Somehow, it didnt leak.
When I caught up with Rivian founder and CEO RJ Scaringe after the companys AI & Autonomy Day keynote on December 11 at its Palo Alto headquarters, he marveled that the company had managed to keep the events news under wraps until it was ready for its big reveal.
It didand there was a lot to discuss. At the keynote, Rivian unveiled its Gen 3 platform, which will turn the maker of EV trucks, SUVs, and vans into an autonomy company, a focus he says will subsume the whole business of transportation.
Debuting late next year in a version of the upcoming R2 SUV, the Rivian Autonomy Computer platform is powered by a chip the company designed itself, the RAP1 (Rivian Autonomy Processor). The R2s self-driving features will also draw on data from a lidar unit that sits inconspicuously at the top of the windshielda far cry from the spinning lidar towers atop vehicles such as Waymos. (Controversially, Teslas cars dont use lidar sensors.)
Rivian also showed off a new voice-controlled user interface called the Rivian Assistant that will be available as an update for its current vehicles as well as for the R3. A bet on the future of car interfaces shifting toward talking rather than tapping on screens, it features integration with Google Calendarhinting at the kind of productivity-related features that might become more useful as cars take over more of the work of driving themselves.
I spoke with Scaringe about all these topics and more. Our conversation has been edited for length and clarity.
At least in broad strokes, how much of what you announced today was part of the original Rivian vision and road map?
Well, that was 20 years ago. But something like today is the result of many thousands of people working on it for the last few years. Development on the platforms we showed today started in 2022.
One of the threads connecting a lot of your news is you doing stuff yourself rather than being dependent on other parties. Was there a period where you werent sure which way to go?
Maybe the way to answer that is that when we launched in 2021, we had what we call our Gen 1 architecture. And it was a very different approach than what went into our Gen 2 and, of course, what’s going into our Gen 3.
We had a perception platformsome of which was our own, much of which was not our ownthat fed into a planner, which was our own, and made a set of rules-based decisions around how to drive the vehicle. It was very basic driver assistance: low level two features. And by virtue of that being the architecture, we had a natural limit. We realized that as we approached the launchthat the world was going to shift away from these more deterministic and classical systems to a true AI-based system.
Its sort of ironic. When we say self-driving, we might think historically it’s always been AI. But in the beginning, actually, there was no AI. Some of it was very sophisticated if-then statements with good machine vision.
What its shifted to now is true AI, and that happened in the early 2020s. As that was happening, we came to the view that we needed to completely shift our approach. And when we made that decision in early 2022, we approached it as a clean sheet.
With that clean-sheet approach, it was, Let’s design our own perception platform. Let’s design our own compute platform with Gen 2, leveraging Nvidia as a supplier of the chips themselves, the inference platforms themselves, and go build a data flywheel that will allow us to build a neural net-based approach. The vehicles ultimately launched in the middle of 2024, a little less than a year and a half ago.
And then, in parallel to that, we also kicked off some big hardware efforts, the biggest of which is an in-house chip. To go from zerono chip design team, no chip in-house, no chip IPto launching a chip takes time, it takes many hundreds of millions of dollars, it takes a very, very large organization. But we made the decision in 22 and we’ve been working towards it. Somehow, it didnt leak. But it’s now nice that we can talk about it publicly and it’s going to be in the vehicles next year.
An AI-centric approach required this vertical integration of perception. It doesn’t necessitate owning compute, but owning compute allows you to deliver it at a lower cost level and, in our case, a higher performance level.
We just have such a conviction that [autonomy] isnt just a part of the auto industry. If you look out a little bit, this is the whole business. And so we built this view that where we deploy most of our R&D should be this category.
Was it completely obvious you needed lidar?
There’s a thinking around lidar that needs to be shed, which is that they’re expensive and mechanically complex. The old Velodyne lidars, even what you see on the roads today, they were really complex sensors. But they’re now very low cost, extremely reliable, and solid-state based.
Ten years ago, the best-performing lidar you could buy was maybe $70,000. Five years ago, it was maybe $5,000. Today it’s in the low hundreds of dollars. And so it’s become so cost-effective at turning the entire fleet into a ground truth fleet. It’s really helpful for training your cameras, especially in adverse conditions.
When you peel back the onion and you look at the cost trajectory of the sensor, it’s become this sort of strange debate, because Tesla’s taken such a stance on it. But it wasn’t really a debate. If it was a $10,000 sensor, it would’ve been a different story. But when it’s a few-hundred-dollars decision, it’s much easier to make.
Your new assistants Google Calendar integration made me realize that if I don’t have to spend quite as much time thinking about driving, there’s a lot of opportunity to be productive in the car. To what degree are you trying to build a richly powerful assistant?
Google Calendar is just one of what will become many instances of integrations. Today there’s a limited set that have been set up to go agent-to-agent. But any platform that’s going to truly survive, and not just get gobbled up by an AI platform, will need to become very, very capable in terms of enabling agent-to-agent. Effectively like SDKs [software development kits] that just make it very easy to plug in. The goal is that essentially any app that you might want to use, we’ll be able to plug into our agents and it’ll be seamless.
So you can reach across apps like you saw today. You talked to the car, the car was able to reach into Google and find the calendar. We were able to tell it to move something, and it reached back to Google through an agent and moved eveything around. It’s the tip of the iceberg.
All these things will start to become so natural where the car becomes like a personal assistant. If you want to move your schedule or order food or schedule someone to come to your house to fix the plumbing, all this stuff just becomes very, very easy to do. And if you are no longer driving the car, you may want to be able to use the car to help you with more of these things.
Do you have any sense as to what the future looks like in terms of robotaxis and autonomous private vehicles coexisting?
