The home networking arm of CEA was hard at work, approving two new standards. CEA-851-A defines an IP-enabled network for connecting cluster networks to a whole-home broadband distribution backbone in order to facilitate integrated operation of appliances and networked components. Based on IEEE 1394, this network will accommodate Ethernet as an attached network via a bridge, and directly with the introduction of IEEE 1394c. Called the versatile home network, it provides a flexible and open network architecture and communications protocol specification for digital devices in the home. CEA-2027-A defines a user-to-machine interface method that allows a source of home-network services, such as a cable or terrestrial set-top box, digital VCR or DTV, to utilize the presentation capabilities in a network-attached renderer such as a DTV display or PC. The standard enables user control of networked devices (either local to the user or remote) via another device�s (e.g., DTV or PC) Web browser graphical user interface (GUI).
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...