AI, Language, the Land of What's Possible, and Standing on the Train Tracks
Important News Today
So I read this from a feed from inside China and the smarties at GAI Insights in exotic Boston.
DeepSeek V4 introduces a highly efficient open-weight Mixture-of-Experts large language model with million-token context support and major long-context architecture upgrades.
The Four Reasons Why That Matters - Three Non-Obvious
This is a good example of the somewhat new phase of the AI race, where architectural changes drive massive efficiencies in operational cost structures.
Given how fast this is moving, if your competitors have people who speak this language and you don't, you are at a disadvantage. There are several ways to solve for that, but inaction is not one of them.
The real challenge for most companies is the horizon and boundaries on what is possible and by when have shifted (a lot). That shift is continuing and is accelerating. A key part of the trajectory of any successful company, now more than ever, is the IT folks helping the business see the land of what is possible. Fred Smith/Jim Barksdale in the early days of FedEx would say, 'we are a technology company that moves boxes around'. Seventeen years there was the best education.
While we are all amazed and excited about what AI can do and how fast it is evolving, when we look back from the distant future, like late 2027, it will be the firms that embraced this tech and thought through the cost structure opportunities well that will have great success stories to tell, as long as they got that extremely difficult strategy-mission-task-talent-structure chain thing correct.
The script in the picture above isn't AI hallucinatory gobbledygook. It is "I think we are standing on the train track," albeit in the Cherokee script. Understanding the language often matters.
