ARTIFICIAL INTELLIGENCE<\/p>\n
The most important AI story of 2025 wasn’t GPT-5 or Gemini Ultra. It was a 7-billion parameter model running on your laptop.<\/strong><\/p>\n The mainstream AI narrative is dominated by frontier models \u2014 the largest, most expensive, most capable systems that require entire data centres to run. But while the industry gazes upward at those peaks, a quiet revolution has been happening at ground level.<\/p>\n A Small Language Model \u2014 anything roughly under 13 billion parameters \u2014 can run locally on a modern laptop or phone. No API call. No data leaving the device. No subscription. No latency beyond the time to process the query. And for the majority of real-world tasks, the output quality difference versus a frontier model is negligible.<\/p>\n This matters enormously for privacy-sensitive use cases. A healthcare provider who wants AI assistance with patient documentation can’t send that data to an external API. A law firm with client confidentiality obligations can’t run queries through a third-party cloud. A defence contractor operating in a classified environment can’t connect to the internet at all.<\/p>\n “For the majority of real-world tasks, the quality difference versus a frontier model is negligible \u2014 and the privacy benefits are enormous.”<\/p><\/blockquote>\n The enterprise adoption of SLMs is accelerating faster than most analysts predicted. Fine-tuning a small model on proprietary company data \u2014 product documentation, internal policies, historical decisions \u2014 produces something remarkably useful at a fraction of the cost of running frontier model queries at scale.<\/p>\n This is the model that will dominate enterprise AI in the next two years: not one giant model for everything, but a constellation of small, specialised models fine-tuned for specific domains and running close to the data they serve.<\/p>\n Tags: Artificial Intelligence \u2022 Opinion \u2022 Technology & Society \u2022 192.168.1.22\/<\/p>\n","protected":false},"excerpt":{"rendered":" While everyone obsesses over the latest frontier model, smaller, faster, cheaper models are quietly winning where it actually counts.<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,23],"tags":[],"class_list":["post-9006","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-technology"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9006","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=9006"}],"version-history":[{"count":1,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9006\/revisions"}],"predecessor-version":[{"id":9066,"href":"http:\/\/iamglover.com\/index.php?rest_route=\/wp\/v2\/posts\/9006\/revisions\/9066"}],"wp:attachment":[{"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=9006"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=9006"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/iamglover.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=9006"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}What Small Language Models Actually Offer<\/h2>\n
The Enterprise Angle<\/h2>\n