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Introducing OpenVenice — an open-source, customizable frontend for Venice. Your API key stays in your browser, talks directly to Venice. No server, no backend. - Chat, image gen, audio, music, video, embeddings — everything venice offers in one clean UI - Visual workflows — chain models together (vision →...

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nikshep

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40,500 görüntüleme • 4 ay önce •via X (Twitter)

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Ansem shares his thesis on $VVV “Venice AI is essentially a private inference platform… you can access all of the top state-of-the-art models, all the best open source models but through Venice, it doesn’t store any of your information” “They’ve done really well. They have over 2 million users. I think they have 50k daily actives on their app and they’re making money from the subscription” “One of the cool features of Venice that I thought was interesting is they have a second token that’s called DIEM… if you have 1 DIEM, you get to use $1 of compute per day for that 1 DIEM that you have” “It’s a really interesting model. I think it’s honestly attracted a lot of people to stake $VVV. We don’t have a lot of real protocols there in the crypto and AI space that aren’t vapor and are actually doing well”
2:27

Ansem shares his thesis on $VVV “Venice AI is essentially a private inference platform… you can access all of the top state-of-the-art models, all the best open source models but through Venice, it doesn’t store any of your information” “They’ve done really well. They have over 2 million users. I think they have 50k daily actives on their app and they’re making money from the subscription” “One of the cool features of Venice that I thought was interesting is they have a second token that’s called DIEM… if you have 1 DIEM, you get to use $1 of compute per day for that 1 DIEM that you have” “It’s a really interesting model. I think it’s honestly attracted a lot of people to stake $VVV. We don’t have a lot of real protocols there in the crypto and AI space that aren’t vapor and are actually doing well”

Market Bubble

142,486 görüntüleme • 2 ay önce

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.
4:10

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Santiago

56,815 görüntüleme • 1 yıl önce

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!
0:48

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,386 görüntüleme • 3 ay önce

I just built an open NotebookLM clone! Here's what it can do for you: - Process multi-modal data - Scrape websites and YouTube videos - Create a unified knowledge base - Lets you do RAG over it - Remember every conversation - Generate a podcast 🎙️ The idea here is not to reinvent the wheel but to understand how one of the most powerful tools for learning and research actually works, by building it step-by-step! So by the end of this video, you'll learn how to: ↳ Process multimodal data (text, audio, video, URLs, and YouTube videos) into a format ready for LLMs ↳ Store everything in a vector database for fast retrieval ↳ Add a memory layer that remembers conversations and preferences for a personalized experience ↳ Chat with your knowledge base or generate podcasts using a fully open-source, locally running text-to-speech model The podcast generation feature is my favorite part! There's something powerful about turning written content into conversational audio that you can listen to while doing something else. The entire code is 100% open-source. I've shared a link in the replies! ____ Don't forget to drop a like if you enjoy my videos. It shows me I should be making more content like this. Cheers! :)
20:04

I just built an open NotebookLM clone! Here's what it can do for you: - Process multi-modal data - Scrape websites and YouTube videos - Create a unified knowledge base - Lets you do RAG over it - Remember every conversation - Generate a podcast 🎙️ The idea here is not to reinvent the wheel but to understand how one of the most powerful tools for learning and research actually works, by building it step-by-step! So by the end of this video, you'll learn how to: ↳ Process multimodal data (text, audio, video, URLs, and YouTube videos) into a format ready for LLMs ↳ Store everything in a vector database for fast retrieval ↳ Add a memory layer that remembers conversations and preferences for a personalized experience ↳ Chat with your knowledge base or generate podcasts using a fully open-source, locally running text-to-speech model The podcast generation feature is my favorite part! There's something powerful about turning written content into conversational audio that you can listen to while doing something else. The entire code is 100% open-source. I've shared a link in the replies! ____ Don't forget to drop a like if you enjoy my videos. It shows me I should be making more content like this. Cheers! :)

