Welcome to Algorithm Times
Why Algorithm Times exists (and why now)
There's no shortage of AI news. There is a shortage of AI understanding.
The technology industry has watched several cycles of genuine breakthrough get buried under the noise that accompanies them: the hype, the counter-hype, the breathless coverage, and the inevitable backlash that says less about the technology than about how tired everyone got of hearing about it.
AI is different in scale. It may not be different in kind.
The coverage problem is acute. On one end: everything is revolutionary, every model release is a watershed, every benchmark is proof of something. On the other: it's all smoke, it won't work, the bubble is about to pop. Neither of these serves anyone trying to actually understand what's happening and, more importantly, what it means for the systems they build, the businesses they run, and the decisions they're making right now.
Algorithm Times exists to do it differently.
The focus is technical readers: developers, engineers, researchers. People who don't need the jargon explained but do need someone willing to go past the press release and into what the numbers actually say. The model that performs well on one benchmark and poorly on another. The deployment reality behind the demo. The business incentive that explains why a company is saying what it's saying.
That last piece matters more than most AI coverage acknowledges. The economics of this moment are inseparable from the technology. Who's funding what, who's acquiring whom, what's getting commoditized and what isn't: these shape what gets built and what gets abandoned. We cover both, together, because that's the only way either makes sense.
We'll also say when something is overhyped, including things the industry is currently very excited about. That's a bar we're setting publicly because it's easy to promise and harder to hold to. Consider this the record.