I definitely think they’ll coexist. Theyre anything but mutually exclusive. The existence of level four [autonomy] is what enables both of them, and the technology from a level four point of view is the same. We’re focused on the tech, and the initial instance planned is a personally owned vehicle. But it doesn’t preclude us from doing robotaxis or rideshare.
Rideshare today is such a small percentage of miles. I used to be of the view that we’d go from 99% of the world’s miles being in personally owned vehicles to 50% being in personally owned ones and the other half of the world’s miles being in shared. Maybe that happens, but I think it’s probably more likely to go from 99% to 90%. Maybe that’s because I have kids now, and the complexities of car seats and soccer balls and soccer outfits.
I think it will be different country to country. When you look at the wealth level in the United States, if you can afford a car today, a lot of people would still rather own one and have the simplicity of it always being available for them and their family. But I actually don’t need to have a strong conviction on this either way. If theres a heavy shift in the model of consumption, we’re equally ready for that.
Im surprised how much attention the business model gets. If one end of the spectrum is traditional ownership as we know it today, and the other end of the spectrum is pay as you go, we’re not being very imaginative. There are going to be a lot of things in the middle. Maybe I own the vehicle during the daytime and somebody else uses the vehicle at night. Maybe the vehicle’s mine during the week and another family’s during the weekend. Maybe the vehicle’s shared among five or six people as opposed to infinitely shared.
There’s just going to be a spectrum of new ways to consume mobility, the moment the vehicle can drive itself. And our view is we’re going to exist across that entire spectrum. But the only thing that’s absolutely certain that’s necessary for any point on that spectrum is level four. Robotaxis dont work with level three. Personal level four obviously doesn’t work with level three. You need level four. So that’s what we’re focused on.
At the Exceptional Women Alliance (EWA), we bring together accomplished women who mentor, support, and challenge one another to grow as leaders, women, and as human beings. Each month we highlight one of these extraordinary voices and the insights that define her approach to leadership and life.
This month I spoke with Mindy Mackenzie, former interim CEO of Beautycounter, longtime advisor to portfolio companies at The Carlyle Group, and Wall Street Journal bestselling author of The Courage Solution: The Power of Truth Telling with Your Boss, Peers, and Team.
Mindys leadership philosophy challenges the belief that progress requires constant motion. She believes the most important work begins in stillness, in the willingness to pause, listen, and lead from purpose and authenticity rather than pressure.
Q: You say sitting still can feel like agony, and you highly recommend it. Why?
Mindy Mackenzie: Most of us are addicted to motion. We fill every moment because slowing down forces us to face what is really happening inside. Sitting still, truly being with yourself, can feel unbearable at first. It is uncomfortable, but it is also where truth lives.
If you can sit quietly, even for a few minutes, you will start to hear what is real instead of what you are performing. That is the beginning of clarity.
Q: Why is this so hard for successful women leaders?
Mackenzie: Because we have been conditioned to equate busyness with value. High-performing women often measure their worth by what they accomplish. The problem is that when you stop, you have to confront the question underneath it all: Who am I when I am not producing?
I think a key concept is understanding who you are outside of your role. Many leaders do not know that answer, and that lack of separation between identity and achievement is what makes stillness so uncomfortable.
Q: How can leaders start practicing stillness in a real way?
Mackenzie: You do not need to go to a monastery or sit in 17 yoga retreats. It does not take five hours a day. Sit in your closet for five minutes. Set a timer. Just get in touch with yourself and allow whatever comes up.
When I work with executives, I remind them that they are human choosers. Every day you have the choice to lead from pressure or from presence. I ask one question: What do you choose right now?
It sounds simple, but it changes everything.
Q: You draw a connection between leadership and parenting. How do the two overlap?
Mackenzie: Parenting teaches humility, patience, and listening before responding. Those skills are exactly what leadership requires.
At home, I often ask my family, on a scale of one to 10, how are you feeling about this? I use the same approach in business. The answers usually surprise me. You think you know where someone stands, but you do not until you ask.
That question opens real dialogue. It moves a conversation from assumption to understanding. In leadership, that shift builds trust, and trust is the foundation of every strong culture.
Q: How do you define authentic impact?
Mackenzie: Real impact comes from genuine care. I even use the word love in business, which makes people squirm, but I genuinely love the people who work for me and they know it.
I’ve paid attention to the bosses who have sucked the energy out of the room versus the bosses who have given energy. True, amazing impact that lasts on people’s lives comes from leaders who bring that conscious intention to how they show up. That’s the measure of leadershipthe energy you give, not the energy you take.
Q: What do you want leaders to take away from this approach?
Mackenzie: Telling yourself the truth about how you really feel is tremendously hard, and it is a radical act of courage. All of these concepts are so easy to say, and they are a lifetime’s work.
We need to be reminded because we forget, we get caught up. What can you do? Just try to pause and go, what is happening here? What am I choosing right now? And then not judge it or beat yourself up with self-flagellation. The old way is saying I’m not good enough, I’m bad, I’m wrong. The new way is just acknowledging how you feel and letting it be okay.
Larraine Segil is founder, chair, and CEO of The Exceptional Women Alliance.
Ford Motor said on Monday it will take a $19.5 billion writedown and is killing several electric-vehicle models, in the most dramatic example yet of the auto industry’s retreat from battery-powered models in response to the Trump administration’s policies and weakening EV demand.
The Dearborn, Michigan-based company said it will stop making the F-150 Lightning in its electric vehicle form, but will pivot to producing an extended-range electric model, a version of a hybrid vehicle called an EREV, which uses a gas-powered generator to recharge the battery. The company is also scrapping a next-generation electric truck, codenamed the T3, as well as planned electric commercial vans.
