April 2021 Summaries

Arize AI has been named to the Forbes AI 50 list of most promising artificial intelligence companies of 2021, recognizing its leadership in Machine Learning Observability. The company's platform helps make machine learning models work in production by providing real-time monitoring, explanation, and troubleshooting capabilities. Arize AI is focused on addressing performance degradation issues that arise after ML model deployment, which can have significant financial impacts on businesses. The company was evaluated by Forbes alongside other top North American companies using AI to transform industries, and its selection reflects the importance of software that enables AI models to perform as expected in real-world applications.

Arize AI has partnered with Algorithmia to help organizations improve their machine learning operations (MLOps) and observability. The collaboration aims to enable companies to deliver more models into production, maximize model performance, and minimize risks associated with ML models. By integrating Arize's ML observability platform with Algorithmia's enterprise MLOps platform, customers can leverage the combined power of both platforms to deploy models and manage their performance at scale. This partnership aims to streamline machine learning operations, bridge the gap between data science and ML engineering, and provide a comprehensive solution for managing AI investments in businesses.

Coded Bias: An Insightful Look At AI, Algorithms And Their Risks To Society` Coded Bias is Netflix's deepest dive into the state of artificial intelligence, highlighting issues that are uncomfortably relevant to society. Commercially available facial recognition programs have a severe algorithmic bias against women and people of color, as seen in research by M.I.T. Media Lab researcher Joy Buolamwini. Flaws in AI applications can spread discrimination across daily life, affecting hiring, medical treatment, education, financial credit, and prison terms. The film shines a light on the opportunity to improve AI systems through better data leverage and development practices. To address algorithmic harm, innovation is needed, including tools for accountability, to enable marginalized populations to benefit from better technology and experience a better world.

In 2020, global greenhouse gas emissions decreased by 7% due to the COVID-19 pandemic's impact on travel and transportation. However, as people return to their daily routines, there is concern that carbon emissions will rise again. De-urbanization trends may lead to increased dependence on driving in smaller cities and suburbs, which could contribute to unsustainable living and higher carbon emissions. Google Maps has introduced a new feature that optimizes routes for lower fuel consumption based on factors like road incline and traffic congestion. This AI-driven approach incentivizes users to make environmentally friendly decisions, potentially reducing the carbon footprint of increased vehicle use across the country.

The article discusses the importance of Machine Learning (ML) tools for business executives, drawing parallels between the evolution of software development and the current state of ML. It highlights that just as discrete steps in the software development lifecycle were addressed by various solutions and tools, similar categories are emerging around researching, building, deploying, and monitoring models in ML. The article emphasizes that understanding AI/ML initiatives is now crucial for business leaders, especially in data-driven businesses. It also provides an overview of some key ML tools such as Feature Store, Model Store, and Evaluation Store, which can help CEOs participate in technical discussions around ML/AI initiatives.