Here is your today’s AI Dev Brief from Marktechpost, covering core research, models, infrastructure tools, and applied updates for AI developers and researchers. Also, don’t forget to register for NVIDIA GTC 2026 event (In person/Virtual). NVIDIA has been supporting us to bring free and unlocked AI research and dev news content to you.

Is This AGI? Google’s Gemini 3 Deep Think Shatters Humanity’s Last Exam And Hits 84.6% On ARC-AGI-2 Performance Today

Google has just unleashed a massive update to Gemini 3 Deep Think that is officially shattering the ceiling of artificial intelligence. This specialized reasoning powerhouse just obliterated the ARC-AGI-2 benchmark with a verified 84.6% score and crushed the coding world with an elite 3455 Elo on Codeforces. By achieving gold medal-level results in the 2025 Physics and Chemistry Olympiads and setting a new standard on Humanity’s Last Exam at 48.4%, Gemini 3 Deep Think is no longer just a model—it is a scientific engine. Designed to accelerate research and engineering, this update uses advanced reasoning to solve the world's most complex problems with unprecedented precision......… Read the full analysis/article here.

OpenAI Releases a Research Preview of GPT‑5.3-Codex-Spark: A 15x Faster AI Coding Model Delivering Over 1000 Tokens Per Second on Cerebras Hardware

OpenAI has launched GPT-5.3 Codex-Spark, a research preview optimized for near-instant coding by delivering over 1000 tokens per second—a 15x speed increase over the flagship model. This massive performance jump is powered by the Cerebras Wafer-Scale Engine 3 (WSE-3), which eliminates traditional GPU bottlenecks by keeping all compute on a single silicon wafer, paired with a new persistent WebSocket connection that reduces networking overhead by 80%. While Spark is designed for real-time "micro-iterations" and features a 128k context window, it has lower reasoning depth than the flagship GPT-5.3 Codex and does not meet the "High capability" threshold for cybersecurity, making it best suited as a fast interactive partner alongside the more powerful flagship model.......… Read the full analysis/article here.

Project Notebooks/Tutorials

▶ How to Build an Atomic-Agents RAG Pipeline with Typed Schemas, Dynamic Context Injection, and Agent Chaining Codes Tutorial

▶ Meet CopilotKit: Framework for building agent-native applications with Generative UI, shared state, and human-in-the-loop workflows Codes

▶ How to Build a Matryoshka-Optimized Sentence Embedding Model for Ultra-Fast Retrieval with 64-Dimension Truncation Codes Tutorial

▶ A Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow Codes Tutorial

▶ A Coding Implementation to Automating LLM Quality Assurance with DeepEval, Custom Retrievers, and LLM-as-a-Judge Metrics Codes Tutorial

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