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I wanted to test something very specific: Can an AI agent build inside Godot with real engine feedback, instead of just writing files and hoping they work? So I made a small Godot demo project called Kantari using Fennara. Video demo: https://www.youtube.com/watch?v=8y2Ub8pgNSs GitHub repo: https://
Gemma 4 12B uses a new encoding scheme and token prediction to punch above its weight.
The company's new hybrid inference system routes AI tasks between your device and the cloud automatically. Privacy and cost savings are the pitch—and lower server bills.
Before you post, please make sure to: Add a clear title that describes your question. Add all required tags in the tag option (top-right of the post): The platform (e.g., dl-ai-learning-platform or Coursera-platform.) The course week/module Write a detailed Unable to grade the capstone project in Co
Testing fourteen engines on ninety-three human documents The post I Spent May Evaluating Different Engines for OCR appeared first on Towards Data Science.
A comprehensive guide to optimizing LLM inference by eliminating padding overhead with hardware-aware sequence packing. The post I Built a C++ Backend So My GPU Would Stop Eating Air appeared first on Towards Data Science.
Science can already tell you what a molecule is and what it looks like. What it has never been able to tell you, cheaply and at scale, is how the thing behaves once it meets the messy conditions of the real world. That gap is where drugs quietly fail in trials, where food products miss […] This stor
Online publishers are getting more control over whether their websites appear in Google's AI Search features, thanks to a UK regulatory ruling. The new conduct rule imposed by the Competition and Markets Authority (CMA) requires Google to let website owners keep their content out of features like AI
Microsoft’s Majorana 2 quantum chip arrived this week with numbers that are genuinely difficult to contextualise: qubits 1,000 times more reliable than the first generation, a mean qubit lifetime of 20 seconds against an industry norm measured in microseconds, and a revised roadmap targeting a comme
AI.Insaf (@ai_tablet) — Полный архив постов канала Ранние посты (#1-~49) Пост ~1: TabGAN (pet project) Библиотека генерации табличных данных (с 2021) 500+ ⭐, 40K загрузок, 38 цитирований Грант Яндекс Open Source (апрель 2024) Теперь генерация через GAN + LLM + Forest Diffusion pip install tabgan htt
A few months ago, I built an AI agent to automate one of the most repetitive parts of my workflow: research and content preparation. In a controlled environment, everything worked exactly as expected. The agent could research topics, gather sources, extract insights, generate outlines, and feed the
Last week, I ran a small experiment. I wanted to see how well GPT-4 could interact with a real-world API without much hand-holding. Nothing complicated. No multi-agent workflows. No orchestration frameworks. Just a simple task that thousands of applications perform every day. Send an email through S
Hand the same paired before/after dataset (n = 25) to ChatGPT five times. Same prompt: "These are the same subjects measured before and after an intervention. Did their scores change significantly?" Four of the five runs return p = 0.009 from a paired t-test. The fifth run does a Shapiro–Wilk normal
The obvious counterargument to everything I'm building is this: Google already does it. You type "best AI tools for video editing" into Google and an AI Overview surfaces a curated list, synthesized from the same kind of data I maintain, without requiring a click. My three directory sites — Top AI T
Tem uma armadilha clássica em projetos de ciência de dados com regressão linear que pega muita gente: o modelo treina, a loss parece ok, o R² até aparece razoável — mas as estimativas de coeficiente são uma bagunça. O motivo, quase sempre, é simples: X não varia o suficiente. Na regressão linear sim
In the era of artificial intelligence, some companies have struggled to adopt artificial intelligence and others have pivoted to an AI framework that has yielded positive results. Snowflake Inc. this week confirmed it’s firmly in the latter category. The cloud data platform giant took what amounted
Microsoft on Tuesday took the wraps off Adaptive Spec-driven Scoring for Evaluation and Regression Testing, an open source framework for spinning up AI evaluations.
Anthropic laid down some sobering words on Tuesday. “A successful attack on their codebase could be catastrophic. For most partners, The post “A successful attack could be catastrophic”: Anthropic gives more groups access to Claude Mythos appeared first on The New Stack.
I wrote a post yesterday about why GPUs barely help small text embeddings at batch=1. Different workload, same machines. This time I ran a local LLM inference benchmark across the same three boxes. The result complicated my hardware mental model in a way I think is worth sharing. Three machines. A M
Microsoft AI has fully joined the conversation with MAI-Thinking-1, alongside new coding, image, and voice models.
