Ready Tensor, Inc.

Attention AI and ML enthusiasts!!🚨🚨 Have you heard about Ready Tensor? Whether you’re a seasoned expert or just starting your journey, Ready Tensor is your stage. You can Share your projects, Collaborate with peers, and Shape the future of AI. Sign up Today! , and have all your…

🚀 75,000 Builders. 170 Countries. One Global AI Community. We’re thrilled to share that the Ready Tensor community has now grown to over 75,000 AI builders across 170 countries, all using Ready Tensor as their go-to platform for learning, building, and publishing in AI. 🌍 At…

Data is the foundation of every fine-tuned Large Language Model. Before you fine-tune an LLM, your dataset needs to be instruction-ready — meaning it’s clean, structured, and aligned with the behavior you want your model to learn. You can build this kind of dataset in three…

Supervised fine-tuning and pretraining use the same learning process — next-token prediction, but what really sets them apart? 👇 There are three key differences: 1️⃣ Starting point- Pretraining begins from scratch, while fine-tuning starts from a model that already understands…

🚀Early Enrollment window is Still Open for the LLM Engineering & Deployment Program 💡 Why Enroll Now? Early enrollees get exclusive access at a heavily discounted rate! And here’s an even better offer for our community 🎓 Graduates of the Agentic AI Developer Program: You…

Ever wondered how large language models (LLMs) generate text so intelligently? They’re not magical text generators; they’re massive classifiers trained through a simple but powerful mechanism called next-token prediction. At every step, the model computes probabilities for…

We recently launched our LLM Engineering and deployment certification program. This program was built with insights from analyzing hiring trends around AI/LLM roles. It’s a 9-weeks certification program divided into two practical modules, each culminating in a hands-on capstone…

Learn and Stay Up to Date with AI Engineering, for Free! 🚀 Ready Tensor has launched the most comprehensive Agentic AI Developer Program, now joined by over 30,000 learners from 130+ countries! This program is completely free and deeply hands-on. You’ll learn by building…

There are three key decision layers that define how you fine-tune: 1️⃣ Model Access- Are you fine-tuning a frontier model through an API (like GPT-4, Claude, or Gemini), or an open-weight model (like LLaMA-3, Mistral, or Phi-3) that you can fully control and customize? 2️⃣…

Should you fine-tune at all? 🤔 With fine-tuning, you’re teaching the model new behaviors by training it on your own dataset and updating its internal weights, making those behaviors permanent. You’d typically fine-tune when: ✅ You want consistent, repeatable output for…

Fine-tuning can be incredibly powerful but it’s not always the first step. Sometimes, great results come simply from clever prompting or by connecting your model to external knowledge using RAG (Retrieval-Augmented Generation). When adapting an LLM to your specific use case, you…

The Two Ecosystems of LLMs The LLM world divides into two major ecosystems: ⚡ Frontier models- accessed via APIs like GPT-4 and Claude. 🧠 Open-weight models - downloadable and self-hosted, like LLaMA and Mistral. Each comes with its own trade-offs in control, cost, and…

🚀 Intro to Agentic AI  Workshop We recently hosted an introductory workshop on Agentic AI, led by our Founder, Dr Abhyuday Desai, for the MS in Applied AI and MS in Applied Data Science students at the University of San Diego.@UCSanDiego This session kicked off a 3-part…

Modern language models are built on the Transformer architecture, but not all Transformers are the same. There are three main types, each designed for different kinds of tasks: 🔁 Encoder–Decoder → Transforms one sequence into another. 📊 Encoder-Only → Focuses on…

Google’s paper “Attention Is All You Need”  introduced the Transformer architecture, which became the foundation of all modern Large Language Models (LLMs). The Transformer is built around two key components: ✅  Encoder - Reads and understands the input by looking both forward…

What Do Employers in AI Actually Look For? We analyzed hundreds of AI and LLM engineering job postings to design a curriculum aligned with what employers actually seek. Our biggest takeaway? Most roles today demand a combination of LLM technical depth and cloud deployment…

🎯 LLM Engineering Pre-Assessment Test We’ve created a fun and insightful assessment for anyone interested in joining our LLM Engineering & Deployment Program! 🚀 This test is designed to evaluate your readiness for the program and covers key areas such as: 💻 Core Python…

Looking to understand AI Engineering ? You need just one program . Ready Tensor's Agentic AI developer program . Free, hands-on and self-paced . readytensor.ai/agentic-ai-cer…

How to Get the Best Learning Experience in Our Program 🚀 Start with the Project Begin each module by exploring the project first. Identify what you don’t yet know, learn those concepts, and apply them as you build. This approach mirrors how real engineers work, learning through…

Master the Full Lifecycle of Large Language Models Our 9-week certification program is designed to help you go beyond prompting and master hands-on LLM engineering, from fine-tuning to deployment. We’ve divided the program into two core modules: 🧠 Module 1: LLM Fine-Tuning &…

🚀 Are You Ready to Become an LLM Engineer? Our LLM Engineering & Deployment Program is an advanced, hands-on certification — which means a solid grasp of the fundamentals will help you transition smoothly and get the most out of your learning experience. Here’s a quick preview…