Post by account_disabled on Feb 25, 2024 5:21:58 GMT
We hear about it every day but what is artificial intelligence really? Jordi Iparraguirre, Innovation Manager at EURid , shared with us his opinions on the limits and vulnerabilities related to artificial neural networks to also show the other side of the coin of technological evolution. Content index: Artificial intelligence is now part of our everyday life, we all talk about it. But what really is artificial intelligence? We always talk about the advantages linked to artificial neural networks, but what are the main limitations and how are they addressed? We are witnessing an increasing use of AI and intelligent systems applied to different fields. How do attackers exploit vulnerabilities and weaknesses? Are there any notable examples to share? How is artificial intelligence applied in EURid? Artificial intelligence is now part of our everyday life, we all talk about it.
But what really is artificial intelligence? Artificial intelligence (AI) is the ability Chinese Student Phone Number List of a machine to exhibit human-like capabilities such as reasoning, learning, planning, and creativity. For example, image and text recognition, grouping elements into classes, speech recognition, identifying complex patterns based on thousands of parameters, etc. The programming model used in artificial intelligence systems is different from that used in traditional systems. In traditional systems you take an input, write a set of sequential rules to process that input, and get an output. For example, to calculate the VAT for a specific product, you enter the price of the product as an input, multiply that value by the tax to be applied (%), and obtain the amount of tax (€) to be applied to that specific product. By entering a different price, we will obtain the tax to be applied to a different product.
Artificial intelligence techniques, however, work differently. Initially the system is "trained" by entering both the input data and the desired output. For example, the system is shown images and taught that these images show apples, other images show oranges, and so on. The AI system is then asked to develop, on its own, a set of rules that allow it to correctly classify a new image. However, if the machine is shown a type of fruit different from that shown to the system initially, or a fruit already inserted into the machine but in a context or with characteristics different from those shown during the "training" phase of the machine (for example an apple blue, instead of green), the system may not be able to classify it.
But what really is artificial intelligence? Artificial intelligence (AI) is the ability Chinese Student Phone Number List of a machine to exhibit human-like capabilities such as reasoning, learning, planning, and creativity. For example, image and text recognition, grouping elements into classes, speech recognition, identifying complex patterns based on thousands of parameters, etc. The programming model used in artificial intelligence systems is different from that used in traditional systems. In traditional systems you take an input, write a set of sequential rules to process that input, and get an output. For example, to calculate the VAT for a specific product, you enter the price of the product as an input, multiply that value by the tax to be applied (%), and obtain the amount of tax (€) to be applied to that specific product. By entering a different price, we will obtain the tax to be applied to a different product.
Artificial intelligence techniques, however, work differently. Initially the system is "trained" by entering both the input data and the desired output. For example, the system is shown images and taught that these images show apples, other images show oranges, and so on. The AI system is then asked to develop, on its own, a set of rules that allow it to correctly classify a new image. However, if the machine is shown a type of fruit different from that shown to the system initially, or a fruit already inserted into the machine but in a context or with characteristics different from those shown during the "training" phase of the machine (for example an apple blue, instead of green), the system may not be able to classify it.