Akshay 🚀

83,187 görüntüleme • 9 ay önce

Ali's Wan 2.2 is absolutely insane 🤯 Map your voice and motion into a video clip featuring anyone with a single photo. In this video I shape-shift between an avatar woman, Matthew Mcconaughey, Anne Hathaway, Martin Luther King Jr., and Bane. Tools used: - Wan 2.2 for video gen - FreePik for image gen - ElevenLabs for voice cloning and voice changing Want the full prompting guide and a step-by-step tutorial video where I walk through exactly how I built it? Like, RT, and comment "REALITY", and I'll DM it to you. (must be following so I can dm you)
0:22

Ali's Wan 2.2 is absolutely insane 🤯 Map your voice and motion into a video clip featuring anyone with a single photo. In this video I shape-shift between an avatar woman, Matthew Mcconaughey, Anne Hathaway, Martin Luther King Jr., and Bane. Tools used: - Wan 2.2 for video gen - FreePik for image gen - ElevenLabs for voice cloning and voice changing Want the full prompting guide and a step-by-step tutorial video where I walk through exactly how I built it? Like, RT, and comment "REALITY", and I'll DM it to you. (must be following so I can dm you)

David Roberts

126,130 görüntüleme • 8 ay önce

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!
0:36

I'm now building Executor full time as a startup! The state of tool calling is a mess: - Everyone is using different agents - You have no idea what actions are going to run - Destructive actions are treated the same as normal Executor lets you set up everything once & use it with any agent. You're able to control what tools can be called, require approval on destructive actions, and invite your team to all use them. Under the hood, it's built on codemode to let you add thousands of tools with 0 context bloat. I've been using it for a month so far and it has completely changed how I interact with agents. There's so much to be built here, immediately next up on the roadmap is workspaces, skills, workflows, and generative ui. Everything is being built open source over at there's a lot more coming on an SDK to embed it into your own agents, a self hostable cloud app, and plugins There's an early beta version over at It's very early on - if you hit any bugs let me know and I'll get them fixed up, excited to share more as I build it!

Rhys

220,043 görüntüleme • 2 ay önce

spent months on HumanPlane, a closed source Polymarket terminal. it did $250k+ in volume but i scrapped it anyways. why? cause every polymarket terminal is the same thing. closed source. a reskin of with marginal ux gains. polymarket already takes a 1–1.8% taker fee on every trade, so terminal fees are fees on top of fees you already pay. for a ui. the free ones are vc-funded — they won't stay free. so i rebuilt humanplane as the first free, open source, fully customizable polymarket terminal. run it locally, forever. don't like something? ask claude to modify it and make it yours. built w/ a performant rust backend and solidjs, supports market and trader exploration, live charts, orderbook and order execution (market + limit) -- intelligence, perps, trader scoring and more soon try it out:
0:42

spent months on HumanPlane, a closed source Polymarket terminal. it did $250k+ in volume but i scrapped it anyways. why? cause every polymarket terminal is the same thing. closed source. a reskin of with marginal ux gains. polymarket already takes a 1–1.8% taker fee on every trade, so terminal fees are fees on top of fees you already pay. for a ui. the free ones are vc-funded — they won't stay free. so i rebuilt humanplane as the first free, open source, fully customizable polymarket terminal. run it locally, forever. don't like something? ask claude to modify it and make it yours. built w/ a performant rust backend and solidjs, supports market and trader exploration, live charts, orderbook and order execution (market + limit) -- intelligence, perps, trader scoring and more soon try it out:

nikshep

22,977 görüntüleme • 3 ay önce

Fck it. We no longer need Foundation. I built a free tool for every artist affected by the shutdown. Paste your wallet, see exactly what you created and what you collected - no wallet signature required. Two steps: 1. Paste your address. See every Foundation NFT you created or own, pulled straight from on-chain contract data. 2. Get a free Pinata account and pin your art to IPFS in one click. Your content, your storage, nobody can take it down. The tool also shows art you collected from other artists - so you can tell them before their work disappears. --- The Art Revolution starts now. So, I also built UNDERPIN to kick it off- a vision for a decentralized art marketplace with no company behind it. No gatekeepers, no single point of failure. AI dev tools exist now. Artists can run their own infrastructure. Foundation shutting down is not a loss - it's proof we need to own the stack. Everything is open source. Fork it, build on it, make it yours. links below.
0:24

