Editors Pick

Editors Pick New Releases

Polaris-4B and Polaris-7B: Post-Training Reinforcement Learning for Efficient Math and Logic Reasoning
ByRicardo June 27, 2025

The Rising Need for Scalable Reasoning Models in Machine Intelligence Advanced reasoning models are at the frontier of machine intelligence, especially in domains like math problem-solving and symbolic reasoning. These models are designed to perform multi-step calculations and logical deductions, often generating solutions that mirror human reasoning processes. Reinforcement learning techniques are used to improve…

Read More Polaris-4B and Polaris-7B: Post-Training Reinforcement Learning for Efficient Math and Logic Reasoning
Artificial Intelligence Editors Pick

GURU: A Reinforcement Learning Framework that Bridges LLM Reasoning Across Six Domains
ByRicardo June 27, 2025

Limitations of Reinforcement Learning in Narrow Reasoning Domains Reinforcement Learning RL has demonstrated strong potential to enhance the reasoning capabilities of LLMs, particularly in leading systems such as OpenAI-O3 and DeepSeek-R1. However, most RL research has focused narrowly on math and code, limiting its general applicability. This narrow scope poses two issues: our understanding of…

Read More GURU: A Reinforcement Learning Framework that Bridges LLM Reasoning Across Six Domains
Editors Pick New Releases

Google DeepMind Releases Gemini Robotics On-Device: Local AI Model for Real-Time Robotic Dexterity
ByRicardo June 25, 2025

Google DeepMind has unveiled Gemini Robotics On-Device, a compact, local version of its powerful vision-language-action (VLA) model, bringing advanced robotic intelligence directly onto devices. This marks a key step forward in the field of embodied AI by eliminating the need for continuous cloud connectivity while maintaining the flexibility, generality, and high precision associated with the…

Read More Google DeepMind Releases Gemini Robotics On-Device: Local AI Model for Real-Time Robotic Dexterity
Editors Pick Tutorials

A Coding Implementation for Creating, Annotating, and Visualizing Complex Biological Knowledge Graphs Using PyBEL
ByRicardo June 25, 2025

In this tutorial, we explore how to leverage the PyBEL ecosystem to construct and analyze rich biological knowledge graphs directly within Google Colab. We begin by installing all necessary packages, including PyBEL, NetworkX, Matplotlib, Seaborn, and Pandas. We then demonstrate how to define proteins, processes, and modifications using the PyBEL DSL. From there, we guide…

Read More A Coding Implementation for Creating, Annotating, and Visualizing Complex Biological Knowledge Graphs Using PyBEL
Editors Pick Staff

Getting Started with Microsoft’s Presidio: A Step-by-Step Guide to Detecting and Anonymizing Personally Identifiable Information PII in Text
ByRicardo June 24, 2025

In this tutorial, we will explore how to use Microsoft’s Presidio, an open-source framework designed for detecting, analyzing, and anonymizing personally identifiable information (PII) in free-form text. Built on top of the efficient spaCy NLP library, Presidio is both lightweight and modular, making it easy to integrate into real-time applications and pipelines. We will cover…

Read More Getting Started with Microsoft’s Presidio: A Step-by-Step Guide to Detecting and Anonymizing Personally Identifiable Information PII in Text
Editors Pick Tutorials

Build a Groundedness Verification Tool Using Upstage API and LangChain
ByRicardo June 24, 2025

Upstage’s Groundedness Check service provides a powerful API for verifying that AI-generated responses are firmly anchored in reliable source material. By submitting context–answer pairs to the Upstage endpoint, we can instantly determine whether the supplied context supports a given answer and receive a confidence assessment of that grounding. In this tutorial, we demonstrate how to…

Read More Build a Groundedness Verification Tool Using Upstage API and LangChain
Editors Pick Staff

A Coding Guide to Build a Production-Ready Asynchronous Python SDK with Rate Limiting, In-Memory Caching, and Authentication
ByRicardo June 23, 2025

In this tutorial, we guide users through building a robust, production-ready Python SDK. It begins by showing how to install and configure essential asynchronous HTTP libraries (aiohttp, nest-asyncio). It then walks through the implementation of core components, including structured response objects, token-bucket rate limiting, in-memory caching with TTL, and a clean, dataclass-driven design. We’ll see…

Read More A Coding Guide to Build a Production-Ready Asynchronous Python SDK with Rate Limiting, In-Memory Caching, and Authentication
Artificial Intelligence Editors Pick

Do AI Models Act Like Insider Threats? Anthropic’s Simulations Say Yes
ByRicardo June 23, 2025

Anthropic’s latest research investigates a critical security frontier in artificial intelligence: the emergence of insider threat-like behaviors from large language model (LLM) agents. The study, “Agentic Misalignment: How LLMs Could Be Insider Threats,” explores how modern LLM agents respond when placed in simulated corporate environments that challenge their autonomy or values. The results raise urgent…

Read More Do AI Models Act Like Insider Threats? Anthropic’s Simulations Say Yes
Artificial Intelligence Editors Pick

VERINA: Evaluating LLMs on End-to-End Verifiable Code Generation with Formal Proofs
ByRicardo June 23, 2025

LLM-Based Code Generation Faces a Verification Gap LLMs have shown strong performance in programming and are widely adopted in tools like Cursor and GitHub Copilot to boost developer productivity. However, due to their probabilistic nature, LLMs cannot provide formal guarantees for the code generated. The generated code often contains bugs, and when LLM-based code generation…

Read More VERINA: Evaluating LLMs on End-to-End Verifiable Code Generation with Formal Proofs
Editors Pick New Releases

EmbodiedGen: A Scalable 3D World Generator for Realistic Embodied AI Simulations
ByRicardo June 22, 2025

The Challenge of Scaling 3D Environments in Embodied AI Creating realistic and accurately scaled 3D environments is essential for training and evaluating embodied AI. However, current methods still rely on manually designed 3D graphics, which are costly and lack realism, thereby limiting scalability and generalization. Unlike internet-scale data used in models like GPT and CLIP,…

Read More EmbodiedGen: A Scalable 3D World Generator for Realistic Embodied AI Simulations

Editors Pick

Polaris-4B and Polaris-7B: Post-Training Reinforcement Learning for Efficient Math and Logic Reasoning

GURU: A Reinforcement Learning Framework that Bridges LLM Reasoning Across Six Domains

Google DeepMind Releases Gemini Robotics On-Device: Local AI Model for Real-Time Robotic Dexterity

A Coding Implementation for Creating, Annotating, and Visualizing Complex Biological Knowledge Graphs Using PyBEL

Getting Started with Microsoft’s Presidio: A Step-by-Step Guide to Detecting and Anonymizing Personally Identifiable Information PII in Text

Build a Groundedness Verification Tool Using Upstage API and LangChain

A Coding Guide to Build a Production-Ready Asynchronous Python SDK with Rate Limiting, In-Memory Caching, and Authentication

Do AI Models Act Like Insider Threats? Anthropic’s Simulations Say Yes

VERINA: Evaluating LLMs on End-to-End Verifiable Code Generation with Formal Proofs

EmbodiedGen: A Scalable 3D World Generator for Realistic Embodied AI Simulations

Curated by experts. Filtered for relevance.

Resources

About

Subscribe & learn more every day!