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https://stitch.withgoogle.com/
Stitch is available for free of charge with certain usage limits. Each user receives a monthly allowance of 350 generations using Flash mode and 50 generations using Experimental mode. Please note that these limits are subject to change.
https://runwayml.com/news/runway-amc-partnership
Runway and AMC Networks, the international entertainment company known for popular and award-winning titles including MAD MEN, BREAKING BAD, BETTER CALL SAUL, THE WALKING DEAD and ANNE RICE’S INTERVIEW WITH THE VAMPIRE, are partnering to incorporate Runway’s AI models and tools in AMC Networks’ marketing and TV development processes.
https://lumalabs.ai/blog/news/introducing-modify-video
Reimagine any video. Shoot it in post with director-grade control over style, character, and setting. Restyle expressive actions and performances, swap entire worlds, or redesign the frame to your vision.
Shoot once. Shape infinitely.
https://github.com/poloclub/transformer-explainer
Transformer Explainer is an interactive visualization tool designed to help anyone learn how Transformer-based models like GPT work. It runs a live GPT-2 model right in your browser, allowing you to experiment with your own text and observe in real time how internal components and operations of the Transformer work together to predict the next tokens. Try Transformer Explainer at http://poloclub.github.io/transformer-explainer
https://www.linkedin.com/posts/upskydown_vr-googleveo-veo3-activity-7334269406396461059-d8Da
If you prompt for a 360° video in VEO (like literally write “360°” ) it can generate a Monoscopic 360 video, then the next step is to inject the right metadata in your file so you can play it as an actual 360 video.
Once it’s saved with the right Metadata, it will be recognized as an actual 360/VR video, meaning you can just play it in VLC and drag your mouse to look around.
https://replicate.com/blog/flux-kontext
https://replicate.com/black-forest-labs/flux-kontext-pro
There are three models, two are available now, and a third open-weight version is coming soon:
We’re so excited with what Kontext can do, we’ve created a collection of models on Replicate to give you ideas:
the 8 most important model types and what they’re actually built to do: ⬇️
1. 𝗟𝗟𝗠 – 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹
→ Your ChatGPT-style model.
Handles text, predicts the next token, and powers 90% of GenAI hype.
🛠 Use case: content, code, convos.
2. 𝗟𝗖𝗠 – 𝗟𝗮𝘁𝗲𝗻𝘁 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 𝗠𝗼𝗱𝗲𝗹
→ Lightweight, diffusion-style models.
Fast, quantized, and efficient — perfect for real-time or edge deployment.
🛠 Use case: image generation, optimized inference.
3. 𝗟𝗔𝗠 – 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗔𝗰𝘁𝗶𝗼𝗻 𝗠𝗼𝗱𝗲𝗹
→ Where LLM meets planning.
Adds memory, task breakdown, and intent recognition.
🛠 Use case: AI agents, tool use, step-by-step execution.
4. 𝗠𝗼𝗘 – 𝗠𝗶𝘅𝘁𝘂𝗿𝗲 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝘁𝘀
→ One model, many minds.
Routes input to the right “expert” model slice — dynamic, scalable, efficient.
🛠 Use case: high-performance model serving at low compute cost.
5. 𝗩𝗟𝗠 – 𝗩𝗶𝘀𝗶𝗼𝗻 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹
→ Multimodal beast.
Combines image + text understanding via shared embeddings.
🛠 Use case: Gemini, GPT-4o, search, robotics, assistive tech.
6. 𝗦𝗟𝗠 – 𝗦𝗺𝗮𝗹𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹
→ Tiny but mighty.
Designed for edge use, fast inference, low latency, efficient memory.
🛠 Use case: on-device AI, chatbots, privacy-first GenAI.
7. 𝗠𝗟𝗠 – 𝗠𝗮𝘀𝗸𝗲𝗱 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹
→ The OG foundation model.
Predicts masked tokens using bidirectional context.
🛠 Use case: search, classification, embeddings, pretraining.
8. 𝗦𝗔𝗠 – 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗔𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹
→ Vision model for pixel-level understanding.
Highlights, segments, and understands *everything* in an image.
🛠 Use case: medical imaging, AR, robotics, visual agents.
https://blog.comfy.org/p/comfyui-native-api-nodes
https://github.com/Conor-Collins/ComfyUI-CoCoTools_IO
https://vivariumnovum.it/saggistica/varia/la-vita-pittoresca-dellabate-uggeri
Book author: Claudio Tosti
Title: La vita pittoresca dell’abate Uggeri – Vol. I – La Giornata Tuscolana
Video made with Pixverse.ai and DaVinci Resolve
https://github.com/RupertAvery/DiffusionToolkit
It aims to help you organize, search and sort your ever-growing collection.
https://github.com/RupertAvery/DiffusionToolkit/blob/master/Diffusion.Toolkit/Tips.md
If you’re serious about AI Agents, this is the guide you’ve been waiting for. It’s packed with everything you need to build powerful AI agents. It follows a very hands-on approach that cuts down your time and avoids the common mistakes most developers make.