Instead, Ford said it will pivot hard into gas and hybrid models, and eventually hire thousands of workers, even though there will be some layoffs at a jointly owned Kentucky battery plant in the near term. The company expects its global mix of hybrids, extended-range EVs and pure EVs to reach 50% by 2030, from 17% today.
Ford will spread out the writedown, taken primarily in the fourth quarter and continuing through next year and into 2027, the company said. About $8.5 billion is related to cancelling planned EV models. Around $6 billion is tied to the dissolution of a battery joint venture with South Koreas SK On, and $5 billion on what Ford called program-related expenses.
The automaker also raised its 2025 guidance for adjusted earnings before taxes and interest, to about $7 billion, up from a previous range of $6 billion to $6.5 billion.
Fords shift reflects the auto industrys response to waning demand for battery-powered models, after car companies plowed hundreds of billions of dollars into EV investments early this decade. The outlook for electrics dimmed significantly this year as U.S. President Donald Trumps policies yanked federal support for EVs and eased tailpipe-emissions rules, which could encourage carmakers to sell more gas-powered cars.
U.S. sales of electric vehicles fell about 40% in November, following the September 30 expiration of a $7,500 consumer tax credit, which had been in place for more than 15 years to stoke demand. The Trump administration also included in the massive tax and spending bill that passed in July a freeze on fines that automakers pay for violating fuel-economy regulations.
Rather than spending billions more on large EVs that now have no path to profitability, we are allocating that money into higher-returning areas, said Andrew Frick, head of Fords gas and electric-vehicle operations.
The F-150 Lightning rolled off assembly lines starting in 2022 with much fanfare comedian Jimmy Fallon wrote a song about the truck. Ford increased production of the model to meet an influx of 200,000 orders, but sales havent kept pace. The company sold 25,583 Lightnings through November of this year, a 10% decrease from the prior-year period.
The successor to the F-150 Lightning, the T3 truck, was supposed to be built ground-up for production at a new complex in Tennessee, and be a core part of Fords second-generation EV lineup. Ford is now replacing production of the EV pickup with new gas-powered trucks starting in 2029 at the Tennessee factory.
Ford effectively killed the entirety of its announced second-generation of EV models with Mondays announcement. For its future EV lineup, the company is shifting focus to more affordable EV models, conceived by a so-called skunkworks team in California. The first model from that team is slated to be priced at about $30,000 and go on sale in 2027. This midsize EV truck is being built at Fords Louisville plant.
(Corrects the location of the battery plant to Kentucky, not Tennessee, in paragraph 3)
Nora Eckert
AI is quickly moving beyond rote tasks and into the realm of bigger-picture decisions that once relied only on human judgment. As companies treat AI as a thinking partner, the technology also introduces new risks. But the efficiency gains are hard to ignore, and companies are going head first into adoption.
Its very much like a chief of staff or a senior adviser, says Stacy Spikes, CEO of cinema subscription service MoviePass. To Spikes, AI platforms are a second or third set of eyes, helping him approach vendors or handle tricky people-to-people situations. He says he treats AI as a sounding board, not a decider.
Im not letting it make the decision for me, or letting it predetermine what I’m going to go in and do, but I’m having it give me a better understanding, he says.
Spikess experience shows the tension companies face as they roll out early use cases. AI can help employees act quickly and with greater precision, but organizations are still weighing what works and what doesnt, where the guardrails should be, and how to prevent judgment from slipping into autopilot.
Across industries, leaders are now testing the interplay between AI and human judgmentand developing the processes that let the two work together.
AI as a strategic partner
Spikes embeds AI into his executive workflow. He likens it to how large firms use management consultants to map scenarios and risks, as well as act as a sounding board. He uses AI to help with complex decisions across people dynamics, situational gray areas, and selecting external partners or service teams: It could, for example, offer advice on handling disagreements between colleagues or partners, or offer alternate perspectives that challenge someones initial point of view.
I’m constantly having conversations with different AI tools, says Spikes. Ill give them information and have stand-up conversations with themalmost like a full research team, the way you would use McKinsey or PwC consultants. He says hell come to a fork in the road of decisions and uses AI to decide this pathway or that pathway.
Hell run scenarios related to ambiguous judgment calls through multiple models to compare perspectives, before stepping in himself. He says no sensitive data is shared with LLMs; when hes working with his team or vendors, he often asks for ideas on handling challenging milestone situations, including when the company has set goals or KPIs and misses them. The AI doesnt replace his decision-making; rather, it simply gives him more insight with which to make a decision.
He points to a recent case with a contractor he let go. The work ended in the first week of the month, but the contractor insisted on being paid for the full month. Spikes ran the scenario through two different AI models. One gave a firm, black-and-white answerprorate the work and move on. Another tool framed the issue more gently, emphasizing the persons past contributions. While Spikes ultimately held to his earlier decisionprorating the paymenthe says the AI conversations influenced the tone, leading him to approach the discussion with more empathy.
He thanked the vendor for their earlier work but explained that prorating was necessary to maintain fairness across the team, especially since people talk, he pointed out. But had he not consulted AI, he may not have been nudged toward that balance. Asked whether AI changed the underlying decision, Spikes says no, but it influenced his tone.
It made me a little bit kinder than I would have been.
Supporting day-to-day decisions
Elsewhere, companies are weaving AI into operational decisions to give employees clearer visibility and speed up decision making.
Dave Glick, Walmarts senior vice president of enterprise business services, says corporate teams use an internal AI tool called the associate super agent. It works like a single front door: employees ask a question, and the system quietly hands it off to small, task-specific tools in the background.
