How can Big Data Analytics and Data Science, supported by generative artificial intelligence technology, support conducting scientific research and publishing its results?
In the age of digitalisation, where science generates unprecedented amounts of data, big data analytics and data science, supported by generative artificial intelligence, are becoming key tools to support the research process. They enable researchers not only to process and analyse this data effectively, but also to discover hidden patterns and trends that would be inaccessible using traditional methods. Thanks to machine learning algorithms, researchers can identify complex relationships, formulate new hypotheses and generate innovative theories, which significantly accelerates scientific progress. Generative artificial intelligence, which is capable of creating new content based on existing data, opens up new possibilities for automating analysis, generating hypotheses and supporting the publication of research results, allowing scientists to focus on interpreting and formulating conclusions. However, to fully utilise the potential of these technologies, it is necessary to continuously develop methodologies and algorithms, as well as to consider the ethical aspects of their application, which emphasises the key role of scientific research in this field.
The research and observations that I conduct show that artificial intelligence technology has been developing rapidly in recent years and is finding new applications, with new opportunities and threats emerging. I have described the main determinants, including the potential opportunities and threats to the development of artificial intelligence technology, in my article below:
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And what is your opinion on this topic?
What is your opinion on this matter?
Please answer,
I invite everyone to the discussion,
Thank you very much,
Best wishes,
I invite you to scientific cooperation,
Dariusz Prokopowicz
Cuando la información es tan grande y precisa y se tiene un IA que lo puede relacionar entonces el error es mínimo y util
Dear Judith Beatriz Bello Durand,
Thank you for your reply. You have highlighted some important issues in this area.
In this regard, I believe that big data analysis and data science, supported by generative artificial intelligence (AI), are revolutionising scientific research by enabling the processing and analysis of massive amounts of data in a way that would be impossible for humans.
Thanks to AI algorithms, scientists can quickly identify complex patterns, correlations and anomalies in huge data sets, leading to the discovery of new hypotheses and theories. Generative AI is capable of automating processes such as summarising literature, generating preliminary versions of manuscripts and even designing experiments, which significantly speeds up the research cycle. However, the use of AI chatbots and AI agents carries serious risks and threats. There is a risk of AI hallucinations, i.e. the generation of false or unfounded information, as well as algorithmic bias, which can replicate prejudices contained in the training data. It is therefore crucial that researchers maintain critical thinking, verify all AI-generated results, and treat them as a supporting tool rather than an authority, which highlights the need for international cooperation on AI ethics in science.
What is your opinion on this issue?
Please reply.
Best wishes,
I invite you to collaborate on research.
Dariusz Prokopowicz
AI and advanced data pipelines can automatically gather, clean, and integrate massive datasets from multiple sources, including experiments, simulations, sensors, and literature, leading to a reduction of manual efforts.
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