دانلود کتاب مدل‌های بزرگ قابل اعتماد با افزایش دانش

We are in an era of transformation and opportunity, witnessing a flourishing of technological progress and application of Artificial Intelligence. The rapid development of Large Language Models (LLMs) has shown us the dawn of Artificial General Intelligence (AGI) and a future landscape filled with infinite possibilities. In November 2022, ChatGPT burst onto the scene. I was captivated from my very first interaction and subsequently devoted myself wholeheartedly to the research and application of large models. During the Spring Festival holiday of 2023, I wrote an article titled “NLP’s Five-Year Sprint, AGI’s First Light,” which systematically chronicled the remarkable achievements of LLMs since 2018 and looked forward to the magnificent blueprint of a potential AGI era. Beginning in 2023, AGI became a subject of widespread discussion, gradually emerging as a global hot topic. I have been profoundly involved in this “heatwave” of LLMs and AGI—from training and fine-tuning models and developing LLM applications to studying research papers, writing articles, and participating in discussions, live streams, and lectures. Through deep exploration, extensive practice, and rational analysis, I have come to realize that while the changes brought by large language models are undoubtedly revolutionary, they are not omnipotent and have certain limitations. I delved into the history of artificial intelligence, reading over 300 seminal academic works from the 1940s to 2024. During the 2024 Spring Festival, I authored an essay, “Learning from History: The Past, Present, and Future of Artificial Intelligence Technology.” I discovered that similar fervent pursuits of new technologies and grand narratives are not unique to our time; there are numerous historical precedents. For instance, the currently debated concept of “intelligence emergence” is not new. John Hopfield, a 2024 Nobel laureate in Physics, explored neural networks with emergent computational abilities in his 1982 paper, “Neural Networks and Physical Systems with Emergent Collective Computational Abilities.” This research into the spontaneous generation of intelligence in complex systems was a precursor to many of today’s AI theories. The vision of “Artificial General Intelligence” proposed by AI leaders like Sam Altman and Geoffrey Hinton is not an “original creation” either. As early as 1967, AI pioneer Marvin Minsky predicted in his book Computation: Finite and Infinite Machines, “Within a generation, I am convinced, few compartments of intellect will remain outside the machine’s realm—the problems of creating ‘artificial intelligence’ will be substantially solved.”