Jaime Vélez

Product Marketing Specialist at Barbara

🚀 Experience, Expertise, and Innovation in Edge AI 🚀In the dynamic landscape of technology, Edge AI has emerged as a game-changer. I bring a diverse background to this transformative journey, with a passion for bridging the gap between the Cloud and the Edge.

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List of articles

Edge Computing in Oil and Gas: Driving Efficiency in Digital Transformation

Edge Computing emerges as a transformative technology in the oil and gas industry, driving efficiency and innovation in digital transformation efforts. By harnessing the power of edge computing, organizations can optimize operations, enhance safety protocols, and extract greater value from their resources.

Industry at the Edge

How to Deploy Models in Multiple Locations?

Deploying machine learning models in various locations is becoming increasingly important for businesses. Whether you're a tech company looking to scale your AI infrastructure or a data scientist deploying models for different clients, understanding the nuances of deploying models in multiple locations is essential. This comprehensive guide will explore the strategies, challenges, and best practices in deploying models across diverse environments.

Industry at the Edge

Barbara platform release 2.7.0: Deploying models directly in TensorFlow

We are excited to announce the release of Barbara 2.7.0, a significant upgrade to our Edge AI Platform. Barbara continues to empower energy distributors, infrastructure managers, logistics operators, and manufacturers to seamlessly integrate the IT/OT worlds, harnessing the full potential of AI with unmatched privacy, autonomy, and real-time latency.

Release Notes

Adaptive AI and the Role of Edge Computing

As artificial intelligence continues to advance, the need for real-time, adaptive, and efficient AI systems becomes increasingly critical. In this article, we dig in into how edge computing complements and enhances adaptive AI, enabling intelligent applications to thrive in diverse and dynamic environments. Join us as we explore the revolutionary synergy between edge computing and adaptive AI.

Technology

How Edge Computing drives Maritime Business Revolution through Energy Optimization

Edge Computing plays a pivotal role in revolutionizing the marine business, particularly in the domain of energy optimization. By bringing computing resources closer to the data source, edge computing enables real-time data processing and analysis onboard ships and marine installations. This paradigm shift allows for more efficient energy management and optimization, leading to significant cost reductions and a reduced environmental impact.

Technology

Barbara platform release 2.4.0: Virtual Nodes arrive to Barbara!

This release, version 2.4.0, of the Barbara platform introduces significant enhancements that will expedite your proof of concepts and production deployments. Additionally, we have revamped various views and cards to improve the platform's usability, making interactions smoother and faster.

Release Notes

Edge AI for Computer Vision: What Industry Needs to Know About Optimizing Operations with Edge Computer Vision

In today's fast-paced and competitive landscape, optimizing operations is crucial for success. With the advent of cutting-edge technologies like Edge Computer Vision, businesses can gain a significant advantage by leveraging real-time data analysis and decision-making. In this article, we will explore what industries need to know about optimizing operations with Edge Computer Vision and how this transformative technology can propel their growth.

Industry at the Edge

What Companies Need to do to be EU AI Compliance

Artificial Intelligence (AI) is revolutionizing all industries, providing new opportunities and challenges for growth and innovation. However, with great power comes greater responsibility. The European Union (EU) has recognized the urgent need for ethical and transparent AI practices to protect individuals' rights and to ensure fair and accountable use of AI technologies. This article aims to guide companies on what they must do to comply with EU AI regulations.

Technology

MLOps at the Edge: Advantages and Challenges of Deploying Machine Learning Models in Edge Computing Environments

‍‍In today's fast-paced business landscape, artificial intelligence (AI) and machine learning (ML) have become instrumental in many business processes. MLOps is a rapidly growing field that is revolutionizing the way Machine Learning models are being deployed and managed. By using MLOps in the Edge, organizations can take advantage of the benefits of local processing, increased security and privacy, and reduced bandwidth usage. This article delves into the advantages and challenges of deploying ML in the Edge.

Technology

Green AI and the Critical Role of Edge Computing in its Success

With the rapid growth of artificial intelligence, the environmental impact of AI is a hot topic. Green AI aims to create sustainable, energy-efficient, and environmentally-friendly AI systems. However, achieving this goal requires a combination of different technologies and one of the most critical ones is Edge Computing. In this article, we'll explore Green AI, its importance, and the critical role of Edge Computing in its success.

Barbara

Confidential AI: The Edge as an Infrastructure for Private, Compliance, and Secure AI Deployment

AI is transforming the way businesses operate, but it also introduces new security concerns. Companies must protect their data from cyberattacks, comply with data protection regulations, and ensure their AI models are ethical and transparent. Deploying AI at the Edge can provide a secure infrastructure for private, compliance, and secure AI deployment.

Cybersecurity

Optimized Retraining Guide for MLOps

In general, it is important to clearly understand your business requirements and the problem you are trying to solve when determining the best approach to automate the retraining of an active machine learning model. It is also important to continuously monitor the performance of the model and make adjustments to the retraining cadence and metrics as needed.

Barbara