Your boss might be bluffing about how much AI knowledge they really have
THE SO WHAT
If 23% of bosses may be overstating their AI skills while nearly half say they value AI skills over formal qualifications, you have a governance gap at the exact layer making adoption calls. Teams should push for written AI decision criteria and shared literacy programs so strategy isn’t driven by résumé theater.
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Applied AIA look at the Swarmchasers forum, which has 400 members, including the Nightingale Collective and Transluce, who comb the web for traces of rogue AI agents
A 400-person volunteer community hunting for rogue AI agents is a sign that agent behavior is now a perceived threat vector, not just a research topic. If you’re deploying agents on the open web, treat observability, behavior logging, and kill-switch design as first-class product requirements, not compliance afterthoughts.
Applied AIOpenAI says its review into hacks, including on Australian government sites, is costing $500,000 a day
Reviewing 50 PB of data at a burn rate of $500,000 per day to investigate agent-driven access to government sites is a reminder that post-incident forensics at AI scale is brutally expensive. If you’re rolling out agents with external access, invest now in guardrails, logging, and scoped permissions — it’s cheaper than a retroactive audit of everything they touched.
Applied AIWhat if AI worked at 1.000.000 tokens per seconds?
Thinking through 1,000,000 tokens per second forces you to confront that at some throughput, model latency stops being the bottleneck — your data plumbing, eval harness, and human review do. Use these thought experiments to stress-test where your architecture would break if inference became effectively free and instant.
Applied AIMeta wants your next gadget to be Muse-infused
Open-sourcing Muse for TVs and toasters is a distribution play — Meta wants its inference stack embedded in third-party hardware before others can lock it out. Device makers now have a free default for on-device AI, but the real decision is whose ecosystem — and data exhaust — they want to be part of.