How to build an intelligent computerized Big Data Analytics system that would retrieve real-time data and information from specific online databases, scientific knowledge indexing databases, domain databases, online libraries, information portals, social media, etc., and thus provide a database and up-to-date information for an intelligent chatbot, which would then be made available on the Internet for Internet users?
Almost every major technological company operating with its offerings on the Internet either already has and has made its intelligent chatbot available on the Internet, or is working on it and will soon have its intelligent chatbot available to Internet users. The general formula for the construction, organization and provision of intelligent chatbots by individual technology companies uses analogous solutions. However, in detailed technological aspects there are specific different solutions. The differentiated solutions include the issue of the timeliness of data and information contained in the created databases of digitized data, data warehouses, Big Data databases, etc., which contain specific data sets acquired from the Internet from various online knowledge bases, publication indexing databases, online libraries of publications, information portals, social media, etc., acquired at different times, data sets having different information characteristics, etc.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How to build an intelligent computerized Big Data Analytics system that would retrieve real-time data and information from specific online databases, scientific knowledge indexing databases, domain databases, online libraries, information portals, social media, etc., and thus provide a database and up-to-date information for an intelligent chatbot, which would then be made available on the Internet for Internet users?
How to build a Big Data Analytics system that would provide a database and up-to-date information for an intelligent chatbot made available on the Internet?
And what is your opinion on this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
Dariusz Prokopowicz,
To build such a system, there must be the need to integrate different online databases, scientific knowledge indexing databases, domain databases, online libraries, information portals, social media platforms, and more. By doing so, we can create a comprehensive database that provides up-to-date information on any given topic.
The first step in building this system is to identify and gather relevant sources of information. This includes partnering with online databases and libraries to gain access to their vast collection of resources. Additionally, collaborating with scientific knowledge indexing databases will ensure that the latest research findings are included in our database.
Next, we need to develop algorithms that can efficiently retrieve data from these sources in real-time. These algorithms should be able to filter out irrelevant information and present only the most accurate and reliable data to users.
Once we have gathered and organized the data, it is time to create an intelligent chatbot that can interact with users on the internet. This chatbot should be capable of understanding natural language queries and providing relevant answers based on the available data.
By making this intelligent chatbot available on the internet, users will have instant access to a wealth of up-to-date information at their fingertips. Whether they are looking for scientific research papers or general knowledge about a specific topic, this system will provide them with accurate answers quickly.
Proof of Viability: Grok "Reporting" OpenAI Drama
On Friday, Nov. 17th, Sam Altman, the cofounder of OpenAI, was removed from his position as CEO. Amidst the drama, with various sources offering different perspectives, Grok, a language model built by Musk's xAi, reported the situation with surprising accuracy. Developed in just four months, Grok demonstrates its real-time capabilities, having been trained on data from X (formerly Twitter). This instance exemplifies the potential of language models in accessing and processing real-time data.
The Data Challenge: Numerical Data
While Grok exemplifies the feasibility of creating real-time language models, its primary data source is text-based (posts on X). Language models, not inherently designed for computation and mathematical reasoning, face challenges in this realm, especially when compared to text-based real-time chatbots. Currently, accessing external data sources mainly involves function calls, but this approach is limited due to a narrow selection of available functions for specific database retrieval. The development of custom AI-generated functions is still in question but represents a promising area for research. A key consideration is whether we need a similar mechanism for compressing databases, akin to how language models compress text-based knowledge. Further, how can this be integrated with databases for real-time applications, and what metrics should be used to assess the quality of numerical data?
How to Build? Future Research Directions
While I am not actively engaged in this specific area of research, I do have some overarching ideas:
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