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Theo is an AI workspace for physics research: literature, derivations and code in one place. Sign up free and get 1,500 credits.

Many AI teams are trying to reduce dependency on unpredictable cloud availability, on-demand shortages, or marketplace-based GPU access. Dedicated infrastructure can help teams plan training, inference, and production workloads with more confidence. CambridgeNexus helps AI companies access dedicated NVIDIA GB300 infrastructure, including bare metal and larger reserved clusters. We currently have access to 350+ NVIDIA GB300 bare-metal racks for teams planning capacity over the next 6–12 months.

Il merchandising non aspetta più il prossimo ciclo di pianificazione. Scopri come i segnali di domanda connessi e l'AI ti aiutano a rispondere più rapidamente con l'Oracle Playbook.

Detrás de un medicamento que llega al paciente hay una verificación esencial de autenticidad. Y detrás de esa verificación, una pregunta: ¿dónde están los datos y quién los gestiona? Arvato Systems ha elegido Oracle EU Sovereign Cloud, nuestra nube soberana para la Unión Europea, para desplegar su sistema de verificación de medicamentos en 15 países europeos, incluida España. Cientos de millones de verificaciones al año que ayudan a evitar que medicamentos falsificados lleguen a los pacientes. Los datos permanecen en la UE y la infraestructura está gestionada por entidades y personal de la UE. Con el rendimiento, la seguridad y la capacidad de escalar que exige un servicio sanitario tan crítico. Este caso refleja algo que considero fundamental: poder elegir dónde y cómo desplegar la tecnología, con la confianza de contar con las capacidades de OCI, el control que requiere cada negocio, y la tranquilidad de cumplir con las normativas de residencia de datos locales y regionales. Soberanía europea con impacto real en un servicio del que dependemos todos. Si quieres conocer más casos como este, atento a las novedades de nuestro #AIWorld 2026, que se celebrará en Las Vegas del 25 al 28 de octubre. Y puedes leer la hstoria completa del proyecto de Arvato Systems aqui: https://lnkd.in/eFfkVhTy #Oracle #OCI #CloudSoberano

When your AI agents speed ahead, who’s holding the brakes for you? If you’ve ever felt a twinge of anxiety about agents making decisions in your name, you’re not alone. Join WPP’s CAIO on a webinar on 10 Nov to get a six-stage lifecycle that helps you feel confident, not conflicted, about when agents start, stop, and escalate, and how you stay in control while still moving fast.

Today we're launching something special. 🔥 𝐀𝐈 𝐕𝐚𝐥𝐮𝐞 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧 is built for funds that need AI to become a portfolio value lever, not another set of isolated pilots. The story behind this is that across funds and portfolio companies come to us, we continue to see that AI ambition is high, but execution capacity is often limited. Why? 1. Scattered use cases. | 2. No clear ROI. | 3. Too many projects stop at the proof-of-concept stage. That is exactly why we are opening our AI Value Creation offering for PE & VC portfolios, after proving this path with other clients of this type 👉 https://lnkd.in/dsuKHZkw/?utm_campaign=%255Btraffic%255DMaincampaign&utm_source=linkedin&utm_medium=paid&utm_id=1206642164&hsa_acc=508184568&hsa_cam=1206642164&hsa_grp=884912774&hsa_ad=1606012084&hsa_net=linkedin&hsa_ver=3 At deepsense.ai, 𝐰𝐞 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭 𝐭𝐞𝐚𝐦𝐬 𝐚𝐧𝐝 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐨𝐧 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐀𝐈 𝐢𝐧𝐢𝐭𝐢𝐚𝐭𝐢𝐯𝐞𝐬: - from fund-level research agents, - competitive intelligence systems, - portfolio-company enablement, - AI maturity assessment, - use case prioritization, - and production-grade implementation. One example: for a private equity portfolio platform, we designed an 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐨𝐫 🚀 to help identify where AI could create real business value across multiple portfolio companies. The goal was to help leadership teams decide where AI is worth investment, where it is technically feasible, and what needs to happen for the initiative to move beyond experimentation. For PE and VC funds, this matters because 𝐀𝐈 𝐜𝐚𝐧 𝐛𝐞𝐜𝐨𝐦𝐞 𝐚 𝐫𝐞𝐚𝐥 𝐯𝐚𝐥𝐮𝐞 𝐜𝐫𝐞𝐚𝐭𝐢𝐨𝐧 𝐥𝐞𝐯𝐞𝐫, but only when it is treated as an operating model, not a collection of one-off ideas. Our approach helps funds and portfolio companies: > reduce low-impact experimentation > prioritize initiatives with measurable business potential > align business and technical stakeholders > shorten the path from idea to decision > build reusable AI playbooks across the portfolio > move validated opportunities into production systems We built this offering around what we already see in the field: 𝐟𝐮𝐧𝐝𝐬 𝐧𝐞𝐞𝐝 𝐚 𝐫𝐞𝐩𝐞𝐚𝐭𝐚𝐛𝐥𝐞 𝐰𝐚𝐲 𝐭𝐨 𝐭𝐮𝐫𝐧 𝐀𝐈 𝐩𝐫𝐞𝐬𝐬𝐮𝐫𝐞 𝐢𝐧𝐭𝐨 𝐩𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨-𝐰𝐢𝐝𝐞 𝐢𝐦𝐩𝐚𝐜𝐭. Explore how we help PE & VC companies here: 👉 https://lnkd.in/dsuKHZkw/?utm_campaign=%255Btraffic%255DMaincampaign&utm_source=linkedin&utm_medium=paid&utm_id=1206642164&hsa_acc=508184568&hsa_cam=1206642164&hsa_grp=884912774&hsa_ad=1606012084&hsa_net=linkedin&hsa_ver=3

