When we break down artificial intelligence based on its function, we can see it falls into two main types: decision-making AI and generative AI.

Decision-making AI: Decision-making AI zeroes in on scrutinizing scenarios and reaching decisions. It aids users or systems in picking the optimal path by weighing various options and potential results.

For instance, in autonomous vehicles, decision-making AI systems determine the timing for accelerating, decelerating, or changing lanes.

Generative AI: Generative AI, in essence, harnesses machine learning models and deep learning techniques to craft fresh content—be it text, images, audio, or video—by delving into patterns within past data.

As big data and computer capabilities keep advancing, there's a growing anticipation for computers to produce content and spark novel ideas akin to humans. This surge has propelled the emergence of generative AI, empowering computers to mimic human creativity, thereby fostering further innovation and progress.

Deep learning models form the core of AIGC, serving as its fundamental framework. Consider text generation: we often rely on neural network-based language models like generative adversarial networks (GANs), recurrent neural networks (RNNs), and variational autoencoders (VAEs). These models learn from the input data's distribution and patterns, enabling them to produce content that mirrors or diverges from the original dataset.

Looking at examples like ChatGPT and Sora, the current realms where generative artificial intelligence is making waves mainly encompass: first, text translation, compilation, abstraction, and summarization; second, crafting and refining code frameworks; third, dynamically generating images and video content from text cues; and fourth, powering intelligent customer service.

More AI-based software

- ChatGPT: Excels at crafting smooth and coherent conversations from given text. It's handy for crafting smart chatbots that offer users entertainment, educational insights, consultations, and more. Moreover, ChatGPT proves versatile in generating various text forms, including articles, stories, lyrics, and the like.

- DALL·E: Adept at crafting lifelike images from provided text descriptions. It's handy for crafting artworks, designing products, and developing advertisements, among other applications. Additionally, DALL·E can tackle intricate and abstract text descriptions, producing surreal and imaginative visuals.

- Jukebox: Designed to craft original music tailored to specific input parameters like the singer, style, and lyrics. It's handy for composing music, emulating singers, blending styles, and more. Moreover, Jukebox can produce unique and unconventional tunes, such as animal-inspired melodies or classical music infused with rap elements.

- DeepMind AlphaFold: A protein structure prediction system rooted in deep learning, is adept at constructing the three-dimensional arrangement of a protein from its amino acid sequence. Its application spans expediting biomedical studies and aiding in the discovery of novel drugs and therapies. Notably, AlphaFold made a significant stride in the 2023 protein structure prediction contest, marking a triumph in tackling a challenging biological puzzle.

In recent times, owing to the substantial surge in data, the leap in computing prowess, and the strides in algorithmic advancements, artificial intelligence (AI) technology has experienced rapid evolution, expanding its array of application scenarios significantly. It has proven instrumental in fostering fresh productivity standards, shaping novel developmental dynamics, and propelling high-caliber progress. Simultaneously, it has ushered in novel challenges to economic and social governance, particularly concerning security issues throughout its developmental journey. For instance, generative artificial intelligence technology might be leveraged to fabricate misinformation and spread fake news, manipulating public sentiment. Additionally, it could facilitate the production of deepfake videos and images, leading to online scams. Moreover, it could be utilized to generate false orders, manipulate rankings, and inundate platforms, thus distorting consumer choices and disrupting fair market competition. Furthermore, it could automate the creation of substantial digital content, potentially infringing on others' digital copyrights.

However, generative artificial intelligence is still relatively nascent in its development journey, with its risks not yet fully unveiled, and its potential applications challenging to predict accurately. Therefore, it's imperative to embrace an inclusive and cautious approach, maintaining a delicate balance between advancement and security. We should encourage innovation while ensuring adherence to legal governance. Implementing effective measures is essential to foster the innovative progression of generative artificial intelligence.