The first time I heard about ONNX was during my internship at INRIA. I was working to develop Neural Network Pruning algorithms in the Julia language. There weren't many pre-trained models yet that I could use, so utilizing ONNX to import models developed with other languages and frameworks might have been a solution. In this article, I want to introduce ONNX and explain its enormous potential by also seeing a practical example. ONNX, or Open Neural Network Exchange, is an open-source standard for representing deep learning models. It was developed by Facebook and Microsoft in order to make it easier for researchers and engineers to move models between different deep-learning frameworks and hardware platforms.

AS headwinds like the pandemic and supply chain crisis continue, companies will look to leverage artificial intelligence (AI) to further fuel digital advantage that can increase competitiveness, drive greater efficiencies and generate new revenue streams. The complexity of telco networks today and the speed of change has made management and control of infrastructure extremely painful. It is clear the tools, systems and methods of managing networks today are simply not fit for purpose for the network of tomorrow. To advance the rollout of 5G connectivity worldwide, communications services providers are turning to AI-powered automation and network orchestration to improve the control and management of networking to deliver faster customer experiences. Innovations like network slicing allow organizations to set service levels for each device appropriate to their use of the network.

OCR or optical character recognition is becoming increasingly important and needed for many companies and organizations that look for ways to automate and streamline their digitalization pipelines. Many companies for example need invoice automation or handwriting recognition. These companies use OCR extensively. With the rise of AI, we can now tackle OCR problems in an unprecedented way. ORPALIS is at the forefront of developing deep learning-based solutions for solving challenging OCR tasks.

Over 300 companies and organizations have used Peltarion's AI technology including: Over 300 companies and organizations have used Peltarion's AI technology including:

We live in the'age of the customer'; a time when customers use multiple channels to interact with your brand, spend more, and have access to more information about you, than ever before. It is a time when customers are two swipes away from a list of reasons why they should switch to your competitor. Banks, global vehicle OEMs, major enterprises, even governments, used to wait and react to customer interactions when customers visited their stores, dealers, branches, or offices. They were, in other words, reactive in dealing with customers. Enter the new era of customer experience.

General Data Protection Regulation (GDPR) came into force in European Union (EU) member states from 25th May 2018. It has far reaching ramifications for businesses and organizations given that data is ubiquitous and all businesses today rely on customer data to remain competitive in their industry and relevant to their customers. In this blog we will examine some of the challenges that businesses in certain industries can face and what businesses can do about it. GDPR restricts itself to personal data thereby limiting its regulatory reach to all such companies and organizations that are serving direct consumers of their services. In this era where advertisements on social media, advertisements on web pages, advertisements on mobile applications are personalized by gathering and processing information about the specific user how can companies that use these media of connecting with their customers continue to send pertinent communication/messages to their customers.

Sue Zoldak is a public relations expert with a fierce competitive streak. Her surname in Slovak, as she likes to point out, means "mercenary." Her firm, the Zoldak Agency, uses targeted advertising and grassroots campaigning to help clients spur voters to press elected officials into voting yes or no on specific bills. While not strictly a lobbyist--she doesn't communicate directly with lawmakers--Zoldak fits squarely into the influence-peddling milieu of Washington, DC, with 15 years' experience on K Street, where lobbying firms are traditionally headquartered. Put simply, she's a go-to person for companies and organizations determined to shape public policy.

When a technology has its breakthrough, can often only be determined in hindsight. In the case of artificial intelligence (AI) and machine learning (ML), this is different. ML is that part of AI that describes rules and recognizes patterns from large amounts of data in order to predict future data. Both concepts are virtually omnipresent and at the top of most buzzword rankings. Personally, I think – and this is clearly linked to the rise of AI and ML – that there has never been a better time than today to develop smart applications and use them.