AI Technology


AI at the edge T


By Nick Wood, sales and marketing director, Insight SIP


he Artifi cial Intelligence (AI) revolution is well underway. We actively use AI via services like ChatGPT, DeepL natural language translation services and the “Assistants” in the latest phones, smart speakers and photo editing services. We are also passive users when we interact with many entities via phone or online services, with AI being used at least to control and fi lter the fi rst stage of interactions.


Beyond this type of relatively simple labour-saving tasks, there are already serious studies underway as to how AI can assist with important topics such as analysing medical scans to improve detection of anomalies, or maintaining security by analysing CCTV feeds.


Traditional AI


Most of these services rely on the model of an end device with diverse input methods


(voice, keyboard, camera, file transfer), which then sends the request to a server farm somewhere in the cloud where the AI processing is done. This has the clear advantage that you can throw almost unlimited computing power at the problem and, if relevant, make widescale use of the search function to produce answers and output.


The results obtainable can be impressive – well written essays, photorealistic images,


natural translations and much more. However, this approach does come with several drawbacks.


Issues with AI solutions Firstly, the server farms used to run all purpose AI engines are incredibly expensive to run. They use large numbers of racks of expensive dedicated processors, which can cost $10,000 or more each for the latest generation devices. Such data centres are


24 June 2025


Components in Electronics


www.cieonline.co.uk


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