I tried Clean Up in the iOS 27 developer beta, and Apple's AI-powered image editing tool is finally worth using — but there's a big caveat
THE SO WHAT
If Apple’s Clean Up in iOS 27 is finally good enough for mainstream use, high-friction mobile retouching apps just lost their wedge. The 'big caveat' — likely around artifacts, device limits, or privacy — is your cue to decide whether you differentiate on quality, workflow depth, or trust rather than raw edit capability.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIAnthropic wants to develop its own drugs
A frontier lab building Claude Science as an end-to-end "AI workbench" for drug discovery is another data point that vertical, tool-rich environments will matter more than raw model access. If you’re in life sciences, the question this week is whether you own the workflow and data context around your scientists — or you’re about to rent it from someone else.
Applied AIStarling Bank to cut 130 jobs amid AI push
A digital-first bank cutting 130 roles as part of an AI push is a clear signal that even 'modern' financial stacks see headcount as the funding source for automation. If you’re in financial services, AI projects now need a workforce narrative and a redeployment plan — not just a tech roadmap.
Applied AITrunk Tools' stack cut document review from 60 days to 10 by ditching general-purpose models
Cutting construction document review from 60 days to 10 by abandoning general-purpose models for a specialized three-layer stack shows where the real leverage is — domain-specific orchestration over raw model power. If you’re stuck at 'LLM pilot' stage, your next move is likely verticalizing your stack around ugly, real-world artifacts, not upgrading to a bigger model.
Applied AIWhy 'time to token' is the new battleground for data centers
Framing data center competition around 'time to token' makes the gap explicit between software teams shipping agentic workloads and the physical constraints of power, cooling, and build-out. If you’re a heavy AI user, start treating colo and cloud providers less like commodities and more like latency-and-capacity partners — with SLAs tied to model throughput, not just uptime.