Andreas Horn on AI Agents vs Agentic AI
1. 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗧𝗼𝗼𝗹𝘀 𝘄𝗶𝘁𝗵 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆, 𝗪𝗶𝘁𝗵𝗶𝗻 𝗟𝗶𝗺𝗶𝘁𝘀
➜ AI agents are modular, goal-directed systems that operate within clearly defined boundaries. They’re built to:
* Use tools (APIs, browsers, databases)
* Execute specific, task-oriented workflows
* React to prompts or real-time inputs
* Plan short sequences and return actionable outputs
𝘛𝘩𝘦𝘺’𝘳𝘦 𝘦𝘹𝘤𝘦𝘭𝘭𝘦𝘯𝘵 𝘧𝘰𝘳 𝘵𝘢𝘳𝘨𝘦𝘵𝘦𝘥 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘰𝘯, 𝘭𝘪𝘬𝘦: 𝘊𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘣𝘰𝘵𝘴, 𝘐𝘯𝘵𝘦𝘳𝘯𝘢𝘭 𝘬𝘯𝘰𝘸𝘭𝘦𝘥𝘨𝘦 𝘴𝘦𝘢𝘳𝘤𝘩, 𝘌𝘮𝘢𝘪𝘭 𝘵𝘳𝘪𝘢𝘨𝘦, 𝘔𝘦𝘦𝘵𝘪𝘯𝘨 𝘴𝘤𝘩𝘦𝘥𝘶𝘭𝘪𝘯𝘨, 𝘊𝘰𝘥𝘦 𝘴𝘶𝘨𝘨𝘦𝘴𝘵𝘪𝘰𝘯𝘴
But even the most advanced are limited by scope. They don’t initiate. They don’t collaborate. They execute what we ask!
2. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜: 𝗔 𝗦𝘆𝘀𝘁𝗲𝗺 𝗼𝗳 𝗦𝘆𝘀𝘁𝗲𝗺𝘀
➜ Agentic AI is an architectural leap. It’s not just one smarter agent — it’s multiple specialized agents working together toward shared goals. These systems exhibit:
* Multi-agent collaboration
* Goal decomposition and role assignment
* Inter-agent communication via memory or messaging
* Persistent context across time and tasks
* Recursive planning and error recovery
* Distributed orchestration and adaptive feedback
Agentic AI systems don’t just follow instructions. They coordinate. They adapt. They manage complexity.
𝘌𝘹𝘢𝘮𝘱𝘭𝘦𝘴 𝘪𝘯𝘤𝘭𝘶𝘥𝘦: 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘵𝘦𝘢𝘮𝘴 𝘱𝘰𝘸𝘦𝘳𝘦𝘥 𝘣𝘺 𝘢𝘨𝘦𝘯𝘵𝘴, 𝘴𝘮𝘢𝘳𝘵 𝘩𝘰𝘮𝘦 𝘦𝘤𝘰𝘴𝘺𝘴𝘵𝘦𝘮𝘴 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘪𝘯𝘨 𝘦𝘯𝘦𝘳𝘨𝘺/𝘴𝘦𝘤𝘶𝘳𝘪𝘵𝘺, 𝘴𝘸𝘢𝘳𝘮𝘴 𝘰𝘧 𝘳𝘰𝘣𝘰𝘵𝘴 𝘪𝘯 𝘭𝘰𝘨𝘪𝘴𝘵𝘪𝘤𝘴 𝘰𝘳 𝘢𝘨𝘳𝘪𝘤𝘶𝘭𝘵𝘶𝘳𝘦 𝘮𝘢𝘯𝘢𝘨𝘪𝘯𝘨 𝘳𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘶𝘯𝘤𝘦𝘳𝘵𝘢𝘪𝘯𝘵𝘺
𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲?
AI Agents = autonomous tools for single-task execution
Agentic AI = orchestrated ecosystems for workflow-level intelligence
Next, here 𝗮𝗿𝗲 𝘁𝗵𝗲 𝘁𝗼𝗽 10 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 𝗳𝗿𝗼𝗺 𝗢𝗽𝗲𝗻𝗔𝗜’𝘀 𝗚𝘂𝗶𝗱𝗲:
https://www.linkedin.com/pulse/hidden-risks-using-chatgpt-anonymous-ai-tools-workflows-wilson-govcc
If you’re serious about protecting your IP, client relationships, and professional credibility, you need to stop treating generative AI tools like consumer-grade apps. This isn’t about fear, it’s about operational discipline. Below are immediate steps you can take to reduce your exposure and stay in control of your creative pipeline.
https://cyberinsider.com/disney-hacker-admits-using-malware-laced-ai-art-app-to-achieve-breach/
A 25-year-old Santa Clarita man has agreed to plead guilty to hacking a Disney employee’s personal computer, stealing login credentials, and exfiltrating 1.1 terabytes of confidential data from internal Slack channels.
The charges stem from a targeted cyberattack carried out in the spring and summer of 2024 that compromised Disney’s internal communications and led to the public leak of sensitive corporate data.
“Kramer, operating under the alias “NullBulge,” created and distributed a malicious program disguised as an AI art generation tool. He uploaded this trojanized application to GitHub and other public repositories in early 2024, enticing users interested in generative AI. At least three victims, including one Disney employee, downloaded the program. Once executed, the software provided Kramer with remote access to the victims’ machines and stored credentials.”
After infiltrating the employee’s personal system, Kramer accessed corporate Slack credentials to infiltrate Disney’s internal Slack workspace and downloaded around 1.1 terabytes of data from nearly 10,000 channels including unreleased media projects, internal code, links to APIs, and credentials for internal web services.
https://robbredow.com/2025/05/ted-artist-driven-innovation/
https://www.ted.com/talks/rob_bredow_star_wars_changed_visual_effects_ai_is_doing_it_again
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