The high-speed train now has a new builder onboarded for the project. Photo of the N700 courtesy of © JR Central

The Texas high-speed train that plans to zip between Houston and Dallas still has some obstacles to plow through, but the project now has a builder at least.

Texas Central, the developer of the Texas Bullet Train, has signed a contract with Salini Impregilo, an Italian construction company and one of the largest civil engineering contractors in the world, and its American subsidiary, Lane Construction.

"This agreement brings us one step closer to beginning construction of the civil infrastructure segments of the project," said Texas Central CEO Carlos F. Aguilar, in a release.

The train still can't move forward because it doesn't own all of the land necessary for the route.

But if/when it does get the land, Salini Impregilo will do the following:

  • supply the civil and infrastructure scope, including the design and construction of the viaduct and embankment sections along the entire route
  • install the track system
  • oversee alignment and construction of all buildings and services that will house maintenance and other rail system equipment

Salini-Lane had previously provided front-end engineering and design for the train's civil infrastructure, as well as an analysis of construction costs and schedule estimates.

"Salini-Lane's unmatched track record with rail infrastructure and, very specifically, its world-class high-speed rail expertise across the globe will be central to the completion of America's first end-to-end high-speed rail system," Aguilar says.

Salini's CEO Pietro Salini says in a statement that the company is both thrilled and honored to bring its large-scale railway expertise to the project.

Salini Impregilo is active in more than 50 countries on five continents, with experience building more than 4,000 miles of railway infrastructure around the world. It has built high-speed train projects in Europe and some iconic projects in the world, including the expansion of the Panama Canal.

Although the company has worked in the U.S. since the 1980s, it expanded its presence in 2016 when it merged with The Lane Construction Corporation, a U.S.-based company with almost 130 years of experience in infrastructure work.

The Texas train will be based on Central Japan Railway's Tokaido Shinkansen train system, which is considered the safest mass transportation system in the world.

The system has transported more than 10 billion passengers in 54-plus years, with no fatalities or injuries from operations, and has an impeccable on-time performance record.

It will debut a new train, the Shinkansen N700S, the sixth generation of this train, before the 2020 Olympics.

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This article originally ran on CultureMap.

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Houston college joins inaugural workforce accelerator supported by Google

hands-on training

Houston City College (HCC) is one of 15 community colleges from around the country to be selected for the first-ever Workforce Futures Accelerator.

The three-year effort is supported by Google.org, the tech company’s philanthropic arm, and led by the Association of Community College Trustees (ACCT), a non-profit educational organization that represents over 500 community, junior, and technical colleges. The accelerator focuses on helping colleges embed virtual, employer-sponsored training opportunities into short-term workforce training programs, giving participants access to opportunities that they might otherwise receive through internships or other "work-based learning" stints.

"The Workforce Futures Accelerator reflects the Houston City College mission of offering a high-quality, affordable education for workforce training and career development," Pretta VanDible Stallworth, HCC trustee and chair-elect of the ACCT board of directors, said in a news release. "Advancing student success and creating pathways to opportunities ensures that our students are well equipped to succeed and build a secure future in today's economy.”

Through the accelerator, HCC is tasked with fusing online project-based learning opportunities with its workforce education programs. The idea is to give students hands-on experiences working on projects sponsored by employers, allowing them to gain real-world knowledge in the process.

HCC will select two workforce programs that meet the accelerator’s criteria and insert into them into coursework. In the second and third year of the accelerator, the selected colleges are expected to scale the programs by adding instructors and programs to develop a network of to support their continued implementation.

“Participation by HCC will strengthen how we provide students with career-connected learning experiences that complement their classroom education and align with the needs of employers,” HCC Chancellor Margaret Ford Fisher added in the news release. “We are focused on ‘future forward’ strategies to meet the present and future needs of our region’s businesses.”

Two other Texas colleges were chosen to participate in the accelerator: Lamar Institute of Technology in Beaumont and Grayson College in Denison.

The remaining cohort includes:

  • Bergen Community College in Paramus, New Jersey
  • Central Louisiana Community College in Alexandria, Louisiana
  • Clark State College in Springfield, Ohio
  • Great Basin College in Elko, Nevada
  • Heartland Community College in Normal, Illinois
  • Hudson County Community College in Jersey City, New Jersey
  • Manchester Community College in Manchester, New Hampshire
  • Mesa Community College in Mesa, Arizona
  • Mohave College in Kingman, Arizona
  • San Joaquin Delta Community College in Stockton, California
  • San Juan College in Farmington, New Mexico
  • West Virginia University Parkersburg in Parkersburg, West Virginia

New report ranks Texas among top 10 states where AI could disrupt jobs

AI Workforce

A new nationwide report examining where AI could "reshape" the most jobs has ranked Texas No. 9 among the most at-risk states for AI job disruption.

The new SmartAsset report compared all 50 states and the District of Columbia to calculate the estimated percent of the workforce employed in the 26 occupations with the highest AI exposure, as determined by June 2026 research by the Virginia Economic Information and Analytics Division.

The findings revealed that 500,000 Texas workers, or 3.55 percent of the total workforce, are employed in occupations with "high exposure to potential AI disruption."

