roadmap

Youssef Hosni announced that his LLM Roadmap book, which became a bestseller on To Data & Beyond, is now open source and freely available, aiming to provide a clear learning path for LLMs and generative AI.

A beginner electronics roadmap from a maker who went from not knowing how to light an LED to building rovers and winning hackathons. It covers understanding circuits, using an Arduino, and building real projects.

Google DeepMind introduces its AI Control Roadmap, a framework for building and managing advanced AI to ensure it behaves as intended.

Amazon and QuEra promise useful error-corrected quantum computing by 2028 with their Libra hardware, aiming to achieve a million quantum operations over hundreds of logical qubits for scientific applications beyond classical and NISQ computers.

DeepMind introduces an AI Control Roadmap, a defense-in-depth framework for securing internal AI agents against potential misalignment, treating them as insider threats and implementing layered detection, prevention, and response measures.

Mozilla shares upcoming Firefox features including modernized design, tab organization, PDF tools, VPN, AI browsing option, and improved privacy protections.

A comprehensive roadmap for learning agentic AI, covering 12 stages from Python basics to production deployment, with free and freemium resources.

A comprehensive roadmap for becoming a full-stack AI engineer, covering coding fundamentals, LLM APIs, RAG, agents, production infrastructure, observability, security, and advanced workflows.

A free comprehensive step-by-step projects roadmap for becoming an AI researcher, covering topics from tokenizers to full capstone model systems.

This paper presents a formal roadmap for transitioning from late-fusion multimodal approaches to native multimodal modeling (NMM) within a unified transformer framework, categorizing existing models by input-output duality and systematically addressing architectural coordination, data curation, training recipes, and evaluation.

A free, open-source AI engineering curriculum that covers math, LLMs, and agents across 20 phases and 435 lessons in Python, TypeScript, Rust, and Julia, designed to fill gaps in fragmented AI tutorials.

This paper surveys the capabilities and limitations of AI across the full research lifecycle, from idea generation to dissemination, identifying a sharp boundary between reliable assistance and unreliable autonomy. It provides a taxonomy, benchmark suite, tool inventory, and design principles for human-governed AI collaboration in research.

A detailed 12-stage roadmap for becoming a Generative AI Engineer in 6 months, covering Python async, multimodal LLMs, RAG, agentic workflows, production deployment, MLOps, and safety, emphasizing building over tutorials.

A comprehensive, open-source GitHub repository providing structured learning roadmaps and curated resources for mastering AI, machine learning, deep learning, and large language models from beginner to advanced levels. Designed for students and professionals, it covers foundational concepts, programming frameworks, career tracks, and emerging AI topics.

A commerce beginner seeks a step-by-step roadmap and tool recommendations to automate web-to-PDF-to-Excel workflows plus AI-driven Excel formulas without coding experience.