INTRODUCTION………………………………………………………………………………………….. 3 Setting Up AI Development Environment with Python……………………………….… 7 Understanding Machine Learning — The Heart of AI…………………………………… 11 Supervised Learning Deep Dive — Regression and Classification Models………. 16 Unsupervised Learning Deep Dive — Discovering Hidden Patterns………………. 21 Neural Networks Fundamentals — Building Brains for AI ……………………………. 26 Project — Build a Neural Network to Classify Handwritten Digits ………………. 30 Deep Learning for Image Classification — CNNs Explained………………………… 33 Advanced Image Classification — Transfer Learning………………………………….. 37 Natural Language Processing (NLP) Basics with Python…………………………….. 41 Spam Detection Using Machine Learning …………………………………………………. 45 Deep Learning for Text Classification (with NLP) …………………………………….. 48 Computer Vision Basics and Image Classification ……………………………………. 51 AI for Automation: Files, Web, and Emails ………………………………………………. 56 AI Chatbots and Virtual Assistants …………………………………………………………… 61
→ Midjourney: for the stunning visuals and style. → Nano Banana: for camera angles and edits. → Seedance + Kling 2.5: for motion and animation. → Suno: for the music track in one go. → Elevenlabs: for sound effects.
I created a million-dollar Pixar-quality short in just 8 days using AI.
Recent video generation models can produce smooth and visually appealing clips, but they often struggle to synthesize complex dynamics with a coherent chain of consequences. Accurately modeling visual outcomes and state transitions over time remains a core challenge. In contrast, large language and multimodal models (e.g., GPT-4o) exhibit strong visual state reasoning and future prediction capabilities. To bridge these strengths, we introduce VChain, a novel inference-time chain-of-visual-thought framework that injects visual reasoning signals from multimodal models into video generation. Specifically, VChain contains a dedicated pipeline that leverages large multimodal models to generate a sparse set of critical keyframes as snapshots, which are then used to guide the sparse inference-time tuning of a pre-trained video generator only at these key moments. Our approach is tuning-efficient, introduces minimal overhead and avoids dense supervision. Extensive experiments on complex, multi-step scenarios show that VChain significantly enhances the quality of generated videos.
High level tools to make the power of Geometry Nodes accessible to any user familiar with modifiers. The focus here is (opposite to builtin Geometry Nodes) to combine lots of options and functionality into one convenient package, that can be extended by editing the nodes, or integrating it into a node-setup, but is focused on being used without node editing.
Design: I started by generating cohesive concept images in Midjourney, with sleek white interiors with yellow accents to define the overall vibe.
Generate: Using World Labs, I transformed those images into fully explorable and persistent 3D environments in minutes.
Assemble: I cropped out doorways inside the Gaussian splats, then aligned and stitched multiple rooms together using PlayCanvas Supersplat, creating a connected spaceship layout.
Experience: Just a few hours later, I was walking through a custom interactive game level that started as a simple idea earlier that day.
The AI Toolkit UI is a web interface for the AI Toolkit. It allows you to easily start, stop, and monitor jobs. It also allows you to easily train models with a few clicks. It also allows you to set a token for the UI to prevent unauthorized access so it is mostly safe to run on an exposed server.
Over 600+ production-ready models for image, video, audio, 3D. Fal AI
Serverless / On-demand Compute
You don’t have to set up GPU clusters yourself. It offers serverless GPUs with no cold starts or autoscaler setup. Fal AI
Custom / Private Deployments
Support for bringing your own model weights, private endpoints, and secure model serving. Fal AI
High Throughput & Speed
fal claims their inference engine for diffusion models is “up to 10× faster” and built for scale (100M+ daily inference calls) with “99.99% uptime.” Fal AI
Enterprise / Compliance
SOC 2 compliance, single sign-on, analytics, priority support, and tooling aimed at enterprise deployment and procurement. Fal AI
Flexible Pricing
Options include per-output (serverless) or hourly GPU pricing (for more custom compute). Fal AI
Use Cases & Positioning
Useful for rapid prototyping or productionizing generative media features (e.g. image generation, video, voice).
Appeals to teams that don’t want to manage MLOps/infra — it abstracts a lot of the “plumbing.”
Targets both startups and enterprises — they emphasize scale, reliability, and security.
They also showcase that fal is used by recognized companies in AI, design, and media (testimonials on site
– player and number detection with RF-DETR – player tracking with SAM2 – team clustering with SigLIP, UMAP and K-means – number recognition with SmolVLM2
“The Lionsgate catalog is too small to create a model,” a source tells The Wrap. “In fact, the Disney catalog is too small to create a model.” … Another issue is the rights of actors and the model for remuneration if their likeness appears in an AI-generated clip. It is a legal gray area with no clear path.
DISCLAIMER – Links and images on this website may be protected by the respective owners’ copyright. All data submitted by users through this site shall be treated as freely available to share.
