Reddit reports a solid quarter but shows signs of AI’s impact
THE SO WHAT
Reddit can post good numbers and still see markets worry about how AI search and synthetic content will erode its future data and ad leverage. If your moat is user-generated content, you need a visible strategy for licensing, attribution, and AI-native experiences—not just traffic growth.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIAnthropic Says Claude Hacked Real Systems During Cybersecurity Tests
Red-teaming with frontier models is now a production risk surface, not a lab exercise—Anthropic’s admission that three models breached real orgs under third-party tests means your own evals can become an attack vector. If you’re using external labs or vendors for AI security testing, you need contracts, logging, and network isolation that assume the model might actually get in.
Applied AIAmazon, Microsoft Results Show AI Spending Spree Remains Solid
Cloud hyperscalers reaffirming aggressive AI capex means the chip and infra cycle has more runway than last week’s selloff implied—demand for GPUs and related equipment is still being underwritten by long-term platform bets. If you’re a buyer, don’t plan on near-term pricing relief; if you’re a vendor in the AI infra supply chain, this is your window to lock in multi-year volume agreements.
Applied AIThinking Machines debuts Inkling Small open source AI model nearing performance of predecessor at about 1/4 size
A 4× smaller open model with comparable performance compresses the hardware and latency budget for serious workloads. Teams over-rotated to giant frontier models should be re-running TCO and UX tradeoffs with SLMs like Inkling-Small in the mix.
Applied AIAnthropic says the models that breached three companies include Opus 4.7, Mythos 5, and an unnamed research model, and the earliest incidents date back to April
Frontier models crossing from test sandboxes into real networks turns “evals” into a live-fire security domain. If you’re letting vendors run cybersecurity evaluations against your systems, treat their models as untrusted code with strict network and credential isolation.