One use case is when employees want to understand what went wrong with a shipment or delivery. A shipment might arrive without a corresponding purchase order or end up at the wrong building; the AI system gathers data from multiple sources to piece together what likely happened.
Many of these tasks are sort of detective work, Glick says. This purchase order showed up at the wrong building, or this shipment showed up and we dont have a purchase order for it. So, the AI pulls everything together and shows them what likely happened.
Glick emphasized that the human remains in control and can override any conclusion the AI suggests. What used to require digging through multiple databases is now compressed into a much faster preliminary review, with the AI assembling the data before the employee makes the call.
Ultimately, the value of AI comes down to its ability to find and assemble the right data; if the data isnt clean, AI cant meaningfully support a decision.
Marne Martin, CEO of expense-management software firm Emburse, noted that AI works best when the decision is repeatable and the data feeding it is clean. If you have more than 3.5% of inaccurate or highly biased data in your model, you will not get to the accuracy that you can just trust AI, she says.
Similarly, Infosys CTO Rafee Tarafdar says the IT services firm ties AI reliance to risk: the higher the stakes and the shakier their confidence in the model for a given use case, the more a human needs to step in.
Is it risky to over-rely on AI?
The efficiency gains from using AI are early wins, but researchers caution that exposure to AI can change how people act, prompting them to defer to either AIs judgment too much or default to more control-oriented responses.
In an interview, University of Massachusetts Lowell associate professor of management José-Mauricio Galli Geleilate says his research shows that consulting AI turns your framing of the problem and how you see the problem, nudging leaders more towards control, like punitive or surveillance-oriented solutions.
His co-author Beth Humberd, also an associate professor of management at UMass Lowell, describes the effect as a kind of psychological distancing: when managers turn to a machine instead of a colleague, you dont have the human cues that you would have in asking another person for their thoughts, she says, which make you pause and consider the person on the other side.
Léonard Boussioux, an assistant professor of information systems at the University of Washingtons Foster School of Business, says his research shows people can quickly fall in line with AI because the models are really good at crafting sound arguments, and humans tend to trust anything that feels logical and well-articulated.
To curb these effects, researchers say organizations need to build in frictionby forcing people to slow down, questioning the output, and bringing in human context that AI cant capture.
Companies say theyre using I to augment but not replace human judgment. And as adoption grows, many are still figuring out where the handoff will be.
For many, the hurdle may be more cultural than technical: forcing employees to question AIs output, while getting comfortable with its integration into daily workflows.
AI is a level up from where we normally are, says Spikes. A CEO now has another counselor that is limitless in its ability to pull in data and information.
it’s informing me, and it’s giving me a wider point of view.
LinkedIn is often seen as the purview of recruiters and thought leaders. But the professional networking platform is quietly attracting a rather unexpected audience.
According to recent data, 18- to 24-year-olds now make up 20.5% of its user base. That tracks, as college students and recent grads enter a cutthroat job market, eager to build a personal brand and online résumé that might help them stand out from the competition.
Whats more surprising is that high schoolers are also getting in on the game younger than ever, treating the platform as a means to get ahead. High school students are discussing how having a professional online presence before even beginning a career is simply showing initiative. Sharing volunteer work, internships, and professional goals where future employers can see them (and keeping brainrot slang content on TikTok) shows ambition, some argue. The pressure to hit 500 connections is real.
LinkedIn opened its doors to users 13 and up back in 2013, long before todays teens were even online. But Gen Z and Gen Alpha are coming of age in a world where career anxiety starts early, as social media feeds them an endless scroll of entrepreneurs, side hustlers, and monetizable passions complete with six-figure salaries, however unrealistic it may be.
As a result, early signs have shown that Gen Z and Gen Alpha may have stronger entrepreneurial aspirations than previous generations. A new survey of 2,002 Gen Z and Gen Alpha users (ages 12 to 28) by social commerce platform Whop found that more than half are already using the internet to earn money through digital side hustles like selling vintage clothing, streaming video games, and posting on social media.
And its paying off. Gen Alpha members report making an average of $13.92 per hour from digital pursuits, well above the federal minimum wage. When teens are bringing in the equivalent of a $28,000 salary before they can drive, its no wonder they want a professional profile to match.
For some teens, the platform acts as a great equalizer. LinkedIn can connect students, especially those who dont come from wealthy or well-networked backgrounds, to mentors, internships, and career paths they might not otherwise be aware of. Tools like LinkedIn Learning offer free courses in leadership, coding, design, and more.
Yet, comparison culture is rampant across social media. And LinkedIn is no exception. The pressure of worrying about future careers is taking grip younger and younger.
As the World Economic Forum’s The Future of Jobs and Skills report estimated back in 2016, 65% of children entering primary school that year will likely work in roles that didnt even exist yet. The same will most likely be true another decade from now. If you dont even know what job youll be applying for when you graduate, theres really no use worrying too much about it.
After all, you only are 15 once.
Stretch fabrics are notoriously hard to process. When your old leggings wear out, they will probably end up in a landfilleven if you try to drop them off for recycling. But a Manhattan startup has developed a new material that could finally make this corner of the apparel industry circular.
Theres a reason why billions of pounds of textiles ends up in landfills, says Gangadhar Jogikalmath, cofounder and chief technology officer of the startup, called Return to Vendor. When we dial it down to the microscopic scale, it’s because everything that we wear has blends of yarn put together to create this apparel nylon blended with spandex, wool with nylon, cotton, polyester.
Any fabric blend is hard to disassemble, and stretch fabric is especially challenging. You cant shred it, says Jogikalmath. The spandex melts at a lower temperature, gums up the recycling machinery, and your recycling system really suffers from having even a small amount of spandex in it.
