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large language models (LLMs)

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From Headshots to Hackathon-Ready: How AI Saved My Design in 2 Minutes

2026-03-26T20:33:03+00:00

You only have four hours left to create an eye-catching social media post introducing the judges of your upcoming hackathon and all you have are inconsistent headshot images. This is not just another graphic. You are designing a visual that represents respected professionals–people whose credibility reflects directly on your event. But working with mismatched headshots (different angles, lighting, crops, and backgrounds) makes it nearly impossible to achieve a cohesive design. And it’s already 1 AM. Reaching out to them for new photos isn’t an option. So what do you do? When Time, Quality, and Expectations Collide If you’ve worked in event marketing [...]

From Headshots to Hackathon-Ready: How AI Saved My Design in 2 Minutes2026-03-26T20:33:03+00:00

Voice AI Hackathon Manila 2026

2026-03-28T14:13:27+00:00

You've won an opportunity at the Innovation Cup 2025 hackathon competition to represent Agora Philippines as an ambassador, along with your teammates. Now that you’ve become an Agora Ambassador–what comes next? In frame: Ashley Nicole Santos, Kendrick Zamudio, Christine May Ponciano, and Dearah Mae Barsolasco You build something impactful. You host a hackathon. Together with AWS Cloud Club Philippines, the Agora Philippines Ambassadors successfully launched the Voice AI Hackathon Manila 2026, a high-energy, one-day innovation sprint held on March 16, 2026, at the AWS Office in Bonifacio Global City. The event gathered 27 competitive teams composed of developers, [...]

Voice AI Hackathon Manila 20262026-03-28T14:13:27+00:00

Amazon Bedrock’s LLM-as-a-Judge: Automate AI Evaluation with Nova Lite + Claude

2026-01-23T15:25:15+00:00

Evaluating your LLM’s quality should not cost you too much money or even weeks of your time.  You’re probably  stuck in a limbo of choosing between two options that have their own drawbacks: Automated metrics like BLEU, ROUGE and accuracy scores? Sure, they are quite fast and cheap, but they ultimately fall short in judging real conversations. Since they simply match word patterns, they're not a good fit for open ended responses simply because they can't tell  if they actually understood the question or its tone. As for human reviewers, they do get it right. They captured the context/subtlety and [...]

Amazon Bedrock’s LLM-as-a-Judge: Automate AI Evaluation with Nova Lite + Claude2026-01-23T15:25:15+00:00

Large Reasoning Models (LRMs): The AI That Actually Shows Its Work

2025-07-08T12:38:54+00:00

Imagine you are in a Math Class, and the teacher just gave a complex problem for everyone to solve. Then, after a few minutes, a classmate just shouted an answer. You’re all shocked because how did he come up with it? Was it the correct answer or they just made a guess? When the teacher asked them to elaborate they refused and said that they already did their work.  This scenario displays the frustrations with traditional AI systems: fast answers with zero transparency.  Now imagine that same classmate going up to the board, writing all of the formulas and calculations, [...]

Large Reasoning Models (LRMs): The AI That Actually Shows Its Work2025-07-08T12:38:54+00:00

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens)

2025-07-09T15:12:24+00:00

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens) The Big Question: Can You Build AI Without Breaking the Bank? We asked ourselves a simple question: Can you build a chatbot without using any paid API at all? Most tutorials on AI chatbots start the same way: "First, grab your OpenAI API key and add your credit card..." But what if you don't have one? Or don't want to use one? Maybe you're a student on a tight budget. Maybe you're tired of hitting rate limits just when your chatbot gets interesting. Or maybe, just maybe, [...]

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens)2025-07-09T15:12:24+00:00

What is Retrieval Augmented Generation (RAG) in Machine Learning?

2025-06-30T03:46:57+00:00

Retrieval-Augmented Generation (RAG) Cheat Sheet Retrieval-Augmented Generation (RAG) is a method that enhances large language models (LLMs) outputs by incorporating information from external, authoritative knowledge sources. Instead of relying solely on pre-trained data, RAG retrieves relevant content at inference time to ground its responses. LLMs (Large Language Models) are trained on massive datasets and use billions of parameters to perform tasks like: Question answering Language translation Text completion RAG extends LLM capabilities to domain-specific or private organizational knowledge without requiring model retraining. It provides a cost-efficient way to improve the relevance, accuracy, and utility of LLM outputs in dynamic or [...]

What is Retrieval Augmented Generation (RAG) in Machine Learning?2025-06-30T03:46:57+00:00

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