsoft Word to turn rough notes into first drafts, untangle tricky paragraphs, proofread, and get suggested edits—all without leaving your document.
It can even spot formatting issues. Which means a few less things to fix later 🔍
Mapas retweeted
GLM-5.3-Flash (320B MoE) serving on Kaggle's free TPU: ~64 tok/s, 262k context.
No stack could run this model on a TPU, so I wrote
a JAX engine for it: 3-bit experts (from @UnslothAI) in HBM; Pallas kernels decode them inside the matmul.
github.com/ARahim3/kaggle-tp…
@Zai_org @kaggle
Mapas retweeted
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient.
🔹 Introducing the smallest model in our new architecture family, with native visual understanding.
🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models.
1/6
Introducing GLM-5.3-Flash
- Leading capabilities at a highly competitive price
- Natively multimodal with a 1M-token context window
- A 320B-A18B model released under the MIT License
- Previously previewed as Ox Alpha, running entirely on Chinese AI chips
Blog: z.ai/blog/glm-5.3-flash
Available now across all official platforms:
Weights: huggingface.co/zai-org/GLM-5…
API: docs.z.ai/guides/llm/glm-5.3…
Coding Plan: z.ai/subscribe
ZCode: zcode.z.ai/en
Chat: chat.z.ai
AutoClaw: autoclaw.z.ai
Mapas retweeted
Prompt share: Quirky Editorial Sketch
💬Prompt: A simple illustration of a [subject] wearing [outfit], [doing action], with a [facial expression] expression. Playful hand-drawn linework, quirky character design, minimal details, expressive body language, whimsical personality, clean white background, and charming editorial illustration aesthetic inspired by Gemma Correll.
Try it and share yours 🔥
Mapas retweeted
Un abogado pierde una semana en un contrato de 500 páginas.
Un contador, cuatro días en 200 facturas.
Un investigador, dos semanas en 50 PDFs.
Todos copiando y pegando.
MinerU lo cambia todo.
Herramienta gratuita y open source que convierte cualquier PDF, Word, Excel o imagen escaneada en Markdown limpio en segundos:
• Texto en orden correcto
• Tablas en HTML
• Ecuaciones en LaTeX
• OCR potente
• 109 idiomas
Un PDF de 200 páginas → Markdown perfecto en 90 segundos.
Funciona en CLI, Python o web (mineru.net). Corre en tu PC. 100% privado.
Más de 68.000 estrellas en GitHub.
La abogada: contrato listo en 4 min.
El contador: 200 facturas en 12 min.
El investigador: revisión lista en una tarde.
Adiós papeleo manual. Bienvenido tu tiempo.
Introducing LFM2.5-230M: our smallest model yet, built to run fast anywhere (CPUs, NPUs, and GPUs) to enable agentic tasks on phones, robots, home and network automation devices.
> 230M parameters, built on the LFM2 architecture
> Pre-trained on 19T tokens, with a 32K context extension
> Post-trained with distillation from LFM2.5-350M
> 213 tok/s decode speed on Galaxy S25 Ultra (CPU)
> 42 tok/s on a Raspberry Pi 5 (CPU)
> Competes with and often beats models more than twice its size on instruction following, data extraction, and tool use.
> use it for large-scale data extraction pipelines or lightweight on-device agentic workloads.
🧵
Aloha! 🌺 Meet Ornith-1.0, a family of open-source LLMs specialized for agentic coding.
Ornith-1.0 spans the full parameter sizes including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. It achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks including:
✅Terminal-Bench 2.1(77.5)
✅SWE-Bench(82.4 on verified, 62.2 on pro, 78.9 on Multilingual)
✅NL2Repo(48.2)
✅SWE Atlas(41.2 on QnA, 42.6 RF, 39.1 TW)
✅ClawEval(77.1)
Post-trained on top of gemma4 and qwen3.5, Ornith-1.0 employs a novel self-improving training strategy in which reinforcement learning is used to generate not only solution rollouts, but also the task-specific scaffolds that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model generate higher-quality solutions in agentic coding.😎
All models are released under the MIT license, enabling full commercial and research use.
📖Tech Blog: deep-reinforce.com/ornith_1_…
🤗Huggingface: huggingface.co/collections/d…
Mapas retweeted
SIFIR KOD BİLGİSİ İLE 3D WEB SİTESİ OLUŞTUR.
Claude ile sadece 12 dakikada etkileyici 3D web siteleri oluşturabilirsiniz.
> 3D web sitesi.
> modern animasyonlar.
> profesyonel görünüm.
> sıfır tasarım bilgisiyle.
işte adım adım süreç:
GLM-5.2 is free when used with Hugging Face Inference Providers for the next 5 hours:
huggingface.co/zai-org/GLM-5…
Open source MUST win 🔥
GLM-5.2 is free when used with Hugging Face Inference Providers and for every available provider for the next 6 hours (Zai, Together AI, Novita, Fireworks, DeepInfra) the cost is on us.
Set it up with Pi, opencode, Codex, Claude Code or any coding agent to understand why people are saying open source has caught up 🔥
Mapas retweeted
兄弟们,我一直有个判断:OCR 这种活,早晚会被多模态大模型给吃掉。
这周看到百度发的 PP-OCRv6,我改主意了。
一个 1.5MB 的模型,能直接塞进浏览器里跑,单图最快 97 毫秒就能出结果,逐字识别的准确率还反超了 GPT-5.5、Gemini-3.1-Pro 和 235B 参数的 Qwen3-VL,我有点震惊了!
