You can code, write poems, translate novels, even take exams and make online consultations … ChatGPT, an artificial intelligence chat robot that is responsive, has exceeded 100 million monthly active users only two months after its launch.
ChatGPT’s popularity has once again triggered widespread concern about the development of artificial intelligence technology around the world. ChatGPT adopts the route of "big data+big computing power+strong algorithm=big model" in the technical path, and explores a new paradigm in the direction of "basic big model+instruction fine-tuning", in which the basic big model is similar to the brain, and instruction fine-tuning is interactive training, and the combination of the two realizes the language intelligence approaching human beings.
At present, the development of AI mainly relies on large-scale model technology, and it is necessary to train very large-scale models with huge parameters based on massive natural language or multimodal data sets. To successfully train a large model with larger parameters, higher accuracy and higher capability, not only a huge amount of high-performance AI computing power is needed to support it, but also a large number of high-quality data sets obtained by careful cleaning and an efficient data platform are needed to ensure a long-term model training process.
After more than 20 years’ experience in data management, Julong Information adopts technologies such as big data, cloud computing and artificial intelligence combined with hierarchical architecture design of data warehouse to build a smart cube platform. Through algorithms such as relationship mining, time series mining and spatio-temporal mining, the standard data model is uniformly built in the way of business backward, so as to realize in-depth mining, serial-parallel analysis, early warning and prediction, etc., and meet the goal of "artificial intelligence driving business to improve efficiency".
Introduction to the Application Scenarios of Smart Cube Platform
Portrait analysis: based on the ontology conceptual model of the entity, build the entity portrait and refine the label. Through natural language processing technology and structured data processing technology, the emotion mining of characters is carried out by using template rules, automatic mode and mixed mode. Finally, according to the business needs, we use tag mining, emotional polarity analysis, similarity analysis, relationship analysis and other algorithms to create a portrait of the entity for analysis.
Correlation analysis: Based on the behavior, relationship and portrait data of knowledge map construction, the potential correlation between objects is portrayed by using random walk of the map, factor association, community discovery, intention recognition, semantic search, relationship mining and similarity algorithm, which helps the police to make in-depth judgment and analysis.
Clue mining: Deep-level mining is carried out in combination with emotional business scenarios, and hidden information such as people, clues, elements, relationships, behavior patterns, etc. are found through frequent item mining, association mining, classification and clustering, and anomaly detection technologies to assist the police in deep judgment and analysis.
Prediction and early warning: According to the temporal and spatial distribution characteristics of historical events, the future development trend of events is predicted and judged by using node intimacy calculation, narrative event evolution diagram, element extraction, correlation analysis, relationship mining, comparison collision, behavior pattern analysis and temporal and spatial analysis algorithms, such as event trend prediction and spatial hot spot prediction.
Case sharing: At present, the crime of electric fraud continues to be high, resulting in huge asset losses, accounting for nearly 50% of the criminal cases. At the same time, electric fraud has the characteristics of strong concealment of crime, great difficulty for the masses to prevent publicity, and rapid renovation of means. Based on more than 12,000 case transcripts, 615 million population data and more than 20,000 phone bill data collected by law enforcement users in a certain place as data input, the platform was analyzed, modeled and mined. After multi-level data screening and analysis and modeling, 10+ high-value and vulnerable portrait features were finally analyzed and mined, which was highly recognized by users.
Julong Information Artificial Intelligence organically organizes billions of data into a knowledge network that conforms to people’s cognitive style in a scientific, reasonable and efficient way, making the data easier to be understood and processed by people and machines, and providing application support such as search, analysis, mining, application, presentation, prediction and early warning in various business scenarios.
The development of artificial intelligence is inseparable from the combination of human and artificial intelligence, and our future will also be an era of co-evolution of human and artificial intelligence.
ChatGPT depicts the future world of artificial intelligence
Robots are like humans.
Thought and wisdom have surged
In this dreamy world
Seamless combination of technology and human beings
Life is like a poem.
Calm and beautiful, never stop.
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