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12 articles
How Healthcare Leaders Can Get Started With Artificial intelligence

How Healthcare Leaders Can Get Started With Artificial Intelligence

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about reaching our AI-focused executive audience on our Emerj advertising page.

How to Get Started with AI in Healthcare - A 3-Phase Approach

How to Get Started with AI in Healthcare – A 3-Phase Approach

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about reaching our AI-focused executive audience on our Emerj advertising page.

Artificial Intelligence: State Initiatives and  C-Suite Implications

Artificial Intelligence: State Initiatives and C-Suite Implications

This article was written and contributed by Thomas A. Campbell, Ph.D. and Jon Fetzer of FutureGrasp, and was edited and published by the Emerj team.

Why Should Enterprises Care About Full-Stack Optimization of AI?

Why Should Enterprises Care About Full-Stack Optimization of AI?

In 2018, James Kobielus wrote an article on the AI market’s shift to workload-optimized hardware platforms, in which he proposed:
Workload-optimized hardware/software platforms will find a clear niche for on-premises deployment in enterprises’ AI development shops. Before long, no enterprise data lake will be complete without pre-optimized platforms for one or more of the core AI workloads: data ingest and preparation, data modeling and training, and data deployment and operationalization.
We are seeing Kobielus’ words come true. In the past year, nearly 100 companies have announced some sort of AI-optimized IP, chip, or system optimized, primarily for inferencing workloads but also for training. Hyperscalers like Facebook, Amazon, and Google are increasingly talking publicly about "full-stack" optimization of AI, from silicon, through algorithms, up to the application layer.

Cognitive Robotic Process Automation – Current Applications and Future Possibilities

Cognitive Robotic Process Automation – Current Applications and Future Possibilities

The following brand partnership article was written by BIS Research analyst Rahul Papney, and edited by Raghav Bharadwaj of Emerj. For information about our advertising and publishing arrangements with brands, please visit our partnerships page.

InfoSys AI Research

The Impact of AI on Business Leadership and the Modern Workforce

This article was written by Sudhir Jha (Senior Vice President & Global Head of Product Management and Strategy), and was edited and created in partnership with Infosys. For more information about content and promotional partnerships with Emerj, visit the Emerj Partnerships page.

The Analogy of AI and the Fourth Industrial Revolution

The Analogy of AI and the Fourth Industrial Revolution

Emerj's own Daniel Faggella will be speaking at BootstrapLaps Applied Artificial Intelligence Conference on April 12th, 2018. Leading up to the #AAI18 event, we've partnered with BootstrapLabs to spark a conversation around AI in industry by putting together an article about Dan's recent conversation with  Nicolai Wadstrom, Founder and CEO of BootstrapLabs.

How Microtasking Helps Optimize AI-Based Search - in Media, eCommerce and More

How Microtasking Helps Optimize AI-Based Search – in Media, eCommerce and More

When we search on Google or Amazon, we’re reminded of the improved capabilities of artificial intelligence over the last half decade.
What we often don’t realize is the role that human beings have in tagging and manually working through near-infinite reams of data to develop genuinely relevant search.
Sure, data scientists and ML specialists must construct a search system - but for the time being - much of the “human-like” results that we get in the world of social media, search engines, and Commerce - comes from - well, humans.
This week on AI in Industry we interview Vito Vishnepolsky of ClickWorker. Clickworker is a large and well-rated microtasking marketplace. Clickworker cloud technology platform caters data management and web research services as well as AI algorithms training. The firm claims to have over one million workers on its global platform as of September 2017.
Vito’s perspective is valuable because he has a finger on the pulse of crowdsourced demand, handing business development for various crowdsourced AI support services - both for tech giants and startups.

3 Waves of AI Transformation in Industry - Pattern Matching, Ubiquitous Access, and Deductive Reasoning

3 Waves of AI Transformation in Industry – Pattern Matching, Ubiquitous Access, and Deductive Reasoning

The following article has been written by Josh Sutton, Global Head, Data & Artificial Intelligence at Publicis.Sapient. Publicis is one of the world's largest. Editing and formatting added by the Emerj team. For information about our thought leadership and publishing arrangements with brands, please visit our partnerships page.

Overfit for Purpose: Why Crowdsourced AI May Not Work for Hedge Funds

Overfit for Purpose: Why Crowdsourced AI May Not Work for Hedge Funds

Professor Jonathan Tapson is Director of the MARCS Institute for Brain, Behavior & Development at Western Sydney University in Australia. He holds a PhD in Engineering from the University of Cape Town in South Africa. Professor Tapson's recent research has recently lead him to apply neural networks to problems in finance. See our partnership and thought leadership publishing options on our Emerj partnerships page.

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