Nigel Powell

2 days ago | techradar.com | Nigel Powell

(Image credit: NPowell/GPT Image-1)Foundation models are the big daddy of modern AI systems, as they are the neural networks which act as the backbone of all modern artificial intelligence systems. Some of the most famous of these are Google's Gemini, Anthropic's Claude, OpenAI's GPT range and Llama from Meta. The key feature of these models is that they have been built from scratch and trained on a vast amount of data culled from multiple domains, such as text audio video and images.

2 days ago | flipboard.com | Nigel Powell

12 hours agoThere were over 5,500 people at SuperReturn International 2025, making it the largest private equity event in the world. Robert F. Smith, the CEO of investment firm Vista Equity Partners, said on Thursday that AI will overturn the job market and lead to layoffs for most finance …

3 days ago | techradar.com | Nigel Powell

(Image credit: NPowell/GPT Image-1)AI prompting is typically divided into two parts, the system prompt and the user prompt. The former is the prompt instruction which is embedded inside a model as part of the design process. This system prompt defines the purpose, design and operational parameters of how the AI model will react to user input. As such, it is a crucial part of the utility of an AI model, particularly when that model is applied to specialist uses, as with fine-tuning.

4 days ago | techradar.com | Nigel Powell

(Image credit: NPowell/GPT Image-1)Sparsity is a measured way of optimizing machine learning models by deliberately specifying which nodes are composed of zero values. Sparse models, as opposed to dense models, contain mostly zero values. This is different to models which have missing values, because in the case of a sparse model the zero values are known, but contain no numerical values. This factor may sound irrelevant, but it is important when trying to optimize neural network processing.

5 days ago | techradar.com | Nigel Powell

The current crop of modern AI models were originally pretty basic things. The user entered a text request, and the neural network processed the input, matched patterns and delivered an answer. However over time the technology has matured and evolved, one feature at a time. Chain of thought models arrived shortly after transformer tech from Google revolutionized the whole AI machine learning marketplace.