But an invoice issued is not money collected, and that distinction deserves to be in large print. Especially when credit is expensive or payment terms are long. A company can report healthy sales and still struggle with a lack of liquidity. Invoicing must go hand in hand with collections. If we had to summarize
AI and mathematics are redefining how proofs are discovered, verified, and shared. The case of Caltech’s Mathathon reveals who controls knowledge when machines propose solutions.
Artificial intelligence, Anthropic, and safety: Jacob Coxon’s resignation reveals the risks of accelerating toward superintelligence without sufficient controls.
If a scientist uses a commercial platform to think through an unpublished conjecture, what guarantees do they have that this interaction will not feed, directly or indirectly, systems that could compete with them? If the company offering the tool can mobilize millions of dollars in computing resources to pursue the
What if the real danger of AI surveillance is not that it predicts crimes, but that it makes monitoring anyone cheap? The episode explains that these systems can summarize thousands of posts, cross-reference names, and detect patterns in minutes. That changes the scale: a public protest, a campaign against a
What if a coding agent crashes halfway through a task and can continue without starting from scratch? Muse Code includes a local event log: it records model calls, tools run, approvals, and edits. This enables two very specific things. If the computer restarts, the agent can
Predictive surveillance, Anthropic, and dissent: we analyze how AI can turn protests and criticism into supposed security threats.
The thesis of this episode is simple: the danger lies not only in AI conducting surveillance, but in who defines what warrants surveillance. Because “threat” sounds like a technical term, but it always contains a political decision. Is a threat a concrete threat of violence? Or also a protest that makes investors uncomfortable,
So, does Muse Code herald the end of manual programming? No. It heralds something more interesting: programming can shift from typing out each solution to directing, reviewing, and setting boundaries for systems that carry out increasingly large parts of the process. That changes which skills are valuable. Understanding an architecture, formulating…
Do you think giving an AI all your documents makes it smarter? The exact opposite can happen.
AI graphs, prompts, and agents: discover how to design artificial intelligence systems that are more useful, reliable, and easier to control.
The main trap is confusing activity with progress. Just because five agents produce many pages of text does not mean they have solved the problem better. Sometimes they have only multiplied the opportunities for a mistaken assumption to travel from one node to the next until it becomes a very convincing…
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