Fck it. We no longer need Foundation. I built a free tool for every artist affected by the shutdown. Paste your wallet, see exactly what you created and what you collected - no wallet signature required. Two steps: 1. Paste your address. See every Foundation NFT you created or own, pulled straight from on-chain contract data. 2. Get a free Pinata account and pin your art to IPFS in one click. Your content, your storage, nobody can take it down. The tool also shows art you collected from other artists - so you can tell them before their work disappears. --- The Art Revolution starts now. So, I also built UNDERPIN to kick it off- a vision for a decentralized art marketplace with no company behind it. No gatekeepers, no single point of failure. AI dev tools exist now. Artists can run their own infrastructure. Foundation shutting down is not a loss - it's proof we need to own the stack. Everything is open source. Fork it, build on it, make it yours. links below.

tut™

32,236 görüntüleme • 3 ay önce

Is Windsurf better than Cursor? impossible to say, but... it does one thing better: soooo... I spent an hour testing windsurf... and this is what i created... and app called "boop-boop" lol... one thing windsurf does is it searches the internet. If you've been watching my videos you know that i go to perplexity all the time to get code examples and docs. but with windsurf you can just say, "search the replicate top image gen models and add them to the chat we just created" It will search the internet, find the right model then write the code. This is great for replicate and openrouter. You can have one api key in your .env file then just tell windsurf to search for docs for [insert ai model] and it will just add it to your app. Impressed tbh.
2:30

Is Windsurf better than Cursor? impossible to say, but... it does one thing better: soooo... I spent an hour testing windsurf... and this is what i created... and app called "boop-boop" lol... one thing windsurf does is it searches the internet. If you've been watching my videos you know that i go to perplexity all the time to get code examples and docs. but with windsurf you can just say, "search the replicate top image gen models and add them to the chat we just created" It will search the internet, find the right model then write the code. This is great for replicate and openrouter. You can have one api key in your .env file then just tell windsurf to search for docs for [insert ai model] and it will just add it to your app. Impressed tbh.

Riley Brown

31,043 görüntüleme • 1 yıl önce

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:
9:38

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:

Jerry Liu

20,413 görüntüleme • 1 yıl önce

I built an open-source tool to fix something that drives me nuts. You ask ChatGPT or Gemini for a game asset and get an image with a background baked in. Ask for transparency and you get... a fake checkerboard. Then you hunt for a background remover, then slice each sprite out by hand. So I built Sprite Lab. Drop a spritesheet → it auto-detects the backdrop (checkerboard, white, magenta, green), removes it cleanly with no halo, and slices every frame for you. Export as PNGs + a strip + manifest. 100% in your browser. No uploads, no AI model, no sign-up. Free and open source. #gamedev #indiegame
0:41

I built an open-source tool to fix something that drives me nuts. You ask ChatGPT or Gemini for a game asset and get an image with a background baked in. Ask for transparency and you get... a fake checkerboard. Then you hunt for a background remover, then slice each sprite out by hand. So I built Sprite Lab. Drop a spritesheet → it auto-detects the backdrop (checkerboard, white, magenta, green), removes it cleanly with no halo, and slices every frame for you. Export as PNGs + a strip + manifest. 100% in your browser. No uploads, no AI model, no sign-up. Free and open source. #gamedev #indiegame

Ibrahim Boona

19,969 görüntüleme • 1 ay önce

Happy GPT-5 Day to all who celebrate. Here's what I expect: It will be agentic-first (this is all but confirmed by OpenAI) It will be heavily multimodal (audio, video, music, tool use, and more) It will be a reasoning-first model as well (math, planning, etc) Directionally, I suspect we're looking at moving towards a convergence of "everything to everything" end-to-end models. Sort of like how Tesla improved FSD by doing neural networks for end-to-end perception-planning-control. Likewise, I suspect that, for the foreseeable future on general purpose models, we're going to converge towards "all in one" models. They will just tend to get smarter and smarter the more modalities we stuff into them (world models, math, image, text, video, audio, etc).
9:02

Happy GPT-5 Day to all who celebrate. Here's what I expect: It will be agentic-first (this is all but confirmed by OpenAI) It will be heavily multimodal (audio, video, music, tool use, and more) It will be a reasoning-first model as well (math, planning, etc) Directionally, I suspect we're looking at moving towards a convergence of "everything to everything" end-to-end models. Sort of like how Tesla improved FSD by doing neural networks for end-to-end perception-planning-control. Likewise, I suspect that, for the foreseeable future on general purpose models, we're going to converge towards "all in one" models. They will just tend to get smarter and smarter the more modalities we stuff into them (world models, math, image, text, video, audio, etc).