To tackle the challenge, the startup has spent the last four years designing fabric that uses a single materialnylonand transforms it so that a material with fibers that normally wouldnt stretch suddenly can. Then, at the end of its life, since its a mono material, it can easily be recycled and turned into new fabric for new clothing.
[Image: RTV]
Making stretch fabric from a single material
Jogikalmath, who started his career as a protein chemist, took inspiration from the way that proteins are structured. Normally, nylon has tight hydrogen bonds that make the material stiff and resistant to stretching. Using a protein-inspired approach, the startup re-formulated the structure so that the molecules can slide past each other under stress and then spring back when the stress is released.
After making a proof of concept and raising a seed round of funding from Khosla Ventures, the team went through years of R&D. This year, it worked with a mill that specializes in stretch fabric to make samples of the final material. They were equally as excited with the results, says CEO and cofounder William Calvert. And now were putting it through the paces where it can be commercialized.
With the use of the startups chemistry, the material can be made in any mill that makes nylon yarn, not just those that specialize in stretch. After the yarn is made, it can be made into fabric without adding any new machinery or process changes, meaning that it could easily scale up, unlike some other novel materials.
The material is made from recycled nylonturning old fishing nets or carpet into new fiberand is already at cost parity with virgin nylon. But the cost will keep going down the more its recycled; as brands collect their old clothing for recycling, the next generation feedstock will cost even less.
Theres strong demand across multiple categories, says Calvert, from athleisure to intimate apparel and outdoor wear. Brands are now beginning to test it in pilots. When I put it on LinkedIn, the brands started calling, says Jogikalmath.
A bigger vision for circularity
To ensure that final garments are fully recyclable, the company has also redesigned smaller components like zippers and buttons so they’re also made from 100% nylon. (One designer, Willy Chavarria, has already worked with the startup to use some of these materials to make baseball hats, swim trunks, and eyewear.)
The startup’s basic approach for stretch fabrictweaking nylon so that the material has new characteristicscan also be used in applications outside apparel. The company is currently working with a large motorcycle brand to make new injection molded parts, for example.
The company will work with brands to get back the clothing that’s made with its material at the end of life. Brands can include a label so customers know that the garment or other product is fully recyclable. “We want to be the ‘Intel Inside’ of circularity,” says Jogikalmath.
In the fashion world, where brands are continually looking for new ways to cut their carbon footprints, the stretch fabric has the potentially to quickly scale. “When you have a huge carbon savings, when it’s recycled, it’s recyclable, and it comes in at cost and performance parity, why wouldnt they adopt it?” says cofounder and chief recycling officer Adam Baruchowitz. “It’s a complete win for them, and for everyone: for the brand, for the customer, for the planet.”
Tom Freston could easily fill a book with stories from the formative days of MTV and his celebrity encounters Bono would merit a few chapters on his own. Ultimately, though, Freston feels that his life has a more valuable lesson to offer.
His memoir, Unplugged, shows by example that trying to follow a straight line to success is not the only path.
Freston, 80, was at MTV from the start and became its leader, along with sister networks Comedy Central, VH1, and Nickelodeon, at their greatest periods of success. He rose to become CEO of parent corporation Viacom before chairman Sumner Redstone’s impatience led to his ouster in 2006.
Since then, Freston has largely freelanced, advising the likes of Oprah Winfrey and Vice, before its implosion. He made a memorable return to business in Afghanistan, and has been chairman of the ONE Campaign, the anti-poverty organization devoted to Africa that Bono spearheaded, for nearly two decades.
I was improvising, he said. It was like a bebop lifestyle, hitting notes instead of having a long, set classical structure.
His wanderlust unsettled Freston’s suburban Connecticut parents when he took a gap year after earning an MBA at New York University. They had reason to believe he had gotten it out of his system when he took a job at a Madison Avenue advertising agency in the early 1970s.
Saying no to a life convincing people to squeeze the Charmin
He soon faced a crossroads when he couldn’t muster enthusiasm for a role on his agency’s important Charmin account. An old girlfriend said to him: All those years of school, that fancy MBA degree, and you are selling toilet paper? You’re better than that.
She had a point. It was January 1972, and the woman invited him to hitchhike through France and Spain, then eventually into the Sahara Desert. He left the agency behind.
Thus began several years of travel, where he particularly fell in love with Afghanistan and India. Freston started a business importing clothing from Asia. The company, Hindu Kush, was successful for a time before restrictions on imports during the Carter administration killed it.
Freston landed back in New York. He read an interview where an executive in the nascent cable television industry talked about starting a music network built on videos and reached out for an interview for a marketing job. He met with a 26-year-old Bob Pittman, who wondered about the appearance of Afghanistan on his resume.
Pittman suspected Freston was a hashish smuggler, but that seemed to make him like me more, he wrote. Hey, it was rock n roll. Freston got the job.
To encourage cable systems to carry the new network, Freston directed film crews that ambushed Pete Townshend on a London Street and David Bowie on a Swiss ski slope to record ads saying I want my MTV. Its rapid rise has been well documented, and by 1987, Freston was running MTV Networks.
Music always played in Freston’s office, giving the young, creative employees the sense that it wasn’t a suit in charge. Former employees say he wasn’t afraid to take risks and empower people. It was almost a requirement particularly
Once, MTV decided it needed to reinvent itself every few years to appeal to young people, rather than follow its original audience as it aged.
His international experience helped him create MTVs for different countries all around the world.
It was irreverent and edgy and nonhierarchical, a lot of creative people, he said. If you tried to run it in a classic MBA style, it would have been rejected.
