Here’s how it plays: you register, choose (or create) a character, give him a name, and start talking. You can flirt, make a joke, talk about your boss, or do all the NSFW situations if that’s your thing. Conversations are dynamic. AI remembers your vibe, your previous conversations, your preferences, your kinks even. It’s like … Read more
!pip -q install -U “protobuf<5” “flwr[simulation]” transformers peft accelerate datasets sentencepiece import torch if torch.cuda.is_available(): !pip -q install -U bitsandbytes import os os.environ[“RAY_DISABLE_USAGE_STATS”] = “1” os.environ[“TOKENIZERS_PARALLELISM”] = “false” import math import random import numpy as np from typing import Dict, List, Tuple, Optional from torch.utils.data import DataLoader from datasets import Dataset import flwr as fl … Read more
Earth observation (EO) constellations capture many high-resolution images every day, but most of them do not reach the ground during model training. Downlink bandwidth is the main bottleneck. Images can remain in orbit for days while ground models train with partial and delayed data. Microsoft researchers have introduced the ‘OrbitalBrain’ framework as an alternative. Instead … Read more
When I first started working in the medical device industry nearly 20 years ago, static analysis tools took the limelight and attention of the medical device industry. This was reflected in a 2007 press article, which highlighted a major investment by the United States Food and Drug Administration (FDA) Center for Devices and Radiological Health … Read more
Autonomous AI agents are entering real-world workflows, managing projects and performing complex tasks with increasing automation. As their responsibilities increase, the need for robust security, reliability, and performance control increases. Manufacturing environments require predictable behavior, safe automation, and supervision. This article focuses on how OpenClaw 2026.2.3, the latest version of OpenClaw, strengthens the foundations that … Read more
Robots enter their GPT-3 era. For years, researchers have been trying to train robots using the same autoregressive (AR) models that power large-scale linguistic models (LLMs). If the model can predict the next word in a sentence, it should be able to predict the next movement of the robot arm. … Read more
In this tutorial, we show how we treat data as first-class, versioned artifacts and apply robust regression testing to the behavior of a large language model using MLflow. We design a test pipeline that includes data versions, rapid variations, model outputs, and multiple quality metrics in a fully reproducible manner. By combining classical text metrics … Read more
With a focus on open interactions, Yami allows emotional storytelling, character depth, passionate dialogue, and mature situations to develop naturally without sudden content restrictions. ⚡️ FAVORITE CONVERSATIONS ⚡️ Candy AI Try Candy AI Unfiltered Chat with AI GirlsPictures and voice messagesVideo Generation My dream friend Try Mydreamcompanion Spicy AI ChattingText and voice messagesAI Girlfriend who … Read more
How close can an open model get to AlphaFold3 level accuracy if it matches the training data, model scale and decision budget? ByteDance presented Protenix-v1perfect Reproduction of AlphaFold3 (AF3). for the prediction of biomolecular structure, extracted with code and model parameters under Apache 2.0. The model is directed AF3 level performance for all protein, DNA, … Read more
In this lesson, we go through advanced testing, from the end of the Polyfactorywe focus on how to generate rich, pseudo-realistic data directly from Python type schemes. We begin by setting up the environment and continue to create data class factories, Pydantic models, and atrs-based classes, while demonstrating customization, overriding, calculated fields, and nested object … Read more