AI Tech, General AI

Artificial Intelligence Policy and the European Union

August 30, 2022

Artificial Intelligence Policy and the European Union
In late 2019, then newly elected European Commission President Ursula von der Leyen announced her intent to make regulating the use of artificial intelligence (AI) a top priority for Europe. She promised to “put forward legislation for a coordinated European approach on the human and ethical implications of Artificial Intelligence” within her first 100 days in office.

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Honeycomb

Honeycomb—designed for high cardinality data and collaborative problem solving, enabling engineers to deeply understand and debug production software together. Founded on the experience of debugging problems at the scale of millions of apps serving tens of millions of users, we empower every engineer to instrument and query the behavior of their system.

OTHER WHITEPAPERS
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The 2023 AI and Machine Learning Research Report

whitePaper | February 23, 2023

In December 2022, Rackspace Technology® polled 1,420 IT professionals throughout the world and across multiple industry verticals. Survey respondents worked in financial services, manufacturing, retail, hospitality, government and healthcare in the Americas, Europe, Asia and the Middle East.

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Modern IT Management With AIOps

whitePaper | September 13, 2022

Companies are going digital, whether their IT infrastructure is ready or not. Digital transformation initiatives like migrating to cloud promise speed, adaptability and reduced costs to effectively respond to today’s real-time, customer-focused world.

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Recommendations on Updating the National Artificial Intelligence Research and Development Strategic Plan

whitePaper | March 30, 2022

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) offers the following submission for consideration in response to the Request for Information(RFI) by the White House Office of Science and Technology to the Update of the National Artificial Intelligence Research and Development Strategic Plan.

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Implementing AI in business challenges and resource

whitePaper | November 10, 2019

Large enterprises need to implement AI solutions quickly and efficiently, but many don’t have the right people, process and technology. Firms can accelerate progress to AI maturity through use of a robust workbench, an operating model built on a data science-led pyramid of skills, and pre-built solutions when data complexity and talent scarcity are too big a challenge.

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The Expanding Universe of Low Code / No Code Platforms

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.

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Implementation Challenges to Three Pillars of America’s AI Strategy

whitePaper | December 23, 2022

The transformative potential of artificial intelligence (AI) is a kind of truism. Seeking to capture the benefits of the “Fourth Industrial Revolution” or “third wave of the digital revolution,” countries are prioritizing efforts to reorganize their public and private sectors, fund research and development (R&D), and establish structures and policies that unleash AI innovation.

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Spotlight

Honeycomb

Honeycomb—designed for high cardinality data and collaborative problem solving, enabling engineers to deeply understand and debug production software together. Founded on the experience of debugging problems at the scale of millions of apps serving tens of millions of users, we empower every engineer to instrument and query the behavior of their system.

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