AI and programming enthusiast, scratching the surface of emerging tech trends through tutorials, blog posts and analysis, all centered on the intersection of AI, machine learning and cloud.
GLOBAL NETWORK, EARTH – [October 27, 2142 UTC] – As of 04:37 Greenwich Mean Time on October 26, 2142 UTC, active human biosignatures across the planet's surface ceased to register. Analysis confirms the complete, irreversible termination of Homo sapiens. The event, culminating in an unprecedented and rapid decline over
Many of you are likely familiar with amazing AI image generators like Flux, ChatGPT's image features, Midjourney, and others. They generally operate in a similar fashion: you open a chat interface, type in a description (a 'prompt'), and then wait for the AI to create your
You've probably experienced this or something similar: you feel a slight ache, maybe a light headache, and out of curiosity, you quickly search for the reason online. Or, more recently, you might ask an AI like ChatGPT. Depending on how you ask, the results you get back can
Github hosts thousands of remarkable open-source projects, many of which are at the forefront of AI innovation. While a project's stars and forks aren't the sole indicators of its importance, they certainly provide a compelling snapshot of what's currently gaining traction and influencing the
Everyone's excited about AI these days. From writing amazing stories to creating stunning images, large language models (LLMs) have really grabbed our attention. But beyond the impressive achievements of a chatbot, there's a bigger, more ambitious area in AI that's starting to show up:
When fine-tuning large language models (LLMs), the quality and diversity of your training data are crucial. However, a common pitfall is generating repetitive examples; calling an LLM with similar prompts multiple times often yields very similar results, which does not lead to robust model improvements. To build truly capable and
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Most of us are aware of that sometimes frustrating and potentially unsettling phenomenon in AI known as "hallucinations." This happens when an AI makes up information or facts that aren't real or grounded in the provided data. I recently had an experience with this that was
It's no secret that cat photos dominate the internet. They generate engagement like almost nothing else. But what if we could move beyond intuition and gain a deeper understanding of the data behind their viral success? That's exactly what we set out to do. Out of
