Most enterprises scaling agentic AI are overspending without knowing where the capital is going. This isn’t just a budget oversight. It points to deeper gaps in operational strategy. While building a single agent is a common starting point, the true enterprise challenge is managing quality, scaling use cases, and capturing measurable value across a fleet...
The post The 100-agent...
Obtaining the text in a messy PDF file is more problematic than it is helpful. The problem does not lie in the ability to transform pixels into text, but rather, in maintaining the structure of the document. Tables, headings, and images should be in the right sequence. When using Mistral OCR 3, it is no […]
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If you’ve ever watched a game and wondered, “How do brands actually measure how often their logo shows up on screen?” you’re already asking an ACR question. Similarly, insights like: are all powered by Automatic Content Recognition (ACR) technology. It looks at raw audio/video and figures out what is in it without relying on filenames, […]
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Learning AI isn’t difficult because of the content, it’s difficult because everyone learns differently. Some people need visual explanations. Others want to dive straight into hands-on work. Some prefer structured lessons, others want flexibility. And for many learners, a certificate is the final proof that makes the effort worthwhile. This list is built around that […]
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Coding experts tend to use 30-40% of their time only for comprehending the already existing code. These are two entire working days every week that are wasted on going through obsolete documentation, understanding ambiguous code, and desperately searching for developers who quit months ago. On the November 2025, Google presented a remedy: Code Wiki, an […]
The post Google Code Wiki:...
No matter what your role is, I can bet you waste (at least some) time in your job. Not because you want to. You waste time because your job quietly demands it. Copying data from one tool to another. Chasing approvals. Sending the same update for the tenth time. Such mundane, yet essential tasks decide […]
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This article is divided into two parts; they are: • What Is Perplexity and How to Compute It • Evaluate the Perplexity of a Language Model with HellaSwag Dataset Perplexity is a measure of how well a language model predicts a sample of text.
This article is divided into three parts; they are: • Training a Tokenizer with Special Tokens • Preparing the Training Data • Running the Pretraining The model architecture you will use is the same as the one created in the
This article is divided into two parts; they are: • Simple RoPE • RoPE for Long Context Length Compared to the sinusoidal position embeddings in the original Transformer paper, RoPE mutates the input tensor using a rotation matrix: $$ \begin{aligned} X_{n,i} &= X_{n,i} \cos(n\theta_i) - X_{n,\frac{d}{2}+i} \sin(n\theta_i) \\ X_{n,\frac{d}{2}+i} &= X_{n,i} \sin(n\theta_i) + X_{n,\frac{d}{2}+i}...
Learn why Clarifai is moving to Pay-As-You-Go credits, what’s changing, and how prepaid billing brings more predictability, flexibility, and control.