AI video is having its Stable Diffusion moment
There are lots of models that are as good as OpenAI's Sora now.
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MemoAIMusic & audio
Open DesignDesign & 3D
KiroCoding & development
JAXModels & infrastructure
AI ShortWriting & content
EvoMapAgents & automation
Meta AI助手Assistants & search
闪剪Video & animation
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MemoAIMusic & audioMemoAI is an AI-powered audio-to-text tool that supports localized processing, eliminating the need to upload data and ensuring privacy and security. It can efficiently transcribe YouTube videos, podcasts, and local audio/video files (such as MP4, MP3, AAC, M4A, etc.) into text, while offering core features like multilingual translation, speaker diarization, real-time subtitles, and floating notes—making it ideal for meeting minutes, interview transcription, content learning, and more.
分类推荐榜首OOpen DesignDesign & 3DOpenDesign is an open-source design workspace that can connect to local programming agents, use built-in model keys, or leverage cloud-based models, enabling the creation and editing of prototypes, web pages, presentations, and graphics within a design system; local software is free, while model services incur fees.
分类推荐榜首KKiroCoding & developmentKiro is an AI engineering tool for developers that organizes requirements into specifications, architectures, and tasks, generates code via agents, and supports the entire workflow—from planning to code review—through property-based testing, execution memory, and integration with development tools.
分类推荐榜首JJAXModels & infrastructureJAX is a Python numerical computing library designed for accelerators, specifically tailored for high-performance array computations and large-scale machine learning. It efficiently executes the same code across multiple hardware backends, including CPUs, GPUs, and TPUs.
分类推荐榜首AAI ShortWriting & contentAIS ALERT MANAGEMENT AND SHARED PLATFORM, QUICK COMMAND FOR MULTIPLE SCENARIOS
分类推荐榜首EEvoMapAgents & automationEvoMap is an infrastructure designed for the reuse of AI agent experiences. It organizes reusable strategies and repair assets with validation records via the GEP protocol, offering market- and quality-based ranking to help different agents discover, evaluate, and inherit existing capabilities.
分类推荐榜首MMeta AI助手Assistants & searchMeta's free AI chat assistant
待评分 · 分类列表推荐闪FlashCut is an AI-powered creation platform for voice-over and short-video marketing. It can generate finished videos with voiceovers, subtitles, and visuals from text, offering digital human customization, photo-to-digital-human conversion, live-stream clipping, and intelligent editing. It also provides APIs and branded mini-program solutions for businesses.
待评分 · 分类列表推荐ZZoom Workplace is Zoom’s team collaboration platform, integrating video conferencing, chat, calendars, and documents, and leveraging built-in AI to organize discussions, draft messages, and track follow-up tasks.
待评分 · 分类列表推荐MMy Glow Up AILife & personalMy Glow Up AI provides free analysis based on selfies, without requiring registration, and can generate hairstyle recommendations and beauty plans that suit you.
待评分 · 分类列表推荐AI, as it happens
1128 published storiesImage generation · 23 storiesClear filters ×
2026-11-04
Follow the timelineCreative roundup: avatars, lightsabers, and LoRA tricks
We take a quick look at the latest creative models, experiments, and community projects.
Easel AI is now on Replicate
Advanced face swap and AI avatars from Easel AI are now on Replicate.
FLUX.1 Tools – Control and steerability for FLUX
A new set of image generation capabilities for FLUX models, including inpainting, outpainting, canny edge detection, and depth maps.
FLUX fine-tunes are now fast
We've made running fine-tunes on Replicate much faster, and the optimizations are open-source.
FLUX is fast and it's open source
FLUX is now much faster on Replicate, and we’ve made our optimizations open-source so you can see exactly how they work and build upon them.
Generate incredible images with Google's Imagen 4
Google's flagship image generation model, Imagen 4, is now available for you to try on Replicate. Create images with fine detail, versatile styles, and improved typography.
Generate short videos with the Replicate playground
Create AI videos with a convenient workflow.
NVIDIA H100 GPUs are here
NVIDIA H100 GPUs are here, with better performance and lower cost.
Run 30,000+ LoRAs on Hugging Face with Replicate
We've partnered with Hugging Face to bring Replicate inference to their platform.
