Newly developed #agent #coder solely for #MacOS — run #clusters and build your own #aistack, or schedule an agent to work for you! Find out more here: agentos.tools

The AI price war is here (wsj.com/tech/ai/the-ai-price…). That is good news for buyers, but only if they understand what is actually getting cheaper. The price competition is piling pressure on OpenAI and Anthropic. The story fits a broader pattern we have been seeing for months: model access is becoming less scarce, and buyers are getting more leverage. Stating the obvious first: lower model prices help. Token costs matter, especially when companies move from pilots to production workloads. But here is what people miss. A cheaper model does not automatically make an AI system cheaper. Most enterprise AI cost hides outside the model invoice. Integration costs. Data cleaning. Evaluation. Security review. Human review. Workflow redesign. Monitoring. Incident handling. Vendor management. The kind of work that does not look magical on stage, which is probably why it matters. So the price war changes the buyer playbook. If model prices keep compressing, enterprises should avoid architectures that lock too much logic into one provider. They should separate model selection from workflow design, evaluation, orchestration, and governance. That does not mean model quality is irrelevant. It means the economic power shifts toward the layer that owns the workflow and proves the outcome. For startups, this is uncomfortable but clarifying. If your moat is “we call a frontier model,” the market is coming for you. If your moat is domain workflow, proprietary evaluation data, trust, distribution, or operational integration, falling model prices may actually help. When inference gets cheaper, does your advantage expand or disappear? If the answer is disappear, you do not have an AI strategy. You have a temporary pricing artifact. #AIStack #EnterpriseAI #OpenAI #Anthropic #AITransformation #AIEconomics #CIOMindset

TECHNOLOGY NEWSWIRE: Nvidia Reports Acquisition of Kumo AI for $400 Million  Nvidia is expanding its enterprise software capabilities by acquiring Kumo AI to integrate relational foundation models into its predictive analytics stack.  Nvidia is quietly expanding its grip on the enterprise AI stack, reportedly acquiring Kumo AI in a deal valued at over $400 million. While the chipmaker has yet to issue a formal announcement, the move signals a strategic shift. Nvidia is no longer content with merely selling the hardware that powers AI. it is aggressively moving to control the software layers that turn raw business data into actionable predictions. For years, generative AI has excelled at processing unstructured data like text and images, leaving the vast, structured troves of information in relational databases largely untapped. Kumo AI addresses this gap with its relational foundation model, which treats database records as nodes in a graph. This allows companies to run complex predictive tasks—such as churn analysis, fraud detection, and demand forecasting—without the months of manual feature engineering typically required by traditional machine learning pipelines. By bringing this technology in-house, Nvidia is positioning itself to offer predictive analytics as a seamless, bundled capability for the enterprise. This acquisition carries significant weight for technology leaders. If Nvidia integrates Kumo’s technology into its existing enterprise software suite, it could drastically lower the cost and complexity of deploying predictive AI. However, the move creates friction for major data warehousing platforms like Snowflake and Databricks, which now find a powerful predictive AI vendor absorbed by a critical hardware partner. While the integration roadmap remains unconfirmed and the technology faces the challenge of independent validation, the deal represents a calculated bet. Nvidia is betting that the next massive wave of enterprise value lies within the data warehouse, and it is moving early to ensure that when that wave breaks, the underlying intelligence is powered by its own ecosystem.  FILED UNDER:  #Nvidia, #NvidiaAcquisition, #KumoAI, #NvidiaKumo, #EnterpriseAI, #RelationalAI, #PredictiveAnalytics, #AIAcquisition, #DataWarehouseAI, #GraphAI, #NvidiaSoftware, #AIstack, #RelationalFoundationModel, #FraudDetectionAI, #ChurnPrediction, #DemandForecasting, #NvidiaEnterprise, #AIacquisition, #TechMergers, #PredictiveAI, #DataGraph, #NvidiaNews, #EnterpriseSoftware, #AIdatabases, #400MillionDeal, #NvidiaStrategy, #AIModels, #WarehouseAI, #NvidiaExpansion, #RelationalDatabaseAI, #AIPoweredAnalytics, #TechAcquisition, #NvidiaAI, #BusinessIntelligence, #GraphNeuralNets, #EnterprisePredictive, #NvidiaKumoAI, #AIEcosystem, #DataScienceAI, #CorporateAI, #Nvidia2026, #TechnologyNewswire, #PredictiveModeling, #DatabaseAI, #NvidiaBet, #EnterpriseStack, #AIintegration, #TechConsolidation, #AIfoundationModels

