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... 47:10
My Mission is to Save the Future of AI (by solving its biggest crisis) - io.net CEO | DROPS E2

When Shift Happens

1 month ago 1K views

Building the world's largest AI compute cloud involves offering a better, faster, and cheaper alternative to traditional cloud services. This ambition is driven by an understanding that the AI field faces a significant shortage of computational resources. Drawing from personal experiences and principles learned at West Point, the focus is on effective leadership, empowering teams, and fostering a culture of innovation. The vision includes integrating decentralized AI computing resources using both underutilized GPUs and consumer devices to meet the growing demand for AI processing power.
02:41 - 02:53

Leadership principles from West Point emphasize servant leadership and team empowerment.

IO.net AI cloud services AI Startups
... 16:49
Create Your Own Private Local AI Cloud Stack in Under 20 Minutes

Cole Medin

1 month ago 9K views

Deploying local AI setups to cloud instances provides flexibility and scalability without compromising privacy. The process involves using a comprehensive package that includes various services like LLMs and automation tools. Special attention is given to maintaining secure endpoints through HTTPS, facilitating access for internal teams. The tutorial guides users through the setup process step-by-step, focusing on firewall configurations and DNS records to ensure smooth operation. By utilizing Digital Ocean, users gain access to cost-effective CPU instances suitable for most AI applications, while also addressing considerations for using larger models requiring dedicated GPUs.
02:59 - 03:15

Digital Ocean provides affordable options for CPU instances, ideal for local AI.

AI cloud services Tech & Hardware
... 12:54
Introducing Azure AI Foundry - Everything you need for AI development

Microsoft Mechanics

1 month ago 4K views

Azure AI Foundry provides a comprehensive platform for creating agentic solutions, facilitating the entire AI development lifecycle from concept to production. It features a model catalog with thousands of AI models, including offerings from prominent companies like OpenAI and Microsoft, while allowing customization and integration with existing systems. Users can create AI agents equipped with specific tasks and knowledge sources, such as Bing, and utilize Semantic Kernel for orchestration. Built-in monitoring and security features ensure optimized performance and compliance throughout AI application management.
01:59 - 02:11

Details on model deployment options, including serverless APIs and custom models.

Azure AI cloud services Tech & Hardware
... 5:29
AI took over my AWS

SST

1+ months ago 2K views

Integrating AI into infrastructure and codebase enables querying data effortlessly. Using OpenControl, AI assists in managing AWS resources and customer subscriptions effectively. Simple commands allow users to check billing details, customer statuses in Stripe, and make changes directly through AI. With Claude running locally, the setup securely accesses data and performs tasks while allowing for extensibility, enabling users to create custom tools. OpenControl aims to simplify AI interactions in applications with planned features for better UI and user interfaces for customer requests, enhancing overall productivity in application management.
02:25 - 03:15

Claude Code interacts securely with AWS through the OpenControl API.

AWS AI cloud services Tech & Hardware
... 15:48
Trey Layton, Penguin Solutions | Mastering AI: The New Infrastructure Rules

SiliconANGLE theCUBE

1+ months ago 2K views

Enterprises face challenges in deploying AI due to siloed infrastructures and the need for integrated systems. Achieving peak performance requires environments engineered for parallel processing and optimized workflows while addressing security and operational excellence. The introduction of software tools like Ice Clusterware facilitates automated provisioning and predictive analysis for failures in AI environments, enabling organizations to handle the complexities of large-scale deployments. This context highlights an evolving landscape where traditional IT metrics need reevaluation, focusing on real-time processing and responsiveness to ensure reliability and future-proofing in AI workloads.
04:43 - 04:43

The need for predictive failure analysis in AI systems is crucial.

Penguin Solutions AI cloud services Tech & Hardware
... 19:19
Ep. 35 Is Agentic AI Hurting Large Cloud Providers? | AI Insights & Innovation

SiliconANGLE theCUBE

1+ months ago 3K views

Agentic AI systems are autonomous, goal-driven technologies that optimize processes with minimal input, posing challenges for public cloud providers reliant on resource-intensive infrastructure. As enterprises adopt these systems, demand for high-end compute and data storage may decline, shifting preferences toward localized processing and smaller data footprints. The trend leans toward self-sufficient, cost-effective autonomous systems, diminishing cloud dependence, while maintaining flexibility in environments like edge computing. Thus, public cloud providers must adapt to remain relevant in a landscape increasingly favoring Agentic AI's efficiency and lower operational costs.
02:21 - 02:35

Localized processing enables Agentic AI to operate independently of cloud systems.

AI cloud services Research & Innovations
... 53:2
AI Genius Series - Session 5 - Leverage Cloud Native Infra for Intelligent Apps

Microsoft Reactor

1+ months ago 1K views

Exploring intelligent applications leveraging Azure Kubernetes Service (AKS) to enhance AI capabilities in cloud-native environments is pivotal. The integration of AI, such as OpenAI models, streamlines the development and operational processes, allowing for rapid deployment of innovative features. Key themes include transforming traditional applications through AI enhancements, utilizing microservices to facilitate incremental improvements, and leveraging tools like Argo for seamless automation. Emphasizing the role of cloud-native architecture enables improved agility and resilience in application deployment, ensuring organizations can adapt rapidly to changing technological landscapes.
07:20 - 07:46

Discussing Kubernetes microservices to integrate AI capabilities seamlessly.

AI cloud services Education
... 17:16
Introduction to A.I. Builder

Daniel Christian

1+ months ago 1K views

AI Builder enhances businesses by integrating AI models and prompts, allowing users to automate tasks effectively. The solution offers a mix of pre-built and custom AI models tailored to various business needs, encompassing document automation and analysis. Users can monitor usage through credits and tokens based on activity, ensuring efficient management of resources. The video highlights the importance of understanding licensing models and AI capabilities, including how AI supports applications across platforms like Power Automate and Power Apps. A tokenizer tool from a third-party service enables users to grasp AI token consumption which is crucial for effective utilization of the technology.
15:55 - 16:42

Understanding token consumption and licensing is vital for effective AI usage.

Machine Learning Education
... 17:16
Introduction to A.I. Builder

Daniel Christian

1+ months ago 1K views

AI Builder enhances businesses by integrating AI models and prompts, allowing users to automate tasks effectively. The solution offers a mix of pre-built and custom AI models tailored to various business needs, encompassing document automation and analysis. Users can monitor usage through credits and tokens based on activity, ensuring efficient management of resources. The video highlights the importance of understanding licensing models and AI capabilities, including how AI supports applications across platforms like Power Automate and Power Apps. A tokenizer tool from a third-party service enables users to grasp AI token consumption which is crucial for effective utilization of the technology.
15:55 - 16:42

Understanding token consumption and licensing is vital for effective AI usage.

Machine Learning Education