Artificial intelligence promises to be a source of inspiration, and here are six tips to better feed off OpenAI's chatbots.
AI
What is AI? Artificial intelligence is a new technological science that researches and develops theories, methods, technologies and application systems used to simulate, extend and expand human intelligence. It is a process of cognition, decision-making and feedback. Artificial intelligence technology has become the most advanced technology in the field of science and technology. Many countries are competing to open up a new direction of this technology research and strive to seize the commanding heights in this field. What is the core problem of AI technology?
AWS recently announced several new tools for training and deploying generative AI on the cloud platform, extending its reach further into the AI software development space.
Salesforce Announces Plans to Integrate Einstein GPT with Data Cloud, Salesforce Flow
We live in an age of intelligence. Many fields that seem to be exclusive to human beings are being continuously scoured, eroded and scoured by the tide of intellectualization, and painting is no exception.
According to a recent survey conducted by automation software company UiPath, the majority of employees (about 60%) believe that AI-based automation solutions can reduce burnout and significantly improve job satisfaction.
ChatGPT, an artificial intelligence community, has announced a new version - GPT-4 - that will allow users with access to the API to customize the "personality" of the AI.
"AI is not a technology, but a way of thinking," Jordan said. Talk with this scientist who has systematically studied psychology, cognitive science, mathematics, and participated in molecular biology, statistical physics, economics, control theory, linguistics, operations research and other projects, often feeling fresh and fresh.
Neuro AI is a new discipline, which aims to promote the development of AI technology by studying human brain, and use AI to better study human brain. One of the core tools of neural AI is to use artificial neural networks to create computer models of specific brain functions. This method began in 2014, when researchers at MIT and Columbia University found that deep artificial neural networks could explain the reaction process of the brain's object recognition region, the infratemporal cortex (IT). So they introduced a basic experimental method: comparing the artificial neural network with the brain. Then repeatedly and iteratively test various brain reaction processes: shape recognition, motion processing, speech processing, arm control, spatial memory, etc., and establish corresponding brain processing models for each reaction.
The integration of deep learning with traditional industries in application has made AI an unprecedented explosion. But as Li Feifei, a professor at Stanford University, said, there is still a long way to go no matter in terms of intelligence, manpower or machine equipment.