CORTEXSAP AI pact with AWS offers customers more gen AI options
At SAP Sapphire 2025, the two tech giants teamed up to embed generative AI deeper into ERP, targeting supply chain, finance, and beyond.
17 juil.
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At SAP Sapphire 2025, the two tech giants teamed up to embed generative AI deeper into ERP, targeting supply chain, finance, and beyond.
SAP is embedding Nvidia‘s generative AI foundry service into SAP Datasphere, SAP BTP, RISE with SAP, and SAP’s enterprise applications portfolio to equip customers with greater and more simplified access to the technology.
SAP is partnering with Databricks to offer advanced data science and AI capabilities within Business Data Cloud.
SAP is expanding its generative AI copilot Joule to include AI agents. Deeply embedded in SAP systems, the company’s agents aim to solve increasingly complex tasks.
Firewall for AI discovers and protects your public LLM-powered applications, and is seamlessly integrated with Cloudflare WAF. Join the beta now and take control of your generative AI security.
A shockingly inefficient trillion-dollar project
Learn how Cloud Logging uses the log router and log sinks to route log entries to various destinations, such as storage buckets.
Discover, create, share, and run AI agents all in one secure platform, bringing the best of Google AI to every employee, for every workflow.
Anthropic's Claude models on Vertex AI now have improved overall availability with the global endpoint for Claude models. Get started today.
The obvious question: what kind of computer do you need? Running large language models locally requires substantially more computational resources than typical software. The key constraint is memory — specifically, RAM on most systems, or VRAM if using a dedicated graphics card for acceleration. Block's documentation suggests that 32 gigabytes of RAM provides "a solid baseline for larger models and outputs." For Mac users, this means the computer's unified memory is the primary bottleneck. For W
Slack a choisi Claude d'Anthropic pour alimenter son nouveau Slackbot, principalement en raison des exigences de conformité FedRAMP Moderate pour servir les clients du gouvernement fédéral américain. Cependant, cette exclusivité sera temporaire : Slack prévoit d'intégrer d'autres fournisseurs cette année, notamment Google Gemini et potentiellement OpenAI, considérant les modèles de langage comme des commodités. Salesforce garantit qu'aucun modèle n'est entraîné sur les données clients pour préserver la confidentialité et la sécurité.
Microsoft Copilot is your companion to inform, entertain and inspire. Get advice, feedback and straightforward answers. Try Copilot now.
From literacy campaigns to empowering influencers, CIOs are upping their change management game to promote adoption and drive business value with generative AI.
Introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier. Gemini 3.1 Flash-Lite can tackle tasks at scale, like high-volume translation and content moderation, where cost is a priority. And it can also handle more complex workloads where more in-depth reasoning is needed, like generating user interfaces and dashboards, creating simulations or
Learn, plan, and build with Gemini 3. Available today, you can access Gemini 3 on Vertex AI and Gemini Enterprise.
The versatility of large language models (LLMs) led to the creation of diverse benchmarks that thoroughly test a variety of language models' abilities. These benchmarks consist of tens of thousands of examples making evaluation of LLMs very expensive. In this paper, we investigate strategies to reduce the number of evaluations needed to assess the performance of an LLM on several key benchmarks. For example, we show that to accurately estimate the performance of an LLM on MMLU, a popular multiple-choice QA benchmark consisting of 14K examples, it is sufficient to evaluate this LLM on 100 curated examples. We release evaluation tools and tiny versions of popular benchmarks: Open LLM Leaderboard, MMLU, HELM, and AlpacaEval 2.0. Our empirical analysis demonstrates that these tools and tiny benchmarks are sufficient to reliably and efficiently reproduce the original evaluation results.
Gemini Enterprise for Customer Experience is built on Gemini models developed by Google DeepMind. But having access to Google DeepMind's world-leading research and frontier models is the starting line. A brilliant model is only as powerful as the foundation it runs on. To put human-grade customer experience agents into production - where milliseconds of latency matter for voice interactions and hallucinations pose real business risks - you need a platform engineered for performance. This is why
Discover how Google Cloud's billing access control resource allows users to create & update access permissions for various roles in an organization.
After successful procurement, the customer's administrator links the purchase to their actual Gemini Enterprise app environment: Redirect to Gemini Enterprise: The Discovery Engine Administrator will see a "Go to Gemini Enterprise" option directly on the procured Marketplace listing. Project Verification: Clicking this prompts the administrator to log into the Google Cloud project where their Gemini Enterprise licenses are allocated. Note that the customer must ensure this destination Google
Today, we’re bringing partner-built agents from Agent Marketplace directly into the Agent Gallery inside the Gemini Enterprise app. Discover specialized AI from partners like Adobe, Atlassian, and more.
Join us June 17–18 for the London Summit 2026. Explore what’s next for generative AI, infrastructure, and security at the year’s must-attend cloud conference – register now.
AI has collapsed the exploit window to hours. Learn how Netenrich and Google AI Threat Defense close the loop between finding vulnerabilities and surviving them.
Alexa+ gagne en conversation, en compréhension et en capacité à enchaîner plusieurs actions, mais sa latence et sa tendance à trop parler peuvent dégrader l’expérience. Nous constatons que l’assistant est plus humain, sans être encore aussi immédiat et discret que l’on attend d’un appareil domestique. À écouter sur Monde Numérique : Alexa+ arrive en France avec des fonctions boostées à l’IA générative.