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• Comcast’s Universal unit says it will go ahead with plans to release “Musk” in theaters outside the US.
• An earlier report suggested that Universal was having second thoughts about its plan because of Musk’s connections with Donald Trump.
• Distributor Bleecker Street will show the movie in US theaters October 9; Universal hasn’t announced a date for an international rollout.

Comcast’s Universal is going ahead with plans to show a new Elon Musk documentary in theaters outside the US, the company says.

The reason that’s news is that a recent story from The Hollywood Reporter said that Universal was having second thoughts about releasing “Musk,” which is highly critical of the mogul. The story suggests that Universal was worried about blowback because it was “politically sensitive for parts of the Trump administration.”

That’s not true, says Universal rep Evan Langweiler. “The studio remains committed to releasing it in theaters internationally. We’re currently working through a release strategy,” he told me Thursday afternoon.

Universal acquired the rights to distribute the documentary, created by acclaimed filmmaker Alex Gibney, back in 2003. I’ve asked Gibney’s Jigsaw Productions company for comment.

My colleague Jason Guerrasio, after watching the nearly four-hour film, says it portrays Musk in an unflattering light, which isn’t surprising: Gibney has previously made highly critical films about tech figures, including Steve Jobs and Elizabeth Holmes.

Musk, who didn’t cooperate with Gibney during the movie’s production, has been complaining about it for some time. The movie does feature an AI-generated version of Musk’s avatar, “who’s been trained on all available interviews the mogul has given,” Guerrasio says.

US audiences will be able to see the movie in theaters starting October 9, via distributor Bleecker Street. Universal hasn’t announced release dates or any other information about its international rollout.

Comcast has been criticized by Trump for years and is being investigated by Trump’s Federal Communications Commission because of suspicions it is “still engaging in the promotion of DEI.” A story suggesting it was making a concession to Trump registers in part because we’ve seen several media companies offer concessions to Trump in his second term.

It also echoes complaints from the filmmakers behind “The Apprentice,” a scathing Trump biopic in 2024, who argued that Hollywood and tech companies wouldn’t release the movie out of fear of angering Trump or his allies. The movie was subsequently nominated for two Oscar awards, and you can now stream the movie via Amazon’s Prime Video service and rent it via several other outlets, including Apple and YouTube.

• I lost my dad days after Hurricane Sandy destroyed our family home.
• His death pushed me to leave a music career that was burning me out.
• I built a travel-writing career around our shared love of Disney, food, and travel.

In 2012, I was working in a career that many would consider a dream. I was a publicist in the Country music industry. As a lifelong lover of music and a classically trained pianist at New York University, it was thrilling.

Every day was exciting, whether I was working a red carpet in Las Vegas or escorting music legends, like Dolly Parton and Carol Channing, to a media interview. I had the opportunity to travel all over the country, including touring with some incredible artists.

But behind the scenes, I could feel the burnout rising.

My dad died unexpectedly

That same year, the unthinkable happened: My family’s home on the Jersey Shore was destroyed in Hurricane Sandy, and days later, my Dad would pass away from a heart attack in the aftermath. There are moments where your life is split into the before and after — and this was that. My mother, sister, and I were left to pick up the pieces. The rebuild process for our home and the town my family has resided in for decades was a long one.

Inspired by my dad and our shared interest in travel and theme parks, I began exploring how I could follow my passions and turn them into a career. I’ve since completely left the music industry and have created a career as a full-time travel journalist and author, with my first book debuting this year.

My Dad had always been my biggest inspiration

My family has always been close. And it was my dad who instilled in me a love of all things travel, writing, food, and Disney parks. It wasn’t just Walt Disney World — which we’d visit several times a year — but all theme parks, including another favorite, Hersheypark. My family vacations to theme parks are among my happiest memories, and I continue to visit them today with my now-husband, recreating many of those moments.

My dad embraced that “you only live once” attitude I strived for, and he didn’t care what others thought of him. And after he passed, something changed inside me. I was feeling burned out by the music industry and its constant behind-the-scenes struggles and politics. I knew a change was needed.

