正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

I built software to cut docker image sizes by more than 80%. It uses dynamic analysis and and has a LOT more room for improvement. The demo here shows an ETL workflow docker image, cut down from 1.28GB to 193MB (-85%)! If large docker image sizes are becoming a... show more

omkaar

4,342 subscribers

353,266 次观看 • 1 年前 •via X (Twitter)

教育科学技术新闻政治

Anya Rossi• Live Now

Private livecam show

10 条评论

omkaar 的头像

omkaar1 年前

Read more:

harambe_musk🍌 的头像

harambe_musk🍌1 年前

This tool could come in handy for exploring layers of docker that can be shrinked:

omkaar 的头像

omkaar1 年前

dive is awesome!

vivekb.eth | w.ai 的头像

vivekb.eth | w.ai1 年前

this is a common issue we face when running production containers on GPUs, we don’t even have a model in the image just a lot of dependencies. cool stuff would love to check it out

omkaar 的头像

omkaar1 年前

thats the biggest problem with ML dependencies, they are extensible and bloated + dependencies creates a hoard of unused package. static analysis can only get you so far. would love to chat more if this is a pressing problem. Here is a quick explainer -

Adam M. Smith (史亚当) 的头像

Adam M. Smith (史亚当)1 年前

The idea of watching for which parts of the FS are actually touched during execution reminds me of @playablequotes /

Vasco Lameiras 的头像

Vasco Lameiras1 年前

Interesting, thanks for sharing. I usually settle with distroless

omkaar 的头像

omkaar1 年前

distroless is the next best thing, my tool is more aggressive than distroless

Bobai Kato 的头像

Bobai Kato1 年前

Simply reducing the size of the Docker image and confirming that it “still works fine” is not sufficient to guarantee that the image is free of defects. Could you provide more details on the additional testing methods you have used to validate its functionality and stability?

omkaar 的头像

omkaar1 年前

good question, the ETL tool minimal image did precisely the same transformations as the larger image. For images with broader scope, tests on the application are needed to validate whether functionality is working. luckily, most orgs have tests like this. did you have any other ideas?

相关视频

Quick Image Upscale Tutorial 🧬 If you are doing images in Midjourney and want to really push more pixels out of them, this is for you. Here I start with an 1456 x 816px image End up with a 13104 x 7344px image This is great if you need more pixels 🧪

Quick Image Upscale Tutorial 🧬 If you are doing images in Midjourney and want to really push more pixels out of them, this is for you. Here I start with an 1456 x 816px image End up with a 13104 x 7344px image This is great if you need more pixels 🧪

Linus ✦ Ekenstam

159,711 次观看 • 3 年前

There’s a big difference between generating an ad and producing an ad. Generating gives you footage. Producing means deciding what the shots should be, how they connect, how the pacing feels and what needs to change. GPT Image 2.5 is coming to CapCut and will be available through Design Studio and AI Image. I used it to build the storyboard for an iPhone Duo commercial. Then CapCut PC + Seedance 2.5 took it into video production, with editing and AI-powered refinement after generation. That’s the workflow I find more interesting. #GPTImage25 #CapCutPC #AIVideo #Seedance25

There’s a big difference between generating an ad and producing an ad. Generating gives you footage. Producing means deciding what the shots should be, how they connect, how the pacing feels and what needs to change. GPT Image 2.5 is coming to CapCut and will be available through Design Studio and AI Image. I used it to build the storyboard for an iPhone Duo commercial. Then CapCut PC + Seedance 2.5 took it into video production, with editing and AI-powered refinement after generation. That’s the workflow I find more interesting. #GPTImage25 #CapCutPC #AIVideo #Seedance25

MR. ANDERSION Official

24,118 次观看 • 21 天前

P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference shell | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro AI — Ship AI Faster | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.

