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AI Joins the Navy: Major Defense Contractor Taps Artificial Intelligence to Slash Shipyard Delays

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The United States Navy continues to face delays with nearly all of its programs, with some vessels now running up to three years behind schedule. This week, the country’s largest military shipbuilder announced a new partnership with an artificial intelligence (AI) developer that aims to help streamline efforts and address ongoing delays within its shipyards.

The strategic partnership between Huntington Ingalls Industries’ (HII’s) Newport News Shipbuilding and Ingalls Shipbuilding divisions and C3AI further broadens the existing relationship with the enterprise AI application software company to integrate AI solutions across its shipbuilding operations. According to the companies, this will include areas such as planning, operations, supply chain management, and labor allocation.

“Increasing shipbuilding throughput is a critical priority for HII and the U.S. Navy,” said HII CEO Chris Kastner. “We’re proud to partner with C3 AI to leverage data and digital capabilities like artificial intelligence in the urgent work of delivering ships to the U.S. Navy.”

Supporting the U.S. Navy’s Fleet Readiness

The firms also highlighted how enterprise AI will help accelerate production and support the U.S. Navy’s fleet readiness needs. It will further provide opportunities in uncrewed vehicle production and sustainment. The collaboration further builds on a six-month initial enterprise AI production deployment program underway at Ingalls Shipbuilding.

Teams at the company’s shipyards have leveraged complex algorithms to adjust and optimize work schedules. The initial deployment of the C3 AI application, powered by the C3 Agentic AI Platform, has already demonstrated significant improvements in schedule performance. The companies explained that it will now be scaled across HII shipyards.

“C3 AI is proud to team with HII to ensure its vision in maintaining the nation’s maritime industrial dominance through the adoption of next-generation shipbuilding technologies. This collaboration underscores our growing role as a strategic provider to the U.S. government and defense sector,” said Thomas M. Siebel, chairman and CEO of C3 AI.

“By deploying Enterprise AI across planning, operations, and the supply chain, we are powering a modern, intelligent infrastructure to ensure America’s edge in naval readiness,” Siebel added, noting it will significantly aid in digitizing the country’s defense industrial base.

Not Taking Jobs

There have been concerns that AI is replacing human workers and taking jobs. However, the shipbuilding industry has been facing severe worker shortages, and AI could help address some of these issues.

In the short term, this partnership is intended to streamline operations; however, it may lead to some skill positions being handled by AI. Yet, that still shouldn’t be a concern.

The industry is experiencing a shortage of welders, and as previously reported, efforts are underway to utilize robotic welders that can operate around the clock and achieve far greater precision. Moreover, autonomous systems may be charged with handling some of the more repetitive tasks and jobs that require manual labor.

This could lead to further data analysis and programming roles within the shipbuilding industry, along with skilled professionals to develop, manage, and maintain the AI systems that are increasingly being used in shipbuilding.

HII currently employs approximately 44,000 people at its multiple facilities across the country, including Newport News, VA, which builds nuclear-powered aircraft carriers and submarines for the U.S. Navy, and Ingalls Shipbuilding in Pascagoula, MS, which manufactures the service’s amphibious ships and destroyers.

 



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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review – Cureus

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Radiomics-Based Artificial Intelligence and Machine Learning Approach for the Diagnosis and Prognosis of Idiopathic Pulmonary Fibrosis: A Systematic Review  Cureus



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A Real-Time Look at How AI Is Reshaping Work : Information Sciences Institute

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Artificial intelligence may take over some tasks and transform others, but one thing is certain: it’s reshaping the job market. Researchers at USC’s Information Sciences Institute (ISI) analyzed LinkedIn job postings and AI-related patent filings to measure which jobs are most exposed, and where those changes are happening first. 

The project was led by ISI research assistant Eun Cheol Choi, working with students in a graduate-level USC Annenberg data science course taught by USC Viterbi Research Assistant Professor Luca Luceri. The team developed an “AI exposure” score to measure how closely each role is tied to current AI technologies. A high score suggests the job may be affected by automation, new tools, or shifts in how the work is done. 

Which Industries Are Most Exposed to AI?

