Sources: Nvidia is in talks to invest in Perplexity valuing it at $30B+, after weighing a tech licensing deal and staff hires, as Perplexity hits $750M+ in ARR
THE SO WHAT
If Perplexity is doing $750M+ ARR and drawing Nvidia in at a $30B+ valuation, the AI assistant is hardening into a real distribution and demand channel for inference, not just a demo surface. For operators, this raises the bar on “assistant as product” economics — you now have to model both margin pressure from infra vendors and competition from infra-backed assistants that can afford to run hotter models longer.
READ THE SOURCE
MORE FROM THE WIRE
Applied AISource: AI researcher Luke Metz, who returned to OpenAI from TML earlier this year, joins Meta's Superintelligence Labs and will report to Alexandr Wang
Top frontier researchers moving into Meta’s Superintelligence Labs underscores how concentrated the talent race has become at the very top of the stack. If you’re not a frontier lab, assume the cutting edge will be external—optimize for fast integration and differentiated data, not winning the pure research arms race.
Applied AIA look at the playbook tech giants like Google, Microsoft, and OpenAI use to shape American schools to their benefit, and the pushback against unproven AI tools
K‑12 is becoming a strategic distribution channel for AI platforms, not just a social-good story. If you sell into education or adjacent public sectors, expect procurement to harden around evidence of learning impact and data safeguards, not just discounted licenses.
Applied AINvidia Notifies Customers About AI-Related Price Hikes
A 15%+ jump in server prices tied to AI chips and soaring memory costs means total cost of ownership assumptions for GPU-heavy workloads just broke — especially for inference at scale. If you're building on rented Nvidia capacity, revisit your unit economics and pricing this week or risk locking in unprofitable AI features.
Applied AIThe US is now home to 15 of the world's 20 biggest AI data centers — with one state housing 12 on its own
AI compute is concentrating into a few US geographies—Texas and similar markets are becoming de facto control points for power, land, and permitting. If your roadmap depends on large-scale training or inference, you now have to underwrite regional infrastructure and policy risk, not just cloud vendor SLAs.