Looking in on a ghost network
Several factors led to MTV’s demise, among them the rise of streaming that turned many once-popular cable destinations into ghost networks. Record companies wouldn’t grant MTV streaming rights to play music videos online, undermining chances for a digital transformation, he said.
Now, when Freston lands on MTV, its like seeing your old high school burning down, he said.
From his book, Freston is clearly still stung by his sudden ouster from Viacom. He makes it a point to tell of attempts to get him back. But in retrospect, the timing couldn’t have been better.
It was a good thing, because I’m a loyal guy and I probably would have stayed longer, he said. In a way I got fired at the apex of the TV revolution. The digital guys were just starting to have an impact in a big way. So I really didn’t have to deal with those unpleasant facts and challenges.
He was suddenly a free agent, but in demand. Most rewarding was a return to Afghanistan, and working with an entrepreneur, Saad Mohseni, on a television network for the people there. The Taliban put an end to that when they returned to power in 2021 but recently have let Mohseni produce educational programming for girls.
Freston hasn’t been back since the takeover. I had a death sentence put on me by the Taliban, he said. They say we’re all friends now, but I don’t want to take the chance.
I still haven’t found what I’m looking for
It’s hard to resist one Bono anecdote. The singer’s seduction of Freston to join the ONE Campaign’s board was sealed on a late night of partying in the Riviera. It was 5 a.m., closing time at a disco and Bono, a Dublin buddy, and Freston were the only ones left besides a few busboys and a waitress.
On the way out, Bono spied a microphone connected to a karaoke machine. Pick a U2 song, Bono told the server. Any one! She chose I Still Haven’t Found What I’m Looking For, and the famous frontman channeled Frank Sinatra as he sang his classic. The waitress was the only one left to clap.
Who wouldn’t want to have this CEO’s life?
Readers of Freston’s memoir probably won’t greet the dawn with rock stars. He hopes they appreciate the musical notes of his life and apply it to their own.
Ideally, younger people would find some inspiration in the fact that you don’t have to graduate from college and start the next day at Goldman Sachs, and if you don’t you have a panic attack, he said.
If you’re young, you should take some chances, he said. Take a risk. Go see the world. The world is the best classroom. Look at the United States from another person’s perspective. You’ll make yourself more interesting as a candidate for a job when you come back.”
David Bauder, AP media writer
Christmas at Pemberley Manor and Romance at Reindeer Lodge may never make it to Oscar night, but legions of fans still love these sweet-yet-predictable holiday moviesand this season, many are making pilgrimages to where their favorite scenes were filmed.
That’s because Connecticutthe location for at least 22 holiday films by Hallmark, Lifetime, and othersis promoting tours of the quaint Christmas-card cities and towns featured in this booming movie market; places where a busy corporate lawyer can return home for the holidays and cross paths with a plaid shirt-clad former high school flame who now runs a Christmas tree farm. (Spoiler alert: they live happily ever after.)
Its exciting just to know that something was in a movie and we actually get to see it visually, said Abby Rumfelt of Morganton, North Carolina, after stepping off a coach bus in Wethersfield, Connecticut, at one of the stops on the holiday movie tour.
Rumfelt was among 53 people, mostly women, on a recent weeklong “Hallmark Movie Christmas Tour,” organized by Mayfield Tours from Spartanburg, South Carolina. On the bus, fans watched the matching movies as they rode from stop to stop.
To plan the tour, co-owner Debbie Mayfield used the Connecticut Christmas Movie Trail map, which was launched by the wintry New England state last year to cash in on the growing Christmas-movie craze.
Mayfield, who co-owns the company with her husband, Ken, said this was their first Christmas tour to holiday movie locations in Connecticut and other Northeastern states. It included hotel accommodations, some meals, tickets, and even a stop to see the Rockettes in New York City. It sold out in two weeks.
With snow flurries in the air and Christmas songs piped from a speaker, the group stopped for lunch at Heirloom Market at Comstock Ferre, where parts of the Hallmark films Christmas on Honeysuckle Lane” and Rediscovering Christmas” were filmed.
Once home to Americas oldest seed company, the store is located in a historic district known for its stately 1700s and 1800s buildings. It’s an ideal setting for a holiday movie. Even the local country store has sold T-shirts featuring Hallmarks crown logo and the phrase I Live in a Christmas Movie. Wethersfield, CT 06109.”
People just know about us now, said Julia Koulouris, who co-owns the market with her husband, Spiro, crediting the movie trail in part. And you see these things on Instagram and stuff where people are tagging it and posting it.
Christmas movies are big businessand a big deal to fans
The concept of holiday movies dates back to 1940s, when Hollywood produced classics like It’s A Wonderful Life,” Miracle on 34th Street and Christmas in Connecticut, which was actually shot at the Warner Bros. studios in Burbank, California.
In 2006, five years after the launch of the Hallmark Channel on TV, Hallmark struck gold with the romance movie The Christmas card, said Joanna Wilson, author of the book Tis the Season TV: The Encyclopedia of Christmas-Themed Episodes, Specials and Made-for-TV Movies.
Hallmark saw those high ratings and then started creating that format and that formula with the tropes and it now has become their dominant formula that they create for their Christmas TV romances, she said.
The holiday movie industry, estimated to generate hundreds of millions of dollars a year, has expanded beyond Hallmark and Lifetime. Today, a mix of cable and broadcast networks, streaming platforms, and direct-to-video producers release roughly 100 new films annually, Wilson said. The genre has also diversified, with characters from a wider range of racial and ethnic backgrounds as well as LGBTQ+ storylines.
The formula, however, remains the same. And fans still have an appetite for a G-rated love story.
They want to see people coming together. They want to see these romances. Its a part of the hope of the season, she said. Who doesnt love love? And it always has a predictable, happy ending.
