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5 Startups Using AI For Altruistic Ends 

AI is regularly plagued by the headline: ‘robots are going to steal our jobs’. The fear felt by workers in roles which are looking to be automated with intelligent machines is of course understandable and justified, but there is much more to the AI conversation if instead of replacement, we consider what can be added to jobs done by people.

There is a lot of discussion about what AI can do right now, but for Marc Carrel-Billiard, at Accenture, it’s important to also look into the future of AI and consider what the next phase of this world-changing technology might be. “There are a lot of clients that talk about AI, but very few that talk about AI at scale; there’s a big difference between doing AI pilots and then doing AI at scale. Also  Carrel-Billiard explains.

Conversations about AI are never complete without one word: ‘ethics.’ From exploratory discussions surrounding the famous Trolley Problem to more practical plans around data diversity, there are many considerations required to build and use AI responsibly in business and broader society.

We spoke to Laetitia Cailleteau, Global Managing Director, Conversational AI at Accenture, to find out how one of the most influential consultancy firms thinks about responsible AI, both internally and in discussions with their many global clients.

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Meet Futurice and the entire AI community at this year's World Summit AI in Amsterdam. View the full programme, speaker line up and book tickets by visiting worldummit.ai

World Summit AI 2019
October 9th-10th
Amsterdam, Netherlands
worldsummit.ai

Since the release of the full-stack, full-scenario AI strategy at the end of 2018, Huawei has made a strong breakthrough in AI with its powerful computing advantages. In particular, Huawei released the world's most powerful AI processor Ascend 910 on August 23 this year, which earned a ticket for Huawei to enter the field full of world's top players. Giants in the industry quickly realize that Huawei has more than 5G and mobile phones. Huawei is investing greatly in basic research, which is helping Huawei seize the high ground in the future.

Erez Shilon, Head of Product Management at Firefly.ai guides you through 3 simple steps to turn your product into an AI machine. A step-by-step guide for determining the right use case of machine learning for your product

By Infoholic Research

The inception of AI is transforming the traditional way of business operations across enterprises, imbuing newer capabilities, creating business opportunities and enhancing operational efficiencies. Today, the market is witnessing largescale AI adoption and deployment across industries. Every organization is looking for cutting-edge technologies that gives them the necessary edge and lead amid competition. 

Until you break Apache Kafka you don't know how fragile it is. Why would you deliberately break Kafka? Because you want to learn what can go wrong and how to prevent it. When Kafka breaks in production you'll want to fix it as fast as possible. It's cheaper to invest into learning how to chaos test Kafka than it's to hire lawyers because you broke an SLA. The purpose of chaos testing is to see what happens when a service fails. Instead of assertions, chaos tests use monitoring solutions to prove correctness.

AI can transform or replace existing business processes or create new ones, driving down costs and delivering greater speed, agility and quality. There are numerous new use cases and data-driven revenue streams, creating new sources of competitive advantages for bold organizations. Whether you see yourself as a proactive adopter or a watchful bystander when it comes to AI, use this Digital Transformation Review as a reference. Curated by Capgemini’s Digital Transformation Institute.