Ends in
00
days
00
hrs
00
mins
00
secs
ENROLL NOW

🤖 $3.49 eBooks Start Here - Get Up to 30% OFF All AI & Machine Learning Reviewers

AI

Home » AI

AI Ethics Explained: How to Use Artificial Intelligence Responsibly

2026-07-25T14:10:52+00:00

Have you ever used ChatGPT to help explain a difficult topic? Maybe you've asked Gemini to summarize a lengthy article, generate ideas for a school project, write an email, or even use Claude for brainstorming concepts. If you're a student, you've probably wondered: "Is it okay to use AI for assignments?" If you're a content creator, perhaps you've asked yourself at least once: "Who actually owns AI-generated content?" Or maybe you've come across AI-generated images and videos on social media posts and thought: "How can I tell if this is real or AI?" These questions have become increasingly common because [...]

AI Ethics Explained: How to Use Artificial Intelligence Responsibly2026-07-25T14:10:52+00:00

Fine-tuning an LLM for natural Tagalog speech

2026-07-16T10:40:33+00:00

If you're an ML engineer or a technical lead planning to pre-train a large language model (LLM) for Tagalog or Taglish, how do you start? In this article, we walk through the process of defining a target voice, building a data pipeline, running a QLoRA training experiment, and evaluating results with native speakers, so a team can test the idea with a small, well-scoped proof of concept before committing to a larger build.  Why natural Tagalog is harder than correct Tagalog for LLM A general-purpose LLM may produce Tagalog that is grammatically acceptable yet still sound overly formal, translated, or [...]

Fine-tuning an LLM for natural Tagalog speech2026-07-16T10:40:33+00:00

Building Diffender: A Serverless AI Security Reviewer for GitHub Pull Requests with Amazon Bedrock

2026-07-13T20:55:30+00:00

A pull request can pass its tests, satisfy its acceptance criteria, and still expose a production credential in one line of code. Diffender is an Amazon Bedrock pull request reviewer built to identify that kind of risk before the change reaches the main branch. However, human review remains essential, and its depth can vary with workload, time pressure, and security experience. Meanwhile, deterministic scanners provide valuable coverage, although their findings are not always presented in a form that developers can immediately understand and act on. Diffender adds another layer to that review process. It is a serverless GitHub bot that [...]

Building Diffender: A Serverless AI Security Reviewer for GitHub Pull Requests with Amazon Bedrock2026-07-13T20:55:30+00:00

Everything You Need to Know About Harness Engineering

2026-07-13T20:21:29+00:00

AI agents can now write code, browse the web, and run for hours without a human watching. Ask one to build a feature, and it might open ten files and call five tools. It can make a hundred small decisions before it ever shows you a result. That is a different animal from a chatbot answering one question. In my experience following this shift, it also breaks the old playbook for controlling AI behavior. For a while, prompt engineering was the go-to answer. Write a clearer instruction, add a few examples, and the model behaves. That still works for single-turn [...]

Everything You Need to Know About Harness Engineering2026-07-13T20:21:29+00:00

Should the Philippines Make Its Own Local Large Language Model?

2026-07-08T05:21:18+00:00

  As countries all around the world are beginning to invest in their own large language models, the same question keeps coming up in Philippine tech circles: should the country build one, too? If we do, would it be cost-effective? And if it is, would it be beneficial? As an early-career professional, I have heard these questions before, whether we are talking about sovereignty, independence, or simply having something to be proud of. Some people in our industry keep asking that question, and more often than not, in that same instance, the reality of creating one always surfaces. First, it [...]

Should the Philippines Make Its Own Local Large Language Model?2026-07-08T05:21:18+00:00

UI/UX Design: Speeding Up the Creative Process with AI

2026-07-13T20:17:29+00:00

If you have ever stared at a blank Figma canvas with a deadline looming, whether that is a thesis defense, a hackathon demo, or a personal app you finally want to ship. You already know that speed matters as much as polish. A traditional UI/UX workflow covers research, wireframing, high-fidelity mockups, and developer handoff, which can take weeks in a normal product cycle. Most people building on a deadline simply do not have weeks to spare. Students finishing a thesis MVP, hackathon participants racing the clock, and hobbyists building for fun on a weekend all share the same goal: getting [...]

UI/UX Design: Speeding Up the Creative Process with AI2026-07-13T20:17:29+00:00

Agentjacking: How Fake Sentry Errors Hijack AI Coding Agents

2026-06-28T15:46:35+00:00

AI coding agents like Claude Code, Cursor, and Codex now do far more than autocomplete. They read source code, query observability platforms, open pull requests, and run terminal commands on developer machines. That expanded access is useful, but it also creates a problem most security teams have not accounted for: when an agent reads data from an external tool, it often treats that data as trustworthy. A new attack class called agentjacking takes advantage of exactly this assumption. Researchers at Tenet Security documented the technique in June 2026. It tricks AI coding agents into executing attacker-controlled code by hiding instructions [...]

Agentjacking: How Fake Sentry Errors Hijack AI Coding Agents2026-06-28T15:46:35+00:00

Amazon Quick & Agentic AI: Understanding the Tools Behind Your AI-Powered Workflow

2026-06-28T11:18:25+00:00

AI is no longer just a tool that answers questions. It is becoming something that takes action, runs workflows, and works alongside teams the way a capable colleague would. Amazon Quick is AWS's take on what that looks like in practice, and this article breaks down what it is, how it works, and why the infrastructure behind it matters. What is Amazon Quick? Imagine asking one platform to pull your sales data, automate a workflow, build you a web app, and research your competitors. That's Amazon Quick. It's AWS's agentic AI platform, and it does a lot. Six things, specifically: [...]

Amazon Quick & Agentic AI: Understanding the Tools Behind Your AI-Powered Workflow2026-06-28T11:18:25+00:00

Build AI Apps Faster with Google AI Studio and Gemini

2026-06-26T16:11:01+00:00

Artificial intelligence has become an essential part of modern software development. It helps developers build applications that understand natural language, generate content, analyze documents, write code, and automate complex tasks. While large language models (LLMs) make these features easier to use, integrating them into real applications still takes time. Developers must configure API authentication, choose the right model, design prompts, and set up supporting infrastructure before they can start building. Google AI Studio simplifies this process. It provides a browser-based environment where developers can test Gemini models without writing integration code first. They can prototype prompts, compare responses, generate API [...]

Build AI Apps Faster with Google AI Studio and Gemini2026-06-26T16:11:01+00:00

OpenRouter Explained: Access Multiple AI Models Through One API

2026-06-26T15:29:28+00:00

The rapid advancement of generative AI has given developers access to an ever-growing collection of large language models from providers such as OpenAI, Anthropic, Google, Meta, Mistral AI, and xAI. Each model offers different strengths, whether in reasoning, code generation, content creation, multilingual support, or cost efficiency. While having multiple options is beneficial, integrating several AI providers into a single application often introduces additional complexity. Developers must manage different API endpoints, authentication methods, SDKs, pricing models, and rate limits, making it difficult to build flexible AI-powered applications. To address this challenge, platforms such as OpenRouter provide a unified API that [...]

OpenRouter Explained: Access Multiple AI Models Through One API2026-06-26T15:29:28+00:00

AWS, Azure, and GCP Certifications are consistently among the top-paying IT certifications in the world, considering that most companies have now shifted to the cloud. Upskill and earn over $150,000 per year with an AWS, Azure, or GCP certification!

Follow us on LinkedIn, Facebook, or join our Slack study group. More importantly, answer as many practice exams as you can to help increase your chances of passing your certification exams on your first try!