P-Image-Upscale is the fastest and cheapest image upscaler in the world: supporting outputs up to 128 MP under 1 seconds. A couple of weeks ago we released p-image-upscale, and it now works better than ever. It’s the fastest image upscaler in the world, supporting outputs up to 128 MP while keeping pricing simple and predictable: - $0.005/image for 1–4 MP - $0.01/image for 4–8 MP - $0.02/image for 8–16 MP - $0.04/image for 16–32 MP - $0.06/image for 32–64 MP - $0.12/image for 64–128 MP That means you can go from low-res input to production-ready output with extreme speed, while preserving detail and keeping costs easy to understand. Available on: - Pruna AI | - each::labs | - inference shell | - Replicate | - Runware | - Segmind | - WaveSpeedAI | - Wiro AI — Ship AI Faster | If you’re building workflows where image quality, price, latency, and scale all matter, p-image-upscale is built for you.

Pruna AI

24,089 次观看 • 4 个月前

How can we help *any* image-input policy generalize better? 👉 Meet PEEK 🤖 — a framework that uses VLMs to decide *where* to look and *what* to do, so downstream policies — from ACT, 3D-DA, or even π₀ — generalize more effectively! 🧵

How can we help any image-input policy generalize better? 👉 Meet PEEK 🤖 — a framework that uses VLMs to decide where to look and what to do, so downstream policies — from ACT, 3D-DA, or even π₀ — generalize more effectively! 🧵

Jesse Zhang

13,825 次观看 • 11 个月前

It's June 16. My birthday. So I built a Mini version of Kubernetes. You give it a container image → it schedules it, pulls it, runs it, and tracks its lifecycle. What it does: - Submit jobs via a REST API - Move jobs through SUBMITTED → RUNNABLE → RUNNING → SUCCEEDED / FAILED - Pull container images and run real Docker containers - Persist state in Postgres - Use BullMQ + Valkey for scheduling and execution Building this from scratch gave me a much deeper appreciation for how orchestration systems work behind the scenes. There's still plenty to improve, but seeing the control loop model in action was incredibly satisfying. Stack: Node.js · TypeScript · Express · BullMQ · Valkey · Postgres · Docker · Drizzle Not a bad way to spend a birthday. 🎂

It's June 16. My birthday. So I built a Mini version of Kubernetes. You give it a container image → it schedules it, pulls it, runs it, and tracks its lifecycle. What it does: - Submit jobs via a REST API - Move jobs through SUBMITTED → RUNNABLE → RUNNING → SUCCEEDED / FAILED - Pull container images and run real Docker containers - Persist state in Postgres - Use BullMQ + Valkey for scheduling and execution Building this from scratch gave me a much deeper appreciation for how orchestration systems work behind the scenes. There's still plenty to improve, but seeing the control loop model in action was incredibly satisfying. Stack: Node.js · TypeScript · Express · BullMQ · Valkey · Postgres · Docker · Drizzle Not a bad way to spend a birthday. 🎂

Pankaj Kumar

12,510 次观看 • 3 个月前

Cognition’s Scott Wu: “If anything, there’s going to be a lot more software engineers. Everyone talks about Jevons paradox and how it relates to AI; I think there’s nowhere that it’s more true than software, because we really never seem to run out of demand for more code and more software.”

Cognition’s Scott Wu: “If anything, there’s going to be a lot more software engineers. Everyone talks about Jevons paradox and how it relates to AI; I think there’s nowhere that it’s more true than software, because we really never seem to run out of demand for more code and more software.”

