Bryan Johnson shared a simple longevity test at a Business Insider event.

Bryan Johnson says he didn’t teach his son enough about sex and wants to change that.

• A Manhattan jury found Live Nation liable for violating antitrust laws.
• The DOJ and nearly 40 states initially sued to split the Ticketmaster parent company two years ago.
• The verdict could pave the way for a breakup of the company.

Ticketmaster parent company Live Nation holds an illegal monopoly over the concert and live event industry, a Manhattan federal jury found on Wednesday.

The entertainment giant was found liable for violating antitrust laws following a roughly six-week civil trial. The jury’s verdict, which came on the fourth day of deliberations, could pave the way for steep monetary penalties — or a court-ordered breakup of the company.

The Department of Justice, plus 39 states and the District of Columbia, sued Live Nation about two years ago to force a split from Ticketmaster, alleging that the company’s market dominance drove up ticket prices for fans of live music, sports events, and theater.

The plaintiffs have argued that Live Nation controls 78% of the large amphitheaters used by artists and, through Ticketmaster, 86% of primary ticketing at major concert venues — meaning the initial sale of tickets.

Days into the trial in March, it emerged that the Justice Department and Live Nation had agreed to a settlement that would allow the company to remain intact. Several states also signed on to the deal, which still needs approval from US District Judge Arun Subramanian.

A senior Justice Department official told reporters last month that the DOJ was “confident” it would have won at trial, but that its goal was to get American concertgoers “relief as fast as possible.”

The remaining 30-plus plaintiff states moved forward with the court fight against Live Nation as attorneys general bashed the settlement terms, saying they favored the company over consumers.

“This is a historic and resounding victory for artists, fans, and the venues that support them,” California Attorney General Rob Bonta said after the verdict was reached. “In the face of dwindling antitrust enforcement by the Trump Administration, this verdict shows just how far states can go to protect our residents from big corporations that are using their power to illegally raise prices and rip-off Americans.”

Live Nation, which merged with Ticketmaster in 2010, has maintained that it does not have a monopoly and that concert ticket prices are relatively low, especially compared to those for sporting events.

Subramanian is set to schedule future proceedings to determine the total amount in damages, final penalties, and restitution for consumers.

The jury on Wednesday found that Live Nation overcharged consumers for tickets sold between May 2020 through 2024, by $1.72 for each ticket, but the judge can order the company to pay additional damages.

• Elon Musk’s AI company xAI plans to allow Cursor to use some of its compute power for training.
• Cursor will train its AI model Composer 2.5 using tens of thousands of xAI GPUs, sources said.
• The arrangement marks a new strategy for xAI in a competitive AI landscape.

Elon Musk’s AI company, xAI, plans to put its stockpile of computing power to use in a new arrangement with coding startup Cursor, according to people familiar with the matter.

Cursor plans to train its latest AI coding model, Composer 2.5, on xAI infrastructure, the people said. Cursor will use tens of thousands of xAI’s graphic processing units (GPUs), the chips used to train AI models, they said.

The setup effectively turns xAI into a kind of cloud provider. By renting some of its GPUs to other companies, xAI could start generating revenue from its massive infrastructure while still developing its own AI models. The arrangement could help the company offset the costs of building and operating data centers, while also deepening ties with a startup that has access to valuable coding data.

Amazon, Microsoft, and Google, the largest cloud providers, own millions of chips and rent computing power out to thousands of companies and developers, generating huge profits. Newer players like CoreWeave and Lambda have built businesses around supplying GPUs to AI model developers. Access to computing power has become an increasingly competitive aspect of the AI arms race.

Representatives for xAI and Cursor did not respond to a request for comment.

It’s not the first time Cursor and xAI have overlapped. The startup hired two former Cursor product engineering leads in March, Andrew Milich and Jason Ginsburg. Ginsburg and Milich oversee xAI’s product team and report directly to Musk and xAI president Michael Nicolls, Business Insider previously reported.

xAI is one of many companies racing to build the best AI models, and it has one of the largest data center footprints. Musk said during an all-hands last December that xAI would beat competitors like OpenAI and Anthropic because it would have access to more power to train its models.

Over the past two years, xAI has rapidly expanded the footprint of its data centers, a project it has named Colossus. Last year, the company said it had around 200,000 Nvidia GPUs, and Musk has said it plans to expand to 1 million GPUs.

xAI’s infrastructure team has been experiencing a leadership shake-up. It lost its infrastructure lead, Heinrich Küttler, last week. The company moved Jake Palmer into a leadership role over the physical infrastructure team, and SpaceX’s Daniel Dueri took a leadership position over the compute infrastructure team last week, Business Insider previously reported.

