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OpenAI has announced the release of its latest AI model, codenamed Strawberry, now officially named OpenAI o1. This new model is designed to improve how AI handles complex tasks in math, science, and coding by evaluating its steps before providing a response.Key Updates: Advanced Reasoning: Unlike previous models, OpenAI o1 takes more time to think through problems, emulating a more human-like reasoning process. This approach helps the model better handle difficult questions and adhere more closely to safety guidelines. New Naming and Features: OpenAI o1 introduces a new naming system and will be available alongside existing models like GPT-4o. There’s also a lightweight variant, o1-mini, focused on code generation. Rolling Out Access: The new model is being introduced in phases. Starting today, ChatGPT Plus and Team users will get limited access to both o1-preview and o1-mini, with educational and enterprise users gaining access next week. Current Limitations: While promising, O
HP is working to help users get a head start on customizing AI models with open-source AI blueprints available to anyone on Github. Search “Github AI blueprints” on Google or Chat-GPT to quickly find links to HP AI Blueprints for a variety of AI use cases on Github or visit Github directly: https://github.com/HPInc/AI-Blueprints.Happy coding!
Discover the exciting updates in Salesforce Spring ’25, designed to enhance productivity, collaboration, and personalization for end users. From AI-powered insights to improved mobile access and seamless integrations, this release empowers teams to work smarter. With the right Salesforce Admin Training, organizations can fully leverage these features for maximum impact. Let share your view to make it for helpful
IntroductionIn the rapidly evolving landscape of digital creativity, HP's AI Studio emerges as a transformative platform designed to empower creators, developers, and innovators. As generative AI continues to redefine how content is produced, AI Studio by HP provides a robust ecosystem that integrates cutting-edge technologies with user-friendly tools to streamline workflows and unlock new creative possibilities. In-Depth Features of AI StudioAI Studio is built on the foundation of high-performance computing and intuitive design. It seamlessly integrates with Z by HP workstations powered by NVIDIA GPUs, offering creators the computational power needed to train and deploy complex AI models.Key capabilities include:Pre-trained and Custom Models: Access a library of pre-trained models or build your own using the intuitive training interface. Model Testing Environment: Evaluate performance and accuracy before deployment. Collaboration Tools: Real-time team collaboration for AI-driven proje
What Is HP AI Studio?HP AI Studio is a cloud-native, GPU-powered development platform purpose-built mainly for AI developers and data scientists. Part of HP’s AI Creation Center ecosystem, it streamlines the AI workflow by combining compute, collaboration, and reproducibility in one place, which is extremely useful with the plethora of tools that we manage nowadays.Key features include:One-click environments for PyTorch, TensorFlow, Hugging Face, Nvidia NGC Models, local LLMs, and more Containerized, portable workflows Hybrid compute support: local, on-prem, or cloud Built-in experiment tracking Collaboration capabilities for teamsAs a tool that supports the entire AI development process, from building an MVP to running large-scale training and deploying models into production, HP AI Studio is designed to assist you. But as denoted from the title, like many platforms, it offers both Free and Pro (Paid) tiers.So — how usable is the free version? And when does it make sense to upgrade?Wh
Our data science team requires specialized expertise for HP AI Studio implementation and enterprise AI development optimization. We're seeking an experienced consultant with 1-2 weeks availability to support us with:Configuring comprehensive on-premises AI development workflows using HP AI Studio blueprints and workspace management Implementing secure model training and deployment pipelines leveraging NVIDIA NGC catalog integration and custom container environments Establishing collaborative data science projects with MLflow tracking, artifact management, and team-based workspace sharing Optimizing GPU utilization and compute resource allocation for TensorFlow, PyTorch, and custom AI model development Training data science teams on platform best practices, blueprint customization, and end-to-end AI project lifecycle managementOur enterprise organization aims to deploy secure, on-premises AI capabilities while maintaining data privacy and leveraging HP's integrated hardware-software eco
With the release of v1.55.13, HP AI Studio has completed the SOC2 State 2 audit on the path to SOC2 certification. In addition, Penetration Testing compliance elements have released in this version of the software to enhance solution security. Sign-up for the free version or upgrade your software today!
I tried a few free AI tools to prototype small local models. Some outputs were useful, others sounded like a motivational coach I didn’t ask for.Has anyone else tested these? Did it actually help, or just add extra comedy to your workflow?
Salesforce is evolving rapidly, and Agentforce skills are becoming essential for every admin. With AI-driven automation and smarter workflows, Salesforce Admins who master Agentforce can streamline processes, improve user experience, and boost business productivity.Through Salesforce agentforce training, professionals can learn how to leverage Agentforce effectively, making them more valuable in today’s competitive job market. These skills not only enhance problem-solving but also prepare admins for the future of AI-powered CRM. Investing in Salesforce admin training ensures that admins stay ahead, drive innovation, and meet the growing demands of modern organizations. Lets share your views to make it helpful
Image generated using Gemini CanvaThe Hidden Challenge of Connecting AI to Your ServicesPicture this: You’ve built a fantastic API that powers your application. It’s well-documented, follows REST principles, and serves thousands of requests daily. Now, with AI agents becoming mainstream, you’re excited to make it available to LLMs through the Model Context Protocol (MCP). There’s even a tool that can auto-convert into an MCP server. What could go wrong?As it turns out, quite a lot.The rush to make existing APIs available to AI agents reveals a fundamental mismatch: APIs designed for traditional software weren’t built with AI’s unique constraints and capabilities in mind. Let’s explore why simply converting your API into an MCP tool might be setting your AI integration up for failure.Understanding the Players: Agents, Tools, and MCPBefore diving into the problems, let’s establish our terminology. In the AI ecosystem:Agents are LLMs that can take actions beyond just generating text Tool
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