The businesses paying for AI aren't going back
THE SO WHAT
Small businesses sticking with paid AI tools suggests we’ve crossed from experimentation to embedded workflow—even at the low end of the market. If you sell into SMBs, assume AI line items are now competing with your budget and either integrate into that spend or risk being displaced by tools that do.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIBaidu’s CFO on the Company’s Approach to Recruiting Young Talent
Full-stack AI players like Baidu are turning their chip–model–cloud–AV stacks into talent magnets, not just product moats. If you’re not vertically integrated, your recruiting pitch needs a sharper narrative on what young builders can own that they can’t touch at a Baidu-scale shop.
Applied AIWhy did one day of AI cost more than a month of servers?
One retry storm wiping out a month of infra budget is a governance failure, not a cost-of-doing-business. If you’re exposing LLM calls in production, rate-limit retries, cap per-request spend, and make finance part of the rollout review this week.
Applied AIOmen AI raises $31m to watch the water inside AI data centres
$31M for Omen AI to monitor GPU cooling water is a reminder that AI infra risk now includes microbiology and plumbing, not just chips and power. If you’re planning dense GPU deployments, add fluid quality, corrosion, and biofouling monitoring to your design checklist alongside PUE and megawatts.
Applied AIGoogle Cloud will sell specialist AI models built for science
Pairing Gemini with SandboxAQ’s physics- and chemistry-tuned ‘large quantitative models’ is a bet that domain-specific math engines will sit alongside general LLMs in enterprise stacks. If you’re in pharma, materials, or any lab-heavy industry, start mapping which workflows need numerical rigor over language fluency and plan for a dual-model architecture.