AI Blindspots – Blindspots in LLMs I've noticed while AI coding

The author has identified various blindspots in Large Language Models (LLMs) while using AI for coding, and has compiled a list of potential solutions and best practices, including topics such as testing, refactoring, and debugging. The list includes 20 items, each with a brief description and a link to a more detailed explanation, covering a range of topics from coding techniques to cultural and strategic considerations.

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Fine-tune Google's Gemma 3

Gemma 3, Google's new multimodal models, are now supported in Unsloth, with models available in 1B, 4B, 12B, and 27B sizes, and featuring a 128K context window and multilingual support. Unsloth has implemented fixes for Gemma 3, including solutions for infinite activation issues with float16 mixed precision, and offers fine-tuning and other features, making it a suitable framework for working with Gemma 3 models.

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LLM Agents Are Simply Graph – Tutorial for Dummies

AI agents work by using a simple graph system, where nodes represent different tasks or decisions, and edges connect these nodes to determine the flow of actions. This graph-based approach can be broken down into basic components, such as decision nodes, action nodes, and finish nodes, and can be used to build complex AI systems, including those that can think, choose actions, and interact with the real world.

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Stripe adds yet another additional $15 dispute fee, unless you use their AI

Stripe is introducing an additional $15 fee for countering disputes, on top of the existing $15 fee for filing a dispute, which can result in a total of $30 in fees. The only exception is if merchants use Stripe's upcoming Smart Disputes AI, and even then, the fees are only refunded if the merchant wins the dispute.

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Hacking Your Own AI Coding Assistant with Claude Pro and MCP

The author was able to implement Kerberos authentication for their Hadoop cluster on EC2 in just 10 minutes with the help of Claude, an AI assistant, and the Model Context Protocol (MCP), whereas it would have normally taken a full day of work. By using MCP with Claude, the author was able to automate the complex configuration process and save time, while also avoiding the costs of specialized AI coding tools like Cursor Pro.

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Measuring AI Ability to Complete Long Tasks

Researchers have proposed a new metric, the 50%-task-completion time horizon, to quantify AI capabilities in terms of human capabilities, finding that current AI models can complete tasks with 50% success rate in around 50 minutes, a time frame that has been doubling approximately every seven months. If this trend continues, AI systems may be able to automate many software tasks that currently take humans a month within the next five years, driven by improvements in reliability, adaptability, logical reasoning, and tool use capabilities.

ArXiv

MarketSenseAI 2.0: Enhancing Stock Analysis Through LLM Agents

MarketSenseAI is a framework for stock analysis that utilizes Large Language Models to process financial data, news, and macroeconomic information, and has shown significant improvement in fundamental analysis accuracy. The framework has demonstrated strong performance, achieving cumulative returns of 125.9% on S&P 100 stocks over two years and outperforming the market on S&P 500 stocks, while maintaining comparable risk profiles.

ArXiv

The clustering behavior of sliding windows

Clustering timeseries data preprocessed with a sliding window can lead to significant failures, which emerge based on the comparison between the window size and the timeseries length. Theoretical explanations and computational examples are provided to illustrate three specific failure modes that can occur in this context.

ArXiv

Neurosymbolic Decision Trees

Neurosymbolic decision trees (NDTs) integrate neural networks and symbolic reasoning, and a new algorithm called NeuID3 allows for the learning of both the neural and symbolic structure of these models. The NeuID3 algorithm enables NDTs to handle both symbolic and subsymbolic data, such as images, and leverage background knowledge to improve the induction of the tree structure, outperforming traditional data-driven approaches with neural networks.

ArXiv

New Computer with intergrated Brain Computer interface

The PiEEG Box is a portable, all-in-one device that allows users to measure EEG, EMG, EOG, and EKG signals, incorporating a Raspberry Pi-based shield, sensors, and other necessary components. This compact and user-friendly tool offers 8-channel EEG recording capabilities, reducing setup time and complexity, and has the potential to broaden the application of EEG technology in fields such as neuroscience research and education.

ArXiv

Show HN: AI-Powered Documentation Generator for Legacy Codebases

McpDoc is a tool that generates documentation for existing systems using the Model Context Protocol (MCP) and C4 architecture diagrams, providing a hierarchical approach to software architecture documentation. The tool creates summaries and diagrams at different levels of detail, from high-level context diagrams to detailed component diagrams, to help teams maintain useful documentation and navigate complex systems.

Repo

NVIDIA releases AgentIQ – A library to connect any AI agent to any data source

NVIDIA AgentIQ is a flexible library that enables seamless integration of enterprise agents with various data sources and tools, allowing for true composability and reusability of agents, tools, and workflows. AgentIQ offers key features such as framework agnosticism, reusability, rapid development, profiling, and observability, making it a powerful tool for building and managing agent-driven projects.

Repo

Dlib: Modern C++ toolkit containing machine learning algorithms

Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software to solve real-world problems, with documentation and API reference available at http://dlib.net. The library can be compiled and used in various ways, including compiling example programs, creating own C++ programs, and installing the Python API, all with detailed instructions provided.

Repo

I Let an AI Roast My Code for Vulnerabilities–and Honestly, I'm Offended

VibePenTester is an intelligent web vulnerability scanner powered by Large Language Models that discovers security weaknesses and vulnerabilities in web applications, providing detailed reports and reproduction steps. The tool offers various features, including intelligent vulnerability discovery, advanced payload generation, and automated exploit verification, and can be used via a command-line interface or a web interface, with support for multiple LLM providers and models.

Repo

Safely Executing AI Generated Code on your local machine

The author is integrating AI into the software development process, believing it will augment developers' productivity rather than replace them. The project is organized into sections including playbooks, AI prompts, thoughts on AI integration, and tool configurations, serving as a hub for the author's research and investigations into AI-assisted agile software development.

Repo