South Korea's largest cellular company, SK Telecom, has provided a mobile music portal service called �MelOn� since the end of 2004. MelOn is the first integrated, wired and wireless, music service that allows users to enjoy music virtually anytime, anywhere using a portable MP3 player, a PC, or a mobile phone. The main MelOn interface is a music download and streaming Internet portal, www.melon.co.kr. The service is akin to a rental service, with users �renting� tracks on a monthly basis for use on various terminals. MelOn users pay a 5000 won (US$4.50) monthly subscription to stream music to a PC or download tracks to their phone as long as their subscription is current. Digital rights management (DRM) wrappers on the music guarantee a subscriber is current, and tracks are erased from the end-user�s library at the end of the subscription period. To download tracks onto the handset, users pay for airtime at regular call rates, regardless of the size of the track. The key to the model is its ubiquitousness, downloads are possible using wireline and wireless platforms, and a relatively affordable monthly subscription fee. SK Telecom acquires the rights from the record companies for music to use as ringtones, ringbacks and full version downloads. Music companies are not necessarily enamored by the scheme, but SK Telekom has generally used its market heft to have its way. To further strengthen its position, SK Telekom acquired Korea�s YBM Seoul Records, reportedly Korea�s largest record company.
The prevailing narrative around artificial intelligence (AI) has been one of relentless scale. Bigger models, bigger clusters, bigger budgets. The assumption, largely unchallenged until recently, was that raw parameter count translated directly into competitive advantage. New research from Omdia suggests it's time to retire that assumption. According to the latest market study by Omdia, parameter growth in frontier AI models has slowed to around 5 percent annually since 2021, a stark contrast to the more than hundredfold expansion seen between 2019 and 2021. Enterprise AI Market Development For executives who have been making infrastructure and investment decisions based on the assumption that AI would keep demanding ever-larger, ever-more-expensive hardware, this finding deserves serious attention. The race to the top of the model size leaderboard has, at least for now, plateaued. Crucially, Omdia's analysts are not reading this as an AI winter. Alexander Harrowell, senior pri...