20 Best Created Walkthroughs Of Open Source Ai Infrastructure Has Av 1 TikTok Influencers

✓ Why this creator matches:

The source post explicitly details how to create AI videos using 'Huggingface.co' and the 'Animate Diff' space, providing a step-by-step guide starting with 'HERE’S HOW TO DO IT Step 1'. Hugging Face is a prominent platform for open-source AI, making this a direct match for creating walkthroughs of open-source AI infrastructure.

✓ Why this creator matches:

The creator provides walkthroughs on how to use various AI image generators. Specifically, the video 'How to make Opium Birds tutorial' explicitly mentions and discusses 'stable diffusion' and 'SDXL', which are open-source AI infrastructure. While other tools like DALL-E 3 and Midjourney are also mentioned, the inclusion and instruction on Stable Diffusion directly addresses the 'open source AI infrastructure' aspect of the criteria.

✓ Why this creator matches:

The creator's profile description states, "I train AI to do cool things! Full videos on YouTube :)". The video captions and hashtags consistently show demonstrations of AI learning processes, such as "AI Learns to Walk," "AI Learns to Play Dodgeball," and "AI Learns to Jump," using hashtags like #ai, #neuralnetworks, #deepreinforcementlearning, and #aiwarehouse. While this content clearly involves AI development and showcases AI capabilities, it focuses on demonstrating the *results* of AI training rather than providing explicit walkthroughs or tutorials on setting up or utilizing open-source AI infrastructure (e.g., specific frameworks, tools, or platforms). The content is more about showing what AI can do rather than how to build or deploy the underlying systems.

✓ Why this creator matches:

The source post explicitly provides a walkthrough on how to run large language models locally using 'LMS Studio' and mentions 'open source models like OpenAI GPT OSS'. Pinned Post 1 also details how to 'run your G P t chat for free forever on your computer' and mentions downloading Docker, which is a key component for deploying AI infrastructure. These posts directly align with creating walkthroughs of open-source AI infrastructure.

✓ Why this creator matches:

The creator consistently showcases various AI tools and platforms (e.g., AI site builders, app builders, music generators, image generators, game builders, video models). However, the content focuses on demonstrating how to use these AI *products* or *services*, which appear to be proprietary tools (e.g., Readdy, Good Barber, Emergent, Macaroni AI, Runable, Gambo, Dreamina, Seedance, Lovart). There is no explicit mention or demonstration of 'open source' AI infrastructure, nor walkthroughs of setting up or working with underlying AI frameworks or models. The content is about using AI applications, not building or understanding open-source AI infrastructure.

✓ Why this creator matches:

The creator provides a clear tutorial on installing Stable Diffusion locally, which is an open-source AI model, as evidenced by the source post's transcript and caption. Additionally, a recent post explicitly mentions 'AI Town Github' and 'open source starter kit', further confirming their focus on open-source AI infrastructure.

✓ Why this creator matches:

The creator consistently provides 'DEMO's and 'automazioni' (automations) of AI agents and systems. They demonstrate how to build applications and automations using various AI tools and APIs, such as Sora 2, Google AI Studio, and OpenAI models. While this content involves AI infrastructure and walkthroughs, the tools mentioned (Sora 2, Google AI Studio, OpenAI) are proprietary, not explicitly open source. The creator's focus is on leveraging these tools for AI solutions rather than demonstrating open-source AI infrastructure.

✓ Why this creator matches:

The creator discusses 'AI projects' and specific AI applications like 'Digital Jim' and 'Sensay' in their posts. However, there is no evidence in the profile description, video captions, hashtags, or transcripts that they create 'walkthroughs' of 'open source AI infrastructure'. Their content appears to be more about discussing AI news or specific AI tools rather than providing technical tutorials or deep dives into the underlying infrastructure.

✓ Why this creator matches:

The creator explicitly discusses and explains 'hugging face' as an 'open source hub for AI' and 'a massive public library for cutting edge AI models'. They also explain the difference between 'open and closed source AI models', 'Kubernetes' (an open-source system for automating deployment), and 'CUDA' (a parallel computing platform essential for AI infrastructure). This content directly aligns with creating walkthroughs or explanations of open-source AI infrastructure.

✓ Why this creator matches:

The source post (Post 15) explicitly mentions 'Stable Diffusion 2 Puppet 2d animation' and the transcript details a step-by-step process: 'I'm gonna show you how let's go go ahead and save it and then you animate it in 2D and now you've got all these different kinds of animations pick an animation'. Stable Diffusion is a well-known open-source AI model, and the content provides a walkthrough for its application in 2D animation. Other posts also discuss various AI tools and generative AI, reinforcing the creator's focus on AI-related content.