The healing process was a long one, and admittedly, not easy. It would be nearly a year before our family home and business were rebuilt. Our community came together amid the devastation in a way I could have never imagined. Even the Country music community rallied behind my family, supporting us in the rebuilding process. And while things will forever be different, the experience was transformative.

And during that time, I began to consider how I could change my career trajectory and reinvent myself.

I began writing about theme parks and travel

I have always loved writing, since I was a child obsessed with R.L. Stine’s “Goosebumps” and as an active member of Young Authors in my elementary school. And writing was my favorite part of working in the music industry, whether it was a press release or an artist biography for websites. I loved the creative process.

Maybe this was a way to cope with his death, but I sought out career opportunities that combined my two greatest passions: travel writing and theme parks. It may have been a way of keeping his memory alive, getting to write about the many places and things our family had done together.

Journalism is a tough industry with nothing promised, and I had zero clue whether this risk would work. I went after it with every fiber of my being, giving it my all. Thankfully, I had the full support of my husband and my family throughout all of this.

I think my Dad would be proud to see me now

My music career is long in the rearview mirror, as I’ve enjoyed a wonderful career traveling and writing, and, most importantly, living life to the fullest as I knew my dad wanted me to. I’ve had some amazing opportunities that I wish he could see, like sailing on a cruise to Alaska (cruising was one of his absolute favorites) and going on safari in South Africa.

My greatest accomplishment to date is getting to write my debut book, which is all about Disney and food, my dad and I’s greatest shared interests. While it does sting that he won’t be there to see it and experience this high moment of my life and career, I did dedicate it to his memory. My mom, sister, and I are closer than ever and continue to take several annual family trips to Disney parks.

I’m now 40, and what this taught me is that it’s never too late to reinvent yourself and go after what you want. Also, it’s OK to completely change paths at any age.

• Rep. James Comer introduced a bill that would allow sexual abuse victims to break NDAs.
• The House Oversight Committee, which he chairs, is investigating Jeffrey Epstein and his associates.
• The committee voted to hold Leon Black in contempt after he refused to turn over all his NDAs.

The chair of a congressional committee trying to pry non-disclosure agreements from billionaire Leon Black for its Jeffrey Epstein investigation proposed a bill on Wednesday that would allow victims of sexual abuse to break NDAs.

Rep. James Comer announced the bill a day after the House Oversight Committee unanimously voted for a resolution to hold Black, the Epstein associate and former CEO of Apollo Global Management, in contempt of Congress for refusing to comply with a subpoena requiring him to hand over all of his NDAs, and any in his possession that reference Epstein or Ghislaine Maxwell.

“During our investigation, we’ve learned how powerful men weaponized nondisclosure agreements to silence survivors of sexual abuse,” Comer, a Kentucky Republican, said in a statement Wednesday. The proposed bill would ensure that sexual-abuse survivors and other people with information about such abuse could speak freely about it, he said.

Business Insider reported earlier this year that some of Epstein’s accusers have signed confidential settlements with friends of Epstein whom they have also accused of misconduct, according to three people with direct knowledge of such settlements. The settlements include NDAs, the people said. One person told Business Insider they had direct knowledge of settlements with four of Epstein’s friends who were accused of sexual misconduct by more than 20 women between them.

The House Oversight Committee in June issued two subpoenas to Black when he refused to answer questions about NDAs in a closed-door interview about his interactions with Epstein. Black, who gave over $150 million to Epstein for what he said were financial services, walked out of that voluntary interview.

This month, Black sued the committee rather than comply with the subpoenas. One subpoena demanded NDAs; the other required him to testify under oath in a deposition.

Epstein died in 2019 while awaiting trial for federal sex-trafficking charges. Maxwell was sentenced to 20 years in prison after a Manhattan jury found her guilty in 2021 of trafficking girls to Epstein for sex.

Black has said he wasn’t aware of Epstein’s sexual abuse of women. His lawsuit says the committee didn’t have a “valid legislative purpose” for “such a sweeping and intrusive subpoena served upon a private citizen.”