David Shapiro (L/0)

19,305 görüntüleme • 11 ay önce

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai
0:24

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,200 görüntüleme • 2 yıl önce

Harvey is valued at $11B. Legora just raised at $5.5B. I built their entire web application in two weeks and I'm making it open-source and free for everyone to use. Say hi to Mike: When I got the chance to try Harvey and Legora, I was surprised by how simple they were. A thought came to mind: I could probably build something similar in no time at all with Claude. And so I did. Assistant, project, tabular review and workflows. You get it all without vendor lock-in. Mike offers law firms an alternative, where they own the application layer and aren't stuck with a vendor they're renewing forever. You can try Mike in the demo on the website, or go to the GitHub link on the site to download the code and run a local version yourself.
5:03

Harvey is valued at $11B. Legora just raised at $5.5B. I built their entire web application in two weeks and I'm making it open-source and free for everyone to use. Say hi to Mike: When I got the chance to try Harvey and Legora, I was surprised by how simple they were. A thought came to mind: I could probably build something similar in no time at all with Claude. And so I did. Assistant, project, tabular review and workflows. You get it all without vendor lock-in. Mike offers law firms an alternative, where they own the application layer and aren't stuck with a vendor they're renewing forever. You can try Mike in the demo on the website, or go to the GitHub link on the site to download the code and run a local version yourself.

WillC

1,315,781 görüntüleme • 2 ay önce

The corporate system wants you trading time for a paycheck. The alternative is building automated leverage. You do not need a team of engineers. You just need the right open-source architecture. Here are 10 GitHub repos to automate your workflows, replace manual labor, and direct your own reality: 1. n8n Bypass expensive SaaS subscriptions. Build custom AI automation workflows that run on your own servers. 2. Ollama Stop sending your private data to massive API providers. Run heavy AI models locally on your own machine. Complete privacy. 3. Open Interpreter Let language models control your computer. Automate the repetitive corporate tasks they pay you to do manually. 4. Aider An AI pair programmer that lives in your terminal. Stop writing boilerplate code and focus strictly on the architecture. 5. Dify An open-source LLM app development platform. Build and deploy functional AI agents in minutes, not months. 6. Flowise A drag-and-drop UI to build customized LLM flows. You do not need to be a senior developer to build massive leverage. 7. Supabase Spin up a Postgres database, authentication, and instant APIs. Own your backend entirely. 8. Auto-GPT Give an AI an objective and let it execute. It browses the web, writes code, and chains thoughts together autonomously. 9. Outline An open-source knowledge base for your personal leverage. Stop losing your documentation in arbitrary corporate systems. 10. NocoDB Turn any database into a smart spreadsheet. Keep your data on your own infrastructure and stop paying for convenience. The secret to tech survival? Stop playing by their rules. Build your own systems and take your leverage with you.
1:30

The corporate system wants you trading time for a paycheck. The alternative is building automated leverage. You do not need a team of engineers. You just need the right open-source architecture. Here are 10 GitHub repos to automate your workflows, replace manual labor, and direct your own reality: 1. n8n Bypass expensive SaaS subscriptions. Build custom AI automation workflows that run on your own servers. 2. Ollama Stop sending your private data to massive API providers. Run heavy AI models locally on your own machine. Complete privacy. 3. Open Interpreter Let language models control your computer. Automate the repetitive corporate tasks they pay you to do manually. 4. Aider An AI pair programmer that lives in your terminal. Stop writing boilerplate code and focus strictly on the architecture. 5. Dify An open-source LLM app development platform. Build and deploy functional AI agents in minutes, not months. 6. Flowise A drag-and-drop UI to build customized LLM flows. You do not need to be a senior developer to build massive leverage. 7. Supabase Spin up a Postgres database, authentication, and instant APIs. Own your backend entirely. 8. Auto-GPT Give an AI an objective and let it execute. It browses the web, writes code, and chains thoughts together autonomously. 9. Outline An open-source knowledge base for your personal leverage. Stop losing your documentation in arbitrary corporate systems. 10. NocoDB Turn any database into a smart spreadsheet. Keep your data on your own infrastructure and stop paying for convenience. The secret to tech survival? Stop playing by their rules. Build your own systems and take your leverage with you.