You plan training runs, releases, and hiring with care—so why should GPU capacity be a wild card? By shifting to dedicated NVIDIA GB300 bare-metal racks and reserved clusters for the next 6–12 months, you trade on-demand uncertainty for predictable throughput, controllable costs, and reliable performance SLAs. CambridgeNexus lets you line up infrastructure with your pipeline, so every experiment and production deployment runs when you planned—not when a marketplace says you can.

“Fine” never means the same thing twice. Expression Measurement hears the difference, natively in 50+ languages. The same word can carry relief, frustration or doubt depending on who says it and how. Our API measures the expression behind the words across voice, face and language, with no translation layer and no English bias.

Five cuts of your next ad. Test them on measured human reactions instead of gut feel, before you spend on media. Expression Measurement reads facial and vocal expression frame by frame, so you can see which moments land and which ones lose people.

Move healthcare AI forward with people, data, and governance in focus. Watch CNXN Helix and Connection experts discuss responsible adoption

Recognized by Gartner®, we believe Dataiku helps organizations embed AI into decisions and operations to drive meaningful business outcomes and AI success. Explore the report to learn more.

AI in education takes more than tools. Explore practical use cases, student-data safeguards, and a path to responsible adoption for Higher Education and K–12 districts.

Most generative AI providers look good in a demo. Production is a different test. Before you choose a partner, evaluate data governance, human-in-the-loop validation, total cost of ownership, and how the provider monitors models after launch. Get the 8-point buyer’s guide to choosing a generative AI partner.

A rented frontier model makes you one of many. But an open model post-trained on your data, built for your workflows, and compounding with every interaction you feed back into it? That’s intelligence your competitors can never get. Read how 3 companies are building their AI edge with post-trained models from AI21. https://lnkd.in/e3zjm6PT

Banking is becoming more connected, immediate, and intelligence-assisted. Across the Middle East, these shifts are changing how banks serve customers, manage risk and execute decisions. ➢ More connected: Open finance is bringing permissioned data and services together. The opportunity here is to understand a customer’s financial context in its entirety, and use that responsibly across lending, payments, and personalized engagement. ➢ More immediate: Instant payments are moving money in seconds. This raises expectations across the bank includes timely fraud detection, responsive service, and operations that can identify and resolve exceptions quickly. Speed becomes valuable when customers can trust it. ➢ More intelligence-assisted: AI is supporting relationship managers and entering core workflows across credit, compliance and operations. Making it effective requires relevant information, clear decision ownership, and human oversight where judgement matters. Together, these developments are reshaping the banking operating model. Customer experience, risk management, and operational execution need to work in closer coordination. At C5i, our experience with banks in the region informs how we contribute to this transformation. We bring customer intelligence, credit and fraud analytics, data engineering and domain expertise together. Through Agent5i, we connect intelligence to governed enterprise workflows, with human review, traceability and visibility into performance. Our focus is practical: helping teams act on better information, deliver relevant customer experiences, and strengthen the controls that sustain trust. As banking evolves, the ability to turn connected intelligence into timely, accountable action becomes increasingly valuable. That is where C5i brings its expertise. To know more, click here: https://lnkd.in/dsKxmxqJ Hemant Julka | Anees Merchant | Shreyas Sundaresh | Parag Penker | Samer Hamadneh #C5iHumanAIImpact #MiddleEastBanking #UAE #BankingAI #ResponsibleAI #SovereignAI #AgenticAI #BusinessImpact

