Prompted in part by Apple’s paper about the limits of large language models (“The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity”), I spent some time playing with Tower of Hanoi. It’s a problem I solved some 50 years ago when I was in college, and I haven’t felt the desire or need to revisit it since. Now, of course, “We Can Haz AI,” and all that means. Of course, I didn’t want to write the code myself. I confess, I don’t like recursive solutions. But there was Qwen3-30B, a “reasoning […]

The AI Frontiers article (reproduced below) builds on a previous Asimov Addendum article written by Tim O’Reilly, entitled: “Disclosures. I do not think that word means what you think it means.” I (Ilan) think it’s important to first very briefly go through parts of Tim’s original piece to help recap why we—at the AI Disclosures Project—care about protocols in AI markets: At the AI Disclosures Project, we are increasingly coming to see disclosures through the lens of networking protocols and standards. Every networking protocol can also be thought of as a system of disclosures. But these disclosures are far more than just a warning label, or […]

Despite the promise of AIOps, the dream of fully automated, self-healing IT environments remains elusive. Generative AI tools may be the solution that finally abstracts away enough of the workload to get there. However, today’s reality is far more complex. Internet performance monitoring firm Catchpoint’s recent SRE Report 2025 found that for the first time ever, and despite—or perhaps because of—the growing reliance on AI tools, “the burden of operational tasks has grown.” True, AI can smooth out thorny workflows, but doing so may have unexpected knock-on effects. For example, your system may use learned patterns to automatically suppress alerts, […]