Katyayani Shukla

16,964 görüntüleme • 2 ay önce

I trained Adobe Firefly on my images and it changed how I work. Custom Models learns your visual style. Your light, your tones, your grain. Not from a reference image, not from a prompt but from your actual work. The result? Consistent, on-brand outputs that feel like yours. Every time. Here's how it works 👇 🔹 Upload 10–30 of your images 🔹 Firefly analyzes and trains your model 🔹 Generate new work that stays true to your style And it's not just photography. Custom Models works across creative disciplines: 🎨 Illustration to maintain stroke weight, color palette, and shape consistency across icons and graphics ✏️ Character design to recreate your illustrated character across poses, expressions, and scenes without redrawing from scratch 📷 Photography to expand a photo set with matching light, color grade, and composition No complex workflows. No technical expertise. Just your creative vision, at scale. If you've ever spent hours trying to maintain visual consistency across a project, this is the solution. Adobe Firefly Custom Models: your style, your model, your work. Faster. This post is sponsored by Adobe through a paid partnership as an Adobe Firefly Ambassador. #AdobeFireflyAmbassadors #Ad #FireflyCustomModels
3:24

I trained Adobe Firefly on my images and it changed how I work. Custom Models learns your visual style. Your light, your tones, your grain. Not from a reference image, not from a prompt but from your actual work. The result? Consistent, on-brand outputs that feel like yours. Every time. Here's how it works 👇 🔹 Upload 10–30 of your images 🔹 Firefly analyzes and trains your model 🔹 Generate new work that stays true to your style And it's not just photography. Custom Models works across creative disciplines: 🎨 Illustration to maintain stroke weight, color palette, and shape consistency across icons and graphics ✏️ Character design to recreate your illustrated character across poses, expressions, and scenes without redrawing from scratch 📷 Photography to expand a photo set with matching light, color grade, and composition No complex workflows. No technical expertise. Just your creative vision, at scale. If you've ever spent hours trying to maintain visual consistency across a project, this is the solution. Adobe Firefly Custom Models: your style, your model, your work. Faster. This post is sponsored by Adobe through a paid partnership as an Adobe Firefly Ambassador. #AdobeFireflyAmbassadors #Ad #FireflyCustomModels

Alexandra Aisling

13,359 görüntüleme • 4 ay önce

If you could only learn one thing that will be relevant for the next 10-20 years, focus on learning how to deal with data. The future is not about faster hardware, smarter algorithms, or better ideas. The future is about DATA, and those who know how to deal with it will stay relevant much longer than anyone else. I recorded a video to show you how easy it is to get started. In the video, I'm using Kestra. For a long time, I was a fan of AirFlow. Then, I moved to AWS Step Functions. Today, I only use Kestra. Kestra is open-source (repo link below) and kind enough to sponsor my work. The video will show you how easy it is to do the following: 1. Run Kestra locally (literally, one command) 2. Build a simple flow 3. Run Python scripts as part of your flow 4. Connect to HuggingFace models If you have never built a data pipeline, open Kestra's Quick Start Guide and follow their examples. (I think it will take you one weekend to feel comfortable with the application and build the courage you need to get into more serious work.)
5:18

If you could only learn one thing that will be relevant for the next 10-20 years, focus on learning how to deal with data. The future is not about faster hardware, smarter algorithms, or better ideas. The future is about DATA, and those who know how to deal with it will stay relevant much longer than anyone else. I recorded a video to show you how easy it is to get started. In the video, I'm using Kestra. For a long time, I was a fan of AirFlow. Then, I moved to AWS Step Functions. Today, I only use Kestra. Kestra is open-source (repo link below) and kind enough to sponsor my work. The video will show you how easy it is to do the following: 1. Run Kestra locally (literally, one command) 2. Build a simple flow 3. Run Python scripts as part of your flow 4. Connect to HuggingFace models If you have never built a data pipeline, open Kestra's Quick Start Guide and follow their examples. (I think it will take you one weekend to feel comfortable with the application and build the courage you need to get into more serious work.)

