TheChek News Flow

Netflix-Warner Bros. Is a Marriage Made in Competition Heaven

Top executives from Netflix and Warner Bros. Discovery answered antitrust concerns before the Senate on Tuesday. The hearing’s chair, Sen. Mike Lee (R., Utah), said Netflix’s proposed $82.7 billion all-cash purchase of WBD posed a “classic risk” of market consolidation.

Not so fast. If the antitrust inspectors are objective, they should wave the deal home.

Never mind that President Donald Trump favors the other offerer, Paramount Skydance, with its MAGA-friendly owners of CBS, and is tempted to tip the scales their way. Netflix’s purchase of WBD would result in a “big market share” he says with a glint in his eye. That “could be a problem.”

Yet the idea that a Netflix-WBD merger would extinguish video competition is a chimera. The very goal long-clamored for by U.S. policymakers—vanquishing the cable monopolies and opening video markets to bountiful customer choice—has been Netflix’s greatest triumph. That has brought the streamer many industry foes, because it slashed costs and squeezed Hollywood. Viewers, however, have been rewarded with an explosion in program choice. A Netflix-WBD deal would extend both of those trends.

Hollywood may trash Trump in award acceptance speeches, but they must love his open hostility to the Netflix bid. Writers, actors, directors, and studio execs harbor animosity for Netflix, which disrupted their business models and shook up the power structure of the industry incumbents. A real New York Times headline last month: “Everybody in Hollywood Secretly Hates Netflix.”

Netflix came out of nowhere in the mid-2000s to topple Blockbuster in the DVD rental market. The Federal Trade Commission scuttled a Blockbuster acquisition of Hollywood Video in 2005 as a merger to monopoly; Blockbuster, the supposed rental behemoth, declared bankruptcy a few years later. In the background, Netflix was creating a whole new product category: on-demand video streaming.

By 2013, Netflix had built a TV studio. It was producing feature films by 2015. Just a few years later, Netflix was the country’s largest TV and movie producer. It was releasing, on average, a new original film or TV series a day—far beyond what the U.S. studios as a whole used to produce in a year.

Netflix is attempting to acquire the movie and TV studios of Warner Bros., plus its streamer, HBO Max. WBD will spin off its linear cable programming networks, including CNN, into a new entity called Discovery Global, which its shareholders will own. Such an industry restructuring won’t crush rivalry.

Today, Americans pay for about 430 million streaming subscriptions. Netflix accounts for 87 million of those, or 19%. Hulu with 52 million, Disney+ with 50 million, and Paramount+ with 37 million come next, followed by a slew of others. The merger sought by Netflix accounts for about 28% of streaming. The combination sought by Paramount would result in a company with roughly the same share of video services as Netflix-WBD, 26%. But Paramount-WBD would also become the largest cable TV network owner—with a portfolio including CNN, Food, TNT, and TBS, which serve nearly 70 million households each.

During the Comcast and NBC-Universal merger in 2011, the Department of Justice’s antitrust division defined the video marketplace to include traditional cable TV operators and “online video providers” like Netflix. The market is far more open today. Moreover, Netflix isn’t the biggest player. YouTube is. YouTube garners 13% of video streaming, as measured by viewing hours. Netflix and WBD would have just 9%. Counting subscriptions and ad money, YouTube’s parent company, Google, outearns Netflix in video-related revenue by about 20%.

Some skepticism is circulating that Netflix and YouTube are comparable. One antitrust attorney recently told Reuters that the DOJ is “unlikely to see Netflix and YouTube as interchangeable rivals, given their different content, audiences, and business models.”

But firms need not be interchangeable to be fierce competitors. Comcast, Tubi, and Netflix were distinct when the DOJ lumped them into the same market in 2011. Comcast sold a high-price bundle of about 200 program channels, Netflix was a low-price, burgeoning streamer, and Tubi was an ad-supported, free-to-user service. Still, the antitrust enforcers saw their products overlapping and competing. It should see the same in YouTube, which hosts over five billion videos, more than 4,000 of which are free feature films. On YouTube, tens of thousands of titles, including new releases from Hollywood studios, are sold or rented.

We should also include in this market TikTok, where over 16,000 new videos are uploaded each minute. Joseph Stalin once offered: “Quantity has a quality all of its own.” Diabolical, yes, but he had a point.

Should Netflix win the fight over WBD and the DOJ elects to challenge it, a courtroom will hear much about video on demand by other suppliers. You don’t need a prediction market to guess where the facts lead—although Kalshi puts Netflix’s chance of success at nearly three times Paramount’s. Netflix’s offer includes a $5.8 billion breakup fee, an insurance payout for WBD shareholders should the deal fall through. It is the largest breakup fee in history.

