Implementation Challenges to Three Pillars of America’s AI Strategy

whitePaper | August 16, 2020

Unleash the full potential of your cloud native transformation and accelerate innovation with the confidence that your cloud native applications are secured from start to finish, at any scale. Aqua Platform protects your entire stack, on any cloud, across VMs, containers, and serverless. Accelerate development by detecting security issues in your artifacts early and shortening time to remediate. «Shift left» security into the CI/CD pipeline, get full visibility into the security posture of your pipeline and reduce the attack surface before application deployment.

whitePaper | November 24, 2022

High-profile examples of harm associated with algorithm failure and misuse have garnered significant public concern (e.g. manipulation of the democratic process, discriminatory practice in criminal justice sentencing, and bias against racial and gender categories in the labour market). The field of AI ethics refers to the literature and to the community of people interested in this space. One high-profile manifestation of this is the formation of specialist ethics councils and teams to deliberate on conundrums regarding the use, access and openness of platforms and technologies (such as social media and messaging apps, etc.). For instance, the banning of particular public figures as well as lay users for use of the services in a manner that is not acceptable has been a constant theme in the public debate.

whitePaper | July 10, 2020

There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).

whitePaper | May 12, 2023

Onward’s mission is to develop bold and practical ideas to boost economic opportunity, build national resilience, and strengthen communities across all parts of the United Kingdom. Our vision is to address the needs of the whole country: young and old, urban and rural, for all communities across the UK – particularly places that have too often felt neglected or ignored by Westminster. We believe in an optimistic conservatism that is truly national – one that recognises the value of markets, supported by a streamlined state that is active not absent. We are unapologetic about standing up to vested interests, putting power closer to people, and supporting the hardworking and aspirational.

whitePaper | June 30, 2022

Low code and no code (LCNC) development platforms expedite the creation of new applications with minimal or no coding requirements, as well as offer tools for non-programmers to create applications of their own. Low code development was introduced in the early 2000s to increase developer productivity. It uses a variety of approaches that automate and abstract application development activities, such as drag and drop editors, code generation, component assembly and model-driven development.

whitePaper | June 7, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users. To achieve these ambitious goals, they need to optimize their networks – make them more intelligent if you will. Some of the tools needed include artificial intelligence (AI), machine learning (ML) and artificial intelligence operations (AIOps). This document will explore what intelligent networking means to telecoms, vendors and customers, and how AI and ML technologies and tools can be used, the cultural shifts the industry needs to make it a success, and what to bear in mind when deploying machine learning across a telecom network.