对做产品的人来说,这比「又一个 SOTA」重要得多。我有测试,先往下看 👇
🤝 Paid partnership
Mapas retweeted
把一个大字放到人物「后面」,这个人立刻就变成了杂志封面人物。
不是因为他有多有名——是因为你的眼睛会自动读出一个「层次」:背景字 → 人物 → 你。这层纵深感,就是 GQ、Vogue、Sports Illustrated 封面用了几十年的老招:让主体站到标题前面,ta 就自动拥有了「封面主角」的待遇。
这个技巧叫「文字穿插」——人物遮住字母的一部分,平面瞬间变立体。上一批运动海报(RISE/READY)是让人物「冲出画框」;这一批是让人物「站到字前面」。方向反了,效果一样猛。
而这 4 张还是同一套模板:风格锁死(全幅动作照 + 超大奶色镂空字母藏在人物身后 + 蓝天主色 + 角落编辑体小字 + 底栏三词标签),换的只是「谁在动、动作是什么、配哪个词」。模板抄走直接用——
{
"style_name": "Sunlit Kinetic Block Type Photo Poster",
"style_slug": "sunlit-kinetic-block-type-photo-poster-style",
"style_version": "2.1.0",
"style_summary": "A high-energy editorial sports and lifestyle poster style built from full-bleed sunlit photography, oversized cream condensed block typography, diagonal subject crops, compact microcopy clusters, and vivid blue-sky color fields.",
"environment_variables": {
"SUBJECT": "main subject",
"SUBJECT_ACTION": "main action",
"PRODUCT_OR_PROP": "object, product, or prop",
"LOCATION": "environment or setting",
"BACKGROUND_ELEMENTS": "secondary scene details",
"MAIN_TEXT": "main headline or graphic text",
"SECONDARY_TEXT": "small repeated supporting text",
"ACCENT_SYMBOL": "separator or decorative symbol",
"WARDROBE_STYLE": "styling direction",
"STYLE_FIDELITY_ANCHORS": "observable style traits that must remain visible",
"SOURCE_CONTENT_TO_AVOID": "literal source content that generated samples must not recreate",
"ASPECT_RATIO": "9:16 or 16:9"
},
CUT / MOVE / FRESH / SHIFT——如果你是杂志封面,你的那个字会是什么?
🤖 Made with AI
当所有人都在让 AI 出更复杂、更逼真、更炸裂的图时——试试反过来:只给它三种颜色。
黑线、一抹蓝、一点红。一个物件、一个动词、一句小字。没了。
结果?越少,越像「某个人画的」。因为克制本身就是风格——它在说「我知道可以加更多,但我选择不加」。这种「选择不加」的感觉,就是 AI 图最难伪造的东西:审美判断。
Prompt 的高阶操作不是往里塞更多描述,是知道该删掉什么。
而这 4 张还是同一套模板:风格锁死(奶白纸底 + 手绘黑线框 + 蓝色填充 + 红色手写标签 + 单个日常物件 + 右下角小字注释 + 版画颗粒感),换的只是「画什么物件、配哪个动词」。模板抄走直接用——
{
"style_name": "Loose Scribble Riso Print Style",
"style_slug": "loose-scribble-riso-print-style",
"style_version": "1.0.0",
"style_summary": "A sparse handmade riso or screenprint poster style with one large simplified subject, wavering black contour drawing, rough off-white paper, flat blue and coral-red overprint accents, handwritten margin text, and visible print grain.",
"environment_variables": {
"SUBJECT": "The new main subject or simplified object for the print.",
"SUBJECT_ACTION": "The simple pose, placement, or action of the subject.",
"PRODUCT_OR_PROP": "A small supporting prop or object detail that is not the original source prop.",
"LOCATION": "A minimal setting or surface that grounds the subject.",
"BACKGROUND_ELEMENTS": "Sparse background details such as a border, ground line, paper speckles, or one small accent mark.",
"MAIN_TEXT": "A short handmade phrase to place near the margin.",
"SECONDARY_TEXT": "Tiny supporting handwritten text or edition-like microcopy that does not mimic the source identity marks.",
"ACCENT_SYMBOL": "One small decorative mark, scribble, star, arrow, dot, or stamp-like accent.",
"WARDROBE_STYLE": "Styling direction for any character or object treatment, kept flat and handmade.",
"STYLE_FIDELITY_ANCHORS": "Observable style traits that must remain visible in the generated sample.",
"SOURCE_CONTENT_TO_AVOID": "Literal source content that generated samples must not recreate.",
"ASPECT_RATIO": "9:16 or 16:9"
},
雨后的伞、深夜的灯、桌上的收音机、一包种子——哪个最像你此刻的状态?
Mapas retweeted
🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced!
🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite.
🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6.
🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates.
⚡️ 6x High-Speed Mode coming soon!
🔌 Available today via Kimi API and Kimi Code.
🔗 Kimi Code: kimi.com/code
🔗 API: platform.moonshot.ai













