In a memo to staff last week, Nicolls, xAI’s president, said the company’s model FLOPs Utilization (MFUs), a measure of how efficiently a GPU is used during AI training, was “embarrassingly low” at about 11%. Nicolls said he aims for the team to reach 50% in the next few months. For comparison, according to AI infrastructure company Lambda AI, most large-scale AI training operates between 35% to 45% MFU.

Cursor is in talks for a reported valuation of around $50 billion, Bloomberg reported last month. Meanwhile, it faces pressure as major AI startups like Anthropic and OpenAI push aggressively into building coding assistants.

In March, Cursor released Composer 2, a coding model designed to generate and edit code across large projects. Cursor built the model on top of an open-source AI model from Chinese startup Moonshot AI and fine-tuned it using its own data from its developer user base.

Do you work at xAI or have a tip? Contact this reporter via email at gkay@businessinsider.com or Signal at 248-894-6012. Use a personal email address, a non-work device, and non-work WiFi; here’s our guide to sharing information securely.

• Helping my dad plan for Medicaid showed me I had no estate plan of my own.
• I learned how easily a home and assets can be lost without proper preparation.
• I set up a will and trust to protect my family and avoid future complications.

I sat in a stiff chair next to my 86-year-old dad as a lawyer outlined the complicated rules of Medicaid law.

My dad furrowed his brow, trying to understand the legal complexities that could mean the difference between being able to leave his home — where he’d lived for nearly 60 years — for my sisters and me, rather than having it confiscated as collateral should he die in a long-term care facility.

A few months earlier, my dad — who was recently diagnosed with early-stage dementia — called me with an urgent request. “I want you to make sure they don’t take my house,” he said, obviously coming to terms with the possibility that extended memory care could be in his future.

My dad has no savings to cover long-term care

My dad grew up one of nine kids raised during the lean years of the Great Depression and World War II. He knew the value of owning a home, both monetarily and in the sense of pride he derived from knowing he’d at least leave that small piece of property to my sisters and me after he died.

But like many seniors, he lives on a fixed income and doesn’t have savings to cover the often astronomical expense of long-term care facilities, even with Medicare. Should he need long-term care — a possibility despite his age since he’s in great physical shape and had a mother who lived well into her 90s — the ownership of his home could be in jeopardy.

According to federal and many state laws, Medicaid is required to pursue “estate recovery” after a recipient dies, often placing liens on the decedent’s home or estate to recover care expenses. There are several ways to avoid this, including setting up trusts and a form of property co-ownership called a life estate. Ultimately, our lawyer advised we take advantage of a caretaker clause in Medicaid law, which would apply to my sister, who lives with our dad.

As we went through all these scenarios, while also helping my dad set up his will, healthcare power of attorney (who makes healthcare decisions on his behalf if he’s incapacitated), and durable power of attorney (who can make financial decisions on his behalf), I couldn’t help thinking about my own family.

It made me realize I didn’t have a will

My husband and I did not have a will, any power of attorney, or even beneficiaries on our bank accounts. We’re both cruising toward 50, and we have a young son, so I knew we needed to address our own estate planning.

Our bank offers free estate planning consultations, so I booked an appointment for us to go through the basics before speaking with an attorney who will charge for their services.

Though we’ve been married almost 15 years and faced some health crises, such as my breast cancer diagnosis nearly a decade ago, my husband and I had never discussed what would happen if one or both of us died. While these conversations are hard, we knew they were necessary to ensure our son is cared for physically and financially after we’re gone.

In our case, if one spouse died, the other would automatically inherit any assets and assume sole guardianship of our son. But if both of us were to die at the same time, things get more complicated.

Since we have an underage child, we set up a trust where any of our assets — our home, retirement accounts, etc. — would go to benefit our child once he reaches adulthood. Then we had to choose who would not only take guardianship of our son but also manage our estate, taking care of everything from ensuring our final tax returns were filed to managing the money left to our son.

Talking about death can be hard

Through these conversations, we learned that not having specific, legally verified instructions for your assets — even if it’s just a checking account or a car — can cause bureaucratic headaches for grieving loved ones. And not establishing specific instructions via a healthcare power of attorney — such as whether you want to be resuscitated or put on life support — can put family in the difficult position of making life-or-death choices in the midst of a crisis.

