Talk:Artificial intelligence

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A little light relief

We're all doomed! http://www.bbc.co.uk/news/technology-30290540

Artificial Intelligence and its Role in Digital Forensics

Artificial Intelligence and its Role in Digital Forensics

Artificial intelligence (AI) is a well-established area that facilitates dealing with computationally complex and large problems. As the process of digital forensics requires analyzing a large amount of complex data; therefore, AI is considered to be an ideal approach for dealing with several issues and challenges currently existing in digital forensics. Among the most important concepts in different AI systems are associated with the ontology, representation and structuring of knowledge. AI has the potential for providing the necessary expertise and helps in the standardization, management and exchange of a large amount of data, information and knowledge in the forensic domain . The existing digital forensic systems are not efficient to save and store all these multiple formats of data and are not enough to handle such vast and complex data thus they do require human interaction which means the chances of delay and errors exist. But with the innovation of machine learning, this occurrence of error or delay can be prevented. The system is designed in a way that it can help detect errors but in a much faster pace and with accuracy . Several types of research have highlighted the role of different AI techniques and their benefits in providing a framework for storing and analyzing digital evidence. Among these AI techniques include machine learning (ML), NLP, speech and image detection recognition while each of these techniques has its own benefits. For instance, ML provides systems with the ability of learning and improving without being clearly programmed, such as image processing and medical diagnosis. Furthermore, NLP techniques help in extracting the information from textual data such as in the process of file fragmentation. The AI techniques and their role in digital forensics are discussed in the next chapter in detail . Aishasaif141 (talk) 18:13, 28 September 2020 (UTC)

That's an interesting statement, but you have no sources for it. Why have you posted it here in an edit request that doesn't appear to be a request for anything? -Roxy the inedible dog . wooF 18:31, 28 September 2020 (UTC) | answer= Actually I was trying to put it in the article.

Surprisingly, Wikipedia's digital forensics article doesn't mention artificial intelligence either. Jarble (talk) 20:10, 5 October 2020 (UTC)

Semi-protected edit request on 26 November 2020

I would suggest changing and or removing the section in this article entitled "Why AI is important' as it lacks any sources, and is written in broad generalisations without qualification ('AI gets the most out of data', 'critical... incredible accuracy'), while also demonstrating a clear bias. This section is also already largely covered in the subsection, 'applications'. Timborimbo (talk) 09:50, 26 November 2020 (UTC)

 Done – Thjarkur (talk) 10:03, 26 November 2020 (UTC)

Brief definitions

I liked this brief text. It would be hard to cite but I thought we could use it to inspire our outline for the basics we need to cover. One definition which I think is missing is the name for whatever field studies all this, and I would call that "data science".

• Manning, Christopher (September 2020). "Artificial Intelligence Definitions" (PDF). hai.stanford.edu/. Stanford University.

Blue Rasberry (talk) 14:26, 9 December 2020 (UTC)

And "neuron's space".

V eritrocitah esty gelezo (Fe).

Мы эксковаторы ??

213.87.242.192 (talk) 17:48, 12 December 2020 (UTC)

Announcement to remove two Arxiv papers

In general, the current article is written very well, but it is only a bit too long. There are two arxiv papers referenced in the section “Basics” which are problematic for an overview article:

1. #85 Matti, D: Combining LiDAR space clustering and convolutional neural networks for pedestrian detection
2. #86 Ferguson, Sarah: Real-Time Predictive Modeling and Robust Avoidance of Pedestrians with Uncertain, Changing Intentions.

The first one is 7 page long PDF document which was published at Arxiv. It describes a highly specialized attempt for image detection with convolutional neural networks. The second paper is a proceeding from a robotics conference and contains a gaussian forward model for a prediction problem.

Both papers were written for AI experts which have lots of background knowledge. It is unlikely, that in a beginner course about robotics these papers are used to teach the subject to a larger audience. If no counter arguments are provided, i will delete both papers in the near future. This will help to reduce the article size.--ManuelRodriguez (talk) 12:04, 18 December 2020 (UTC)