✓ Why this creator matches:

The creator discusses open-source AI models, such as Minimax M2, and provides explanations and walkthroughs of how to use various AI tools and features, like ChatGPT Atlas for marketing and Claude's 'skills'. While not always a deep dive into the underlying 'infrastructure' code, the content is highly relevant to open-source AI and practical application/explanation of AI tools, which aligns closely with the spirit of the criterion, especially given the instruction to be lenient without a specific business context.

✓ Why this creator matches:

The creator's profile description, source post, and pinned posts consistently discuss and explain new AI models and tools, many of which are explicitly stated as 'open source' and 'free to try'. The content often describes how to access these tools (e.g., 'head over to their platform', 'accedervi attraverso il sito web Hugging Face') and details their features and usage (e.g., 'reasoning toggle', 'built specifically for agentic tasks'). This constitutes creating walkthroughs or detailed explanations of open-source AI infrastructure.

✓ Why this creator matches:

The source post explicitly discusses 'open source models' and how to 'run this' (referring to the models), indicating a walkthrough or explanation of open-source AI infrastructure. The creator also discusses building neural nets with PyTorch and understanding the autograd engine (Post 8), and building an autograd engine from scratch (Post 7), which are directly related to AI/ML infrastructure. The content consistently demonstrates engagement with and explanation of AI infrastructure.

✓ Why this creator matches:

The creator provides walkthroughs for various AI tools (e.g., Hypecaster.AI, AI Cut Dot Pro, Remake It Dot Io, Clippy Dot AI, Faceless Dot Video, Vidago Tech, Transcriptik, Veo 3/3.1, Sora 2) to generate content and automate TikTok. These are typically commercial or proprietary AI platforms/services, not open-source AI infrastructure (like TensorFlow, PyTorch, or specific open-source models/libraries that users would deploy or integrate at a deeper technical level). The content focuses on using these tools, not on the underlying open-source infrastructure.

✓ Why this creator matches:

The creator demonstrates MGX.dev, an AI platform powered by MetaGPT. While MetaGPT is an open-source AI framework, the content is a demonstration of the *platform* building a website, not a walkthrough of the underlying open-source AI *infrastructure* itself (e.g., how to set up, configure, or code with MetaGPT). The creator's overall content also covers a wide range of tech gadgets and lifestyle, not consistently focusing on open-source AI infrastructure walkthroughs.

✓ Why this creator matches:

The source post explicitly describes a walkthrough on how to extract 3D depth from images using 'stable diffusion' and a 'depth map addon'. Stable Diffusion is a well-known open-source AI model, and the description provides clear steps for a walkthrough ('install the depth map addon, locate the depth tab, drop any image there'). This directly matches the criterion.

✓ Why this creator matches:

The creator showcases hyper-realistic AI avatars and mentions using tools like Synthesia, DALL-E, and Deepfake AI, along with 'Behind-The-Scenes: How We Built Her Neural Networks From Scratch!'. While this content is related to AI creation and the underlying technology, it focuses on showcasing the AI model and its aesthetic appeal rather than providing explicit walkthroughs or tutorials of open-source AI infrastructure. DALL-E and Synthesia are not open-source infrastructure.

✓ Why this creator matches:

The creator provides walkthroughs and tutorials for various AI tools such as OpenAI, ChatGPT, Gemini, ElevenLabs, Grok, Nano Banana, Veo 3.1, and Hedra. However, these tools are primarily proprietary AI applications or services, not open source AI infrastructure. The content focuses on using these specific platforms rather than discussing or demonstrating open source foundational AI frameworks or infrastructure.

✓ Why this creator matches:

The creator's bio states 'I build AI systems & teach people to sell them.' Several video captions and transcripts explicitly mention building AI agents, connecting applications, and using tools like n8n (an open-source automation platform). For example, 'How to build a voice agent in 60 seconds #n8n #openai #voiceagent #phoneagent #ai' and 'OpenAI’s agent builders now out.. but here’s how to connect ANY application to use #openai #n8n'. The transcripts also detail steps like 'go to Vapi and create a free account' for building an AI voice agent, which are clear walkthroughs. The frequent mention of n8n confirms the focus on open-source AI infrastructure.

✓ Why this creator matches:

The creator's recent post explicitly discusses 'Running AI locally' and uses the hashtag #opensource, indicating a focus on open-source AI. Additionally, Pinned Post 1 is a tutorial on building 'internet in a box' using a Raspberry Pi, which is a form of local, open-source tech infrastructure often used for DIY AI projects. This demonstrates a pattern of creating walkthroughs for relevant open-source infrastructure.