Stripe

15,819 次观看 • 1 年前

I gave GPT Image 2.5 an iPhone Duo commercial concept instead of asking for one standalone image. The interesting result was the storyboard. GPT Image 2.5 is coming to CapCut, where it will be available through Design Studio and AI Image. That means the visual planning stage can connect directly with the rest of the creative workflow. Start with the product idea → build the storyboard → move into video production → refine with AI Edit. If one scene feels off, you can keep working from the same creative direction instead of rebuilding everything. That feels much closer to commercial production than one-shot generation. #GPTImage25 #CapCutPC #AIVideo #Seedance25

I gave GPT Image 2.5 an iPhone Duo commercial concept instead of asking for one standalone image. The interesting result was the storyboard. GPT Image 2.5 is coming to CapCut, where it will be available through Design Studio and AI Image. That means the visual planning stage can connect directly with the rest of the creative workflow. Start with the product idea → build the storyboard → move into video production → refine with AI Edit. If one scene feels off, you can keep working from the same creative direction instead of rebuilding everything. That feels much closer to commercial production than one-shot generation. #GPTImage25 #CapCutPC #AIVideo #Seedance25

Kuria | AI

11,854 次观看 • 21 天前

Just tested Kling AI 2.5 Turbo with Start–End Frame, and the improvement is real, higher fidelity, cleaner consistency from start to finish, and motion that feels more controlled and cinematic. Definitely a solid step forward for AI video. For filmmakers, this update pushes the workflow closer to real production. Base image Freepik (now Magnific)

Just tested Kling AI 2.5 Turbo with Start–End Frame, and the improvement is real, higher fidelity, cleaner consistency from start to finish, and motion that feels more controlled and cinematic. Definitely a solid step forward for AI video. For filmmakers, this update pushes the workflow closer to real production. Base image Freepik (now Magnific)

Dinda Prasetyo

26,526 次观看 • 10 个月前

Grok Imagine’s image editing literally blows my mind I just edited this entire image from scratch using Grok Imagine and its full set of editing tools The segment + precise editing tools are insanely useful Instead of regenerating the entire image, you can target exactly what you want to change while keeping everything else intact That level of control makes editing much faster and more practical Grok Imagine is becoming a seriously powerful image editor….not just an image generator

Grok Imagine’s image editing literally blows my mind I just edited this entire image from scratch using Grok Imagine and its full set of editing tools The segment + precise editing tools are insanely useful Instead of regenerating the entire image, you can target exactly what you want to change while keeping everything else intact That level of control makes editing much faster and more practical Grok Imagine is becoming a seriously powerful image editor….not just an image generator

X Freeze

4,152,602 次观看 • 1 个月前

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

Tencent Hy

413,175 次观看 • 1 年前

We are thrilled to announce "Layered Diffusion Brushes": a real-time training-free image editor powered by diffusion models. 🎨✨ This is new work from my PhD student Peyman Gholami Peyman Gholami. Explore the interactive demo and check out more videos at:

We are thrilled to announce "Layered Diffusion Brushes": a real-time training-free image editor powered by diffusion models. 🎨✨ This is new work from my PhD student Peyman Gholami Peyman Gholami. Explore the interactive demo and check out more videos at:

Robert Xiao

14,334 次观看 • 2 年前

Hollywood is part of L.A.’s identity. The entertainment industry should be able to thrive in the city that built it. That’s why I cut filming fees, reduced unnecessary production costs, and reopened city buildings for filming to help keep jobs and production in Los Angeles. There’s still a lot more work to do, but we’re finally seeing an uptick in production in L.A.

Hollywood is part of L.A.’s identity. The entertainment industry should be able to thrive in the city that built it. That’s why I cut filming fees, reduced unnecessary production costs, and reopened city buildings for filming to help keep jobs and production in Los Angeles. There’s still a lot more work to do, but we’re finally seeing an uptick in production in L.A.

Karen Bass

151,193 次观看 • 4 个月前

We’re hiring at Deep Piction 🧠🔬 We are looking for a Scientist – Tissue Clearing & Image Analysis (m/f/d) to join our team in Munich. You will help drive tissue-clearing, light-sheet microscopy, and quantitative 3D imaging projects across internal R&D programs and collaborations with biotechnology and pharmaceutical partners. The role combines hands-on experimental work, project ownership, workflow development, and close collaboration with our AI and image-analysis teams. We’re looking for someone with strong experience in tissue clearing, fluorescence microscopy, light-sheet imaging, and large-scale 3D image analysis. Please apply with one single PDF containing your CV and cover letter to: hr@deeppiction.com Subject: Scientist – Tissue Clearing & Image Analysis (DP-TC-2026-01) Applications will be reviewed on a rolling basis until the position is filled.