61.2% of engineering and IT teams told us they’ve lost time rebuilding or maintaining agents that already exist elsewhere in their company. The registration numbers explain a lot of it: only 36% require an agent to be registered before it goes live, and 25.6% have a formal process for retiring one. Unregistered agents keep their access and keep spending tokens long after anyone is watching them.

As Chief AI Officer at WPP, Daniel Hulme governs AI agents at scale. On 10 Nov he shares how. 45 mins, online.

Pick any agent running in your environment and try to answer five things: who owns it, what it can access, what it did last week, what it cost, and what happens if it goes wrong. Most teams we surveyed can’t answer all five. Even the most common owner, engineering and IT, holds only 28.2% of agents, and only 36% of organizations require registration before an agent goes live. The report covers what fixes this: a named owner for every agent, permissions scoped to each agent, session logs, and cost tracked per agent rather than as one combined token bill.

Deepgram is a built-in speech provider in Amazon Connect, so you can add real-time transcription and voice agents to the contact flows you already run.

Deepgram gives you real-time speech-to-text and voice agents that run on the AWS services you already use, including Amazon SageMaker and Amazon Connect.

"What happens when our cloud credits run out?" At TechCrunch Disrupt 2026 last week, we met many AI teams already thinking about the problem we set out to solve. AIEEV joined the event as a Startup Battlefield 200 company. Co-Founder Karen Kim introduced Air Cloud on stage, and our team spent the rest of the week at booth E42, walking AI teams through live demos. Visitors picked a workload and a GPU, then compared the cost with what they run today. A few themes kept coming up: 1. Teams on cloud credits already planning what comes after 2. Small teams wanting to start with only the GPU they need 3. Public sector teams asking where their data is processed Air Cloud is our answer. It connects underused GPUs into a cloud where teams can deploy models and serve requests, without costs growing out of reach as usage scales. Every conversation at the booth helps us shape Air Cloud around what AI teams actually need. Thank you to everyone who stopped by and shared what you're building. We'd love to keep the conversation going. 📖 You can find the full story on our blog: https://lnkd.in/gSce98kP 🚀 Curious how Air Cloud would fit your setup? Try it here: https://www.aieev.com/ #TechCrunch #Disrupt2026 #StartupBattlefield200 #AIEEV

Same Lenovo ThinkSystem quote. 3x the deal. Attach Klique on the services contract and a server sale becomes a platform engagement your customer keeps building on. Lenovo AI Innovator. Lenovo AI Library.

Same HPE ProLiant quote. 3x the deal. Attach Klique and a hardware transaction becomes a platform engagement your customer keeps building on. Unleash AI Partner. TPP Silver Partner. ProLiant Compute Gen12. GreenLake Marketplace.

Over the past three weeks, our Forward-Deployed Researchers [FDRs] collaborated with NVIDIA, Gong, Deel, and Alice (Formerly ActiveFence) to post-train NVIDIA’s recently released Nemotron 3.5 Super VL open model to deliver specialized intelligence across three different use cases. We believe that the companies that get the most out of AI won't all be using the same intelligence. More and more companies are moving towards AI independence, aiming to own their models for the right reasons: lower cost, control over their data and models, and a proprietary edge a rented model can't offer. Few get there alone. Post-training that holds up in production still takes expertise that sits in a handful of labs. We were glad to partner on this path with Gong, Deel and Alice, training specialized models that match or surpass frontier quality – at a fraction of the cost – across data extraction, policy QA and attack resilience use cases. Full results and methods: https://lnkd.in/e3zjm6PT