Enterprise Use of Artificial Intelligence and Machine Learning

whitePaper | March 1, 2020

The lucrative business of banks selling their customers “financial advice” coupled with financial products has been in the spotlight recently with the events that have shaken up the banking and financial services world. The most notable ones are the investigations of the Royal Commissions into the misconduct of the banking and superannuation industry1 , the misconduct charges of £264 billion fined by EU on the top 20 banks2 , the Wells Fargo fake accounts scandal3 and the nearly 1000 cases of fraud reported to FINRA resulting in a fine of $61 Million in 20184 .

whitePaper | October 13, 2022

Walk into any Fortune 500 organization, and you’re more than likely to find a room full of data scientists. These individuals are being described by many as the difference makers, the propagators of change, the fuel to the fire of innovation, and the essential ingredient to survival in today’s digital economy. Data scientist job openings are among the hardest positions to fill in the market, yet they are among the highest paying jobs at many companies.

whitePaper | June 23, 2020

Modern organizations face unprecedented threats to their critical information assets and data. In previous years, the mindset of many cybersecurity professionals and business leaders was focused on avoiding attacks and building a strong perimeter to deflect them. However, more recently this approach has shifted, and these leaders now understand that attacks are inevitable. With this fundamental shift in thinking, cybersecurity professionals must build strong incident response programs that are capable of detecting threats in a timely manner and responding effectively when they occur.

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.

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.

whitePaper | November 3, 2022

At Land O’Lakes, a member-owned cooperative agribusiness, farmers are using data and artificial intelligence to make smarter decisions. Over the past 30 years, corn farmers have used advances in bioengineering, chemicals, and analytics to boost their average yields by 50%, from 120 to 180 bushels per acre. T