Teams across companies lose meeting notes and action items after discussions. This guide builds a lasting fix: an AI Meeting Summarizer and Action Planner using Claude Code with MCP. It processes transcripts into structured summaries with tasks, decisi…
Google has released Gemini 3.1 Flash Live in preview for developers through the Gemini Live API in Google AI Studio. This model targets low-latency, more natural, and more reliable real-time voice interactions, serving as Google’s ‘highest-quality audio and speech model to date.’ By natively processing multimodal streams, the release provides a technical foundation for building […]
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In this tutorial, we explore MolmoWeb, Ai2’s open multimodal web agent that understands and interacts with websites directly from screenshots, without relying on HTML or DOM parsing. We set up the full environment in Colab, load the MolmoWeb-4B model with efficient 4-bit quantization, and build the exact prompting workflow that lets the model reason about […]
The post How to Build a Vision-Guided Web AI Agent with MolmoWeb-4B Using Multimodal Reasoning and Action Prediction appeared first on MarkTechPost.
My main complaint with AI solutions is that they are largely dependent on my presence for any task. Even with agentic AI now in the mix, complete automation of any complex process still seems like a myth. Tools like n8n and make.com need a considerable…
World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel data often leads to ‘representation collapse,’ where the model produces redundant embeddings to trivially satisfy prediction objectives. Current approaches attempt to prevent this by relying on complex heuristics: they […]
The post Yann LeCun’s New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Predictive World Modeling appeared first on MarkTechPost.
The dream of recursive self-improvement in AI—where a system doesn’t just get better at a task, but gets better at learning—has long been the ‘holy grail’ of the field. While theoretical models like the Gödel Machine have existed for decades, they remained largely impractical in real-world settings. That changed with the Darwin Gödel Machine (DGM), […]
The post Meta AI’s New Hyperagents Don’t Just Solve Tasks—They Rewrite the Rules of How They Learn appeared first on MarkTechPost.
In this tutorial, we build an advanced, hands-on tutorial around Google’s newly released colab-mcp, an open-source MCP (Model Context Protocol) server that lets any AI agent programmatically control Google Colab notebooks and runtimes. Across five self-contained snippets, we go from first principles to production-ready patterns. We start by constructing a minimal MCP tool registry from […]
The post How to Design a Production-Ready AI Agent That Automates Google Colab Workflows Using Colab-MCP, MCP Tools, FastMCP, and Kernel Execution appeared first on MarkTechPost.
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine RLax with JAX, Haiku, and Optax to construct a Deep Q-Learning (DQN) agent that learns to solve the CartPole environment. Instead of using a fully packaged RL framework, […]
The post Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent appeared first on MarkTechPost.