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The rise of artificial intelligence (AI) is poised to transform multiple aspects of human life, but it also raises complex questions about ethics, employment, and the future of society. As AI becomes more integrated into everyday life, it’s crucial to explore the implications of its development and application. Below are 10 thought-provoking questions about AI, … Read more
1. Machine Learning for Beginner’s This course is designed to provide a comprehensive roadmap to mastering machine learning in 2025. It covers essential skills, foundational concepts, and practical techniques required for a career in machine learning. The course is ideal for those starting their journey, offering both theoretical and hands-on experience through case studies and … Read more
[ad_1] While large reasoning models (LRMs) have shown impressive capabilities in short-context reasoning through reinforcement learning (RL), these gains do not generalize well to long-context scenarios. Applications such as multi-document QA, research synthesis, and legal or financial analysis require models to process and reason over sequences exceeding 100K tokens. However, RL optimization in such regimes … Read more
[ad_1] Image by Author | Canva Docker containers simplify the development and deployment of applications, but they also introduce security challenges. This tutorial will walk you through five essential best practices to secure your Docker containers effectively. Prerequisites To follow along: You should have Docker installed. You should be comfortable with Docker commands … Read more
[ad_1] import functools import pprint import re import torch from transformers import AutoTokenizer, AutoModelForSeq2SeqLM class AdvancedTextSummarizer: def __init__(self, model_name=“sshleifer/distilbart-cnn-12-6”, quantize=False): “”“Initialize the advanced summarizer with additional features. Args: model_name (str): Name of the pre-trained model to use quantize (bool): Whether to quantize the model for faster inference ““” self.device = “cuda” … Read more
[ad_1] Statistical Methods for Evaluating LLM PerformanceImage by Author | Ideogram Introduction The large language model (LLM) has become a cornerstone of many AI applications. As businesses increasingly rely on LLM tools for tasks ranging from customer support to content generation, understanding how these models work and ensuring their quality has never been more important. … Read more
[ad_1] DistilBart is a typical encoder-decoder model for NLP tasks. In this tutorial, you will learn how such a model is constructed and how you can check its architecture so that you can compare it with other models. You will also learn how to use the pretrained DistilBart model to generate summaries and how to … Read more
[ad_1] Manus AI agent is China’s latest artificial intelligence breakthrough that’s turning heads in Silicon Valley and beyond. Manus was launched last week via an invitation-only preview, and represents China’s most ambitious entry into the emerging AI agent market. Unlike anything seen to date, the Manus AI agent doesn’t just chat with users – it … Read more
[ad_1] OpenAI and Google are each urging the US government to take decisive action to secure the nation’s AI leadership. “As America’s world-leading AI sector approaches AGI, with a Chinese Communist Party (CCP) determined to overtake us by 2030, the Trump Administration’s new AI Action Plan can ensure that American-led AI built on democratic principles … Read more
[ad_1] GenAI systems affect how we work. This general notion is well known. However, we are still unaware of the exact impact of GenAI. For example, how much do these tools affect our work? Do they have a larger impact on certain tasks? What does this mean for us in our daily work? To answer … Read more