Santiago

51,012 görüntüleme • 1 yıl önce

Vysor kept annoying me with ads and paywalls just to mirror my Android screen, so I built my own. Introducing Another: a free, open-source app for mirroring and controlling your Android phone from your desktop. The thing is insanely fast. Near-zero latency screen mirroring over USB. It feels like your phone screen is native to your computer. No lag, no frame drops, just raw performance. 🚀 Built with Tauri, React, and Rust. Uses scrcpy under the hood, which streams your phone's display as raw H.264 over ADB. No cloud, no relay servers, everything stays local. macOS available now. Windows and Linux experimental.
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Vysor kept annoying me with ads and paywalls just to mirror my Android screen, so I built my own. Introducing Another: a free, open-source app for mirroring and controlling your Android phone from your desktop. The thing is insanely fast. Near-zero latency screen mirroring over USB. It feels like your phone screen is native to your computer. No lag, no frame drops, just raw performance. 🚀 Built with Tauri, React, and Rust. Uses scrcpy under the hood, which streams your phone's display as raw H.264 over ADB. No cloud, no relay servers, everything stays local. macOS available now. Windows and Linux experimental.

Chizi

92,404 görüntüleme • 3 ay önce

New short course Multimodal RAG: Chat with Videos, developed with Intel and taught by vasudevlal! In this course, you’ll work with LLaVA (Large Language and Vision Assistant), a Large Vision Language Model (LVLM) that can process both images and text. For example, given an image of a person doing a handstand on a skateboard at the beach, LLaVA doesn't just caption the scene, it’s able to predict possible outcomes, like the person losing balance or falling off. By understanding not just what's in a video frame, but what might happen next, your application can provide more insightful answers to questions about video. You'll build a full multimodal RAG pipeline that can chat about video content: - Use the BridgeTower model to create joint text-image embeddings in a 512-dimensional multimodal semantic space. - Learn video processing techniques to extract keyframes, generate transcripts using Whisper, and create captions. - Use the LanceDB vector database to store and retrieve high-dimensional multimodal embeddings. - Integrate the LLaVA model, combining CLIP's (Contrastive Language Image Pretraining) vision transformer with Llama, for advanced visual-textual reasoning. Your final system will ingest video data, generate embeddings for frames and text, perform similarity searches for relevant content, and use the retrieved multimodal context to inform LVLM-based response generation. The result is a system capable of answering nuanced questions about video content, effectively chatting about the video it has processed. Please sign up here!
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New short course Multimodal RAG: Chat with Videos, developed with Intel and taught by vasudevlal! In this course, you’ll work with LLaVA (Large Language and Vision Assistant), a Large Vision Language Model (LVLM) that can process both images and text. For example, given an image of a person doing a handstand on a skateboard at the beach, LLaVA doesn't just caption the scene, it’s able to predict possible outcomes, like the person losing balance or falling off. By understanding not just what's in a video frame, but what might happen next, your application can provide more insightful answers to questions about video. You'll build a full multimodal RAG pipeline that can chat about video content: - Use the BridgeTower model to create joint text-image embeddings in a 512-dimensional multimodal semantic space. - Learn video processing techniques to extract keyframes, generate transcripts using Whisper, and create captions. - Use the LanceDB vector database to store and retrieve high-dimensional multimodal embeddings. - Integrate the LLaVA model, combining CLIP's (Contrastive Language Image Pretraining) vision transformer with Llama, for advanced visual-textual reasoning. Your final system will ingest video data, generate embeddings for frames and text, perform similarity searches for relevant content, and use the retrieved multimodal context to inform LVLM-based response generation. The result is a system capable of answering nuanced questions about video content, effectively chatting about the video it has processed. Please sign up here!

Andrew Ng

107,825 görüntüleme • 1 yıl önce

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.
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Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Santiago

39,101 görüntüleme • 2 yıl önce