We’re hiring at Deep Piction 🧠🔬 We are looking for a Scientist – Tissue Clearing & Image Analysis (m/f/d) to join our team in Munich. You will help drive tissue-clearing, light-sheet microscopy, and quantitative 3D imaging projects across internal R&D programs and collaborations with biotechnology and pharmaceutical partners. The role combines hands-on experimental work, project ownership, workflow development, and close collaboration with our AI and image-analysis teams. We’re looking for someone with strong experience in tissue clearing, fluorescence microscopy, light-sheet imaging, and large-scale 3D image analysis. Please apply with one single PDF containing your CV and cover letter to: [email protected] Subject: Scientist – Tissue Clearing & Image Analysis (DP-TC-2026-01) Applications will be reviewed on a rolling basis until the position is filled.

Ali Max Erturk

11,166 次观看 • 2 个月前

ComfyUI Tutorial for Beginners: Text-to-Image & Image-to-Image Workflows One graph, two workflows and Module 2 is where you build it node by node instead of loading someone else's. We start from a blank canvas and wire every connection, then change a single value and turn the same graph into image-to-image. What you'll learn: → The 5 core nodes, connected one at a time — checkpoint, CLIP encode, KSampler, empty latent, VAE decode → Why the data flows the way it does, not just where the wires go → Every KSampler setting: seed, steps, CFG, sampler, scheduler → Denoise from 0.9 to 0.0 — the one value that decides how much of your source survives → Locking seeds and generating takes instead of chasing one perfect image → Preview vs. save, and why every image carries the graph that made it → Reopen any result in your asset library as a live workflow → The 6 errors that break Comfy most often → How to read a red node like a sentence Click the links below to run the workflow ⬇️

ComfyUI Tutorial for Beginners: Text-to-Image & Image-to-Image Workflows One graph, two workflows and Module 2 is where you build it node by node instead of loading someone else's. We start from a blank canvas and wire every connection, then change a single value and turn the same graph into image-to-image. What you'll learn: → The 5 core nodes, connected one at a time — checkpoint, CLIP encode, KSampler, empty latent, VAE decode → Why the data flows the way it does, not just where the wires go → Every KSampler setting: seed, steps, CFG, sampler, scheduler → Denoise from 0.9 to 0.0 — the one value that decides how much of your source survives → Locking seeds and generating takes instead of chasing one perfect image → Preview vs. save, and why every image carries the graph that made it → Reopen any result in your asset library as a live workflow → The 6 errors that break Comfy most often → How to read a red node like a sentence Click the links below to run the workflow ⬇️

ComfyUI

58,853 次观看 • 1 个月前

This could be a pretty big shift for small brands. You don't always need a full production setup to test a product ad anymore. GPT Image 2.5 is coming to CapCut, where it will be available through Design Studio and AI Image. I used it to create two product visuals, then took those images into CapCut PC and generated a commercial with Seedance 2.5. From there, the video can be edited and refined like any other commercial project. The workflow is basically: Product → Visuals → Video → Ad. That’s a much more practical use of generative AI. #GPTImage25 #CapCutPC #AIVideo #Seedance25

This could be a pretty big shift for small brands. You don't always need a full production setup to test a product ad anymore. GPT Image 2.5 is coming to CapCut, where it will be available through Design Studio and AI Image. I used it to create two product visuals, then took those images into CapCut PC and generated a commercial with Seedance 2.5. From there, the video can be edited and refined like any other commercial project. The workflow is basically: Product → Visuals → Video → Ad. That’s a much more practical use of generative AI. #GPTImage25 #CapCutPC #AIVideo #Seedance25

Nyama Quarter

89,570 次观看 • 18 天前