10 Keys to AI Success in 2021

whitePaper | October 18, 2022

Tachyum Prodigy is the industry’s first universal processor, unifying the functionality of CPU, GPU, and TPU into a single monolithic package. Prodigy’s revolutionary new architecture provides 6x more raw performance on AI training and inference workloads than the industry’s highest performing GPU, and up to 10x performance at the same power.

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 28, 2022

Artificial intelligence (AI) has been accelerating across sectors. It has great potential to benefit society but the technology’s full potential can only be realized if it includes the diversity of the populations it represents throughout every step of its development. With growing concerns about bias, data privacy and lack of representation, it is critical to re-evaluate the way in which AI is both designed and deployed to ensure that all affected stakeholders and communities reap the benefits of the technology, rather than any harm.

whitePaper | June 29, 2022

The Responsible AI Institute (RAII) is developing one of the world’s first responsible AI certification programs. The RAII Certification Program is aligned with emerging global AI laws and regulations, internationally agreed-upon AI principles, research, emerging best practices, and human rights frameworks.

whitePaper | July 15, 2022

Today, the use cases for AI (artificial intelligence) and machine learning are developing at a remarkable pace. We are beginning to see cases where AI is contributing to society through its implementation in systems and services that are in production and consumer-facing. These include the automation of nuanced decisions that until now could only be made by humans, thereby increasing the profitability of corporations, and increasing customer satisfaction through the personalization of services making them tailored for each user. In addition, important discussions have begun on the adverse effects such AI systems have on humans and the resulting ethical issues they can create.

whitePaper | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.