If passed into law, the proposed bill, called the Survivor’s Voice Protection Act, would void nondisclosure clauses if they prohibit victims of sexual abuse from disclosing those experiences, or if they bar any other person from disclosing facts related to such abuse. The law would also create a fiduciary duty to inform law enforcement about suspected sexual grooming of minors.

Democrats on the House Oversight Committee have not yet said whether they would support the law.

The House of Representatives hasn’t scheduled a vote on whether to hold Black in contempt of Congress. Black’s lawyers called the Oversight committee’s resolution “a complete abomination.”

“This is retaliation — plain and simple,” attorneys Susan Estrich and Aaron Cutler said in a statement. They said the subpoenas were “illegitimate, illegal, and a textbook abuse of power designed to bully and destroy legal protections of private citizens.”

People with non-disclosure agreements can be legally compelled to speak about their experiences with a subpoena, but not in a voluntary interview with Congress. Some of Epstein’s other associates, including Bill Gates, said in voluntary interviews that they didn’t sign any non-disclosure agreements with Epstein or Maxwell victims.

Many states banned NDAs related to sexual abuse during the #MeToo movement following reporting about Harvey Weinstein, but no such ban exists on a federal level.

• The iOS 27 update rolled out to iPhones starting on Monday. The biggest change is Siri AI.
• Siri AI has a waitlist. iPhone users are reporting wait times ranging from four hours to two days.
• A colleague got the full update. His review: It’s a huge improvement, featuring a wonky voice.

Apple released iOS 27 on Monday. Many iPhone users will have to wait a little longer for its most anticipated feature.

Siri AI, Apple’s ambitious overhaul of its virtual assistant, does not automatically arrive with the software update. Eligible users must join a waitlist before they can try it.

Once enabled, Siri AI is supposed to do much more for iPhone users. Apple says it can pull together information from across apps and act on it — for instance, finding a hotel confirmation in a screenshot or suggesting a restaurant after scanning a group chat for different dietary preferences.

To get the AI-powered virtual assistant, users need to update their device to iOS 27, open Settings, tap Siri, and select Try Siri AI (Beta). They will then choose a voice, complete voice enrollment, review privacy settings, and join the queue.

Apple says the wait time varies — and online, and in conversations with Business Insider, customers are reporting wait times between four and 48 hours. Once a user is approved, Siri AI downloads automatically.

Not every iPhone can run the AI-powered Siri. While iOS 27 works on iPhones going back to the iPhone 11, Siri AI requires an iPhone 15 Pro or 15 Pro Max, an iPhone 16 model or later. It is also unavailable on iPhones in the European Union and mainland China.

A Business Insider colleague who joined the waitlist on Monday received access on Wednesday morning. He said Siri AI has been useful for finding information across his apps, though its voice still sounds “very robotic.”

Apple did not immediately respond to a request for comment.

• Safran partners with Loopr AI to enhance defect detection in aviation manufacturing processes.
• Loopr AI uses synthetic data to improve inspection accuracy and efficiency for Safran’s parts.
• Safran’s new AI system reduces inspection time and costly defect recalls.

When parts inspectors at the aviation manufacturer Safran received a toilet lid that the company just manufactured, they used to spend 20 to 30 minutes examining it.

On airplanes, lavatories need to be perfect, so the inspectors search for consistent colors and smooth surfaces free of paint bubbles and scratches, among other defects.

Some inspection professionals have been performing these quality-assurance roles at Safran for more than 10 years and can detect up to 90% of the production defects in cabin galleys, passenger seats, and other parts, said Bindioa Ouali, the senior director and head of digital production, robotics, and automation at Safran.

Still, fatigue can set in after hours of inspections, causing detection rates to vary. AI can help streamline these intensive quality assurance processes — but only if companies have enough data to train the technology, said Zheng Yao, a principal research scientist at Lehigh University’s Energy Research Center, in an interview with Business Insider. When there’s not enough, they can use synthetic data, or artificial information that mimics real data points, he said.