This also places the Lone Star State as the 9th most at-risk state in the U.S. where AI exposure can lead to "declining hiring demand, wage pressure, task automation, and other forms of disruption."

"States with larger concentrations of highly exposed occupations could experience more pronounced labor-market changes, particularly in roles where core tasks are more vulnerable to AI-driven restructuring," the report's author wrote.

Texas' biggest cities, like Houston and Austin, are known for their thriving tech and business industries, and the study noted that many of the occupations within those sectors are the most at risk. The Virginia Economic Information and Analytics Division said the top five most AI-exposed occupations in the U.S. are: mathematicians, proofreaders, correspondence clerks, court reporters, and media and communication workers. Additionally, computer programmers, database administrators, web developers, telephone operators, and communications equipment operators round out the top 10 most at-risk positions.

These are the 16 remaining occupations most exposed to AI disruption, in order:

  • Data Entry Keyers
  • Statistical Assistants
  • Office Support Workers
  • Interpreters and Translators
  • Database Architects
  • Software Quality Assurance Analysts
  • Medical Transcriptionists
  • Software Developers
  • Writers and Authors
  • Payroll Clerks
  • Web Designers
  • Miscellaneous Computer Occupations
  • Insurance Claims Processors
  • Telemarketers
  • Computer Numerically Controlled Tool Programmers
  • Bookkeeping and Accounting Clerks

A separate SmartAsset report from April 2026 found about 20.5 percent of Texas workers use AI to do their jobs in some capacity. That trend will continue to shift further as employers and employees choose to adopt — or reject — AI implementation.

Across the U.S., Washington topped the list as the state with the highest concentration of AI-exposed jobs, with nearly 5.7 percent of the state's workforce employed in the 26 most at-risk positions. SmartAsset said Washington's high prevalence of technology companies is a significant factor that skyrocketed the state to the top of the list.

"Home to major technology companies including Microsoft, Amazon, T-Mobile and Expedia, the state has large numbers of computer programmers and software developers, two occupations with high exposure," the report said.

Meanwhile, Mississippi ranked No. 51 with the lowest concentration of AI-exposed jobs in the nation. About 22,500 workers in Mississippi, or 1.93 percent of its workforce, are at risk for AI disruption.

The top 10 states where AI could reshape the most jobs are:

  • No. 1 – Washington
  • No. 2 – Virginia
  • No. 3 – District of Columbia
  • No. 4 – California
  • No. 5 – Utah
  • No. 6 – Maryland
  • No. 7 – Colorado
  • No. 8 – New Hampshire
  • No. 9 – Texas
  • No. 10 – North Carolina
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This article originally appeared on CultureMap.com.

UH lands $1.2M NIH grant to fight superbugs using AI, quantum sensing

drug defense

The fight against antibiotic-resistant bacteria like MRSA is getting science fiction-like upgrades at the University of Houston thanks to a new four-year, $1.26 million grant from the National Institutes of Health.

The university says the recent funding brings total federal support up to $3.5 million for 11 years for the project, which uses AI and quantum-sensing technology to better understand how bacterial proteins develop resistance to drugs.

Any medical professional will tell you that one of the worst things that can happen is almost killing an infection. Bacteria that survive attacks from conventional antibiotic treatments emerge tougher, more resistant and more aggressive than before–making them much harder to treat. A good example is the superbug methicillin-resistant Staphylococcus aureus (MRSA).

UH chemistry professors Yuhong Wang and Shoujun Xu are working on this issue. They know full well that fighting superbugs requires new technology and new approaches, which is what they aim to pioneer with their new grant.

“Drug-resistant bacterial infections such as MRSA are becoming harder to treat, creating an urgent need for faster ways to understand how antibiotics and other small molecules interact with bacterial proteins,” Wang said in a news release.

Wang and Xu’s work centers around GTP, a cellular fuel that can cause tiny changes to a cell's structure when it mutates. Sometimes, those shape changes make it easier for drugs to breach the wall and attack the cells.

The UH scientists are employing AlphaFold, an AI-powered tool that can scan large molecular libraries in seconds. From these models, they can see promising drug combinations for future testing.

Once identified, the team uses their invention, super-resolution force spectroscopy, to monitor the cells. Tiny magnetic beads are attached to genetic material, then magnified to see how strong that material is when pulled. They can measure this incredible microscopic process through an atomic magnetometer, typically used in quantum physics. Combined, all these tools allow a high-definition look at how each molecule might respond to new chemical approaches.

“We're the only chemists in the world that use an atomic magnetometer for biological research,” Xu said. “It's a technique developed by physicists, and there is usually a gap between techniques developed by physicists and biological applications. Yuhong and I have been bridging that gap together for the past 10 years.”

Eventually, Wang and Xu hope to develop powerful software that can be used by drug manufacturers to model cellular responses. With enough predictive data, the software could even get ahead of superbugs’ own mutation, allowing drugs to be developed before new strains arrive.

"We want an algorithm where you input a protein sequence, score the mutation hotspots, and develop new inhibitors before a drug-resistant species even emerges," Wang added.