What Businesses with AI in Production Can Teach Those Lagging Behind

whitePaper | December 1, 2021

The health and vibrancy of our national economy depends on the health and vibrancy of our organizations. How an organization is staffed is a key driver of its health. Yet only one in three executives rates his or her company as “very effective” at reducing unsuccessful hiring decisions (Bravery et al., 2019). Thus, industrial-organizational (I-O) psychologists help organizations thrive by choosing the right talent for the right job at the right time, using the most accurate, cost effective, and fair tools available (Ployhart, Schmitt, & Tippins, 2017).

whitePaper | September 22, 2021

The value of conversational AI is clear—meaning it’s time to take the next step and begin setting specific goals if you want to see real returns on your investment. Access this beginner’s guide to conversational AI to learn important industry terms and explore the questions you need to be asking as you explore different solutions.

whitePaper | January 20, 2022

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing neural network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present methods for NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.

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 | June 29, 2023

Generative artificial intelligence (AI) is impacting many aspects of the business community. ChatGPT and other similar large language models (LLMs) have captured attention for their amazing ability to create human-like prose.1,2 Additionally, generative AI can create visually captivating artistic content, encompassing images, videos, and audio. Langevin diffusion deep learning models are primarily employed to generate this content, with open-source image generation models, such as Stable Diffusion, being the most popular approach.

whitePaper | August 26, 2022

Started in 2013, Arya.ai is the first deep learning (DL) startup in India and has been one of the very early adopters to use DL in Financial Institutions. AryaXAI by Arya.ai, a full stack ML Observability platform, offers multiple components - AI explainability, ML monitoring, ML audit and Policy controls, which organisations require beyond simple ML monitoring tools.