Installing FSL Run this in your terminal: (or with sh if you prefer): What happens: When it finishes you should see: After installation – set up the environment Close the terminal and open a new…
While both are AI-powered video tools by Google, they serve entirely different purposes and audiences. The short answer: Google Flow is an advanced AI creative studio for visual artists and filmmakers to generate and manipulate…
The CO-STAR Framework Use this structured method to provide all necessary context for a high-quality response: Prompts to Reduce Hallucinations These strategies help ensure the AI sticks to the facts rather than “improvising”: Few-shot prompting:…
Tree of Thoughts (ToT) prompting is a technique where you ask the AI to generate multiple reasoning paths (branches), evaluate them, and then expand on the most promising ones. Unlike “Chain of Thought” (which follows…
Designing a high-quality survey is about more than just writing questions; it’s about minimizing bias, ensuring logical flow, and maximizing completion rates. Here is a guide on how to use AI prompting at every stage…
The Circular Reporting Effect: This is a growing problem in the age of generative AI — a self-reinforcing loop where fake information created by one AI ends up being treated as real by another AI…
Suppose that I put this prompt into Nano banana to create an image for a scientific paper Gemini output this image which looks very undesirable with too many redundant extra details. Writing prompt to edit…
If you’ve ever asked an AI to summarize a long article, you’ve probably experienced a common frustration: the summary is either too vague, misses the most important facts, or is padded with repetitive filler like,…
We’ve all been there. You have a big project, you open up your favorite AI tool, and you dump everything you need into one massive prompt. You ask for a marketing strategy, a breakdown of…
Using AI for difficult emails is a superpower because it removes the emotional tax from the task. When you are stressed or defensive, it’s hard to write clearly; AI, having no ego, can draft a…
Using a pre-training corpus derived from incident databases for safety fine-tuning is a promising, real-world-grounded approach to embedding AI failure knowledge directly into models. It draws on databases like the AI Incident Database (AIID), OECD…
In 2026, AI creative tools have exploded. Whether you’re a designer, marketer, filmmaker, or developer, choosing the right platform for image, video, and audio generation matters more than ever. Today we compare the big five:…
As of March 2026, the AI landscape has matured into clear specialists rather than one-size-fits-all winners. Google’s Gemini 3.1 Pro, Anthropic’s Claude Opus 4.6, xAI’s Grok 4, OpenAI’s ChatGPT (GPT-5.4), and Google’s specialized NotebookLM each…
Download on Hugging Face. Description is in the paper A large-scale heterogeneous 3D magnetic resonancebrain imaging dataset for self-supervised learning FOMO60K is a subset of FOMO300K that includes 60,529 MRI scans collected from 13,900 MRI…
If you’ve ever asked an AI to summarize a long article, you’ve probably experienced a common frustration: the summary is either too vague, misses the most important facts, or is padded with repetitive filler like,…
The Bonferroni correction is a statistical method used to reduce the risk of Type I errors (false positives) when you run multiple hypothesis tests. Every time you test a hypothesis, there’s a chance you’ll incorrectly…
Type I Error (False Positive) You reject a true null hypothesis — you conclude something is happening when it actually isn’t. Example:A medical test says a patient has a disease, but they actually don’t. Type…
🧩 What “Independent Samples” Means Two samples are independent when the individuals in one group have no relationship to the individuals in the other group. This is the setup for the independent‑samples t‑test, also called…
A one‑sample t‑test checks whether the mean of a single sample is significantly different from a known or hypothesized population mean. It answers the question: “Is my sample mean different enough from the population mean…
A t‑test is a hypothesis test used when you want to compare means but you don’t know the population standard deviation and your sample size is small. It’s used for: One‑sample t‑test → compare one…
The significance level, usually written as , is the threshold for how much evidence you require before rejecting the null hypothesis. It is the probability of making a Type I error: So choosing α is…
The p‑value is the probability of getting a result as extreme as (or more extreme than) your sample result if the null hypothesis were true. In other words: The p‑value tells you how surprising your…
Instead of using a p‑value, you compare your test statistic (like a z‑score or t‑score) to a critical value that marks the boundary of the rejection region. If your test statistic falls beyond the critical…
🧪 Ronald Fisher: The p‑value Rebel Philosophy: Evidence, not decisions Fisher believed statistics should help scientists measure evidence against a null hypothesis. Key ideas Fisher’s vibe: The scientist as a detective, gathering clues and weighing…
At the heart of every hypothesis test are two competing statements about a population: They must be:Mutually exclusive (can’t both be true)Exhaustive (cover all possibilities)About population parameters, not sample statistics Let’s break down how to…