🌐 AiStack .com 💰 Sold Price : $65,000 ✔ @DNRater Recommended BIN : $106,310 ✔ Godaddy Estimation : $5,792 ✔ Estibot Valuation : <$100 ✔ InternetX Appraisal : <$100 📌 Venue : @afternic 📆 2026-06-08

AiStack .com SOLD for $65,000 ✅️✅️

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Most people know AI can make them money. Almost nobody knows how. Built AIStack — a beginner guide to earning online with free AI tools. Landing page is live.

📡Market Update: AiStack•com — $65,000 Shop•net — $51,050 Stagehand•com — $42,000 Blockchains•ai — $35,333 EasyFi•com — $34,000 Amphix•com — $20,000 SFdata•com — $14,995 Zavo•ai — $10,000 High-quality .coms and AI brandables are still safely leading the board 🚀

Modern teams are no longer choosing between tools, they’re building ecosystems. At Proven, this stack helps accelerate everything from analysis to content creation to product development. Here’s a look at the tools of Proven: youtube.com/watch?v=ijNaNjoS… #AIStack #FutureOfWork

Главный вывод: я не «гений вайбкодинга». Я продакт, который перестроил workflow. То же делает курс AIstack для своих студентов за 8 недель. Старт 25 июня. aistackca.com 12 дней.

5. **CRM** — внутренний для воронки AIstack. Стек: Next.js Postgres. Лиды, статусы воронки, броадкасты по сегментам. 2 недели. Интегрирован с Telegram-ботом курса.

3. **LMS** — обучающий Telegram-бот @VyudAiBot. Стек: Python aiogram Postgres. 49 органических пользователей без маркетинга. 3 недели соло. Каркас для платформы курса AIstack.

AIStack.com → $65K (Congrats to those parties. What a great transaction) "Stack" = layered collection of infra components that powers the development and deployment of artificial intelligence. Our STACK portfolio: 54 domains across 12 categories. 🏛️ GOVERNANCE (7) GovernanceStack.ai FullStackGovernance.ai/.com AIPolicyStack.ai/.com OversightStack.com 🔐 TRUST (9) AttestationStack.ai/.com ProvenanceStack.ai LineageStack.ai/.com TraceabilityStack.ai/.com BindingStack.ai/.com CustodyStack.ai 📊 ATTRIBUTION (2) AttributionStack.ai/.com 🧠 INTELLIGENCE (4) CognitionStack.ai DecisionStack.ai PrecedentStack.ai/.com IntelligenceStack.ai SemanticStack.ai ⚙️ OPERATIONS (10) ExecutionStack.ai OrchestrationStack.ai/.com ObservabilityStack.ai TelemetryStack.ai IntegrationStack.ai ProcessStack.ai HyperautomationStack.ai/.com InstrumentationStack.com 💰 ECONOMY (3) PaymentStack.ai ValueStack.ai EconomyStack.ai 🌐 FEDERATION (6) FederationStack.ai/.com ConvergenceStack.ai/.com StackFederation.ai/.com 🤖 AGENT (3) MultiAgentStack.ai AutonomyStack.ai UnifiedAgenticStack.com 🏗️ PLATFORM (3) PlatformStack.ai UnifiedStack.ai SolutionStack.ai 🛡️ SECURITY (1) RedTeamStack.com 📡 SENSING/VERTICAL (2) SensingStack.com ManufacturingStack.ai 50 domains. One namespace. Sold in clusters or individually. DM for details. #AI #Domains #AIStack #Trust #AIGovernance #aiinfrastructure #MLOps #DevOps #startups #founders #cognitiveai #enterprise #Cybersecurity

Я учу этому режиму в курсе AIstack — 8 недель от идеи до запущенного MVP для соло-фаундеров ЦА. Старт 25 июня. Demo Day 13 августа. aistackca.com Если делаешь стартап или продукт соло — это, возможно, твой повод.