Enter software companies like Loopr AI, Spectron, and Akridata that are creating synthetic data from computer-generated images, 3D models, and other simulation tools to address data scarcity and help prevent the costly scrapping and reworking of faulty parts.

Solving for data scarcity

Safran began pilot projects two years ago with Loopr AI to see whether artificial intelligence could improve defect identification while reducing inspection and documentation time, Ouali said.

In situations like Safran’s, where the company produces a wide variety of parts but not a high volume of each, “it’s extremely hard to have thousands of data sets very early on,” Priyansha Bagaria, Loopr’s founder and CEO, told Business Insider.

In cases like this, Loopr synthetically generates data by creating new training samples from existing images, altering them to increase the number of samples from which algorithms can learn. This allows Safran to simulate various production scenarios while still using real-world data to validate the results, said Bagaria.

The analysis software works well at detecting cosmetic defects in cabin assemblies, comparing them against the production drawings and the listed parts to use, Bagaria said. She added, “AI is really good at removing the subjectivity and retaining the knowledge of your operators. You can automate the repetitive tasks and standardize your processes.”

With paint analysis, for example, AI learns the visual characteristics of the defect, as well as the specific part on which it could appear, like a table or a toilet seat, Bagaria said. The model also uses data from each specific manufacturing component and from lighting conditions that mimic those in the areas where the parts will ultimately be installed.

With Safran’s toilet seats, inspection now takes five to 10 minutes and includes an automatically created defect and inspection sheet before the parts move to the next stage, Ouali said. This documentation was previously created by the inspector.

Additionally, Loopr’s technology achieved a 90.9% recall — the ability to identify all defects, such as scratches, paint discoloration, and paint bubbles — on the project, Ouali said.

One AI software program, two inspection methods

Depending on the setup, the Loopr AI inspection process can use a more automated or hybrid approach.

For Safran’s paint inspection program, the company already had visualization hardware in place, said Bagaria. The program was automated in that the image capture and AI analysis were automated, but the platform allows a human to review, confirm, or correct the AI’s findings, she said. This feedback also helps improve the model over time.

Loopr is hardware-agnostic and can run on various camera and tablet types a company already uses. For this project, a robotic arm photographed parts prior to and after paint application, then provided them to Loopr for analysis.

With a hybrid approach, like for a cabin assembly that includes a lavatory or galley, the inspectors manually take photos at different angles and upload them to Safran’s computer system. The Loopr algorithm accesses the photos and identifies potential issues, creating a defect and inspection sheet.

With a faster inspection process, “we’re able to produce 10% to 15% more than before. The throughput increased to send parts to the final assembly,” Ouali said.

Bagaria said that with successful pilots completed, Safran is now introducing Loopr’s technology to its Marysville, Washington, and Santa Maria, California facilities.

Modern businesses rely on data systems to guide decisions, serve customers, manage operations, and meet compliance obligations. In connected environments, that increasingly includes data generated by IoT devices, sensors, gateways, applications, partners, and customer touchpoints. Yet even well-designed systems can become fragile when data quality is inconsistent, outdated, duplicated, or incomplete. As organizations collect information from more applications, devices, partners, and customer touchpoints, manual checks are no longer enough to keep data accurate and usable.

A good start to building resilience is working out whether the data entering a system can be trusted. In an IoT environment, this may involve checking device identifiers, timestamps, sensor readings, or telemetry values before they are used by downstream systems. The same principle also applies to associated business and customer data. For example, identifying disconnected phone numbers can help sales, support, and compliance teams avoid wasted outreach and incorrect customer records. Automated validation turns these checks into repeatable processes that run at scale, reducing human error and improving confidence across the business.

Why Data Resilience Matters

A resilient data system keeps performing reliably even when conditions change. That might mean handling sudden spikes in device telemetry, integrating a new software platform or IoT fleet, adapting to regulatory requirements, or recovering quickly from inaccurate inputs. Data resilience is not only about uptime; it is also about maintaining quality, consistency, and usefulness.

