Meta Introduces Segment Anything

This week in AI and ML news: AI-generated models, Meta’s image segmentation project, and more.

Author’s Note

For enterprises in high-risk industries like manufacturing and construction, decluttering and organization can’t wait for springtime. With vision AI solutions for workplace safety, “spring cleaning” is a year-round, round-the-clock process supported by adaptable models and automated alerts. Check out our blog to learn more about computer vision’s potential to support hazard detection, keeping workplaces safe and productive.

Levi’s Casts AI-Generated Models, Attracts Controversy

This week, Levi’s announced its new partnership with digital fashion studio Lalaland.ai. The studio designs realistic, AI-generated models and the partnership was touted for its potential to promote diversity and inclusivity by allowing users to view products on any number of digital models. Raising questions about the potential impact on models, the news inspired near-immediate backlash.

Levi’s issued a response to address the controversy, which the company characterized as the result of misrepresentation in the initial announcement. “We do not,” the second statement reads, “see this pilot as a means to advance diversity or as a substitute for the real action that must be taken to deliver on our diversity, equity, and inclusion goals.” The announcement goes on to confirm that Levi’s will not be reducing the number of human models in its ads, but that its new partnership with Lalaland.ai should allow it to “publish more images of our products on a range of body types more quickly.” Digital models are expected to make their debuts soon.

Meta Unveils its Segment Anything Project

Image segmentation is a core computer vision task, essential for supporting use cases like detecting foreign objects in batches of produce or spotting anomalies on medical scans, among countless others. This week, Meta publicly announced an open source image segmentation project, Segment Anything (SA). Aimed at “democratiz[ing] segmentation,” the project includes an advanced new image segmentation model and a dataset of more than 1 billion images. After checking out Meta’s announcement, read the complete research report.

In other Meta news, the company’s CTO, Andrew Bosworth, recently told Nikkei Asia, that AI is where he, Mark Zuckerberg, and other execs are currently devoting most of their time. He also discussed the organization’s new generative AI-focused team and announced plans to debut an ad-generating solution this year.

The Institute for Human-Centered AI Shares its Latest Index Report

Stanford’s Institute for Human-Centered Artificial Intelligence (HAI) has shared its latest AI Index Report. The annual publication collects, visualizes, and summarizes data related to AI in the spirit of supporting ethical and responsible use of emerging solutions. HAI collaborates with organizations like McKinsey to share data on AI’s impact on the environment, jobs, and more. One notable innovation in this year’s report is significantly more expansive reporting on AI legislation. While the 2022 report included information on AI-centric laws in just 25 nations, the latest covers 127.

One of the report’s key takeaways is that demand for AI-related skills continues to grow across nearly all sectors throughout the US. According to the report, these are ten most in-demand skills for AI professionals:

• Python
• Computer Science
• SQL
• Data Analytics
• Data Science
• Amazon Web Services
• Agile Methodology
• Automation
• Java
• Software Engineering

Learn more from Stanford’s summary of high-level takeaways or the full report.

About the Author & Plainsight

Bennett Glace is a B2B technology content writer and cinephile from Philadelphia. At Plainsight, he plays a central role in planning and delivering content that supports Plainsight’s efforts to make vision AI success a repeatable, scalable reality for enterprises across a range of industries.

Plainsight provides the unique combination of AI strategy, a vision AI platform, and deep learning expertise to develop, implement, and oversee transformative computer vision solutions for enterprises. Through the widest breadth of managed services and a vision AI platform for centralized processes and standardized pipelines, Plainsight makes computer vision repeatable and accountable across all enterprise vision AI initiatives. Plainsight solves problems where others have failed and empowers businesses across industries to realize the full potential of their visual data with the lowest barriers to production, fastest value generation, and monitoring for long-term success. For more information, visit plainsight.ai.