To understand how exposure shifted with new waves of innovation, the researchers compared patent data from before and after a major turning point. “We split the patent dataset into two parts, pre- and post-ChatGPT release, to see how job exposure scores changed in relation to fresh innovations,” Choi said. Released in late 2022, ChatGPT triggered a surge in generative AI development, investment, and patent filings.

Jobs in wholesale trade, transportation and warehousing, information, and manufacturing topped the list in both periods. Retail also showed high exposure early on, while healthcare and social assistance rose sharply after ChatGPT, likely due to new AI tools aimed at diagnostics, medical records, and clinical decision-making.

In contrast, education and real estate consistently showed low exposure, suggesting they are, at least for now, less likely to be reshaped by current AI technologies.

AI’s Reach Depends on the Role

AI exposure doesn’t just vary by industry, it also depends on the specific type of work. Jobs like software engineer and data scientist scored highest, since they involve building or deploying AI systems. Roles in manufacturing and repair, such as maintenance technician, also showed elevated exposure due to increased use of AI in automation and diagnostics.

At the other end of the spectrum, jobs like tax accountant, HR coordinator, and paralegal showed low exposure. They center on work that’s harder for AI to automate: nuanced reasoning, domain expertise, or dealing with people.

AI Exposure and Salary Don’t Always Move Together

The study also examined how AI exposure relates to pay. In general, jobs with higher exposure to current AI technologies were associated with higher salaries, likely reflecting the demand for new AI skills. That trend was strongest in the information sector, where software and data-related roles were both highly exposed and well compensated.

But in sectors like wholesale trade and transportation and warehousing, the opposite was true. Jobs with higher exposure in these industries tended to offer lower salaries, especially at the highest exposure levels. The researchers suggest this may signal the early effects of automation, where AI is starting to replace workers instead of augmenting them.

“In some industries, there may be synergy between workers and AI,” said Choi. “In others, it may point to competition or replacement.”

From Class Project to Ongoing Research

The contrast between industries where AI complements workers and those where it may replace them is something the team plans to investigate further. They hope to build on their framework by distinguishing between different types of impact — automation versus augmentation — and by tracking the emergence of new job categories driven by AI. “This kind of framework is exciting,” said Choi, “because it lets us capture those signals in real time.”

Luceri emphasized the value of hands-on research in the classroom: “It’s important to give students the chance to work on relevant and impactful problems where they can apply the theoretical tools they’ve learned to real-world data and questions,” he said. The paper, Mapping Labor Market Vulnerability in the Age of AI: Evidence from Job Postings and Patent Data, was co-authored by students Qingyu Cao, Qi Guan, Shengzhu Peng, and Po-Yuan Chen, and was presented at the 2025 International AAAI Conference on Web and Social Media (ICWSM), held June 23-26 in Copenhagen, Denmark.

Published on July 7th, 2025

Last updated on July 7th, 2025



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SERAM collaborates on AI-driven clinical decision project

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The Spanish Society of Medical Radiology (SERAM) has collaborated with six other scientific societies to develop an AI-supported urology clinical decision-making project called Uro-Oncogu(IA)s.

Uro-Oncog(IA)s project team.SERAM

The initiative produced an algorithm that will “reduce time and clinical variability” in the management of urological patients, the society said. SERAM’s collaborators include the Spanish Urology Association (AEU), the Foundation for Research in Urology (FIU), the Spanish Society of Pathological Anatomy (SEAP), the Spanish Society of Hospital Pharmacy (SEFH), the Spanish Society of Nuclear Medicine and Molecular Imaging (SEMNIM), and the Spanish Society of Radiation Oncology (SEOR).

SERAM Secretary General Dr. MaríLuz Parra launched the project in Madrid on 3 July with AEU President Dr. Carmen González.

On behalf of SERAM, the following doctors participated in this initiative:

  • Prostate cancer guide: Dr. Joan Carles Vilanova, PhD, of the University of Girona,
  • Upper urinary tract guide: Dr. Richard Mast of University Hospital Vall d’Hebron in Barcelona,
  • Muscle-invasive bladder cancer guide: Dr. Eloy Vivas of the University of Malaga,
  • Non-muscle invasive bladder cancer guide: Dr. Paula Pelechano of the Valencian Institute of Oncology in Valencia,
  • Kidney cancer guide: Dr. Nicolau Molina of the University of Barcelona.



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