The latest scourge of Twitter is AI bots that reply to your tweets with generic, banal commentary slop, often accompanied by a question to “drive engagement” and waste as much of your time as possible. I just found out that the category name for this genre of software is reply guy tools. Amazing. Tags: ai-ethics, twitter, slop, generative-ai, definitions, ai, llms
Every other week, there’s a new wave of viral hype surrounding AI tools. This time around, it’s OpenClaw, a self-hosted autonomous AI agent that can send messages, write emails, browse the web, and perform other tasks. Never mind its potential security vulnerabilities (there are many) and various predecessors that almost worked. The hype is real. Everyone working with Software as a Service (SaaS) products must feel quite uneasy. The wave of “AI wrappers” already taken some casualties, but […]
RL/ML papers love equations before intuition. This post attempts to flip it: each idea appears only when the previous approach breaks, and every concept shows up exactly when it’s needed to fix what just broke. Reinforcement Learning for LLMs “made easy” submitted by /u/zephyr770 [link] [comments]
arXiv:2603.06678v1 Announce Type: new Abstract: Partial Information Decomposition (PID) has become one of the most prominent information-theoretic frameworks for describing the structure and quality of information in complex systems. Despite its widespread utility, there exists no unique solution constraining precisely how a PID should be constructed, leading to a multiverse of different formalisms with different mathematical commitments. In this work, we provide a comprehensive overview of the mathematical landscape of PID. By integrating existing PID measures into a […]
In this quiz, you’ll revisit the core concepts covered in the Python Web Scraping learning path: Learning Path Python Web Scraping 10 Resources ⋅ Skills: Web Scraping, HTTP Requests, Data Parsing You’ll be quizzed on making HTTP requests, parsing HTML with Beautiful Soup, extracting data with Scrapy, working with JSON and CSV response data, and automating browsers with Selenium. Take your time and revisit any topics that feel rusty before moving on. [ Improve Your Python With 🐍 […]
Running AI agents in a local script is straightforward. Running them reliably in production across teams, across restarts, with isolated environments per context is a different problem entirely. BerriAI, the company behind the LiteLLM AI Gateway, is now open-sourcing a purpose-built answer to that problem: the LiteLLM Agent Platform. The platform is described as a simple, self-hosted infrastructure platform for running multiple agents in production. What Problem Does it Solve? It helps to understand what happens when you […]
We introduce TriSearch, a reinforcement learning framework for optimizing objectives over triangulations of a polytope via bistellar flips. The key idea is a circuit-supported subtriangulation action representation: feasible flips are encoded by their supporting circuit and realized local subtriangulation, enabling a learned policy to rank them using local geometric and combinatorial features. This yields a dimension-agnostic interface and enables efficient traversal of the flip graph without explicit enumeration of the full triangulation space. Instantiated in 3D and 4D, […]
For years, builders in tokenization have been waiting for a decisive signal that traditional finance would not just experiment with private blockchain infrastructure, but integrate with it into decentralized finance. That signal arrived when BlackRock’s tokenized money market fund, BUIDL, began trading on Uniswap through UniswapX in partnership with Securitize. This was not a sandbox pilot. It was a $2.1 billion tokenized US Treasury fund connecting directly to decentralized liquidity rails. The development was reported by Fortune, which […]
An AI agent for data science: Amazon Q Developer in SageMaker Canvas New tool lets customers build, train, and deploy machine learning models using only natural language. Machine learning Yaroslav Kharkov Gerald Friedland April 10, 09:00 AM October 10, 06:48 PM Developing AI-powered predictive models for real-world data typically requires expertise in data science, familiarity with machine learning (ML) algorithms, and a solid understanding of the models business context. The complete development cycle for data science applications from […]
arXiv:2602.12349v1 Announce Type: new Abstract: Green’s functions characterize the fundamental solutions of partial differential equations; they are essential for tasks ranging from shape analysis to physical simulation, yet they remain computationally prohibitive to evaluate on arbitrary geometric discretizations. We present Variational Green’s Function (VGF), a method that learns a smooth, differentiable representation of the Green’s function for linear self-adjoint PDE operators, including the Poisson, the screened Poisson, and the biharmonic equations. To resolve the sharp singularities characteristic of […]