by Bosch AIShield | Jul 27, 2023 | AI Ethics, Infrastructure, MLOps, MLOPs Landscape
Executive Summary Generative AI and LLMs: Unlocking new opportunities for innovation, efficiency, and productivity, while posing potential risks including confidentiality breaches, IP infringements, and data privacy violations. Seven Recommendations: Safely integrate...
by Manpreet Dash with Bosch AIShield | May 9, 2023 | Infrastructure, MLOps, MLOPs Landscape, Uncategorized
Executive Summary AI attacks pose a threat to physical safety, privacy concerns, digital identity safety, and national security, making it crucial for organizations to identify the types of AI attacks and take measures to safeguard their products against them. The...
by Manpreet Dash with Bosch AIShield | Nov 2, 2022 | AI Ethics, Governance, Infrastructure, MLOps, MLOPs Landscape, Uncategorized
What are AI attacks? Introduction AI is the gamechanger of this decade. It is rapidly transforming our world and everyday life. The underlying technology, called Machine Learning (ML), is all around us. It’s ML that decides whether you get a loan sanctioned, how much...
by Daniel Jeffries | Jan 7, 2022 | AI Hardware, AutoML, Data Lineage, Data Versioning, Feature Store, Governance, Hyperparameter Optimization, Infrastructure, Labeling, Logging, MLOps, MLOPs Landscape, Monitoring, Production
Just a few years ago, almost nobody was building software to support the surge of new machine learning apps coming into production all over the world. Every cutting-edge tech company, like Google, Lyft, Microsoft, and Amazon rolled their own AI/ML tech stack from...
by AI Infrastructure Alliance | Dec 21, 2021 | Infrastructure, MLOps, MLOPs Landscape
Before the holiday seasons, we reached out to AIIA members and researched many of the companies outside the AIIA to build a comprehensive understanding of their capabilities. You may recall that in the early days of AIIA we built a similar graphic but with...
by Cnvrg | Mar 23, 2021 | AI Hardware, Infrastructure, MLOps
It is not news that machine learning and deep learning is expensive. While the business value of incorporating AI into organizations is extremely high, it often does not offset the computation cost needed to apply these models into your business. Machine learning and...
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