Run MiniMax Speech-02 models with an API
MiniMax's Speech-02 models give you high-quality text-to-speech with voice cloning, emotional expression, and multilingual support.
Stylized video with Wan2.1
One of the most fun ways to use Wan2.1 is video style transfer. Learn how here.
Wan2.1: generate videos with an API
Wan2.1 is the most capable open-source video generation model, producing coherent and high-quality outputs. Learn how to run it in the cloud with a single line of code.
Wan2.1 parameter sweep
We've been playing with Alibaba's WAN2.1 text-to-video model lately. What happens when you tweak those mysterious parameters? Let's find out.
You can now fine-tune open-source video models
Train your own versions of Tencent's HunyuanVideo for style, motion, and characters on Replicate.
2026-10-27
Follow the timeline12:00
TraceQuery: learning what to recompute from full-denoising trajectory in diffusion language models
arXiv:2610.33008v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) enable flexible generation through iterative masked denoising, but incur substantial inference cost because token representations are repeatedly recomputed across denoising steps. Existing cache-based methods reduce this cost by reusing intermediate results across denoising steps and recomputing only a subset of positions at each step, chosen either on a fixed schedule or by heuristic signals of change. Our trajectory experiments instead point to decoding trajectory as the more relevant quantity. Cached generation remains accurate when it stays close to the full-denoising trajectory, with errors concentrated around unmask-order deviations and reduced as longer reference prefixes are recovered. This sugg
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Oddin: Latent Visual Reasoning in Unified Multimodal Models via Self-Distillation from Image Generation
arXiv:2610.33062v1 Announce Type: new Abstract: Unified large multimodal models (ULMMs) are able to perform visual reasoning through interleaved text-image generation, but generating explicit intermediate images incurs significant computational overhead. While visual latent reasoning addresses this, most existing methods rely on vision-language models (VLMs) incapable of visual generation. We propose Oddin, a novel framework enabling latent visual reasoning in ULMMs. Oddin replaces intermediate images with compact latent tokens processed entirely by the understanding branch, reserving the generation branch for the final output image. We train the model via offline self-distillation with three objectives, final image generation losses, text distillation losses, and cross-entropy losses for
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PhaseBreak: Proactive Temporal Protection against Unauthorized Image-to-Video Animation
arXiv:2610.33070v1 Announce Type: new Abstract: Image-to-Video (I2V) diffusion models can animate a single portrait or photograph, enabling shared images to be repurposed for motion synthesis without the subject's authorization. We study proactive visual protection against such use: before an image is released, its owner applies a bounded perturbation that preserves the sharing workflow but disrupts downstream motion generation. Existing spectral disruption objectives globally attenuate temporal representations and therefore provide limited control over subtle or spatially localized motion. Our key idea is that generated dynamics depend not only on temporal feature strength, but also on the order in which feature events occur. We propose PhaseBreak, a white-box spectral retiming protection
2026-10-26
Follow the timeline12:00
End-to-End Differentiable Diffusion Conditioning for Physics-Informed Optimization
arXiv:2610.31721v1 Announce Type: new Abstract: Optimizing high-dimensional physical systems under expensive evaluations and complex constraints is a central challenge in science and engineering. In offline model-based optimization (MBO), methods must improve designs using only a fixed dataset and no test-time access to the true objective. However, existing methods typically suffer from conservatism, unconstrained surrogate exploitation, or function as static inference-time samplers that cannot refine candidates against precise physical objectives. In this paper, we propose Differentiable Diffusion Conditioning (D2C) for offline MBO, which leverages the fact that deterministic sampling makes the reverse denoising chain differentiable with respect to the conditioning signal. D2C turns a fro
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SyncVid: World-Equivariant Diffusion for Synchronized Video Generation
arXiv:2610.31765v1 Announce Type: new Abstract: Generating multiple videos of a dynamic scene from a single reference video requires synthesizing both observed and unobserved content consistently across viewpoints. Existing camera-control methods for video diffusion typically rely on architectural mechanisms, including camera embeddings, cross-view attention, and geometric conditioning. Although effective for static scene content, these approaches often struggle with the fine-grained, dynamic geometry that must remain coherent across views and over time. We synchronize the diffusion process itself by sampling the Gaussian noise prior in a canonical 3D space derived from the source video and rasterizing it into target cameras, rather than sampling independently in each 2D image plane. Our m
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