Building a ‘Human-in-the-Loop’ Approval Gate for Autonomous Agents
In agentic AI systems , when an agent’s execution pipeline is intentionally halted, we have what is known as a state-managed interruption .
In agentic AI systems , when an agent’s execution pipeline is intentionally halted, we have what is known as a state-managed interruption .
We introduce ProText, a dataset for measuring gendering and misgendering in stylistically diverse long-form English texts. ProText spans three dimensions: Theme nouns (names, occupations, titles, kinship terms), Theme category (stereotypically male, stereotypically female, gender-neutral/non-gendered), and Pronoun category (masculine, feminine, gender-neutral, none). The dataset is designed to probe (mis)gendering in text transformations such as summarization and …
Read more “ProText: A Benchmark Dataset for Measuring (Mis)gendering in Long-Form Texts”
Your AI agent worked in the demo, impressed stakeholders, handled test scenarios, and seemed ready for production. Then you deployed it, and the picture changed. Real users experienced wrong tool calls, inconsistent responses, and failure modes nobody anticipated during testing. The result is a gap between expected agent behavior and actual user experience in production. …
Read more “Build reliable AI agents with Amazon Bedrock AgentCore Evaluations”
A suspected system failure froze Baidu’s robotaxis across Wuhan, trapping passengers and reportedly causing traffic disruptions and crashes.
Researchers at Trinity have developed a new light-based technology on a tiny chip that could help make the data centers behind cloud computing, artificial intelligence, and global internet services faster and more efficient. In the new research, recently published in Nature Communications, the Trinity team reported one such promising advance with collaborators at the University …
Read more “Chip-scale light technology could power faster AI and data center communications”
Your monthly “Anzhc’s Posts” issue have arrived. Today im introducing – Mugen – continuation of the Flux 2 VAE experiment on SDXL. We have renamed it to signify strong divergence from prior Noobai models, and to finally have a normal name, no more NoobAI-Flux2VAE-Rectified-Flow-v-0.3-oc-gaming-x. In this run in particular we have prioritized character knowledge, and …
Read more “Mugen – Modernized Anime SDXL Base, or how to make Bluvoll tiny bit less sane”
Your monthly “Anzhc’s Posts” issue have arrived. Today im introducing – Mugen – continuation of the Flux 2 VAE experiment on SDXL. We have renamed it to signify strong divergence from prior Noobai models, and to finally have a normal name, no more NoobAI-Flux2VAE-Rectified-Flow-v-0.3-oc-gaming-x. In this run in particular we have prioritized character knowledge, and …
Read more “Mugen – Modernized Anime SDXL Base, or how to make Bluvoll tiny bit less sane”
This article is divided into three parts; they are: • How Attention Works During Prefill • The Decode Phase of LLM Inference • KV Cache: How to Make Decode More Efficient Consider the prompt: Today’s weather is so .
This article is divided into three parts; they are: • How Attention Works During Prefill • The Decode Phase of LLM Inference • KV Cache: How to Make Decode More Efficient Consider the prompt: Today’s weather is so .
Feature engineering is where most of the real work in machine learning happens.