I know that we’ve done all we can to ensure my dad is taken care of for the remainder of his life, and that everything he has worked so hard for will go where he wants it. And I know my husband, son, or sisters won’t have to shoulder the burden of sorting out my affairs when I die.

Talking about my death, as well as the demise of my father and husband, was hard. No one wants to have these difficult conversations. But knowing that we’ve done the unpleasant work to make sure our wishes are respected and our loved ones are protected upon our deaths is well worth the discomfort.

Automotive IoT has moved from a niche capability embedded in premium vehicles to a foundational layer of modern mobility systems. As vehicles become increasingly connected, they generate and consume large volumes of data that influence everything from safety systems to fleet operations and customer experiences. This evolution is reshaping how vehicles are designed, operated, and monetized across the automotive and transportation industries.

For IoT decision makers and technology leaders, understanding Automotive IoT is no longer optional. It sits at the intersection of connectivity, cloud platforms, edge computing, and software-defined architectures. The convergence of these domains is driving a transition toward connected vehicles, advanced telematics, and software-defined mobility ecosystems.

Key Takeaways

• Automotive IoT connects vehicles to cloud, edge, and infrastructure systems, enabling real-time data exchange and control.
• Telematics platforms are central to fleet management, predictive maintenance, and usage-based services.
• Software-defined vehicle architectures decouple hardware and software, enabling continuous feature updates.
• Cellular connectivity, edge computing, and standardized protocols are key enablers of scalable deployments.
• Security, data governance, and system complexity remain major challenges in Automotive IoT ecosystems.

What is Automotive IoT?

Automotive IoT refers to the integration of connected sensors, embedded systems, and communication technologies within vehicles to enable data exchange with external systems such as cloud platforms, infrastructure, and other vehicles. It forms the backbone of connected vehicles, telematics solutions, and software-defined mobility services.

Within the broader IoT ecosystem, Automotive IoT acts as a mobile and distributed data platform. Vehicles are no longer isolated mechanical systems; they are networked endpoints capable of sensing, processing, and transmitting data in real time. This capability supports applications ranging from fleet optimization to advanced driver assistance and over-the-air software updates.

How Automotive IoT works

Automotive IoT systems rely on a layered architecture that combines in-vehicle hardware, connectivity networks, edge processing, and cloud-based platforms. At the core are embedded electronic control units (ECUs) and sensors that collect data related to vehicle performance, location, environment, and driver behavior.

Data generated within the vehicle is transmitted through a telematics control unit (TCU), which acts as a gateway between the vehicle and external networks. The TCU manages communication via cellular technologies such as LTE, LTE-M, NB-IoT, and increasingly 5G. In some cases, short-range communication technologies such as Wi-Fi or Bluetooth are also used for specific use cases.

Once transmitted, data is processed either at the edge or in the cloud. Edge computing capabilities within the vehicle or nearby infrastructure allow for low-latency decision-making, such as collision avoidance or real-time diagnostics. Cloud platforms, on the other hand, handle large-scale data aggregation, analytics, machine learning, and application orchestration.

The rise of software-defined vehicles introduces a new abstraction layer where software components are decoupled from hardware. This enables continuous updates, remote configuration, and the deployment of new services throughout the vehicle lifecycle.

Key technologies and standards

Automotive IoT depends on a combination of communication technologies, software frameworks, and hardware components. Key technologies include:

• Cellular connectivity: LTE, LTE-M, NB-IoT, and 5G provide wide-area communication for connected vehicles.
• Vehicle-to-Everything (V2X): Enables communication between vehicles, infrastructure, pedestrians, and networks.
• CAN, LIN, and Ethernet: In-vehicle communication protocols connecting sensors and control units.
• Telematics platforms: Systems that collect, process, and analyze vehicle data for fleet and operational insights.
• Edge computing: Local data processing to reduce latency and bandwidth usage.
• Over-the-Air (OTA) updates: Mechanisms to remotely update software and firmware.
• Cloud IoT platforms: Infrastructure for data storage, analytics, and application management.

Standards and industry initiatives also play a key role in ensuring interoperability and scalability across Automotive IoT deployments. These include automotive-grade Linux, AUTOSAR frameworks, and emerging standards for V2X communication.

Main IoT use cases

Automotive IoT enables a wide range of applications across multiple industries, extending beyond traditional passenger vehicles.