Poor data quality can create serious business problems. Marketing teams may target the wrong audiences, finance teams may produce inaccurate forecasts, and operations teams may make decisions based on outdated information. In IoT deployments, inaccurate or incomplete device data can also affect monitoring, maintenance, automation, and operational decisions. Over time, these issues can reduce productivity, increase costs, and damage customer trust. Automated validation helps prevent small data problems from becoming larger system failures.

What Automated Validation Does

Automated validation uses rules, workflows, and sometimes machine learning to check data before, during, and after it moves through business systems. These checks can confirm whether required fields are complete, formats are correct, values fall within expected ranges, and records match known sources of truth.

For example, an IoT system can automatically verify that a device identifier is valid, a sensor reading falls within an expected range, a timestamp is correctly formatted, or a telemetry record is not duplicated. In other business systems, validation may confirm that an email address follows a valid format, a ZIP code matches a state, or a transaction amount is within an approved range. These validations can occur in real time when data is entered or in scheduled batches for existing databases.

By automating these processes, businesses reduce reliance on employees to manually review spreadsheets or correct records after errors have already caused problems. Automation also creates consistency because it applies the same rules every time.

Building Validation Into IoT Data Pipelines

One of the most effective ways to improve resilience is to embed validation directly into data pipelines. In an IoT architecture, this can mean validating data as it moves from connected devices and gateways through ingestion platforms, transformation layers, storage systems, and analytics tools. Instead of treating quality checks as a final step, organizations should validate data at each stage: collection, transformation, storage, and reporting.

At collection, systems can reject incomplete or incorrectly formatted entries and flag unexpected device data. During transformation, validation can confirm that data has been mapped and converted properly. Before storage, systems can check for duplicates or conflicts with existing records. Before reporting, automated checks can flag suspicious trends or missing data.

This layered approach reduces the chance that bad data will spread across multiple tools. It also makes it easier to identify where a problem originated, allowing teams to fix root causes rather than repeatedly correcting symptoms.

Using Rules and Monitoring Together

Validation rules are powerful, but they should be paired with continuous monitoring. Rules identify whether data meets known expectations, while monitoring and analytics pick up unusual patterns that may indicate new or unexpected problems.

For instance, if a connected device fleet typically generates 10,000 telemetry records per day and suddenly produces only 500, monitoring can alert the data team. If the percentage of failed validations rises sharply, that may signal a broken integration, a connectivity issue, a vendor problem, or a change in source data formatting.

Dashboards and automated alerts give teams visibility into data health. Instead of discovering problems days or weeks later, employees can respond quickly and minimize business disruption.

Improving Governance and Accountability

Automated validation also supports stronger data governance. When teams document and enforce validation rules, everyone understands what good data looks like. This helps teams align on standards for accuracy, completeness, security, and compliance.

Clear ownership is important. Businesses should assign responsibility for maintaining validation rules, reviewing exceptions, and approving changes. Data stewards, IT teams, IoT operations teams, compliance officers, and business leaders may all play a role. The goal is to make data quality a shared responsibility rather than an isolated technical task.

Audit trails are another benefit. Automated systems can record when data failed validation, what rule was triggered, and how the issue was resolved. This documentation is valuable for internal reviews, regulatory audits, and long-term process improvement.

Preparing for Scale and Change

As businesses grow, data systems must handle more volume, complexity, and variety. IoT deployments can amplify this challenge as organizations connect additional devices, gateways, locations, and data sources. Automated validation makes scaling safer because it applies quality controls without requiring proportional increases in manual labor. Whether a company adds new customer channels, expands into new markets, connects new device fleets, or adopts new analytics tools, validation helps to make sure that data remains dependable.

Organizations should review validation rules regularly. Business requirements change, regulations evolve, and new data sources introduce new risks. A resilient system is not static; it adapts while maintaining strong controls.

Conclusion

Automated validation is essential for building resilient data systems, particularly as connected devices create larger and more distributed flows of operational data. It improves accuracy, reduces manual work, strengthens governance, and helps teams respond quickly to problems. By embedding validation throughout IoT and enterprise data pipelines and combining it with monitoring and accountability, businesses can create systems that are more reliable, scalable, and ready for change.

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