Month: April 2025

Ever seen this? “Transaction Declined” Your card’s fine. Your money’s real. So…???? You’re not alone (hopefully!). Welcome to the invisible leak no one talks about – credit card authorization failures. It’s not just a customer annoyance. It’s a revenue black hole. And businesses are bleeding silently at the point of payment. So, what should we … Read more

Color is essential in user interface (UI) design; it influences emotions, perception, engagement, and retention. As a designer, understanding the principles of color psychology can help you create interfaces that resonate with users, improve usability, build loyalty, encourage continued interaction, and enhance the overall experience. In this article, we will explore how to use color … Read more

Introduction I guess I’ve always been a Frank Sinatra’s my-way-kind-of-a-man who has followed his instincts in both private and professional life. I obtained an academic degree in 2003 and, as one of the top 30 students in my country, I had a promise of a career as a lawyer or public prosecutor. However, after only … Read more

Table of Links Abstract and 1 Introduction 2 LongFact: Using LLMs to generate a multi-topic benchmark for long-form factuality 3 Safe:LLM agents as factuality autoraters 4 LLMs agents can be better factuality annotators than humans 5 F1@k: Extending F1 with recall from human-preferred length 6 Larger LLMs are more factual 7 Related Work 8 Limitations … Read more

Table of Links Abstract and 1 Introduction 2 LongFact: Using LLMs to generate a multi-topic benchmark for long-form factuality 3 Safe:LLM agents as factuality autoraters 4 LLMs agents can be better factuality annotators than humans 5 F1@k: Extending F1 with recall from human-preferred length 6 Larger LLMs are more factual 7 Related Work 8 Limitations … Read more

Table of Links Abstract and 1 Introduction 2 LongFact: Using LLMs to generate a multi-topic benchmark for long-form factuality 3 Safe:LLM agents as factuality autoraters 4 LLMs agents can be better factuality annotators than humans 5 F1@k: Extending F1 with recall from human-preferred length 6 Larger LLMs are more factual 7 Related Work 8 Limitations … Read more

:::info Authors: (1) Jerry Wei, Google DeepMind and a Lead contributors; (2) Chengrun Yang, Google DeepMind and a Lead contributors; (3) Xinying Song, Google DeepMind and a Lead contributors; (4) Yifeng Lu, Google DeepMind and a Lead contributors; (5) Nathan Hu, Google DeepMind and Stanford University; (6) Jie Huang, Google DeepMind and University of Illinois … Read more

Let me start with a confession. In one of my previous projects, I used to think project chaos was just part of the job. You know the vibe — people stepping on each other’s toes, endless Slack threads trying to figure out who was supposed to do what, decisions made in meetings that no one … Read more

No tariffs, no taxes, no fees Imagine a world where buying an iPhone doesn’t require deciphering a complex web of tariffs, taxes, and fees. Picture a scenario where international trade flows as smoothly as your favorite streaming service — no buffering, no interruptions. Sounds like a utopian dream? Well, with the advent of cryptocurrencies, this … Read more

Image Credit: NightCafe Studio: Link Why the US LLMs Are Showing Poor Returns For Investment Compared to China :::tip The bottleneck is real: the problem is the lack of data! ::: GPT 3.5 to GPT-4-Turbo was a quantum leap. GPT-4.5: hugely enormous computing resources (as evidenced by the massive prices) but not a serious entry … Read more