It's not just U.S. consumers who want a lighter tax burden on phone services, but the telecommunications companies that serve them as well. A recent study by the Telecommunications Tax Task Force of the Council on State Taxation (COST) says that telecom companies have to file thousands more tax returns than other businesses. No wonder telecom companies are fed up. The gory details: The average number of tax returns each telecommunication company has to file per year is a staggering 47,921, compared to 7,501 returns for a general business. New York saddles telecom companies with more returns than any other state: 5,632. How is this possible? Start with New York State's 406 jurisdictions requiring monthly local utility tax returns. Telecoms face 6,683 more taxing jurisdictions nationwide than general businesses -- there is such a thing as a mosquito abatement jurisdiction. The average state and local effective tax rate on telecom services -- some of which is paid directly by customers and some of which is levied on the companies, who then pass on the cost -- is 14.17% throughout the U.S., compared to 6.12% for general businesses, according to the COST study. The worst offender is a state not normally known for its high taxes: Virginia, with a 29.3% rate.
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...