Today, we’re announcing an expanded partnership with the UK AI Security Institute (AISI) through a new Memorandum of Understanding focused on foundational security and safety research, to help ensure
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Artificial intelligence and big data are reshaping digital marketing by providing new insights into consumer behaviour. The technologies allow marketers to create more personalised and effective strategies. As the
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Image by Author # Introduction As a data scientist, you’re probably already familiar with libraries like NumPy, pandas, scikit-learn, and Matplotlib. But the Python ecosystem is vast, and there
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Training a language model with a deep transformer architecture is time-consuming. However, there are techniques you can use to accelerate training. In this article, you will learn about: Using
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Global capability centres (GCCs) in India have moved well beyond their original role as cost-efficient back offices. In 2026, their relevance will be judged by the depth of capabilities
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As AI agents continue to grow in popularity, one question everybody is wondering: When will they reach full autonomy? A recently launched foundation is betting on soon. In September,
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Announcing a new, open suite of tools for language model interpretability Large Language Models (LLMs) are capable of incredible feats of reasoning, yet their internal decision-making processes remain largely
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A recent industry report [PDF] argues that Britain’s railway network could carry an extra billion journeys by the mid-2030s, building on the 1.6 billion passenger rail journeys recorded to
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Image by Author # Introduction Before jumping into the projects, let’s clear up what Docker is and why people care about it. Docker packages an application and everything it
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import dataclasses import os import datasets import tqdm import tokenizers import torch import torch.distributed as dist import torch.nn as nn import torch.nn.functional as F import torch.optim.lr_scheduler as lr_scheduler
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