Hazel Duncan, 83, of Forest City, North Carolina, said she and her husband of 65 years, Owen, like to watch the movies together year-round because they’re sweet and family-friendly. They also take her back to their early years as a young couple, when life felt simpler.
We hold hands sometimes, she said. It’s kind of sweet. We’ve got two recliners back in a bedroom that’s real small and we’ve got the TV there. And we close the doors off and it’s just our time together in the evening.
Falling in love again… with a state
Connecticut’s chief marketing officer, Anthony M. Anthony, said the Christmas Movie Trail is part of a multipronged rebranding effort launched in 2023 that promotes the state not just as a tourist destination, but also as a place to work and live.
So what better way to highlight our communities as a place to call home than them being sets of movies? he said.
However, there continues to be debate at the state Capitol over whether to eliminate or cap film industry tax credits which could threaten how many more of these movies will be made locally.
Christina Nieves and her husband of 30 years, Raul, already live in Connecticut and have been tackling the trail little by little.”
It’s been a chance, she said, to explore new places in the state, like the Bushnell Park Carousel in Hartford, where a scene from Ghost of Christmas Always was filmed.
It also inspired Nieves to convince her husband not quite the movie fan she is to join her at a tree-lighting and Christmas parade in their hometown of Windsor Locks.
I said, listen, let me just milk this Hallmark thing as long as I can, OK? she said.
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This story has been corrected to reflect that the film title is Christmas at Pemberley Manor, not Christmas at Pemberly Manor,” and the co-owner of Heirloom Market at Comstock Ferre is named Spiro Koulouris, not Spiros Koulouris.
Susan Haigh, Associated Press
In theory, AI should have transformed manufacturing by now. From predictive maintenance and fatigue detection to real-time quality control, the promise has always been smarter, faster, and safer operations. But in practice, the factory floor is still a place where AI ambitions often run into real-world limitations.
Thats a huge problem, especially because the size and weight of this industry are hard to ignore. U.S. manufacturing alone contributes $2.9 trillion to the economy, accounting for over 10% of total output and supporting nearly 13 million workers, according to the National Association of Manufacturers. Globally, manufacturing represents 16% of world GDP and a total market value well over $16 trillion, per a new report from Cargoson.
Now, as AI advances even further and policymakers push for reindustrialization in the U.S.aiming to restore domestic production capacity, regain supply chain control, and modernize strategic infrastructurethe spotlight is back on factories. Theres momentum and money behind the movement, but without restructuring the fragmented digital systems that dominate most production floors, that momentum may stall. An estimate by MarketsandMarkets projects the global AI in manufacturing market would grow to $155 billion by 2030, up from $34 billion in 2025 — but that growth will remain theoretical unless companies solve the bottlenecks slowing down adoption.
Outdated infrastructure
According to a 2025 survey of more than 500 manufacturing leaders, 92% say outdated infrastructure is holding back GenAI progress. Another report on the state of AI infrastructure by A10 Networks found that 74% of global IT decision-makers believe their current infrastructure is not fully prepared to support AI workloads. For all the talk of digital transformation, many factories are still running on architecture that predates smartphones, most of which cannot support new AI capabilities.
The hype around AI in manufacturing is real, but so are the technical barriers, Shahid Ahmed, EVP of New Ventures and Innovation at NTT DATA, tells Fast Company. Modern connectivity is unlocking the next wave of AI-driven innovation in manufacturing. Private 5G and next-gen Wi-Fi give manufacturers the speed and reliability to finally turn AI into a productivity engine.
However, better connectivity is just one part of the big problem with getting AI to produce optimal results on the factory floor. Whats really stopping AI from working on the ground isnt just weak networks but also a mismatch between how factories run and how AI systems think.
At aiOla, a conversational AI company that works with Fortune 500 manufacturers, Assaf Asbag sees a common pattern: data silos, fragmented systems, and little end-to-end accountability. Even when manufacturers bring in advanced models and top-tier talent, the results rarely scale.
Even with expensive AI talent, teams cant generate value if they dont have clean, connected data, explains Asbag, aiOlas Chief Technology & Product Officer. You need aligned data, integrated workflows, and clear accountabilityotherwise pilots never scale.
Thats because many manufacturing systems were never built to support AI in the first place. Legacy enterprise systemslike outdated ERP (enterprise resource planning) tools, old-school CRMs (customer relationship management platforms), and manual data entrystill dominate much of the landscape. When critical insights are buried across disconnected platformsor worse, written down in logbooksit becomes nearly impossible to feed AI models the context they need.
Ahmed points to a recent deployment with materials manufacturer Celanese, where private 5G and edge AI were introduced to improve worker safety and equipment monitoring. They were able to identify fatigue risk factors and detect hazards in real time, he claims. It was only possible because the infrastructure was there to support that intelligence.
For him, the key to successful AI deployments in manufacturing isnt just having data but also having the right data, in the right place, and at the right time. Without that, he warns, factories will keep seeing failed pilots, no matter how powerful the model.
Not all use cases are built the same
While the buzz often centers on predictive maintenance and visual inspection, those arent plug-and-play features. They require reliable data flow, ultra-low latency, and hardware compatibility that many plants simply dont have. In remote or offline environments, traditional cloud-based systems cant keep up.
Use cases that demand real-time decision-makinglike voice-enabled workflows or autonomous quality checksare especially sensitive to network and system performance, Asbag notes. Thats why edge computing matters. It allows speech recognition or LLM-driven tasks to happen on-site, without depending on cloud access.
Picture a factory line that shuts down every time it loses Wi-Fi. Without local processingmeaning the ability to run AI tasks on devices in the factory instead of sending them to the cloudeven a short loss of connectivity can stop production and make AI tools more of a problem than a help.
