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2022 Trends in Semantic Technologies: Humanizing Artificial Intelligence

In this contributed article, editorial consultant Jelani Harper discusses how semantic technologies and tenets are some of the most effective ways to oversee enterprise use cases of AI for natural language technologies. These capabilities have been formed by human curated knowledge, which is why the notion of human-in-the-loop is so prominent in contemporary times.

Video Highlights: Expert.ai – Executive Interview

In this interview, expert.ai’s CEO Walt Mayo gives an update on the company’s recent FY20 results. He discusses the technology that is being developed as part of the company’s Path to Lead five-year strategy and outlines how the company expects to commercialise it. He discusses the wider natural language understanding/processing (NLU/NLP) market, highlighting recent M&A activity. Finally, he outlines the key milestones the company is targeting over the next 12 months.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – December 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Deeplite Accelerates AI on Arm CPUs Using Ultra-Compact Quantization

Deeplite, a provider of AI optimization software designed to make AI model inference faster, more compact and energy-efficient, today announced Deeplite Runtime (DeepliteRT), a new addition to its platform that makes AI models even smaller and faster in production deployment, without compromising accuracy. Customers will benefit from lower power consumption, reduced costs and the ability to utilize existing Arm CPUs to run AI models.

Looking Beyond the Incumbent: Setting New Goals for Machine Learning & Artificial Intelligence for 2022

In this contributed article, Patrice Simard, CEO and Co-founder of Intelus.ai, proposes an alternative for organizations of all sizes to develop more effective ways to leverage machine learning and artificial intelligence. The goal is not to disparage anyone’s approach; rather, it is to offer a framework that empowers smaller stakeholders, alongside major players seeking to innovate. 

3 Ways AI Can Boost Conversational Intelligence Across Your Enterprise

[SPONSORED POST] Artificial Intelligence can both help and scale human effort in building the conversational intelligence across the enterprise that drives successful business outcomes. In this eBook from Veritone, we will explore three common use cases of AI applied to customer conversations: contact center insights, social media insights, and conversational compliance.

eBook: 101 Ways to Use Third-Party Data to Make Smarter Decisions

To guide you in becoming a data-driven organization, AWS Data Exchange has created a new eBook, 101 Ways to Use Third-Party Data to Make Smarter Decisions. This innovative resource is designed as a broad compilation of use cases submitted by AWS Marketplace data providers.

87% of US Agriculture Businesses Are Currently Using AI

New research found that agriculture is second only to insurance and exhibitions sectors in scaling its use of AI. The study was carried out by RELX, the parent company of global agricultural data business Proagrica.

3 Organizational Must-Dos When Transitioning to an AI Driven Business

In this contributed article, Shai Gottesdiener, VP of R&D, Lusha, discusses how in an automation-driven business world, humans must work alongside machines to make profit happen. Artificial intelligence is just one example of the way machines are at the service of all parts of an organization’s overall utilization.

2022 Trends in Artificial Intelligence and Machine Learning: Reasoning Meets Learning

In this contributed article, editorial consultant Jelani Harper discusses some important trends for the next year in terms of how 2022 will usher in a surplus of use cases in which converging AI’s respective connectionist and reasoning approaches, as well as the array of learning methodologies between supervised and unsupervised learning, renders the efficiency and scope of these technologies transformational for everyday business needs.