• Fleet management: Real-time tracking, route optimization, fuel efficiency monitoring, and driver behavior analysis.
• Predictive maintenance: Continuous monitoring of vehicle components to detect failures before they occur.
• Usage-based insurance: Insurance models based on driving behavior and vehicle usage data.
• Smart logistics: Integration with supply chain systems to track goods and optimize delivery operations.
• Connected public transport: Monitoring and optimization of buses, trains, and shared mobility services.
• Autonomous and assisted driving: Data exchange supporting advanced driver assistance systems (ADAS).
• Energy and EV management: Monitoring battery performance, charging infrastructure, and energy consumption.

These use cases demonstrate how Automotive IoT extends into industrial IoT, smart city infrastructure, and energy systems, creating interconnected mobility ecosystems.

Benefits and limitations

Automotive IoT delivers significant operational and strategic benefits. It improves visibility into vehicle performance, enhances safety through real-time monitoring, and enables new business models based on data-driven services.

• Operational efficiency: Optimized routing, reduced downtime, and better resource utilization.
• Enhanced safety: Real-time alerts, remote diagnostics, and driver assistance features.
• New revenue streams: Subscription services, data monetization, and mobility-as-a-service models.
• Lifecycle management: Continuous software updates and remote maintenance capabilities.

However, several constraints and challenges remain:

• Connectivity limitations: Coverage gaps and variable network performance can impact reliability.
• Latency requirements: Critical applications require ultra-low latency that not all networks can guarantee.
• Security risks: Connected vehicles expand the attack surface for cyber threats.
• System complexity: Integration of hardware, software, and networks increases development and maintenance complexity.
• Data governance: Managing ownership, privacy, and compliance across jurisdictions is challenging.

Balancing these benefits and limitations is a key consideration for organizations deploying Automotive IoT solutions at scale.

Market landscape and ecosystem

The Automotive IoT ecosystem is composed of multiple stakeholders, each contributing to different layers of the value chain.

• Automotive OEMs: Integrate connectivity and software capabilities into vehicles.
• Tier 1 suppliers: Provide hardware components such as sensors, ECUs, and telematics units.
• Connectivity providers: Mobile network operators and MVNOs enabling global connectivity.
• Cloud and platform vendors: Offer infrastructure for data processing and application development.
• Software providers: Develop operating systems, middleware, and application frameworks.
• System integrators: Combine technologies into end-to-end solutions for enterprises.

The shift toward software-defined mobility is also changing competitive dynamics. Traditional automotive players are increasingly collaborating with technology companies, while new entrants focus on software platforms and data services.

Future outlook

The evolution of Automotive IoT is closely tied to advances in connectivity, computing, and software architectures. The rollout of 5G and future 6G networks is expected to enable higher data throughput and lower latency, supporting more advanced use cases such as cooperative driving and real-time vehicle coordination.

Software-defined vehicles will continue to gain traction, enabling continuous feature deployment and reducing dependency on hardware upgrades. This shift will likely accelerate the adoption of subscription-based services and new revenue models.

Edge computing will also play a larger role, particularly for applications requiring immediate decision-making. At the same time, increasing regulatory scrutiny around data privacy and cybersecurity will shape how Automotive IoT systems are designed and operated.

Overall, Automotive IoT is moving toward a more integrated and platform-driven model, where vehicles are part of a broader digital ecosystem spanning transportation, energy, and urban infrastructure.

Frequently Asked Questions

What is Automotive IoT?

Automotive IoT refers to the use of connected sensors, communication technologies, and software platforms in vehicles to enable data exchange with external systems such as cloud services and infrastructure.

What is a connected vehicle?

A connected vehicle is a vehicle equipped with internet connectivity and communication systems that allow it to send and receive data in real time.

What is telematics in Automotive IoT?

Telematics is the technology that combines telecommunications and data analytics to monitor vehicle location, performance, and usage.

What is a software-defined vehicle?

A software-defined vehicle is a vehicle where functionality is primarily controlled and updated through software rather than fixed hardware configurations.

What connectivity technologies are used in Automotive IoT?

Automotive IoT commonly uses cellular technologies such as LTE and 5G, as well as short-range communication technologies like Wi-Fi and Bluetooth.

What are the main challenges of Automotive IoT?

Key challenges include connectivity reliability, cybersecurity risks, system complexity, and data privacy management.

Related IoT topics

• Edge Computing for IoT
• 5G and Cellular IoT Connectivity
• Industrial IoT (IIoT)
• IoT Security and Device Authentication
• Digital Twins in IoT
• Smart Cities and Urban IoT Infrastructure

The post Automotive IoT: Connected Vehicles, Telematics and Software-Defined Mobility appeared first on IoT Business News.