K
Kathleen Martin
Guest
Synthetic Data Will Be a Requirement to Build the Metaverse
Yashar Behzadi, CEO and founder, Synthesis AI
“The metaverse cannot be built without the use of synthetic data.
“To recreate reality as a digital twin, it’s necessary to deeply understand humans, objects, 3D environments and their interactions with one another. Creating these AI capabilities requires tremendous amounts of high-quality labeled 3D data, which is impossible for humans to label. We are incapable of labeling distance in 3D space, inferring material properties or labeling light sources needed to recreate spaces in high-fidelity.
“Synthetic data built using a combination of generative AI models and visual effects (VFX) technologies will be a key enabler of the AI models required to power new metaverse applications.”
AI Introduces Software Development Teams to the Age of Augmented Analytics
Florian Schouten, vice president of product management, Digital.ai
“AI’s next shining moment will be empowering humans with data-driven recommendations for business decisions, across industries, in the form of augmented analytics.
“With an increased emphasis on governance and risk, we are going to see AI predict risk around software release schedules and tell companies why that release is at risk, providing deeper insights and allowing companies to avoid detrimental errors like the ones Facebook and Twitch could not.”
Model Evaluation and Tuning Goes Mainstream
Wilson Pang, CTO, Appen
“In 2022, the need for regular model evaluation and tuning becomes AI program table stakes. Machine learning models are dynamic, they can’t be deployed and forgotten. ML models in production need to be updated and retrained based on a variety of factors, including the ongoing results, as well as changes in infrastructure, data sources and business models.
“The awareness of the need to regularly evaluate models took a huge leap in 2021. According to the Appen State of AI report, 87% of organizations update their models at least quarterly, up from 80% last year, with 57% updating their models at least monthly; 91% of large organizations update their models at least quarterly, and organizations that use external data providers are most likely to update their models at least monthly.
“In 2022, given the overall maturing of the AI industry, Gartner found that at least 40% already had some form of AI program last year. Enterprises will shift focus from implementation to optimization, resulting in increased reliance on model evaluation tuning and solutions and the vendors that can assist in this process.”
Continue reading: https://www.iotworldtoday.com/2022/01/10/ai-predictions-2022-the-expert-views/
Yashar Behzadi, CEO and founder, Synthesis AI
“The metaverse cannot be built without the use of synthetic data.
“To recreate reality as a digital twin, it’s necessary to deeply understand humans, objects, 3D environments and their interactions with one another. Creating these AI capabilities requires tremendous amounts of high-quality labeled 3D data, which is impossible for humans to label. We are incapable of labeling distance in 3D space, inferring material properties or labeling light sources needed to recreate spaces in high-fidelity.
“Synthetic data built using a combination of generative AI models and visual effects (VFX) technologies will be a key enabler of the AI models required to power new metaverse applications.”
AI Introduces Software Development Teams to the Age of Augmented Analytics
Florian Schouten, vice president of product management, Digital.ai
“AI’s next shining moment will be empowering humans with data-driven recommendations for business decisions, across industries, in the form of augmented analytics.
“With an increased emphasis on governance and risk, we are going to see AI predict risk around software release schedules and tell companies why that release is at risk, providing deeper insights and allowing companies to avoid detrimental errors like the ones Facebook and Twitch could not.”
Model Evaluation and Tuning Goes Mainstream
Wilson Pang, CTO, Appen
“In 2022, the need for regular model evaluation and tuning becomes AI program table stakes. Machine learning models are dynamic, they can’t be deployed and forgotten. ML models in production need to be updated and retrained based on a variety of factors, including the ongoing results, as well as changes in infrastructure, data sources and business models.
“The awareness of the need to regularly evaluate models took a huge leap in 2021. According to the Appen State of AI report, 87% of organizations update their models at least quarterly, up from 80% last year, with 57% updating their models at least monthly; 91% of large organizations update their models at least quarterly, and organizations that use external data providers are most likely to update their models at least monthly.
“In 2022, given the overall maturing of the AI industry, Gartner found that at least 40% already had some form of AI program last year. Enterprises will shift focus from implementation to optimization, resulting in increased reliance on model evaluation tuning and solutions and the vendors that can assist in this process.”
Continue reading: https://www.iotworldtoday.com/2022/01/10/ai-predictions-2022-the-expert-views/