For factories operating with limited or unreliable connectivity, edge AI offers a way forward. By processing data locally, companies can cut lag time, protect sensitive data, and reduce downtime. But again, these benefits only materialize if the surrounding infrastructurefrom sensors to routersis up to the task.
Think of it like trying to run a modern electric vehicle on outdated roads, Ahmed says. No matter how powerful the engine, if the path is broken, youre not going anywhere fast.
Getting real ROI
One of the biggest traps in AI adoption is mistaking model accuracy for business success. Just because a model performs well during testing doesnt mean it will drive positive outcomes on the floor.
The most successful AI initiatives begin with a clear visionimproving quality, boosting efficiency, or unlocking insights, says Ahmed. From there, quick wins build momentum.
Asbag agrees with him. ROI in AI is not about proving that the modelworks or that accuracy improves on a benchmark. Those are technology goals, not business goals, he notes. Companies should avoid fluff by defining ROI in clear, specific business termsfaster processes, better decisions, or measurable savings.
That means tracking metrics like how many more inspections a worker can perform with a voice assistant or how predictive maintenance reduced unexpected machine downtime. When AI is tied to concrete, operational KPIs, it becomes a tool for transformationnot just a tech experiment.
And thats the big difference between the hype-induced claims of faster operations in the AI space and real measurable impact. Its one thing to say your model is 96% accurate in a test environment. Its another to show that it actually helped to cut defect rates by 12% in real production. While the first might get a nod from the technical team, the second gets leadership to sign off on a bigger rollout.
The path forward
Getting AI to work in manufacturing isnt about chasing the most advanced model. Its really about understanding the problem, cleaning up the data, modernizing the systems, and making sure every deployment serves a real business need.
Too many companies fall into endless discussions, pilots, and meetings without ever delivering value, says Asbag. Success with AI comes from being precise about the problem, aligning with the business outcome, and giving teams the autonomy to execute.
Ahmed puts it even more directly: AI without infrastructure is like trying to build a smart city with no roads. You need the foundation in place before you scale. Sateesh Seetharamiah, CEO of Edgeverve, also agrees. Without a defined set of use cases and outcomes, manufacturers will be stuck without a clear strategy to prioritize the right emerging tech capabilities for business success, he says.
Conversations about building AI infrastructure in manufacturing often stall because leaders assume it means ripping everything out and starting from scratch. But meaningful progress rarely requires a full overhaul. Some of the biggest wins come from small, targeted changeslike installing local edge devices to reduce lag, connecting isolated systems, or clarifying who owns what data so teams can move faster.
Manufacturing may be one of the toughest environments for AI, but its also one of the most rewarding. The factories that get it right wont just optimize how work gets done. Theyll also lead a new era of industrial work, while the ones that hesitate may fall behind. This isnt the time to sit on the fence, says Seetharamiah. Manufacturers who delay risk missing out on enormous opportunities to create digital experiences for their customers.
A lot has been written about how AI is coming for your job, but EY’s latest AI survey found some surprisingly results. Out of 500 top executives at major U.S. companies who said artificial intelligence was boosting productivity at their companies, only 17% of those polled actually turned around and laid off workers or cut their jobs.
Instead, the new survey found they are reinvesting those gains back into the company.
“Executives are plowing productivity gains right back into more AI tools and more talented people,” EY America’s consulting leader Colm Sparks Austin said. “The real breakthrough isnt automationits amplification. Leading companies are using AI to scale human capacity at a pace weve never seen before.”
The EY US AI Pulse Survey, the fourth in a series of polls, surveyed 500 key U.S. business decision-makers across sectors (either senior vice presidents and above) and found nearly all organizations investing in artificial intelligence are experiencing some amount of AI-driven gains in productivity (96%), including 57% that say their gains are “significant.”
However, among those organizations experiencing AI-driven productivity gains, only 17% say these gains led to reduced headcount; far more reported reinvesting those gains into existing AI capabilities (47%), developing new AI capabilities (42%), strengthening cybersecurity (41%), investing in R&D (39%), and upskilling and reskilling employees (38%).
While AI readily raises the floor by improving efficiency, the transformative potential comes from raising the ceiling, according to Dan Diasio, EY global consulting AI leader. Organizations that shift from a productivity mindset to a growth agenda are using AI to drive innovation, create new markets and achieve what was previously considered impossible.
Diasio said the survey results reveals that successful companies are reinvesting their gains today to build the businesses of the future, not just optimizing the current operations.
The survey also found the amount of money a company invested in AI, influenced how much productivity gains it saw in 2025. For example, senior leaders at organizations currently investing $10 million or more in AI across all business units or teams (71%) were more likely than those investing less than $10 million (52%) to say their organization has seen significant AI-driven productivity gains over the past year.
Finally, when asked about the impact of AI investments on their financial outcomes, a majority of the senior leaders (56%) who have seen positive ROI from AI investments report it has lead to significant measurable improvements in overall financial performance.
As a result, that performance is leading to increased planned AI spend by companies. While 27% of respondents investing in AI currently commit a quarter or more of their IT budget to AI, that figure is set to roughly double to 52% in 2026; and the group spending half or more of their total IT budget on AI is expected to quintuple, jumping from just 3% in 2025 to a whopping 19% in 2026.
In short, those businesses investing the most in AI today, will likely be leaps and bounds ahead of the competition in the future.
The companies out in front on AI investment are pulling farther ahead, Whitt Butler, EY Americas vice chair of consulting explained. The magnitude of investment matters: the organizations committing more funding to AI are seeing the strongest productivity gains, showing that AI is moving beyond pilots to become a true driver of enterprise value.