These bets indicate the disruptive innovation of Netflix will be recognized by regulators or, if necessary, federal judges. And the next restructuring of video markets will proceed— Film at 11, and any other time you’d care to watch.

Thomas W. Hazlett formerly served as chief economist of the Federal Communications Commission. He is the Hugh H. Macaulay Endowed professor of economics at Clemson University.

On Tuesday, the roof caved in on software, media, and information company stocks like Salesforce, Reddit and Thomson Reuters. The proximate cause was the introduction of the latest artificial-intelligence tools from start-up Anthropic, which much of the market interpreted as an existential threat to any company that doesn’t make or sell physical goods.

The handwringing is overblown. While the AI tools show the potential power of AI in office work, they’re not ready for prime time and, in fact, could prove dangerous to the companies that use them. More importantly, these agents remain dependent on the same software and information sources that investors seem to think they will replace.

Once the dust settles, there will be a lot of companies in the software, media, and information sectors with attractive valuations. Private equity buyers are probably licking their chops; Orlando Bravo, the founder of private-equity firm Thoma Bravo, said as much during an interview from Davos last month. Salesforce, the pioneer in cloud software, now trades for just 15 times forward earnings, its lowest price/earnings ratio on record.

The technologies at the root of the selloff all are part of Claude Cowork, a desktop agent that for now is only available on Mac computers. Agents use large-language models to accomplish a complex series of tasks from a simple prompt. For example: “Go through my emails and messages, find all the deliverables I have this week, and create first drafts of them, including any charts and slide decks. Then email the drafts to the team and solicit feedback.”

On Wednesday, Anthropic released 10 plugins to Cowork that seek to accomplish these tasks in a variety of areas from sales and finance to legal and customer support. The news expanded the agent disruption worries beyond enterprise software into information services. Thomson Reuters fell 16% Tuesday, S&P Global, and advertising holding company WPP 13%.

Science fiction author Arthur C. Clarke once wrote, “Any sufficiently advanced technology is indistinguishable from magic,” and agents seem like magic when they work. But they don’t always work. When agents are given a lot of access and privileges, disasters can occur.

All of the AI worries stem from a misunderstanding about how large-language models like Claude and OpenAI’s ChatGPT actually work. These are advanced probability machines that make guesses at writing sentences one word at a time, based on the human language in its training data. In the end, it’s just trying to sound like the humans in its training data, be it a renowned physicist or a social media troll. It’s so good at mimicking humans, that we assign words like “reasoning” and “feeling” to them even though these probability machines do nothing of the sort.

As good as these models are at sounding like an all-knowing person, they also regularly make believable, authoritatively-worded fabrications known as hallucinations. A lot of research has gone into eliminating hallucinations, but it remains an unsolved problem. No one is exactly sure why they happen.

In tiny print at the bottom of its Claude chatbot, Anthropic warns that “Claude is AI and can make mistakes. Please double-check cited sources.” I use Claude, ChatGPT, and Google’s Gemini every day, and I can vouch for the truth in the Claude warning. In its documentation Anthropic adds, “Users should not rely on Claude as a singular source of truth and should carefully scrutinize any high-stakes advice given by Claude.”

Does that sound like a reliable assistant to which you would hand over your computer?

This isn’t just theoretical; we already see the dangers of hallucinations in the real world. Shares of Thomson Reuters, which provides news and information services to the legal profession, got clobbered because of the Cowork legal plugin, which promises to “review contracts, triage NDAs, navigate compliance, assess risk, prep for meetings, and draft templated responses.”

But lawyers using AI language models to speed up their work have already run into a lot of trouble. HEC business school researcher Damien Charlotin maintains a list of incidents in which lawyers filed AI-written briefs that contained completely fabricated precedents and quotes. He’s up to 355 such incidents, with 34 in 2026. Many of these attorneys are liable for fines, professional discipline, and may be subject to malpractice suits from their clients.

“The main thing to know is that Claude can take potentially destructive actions,” Anthropic said in the safety section of its Cowork launch announcement. Anthropic also recommends against using Cowork for any regulated workload, such as medical records. Agents are also vulnerable to an unsolved class of cyberattacks known as prompt injections, a threat organizations aren’t prepared for.

This isn’t to say that agents won’t ever perform business tasks without hallucinations and security holes. It’s coming one day, just not soon. Anyone using them for mission-critical tasks today will eventually find themselves knee-deep in a catastrophe.

But even then, agents aren’t the end of software. On GitHub, the largest code repository, which is owned by Microsoft, Anthropic lists the software currently being used by Claude agents and it’s full of all the largest software names. In fact, the Cowork legal plugin uses Microsoft 365, Jira, Slack, and Box software to accomplish its tasks. No one at Anthropic has replicated any of these applications with ones coded by the company’s Claude Code agent.

Finally, as information and media businesses shed value in the market, investors would be wise to think through the broader implications. Training AI models requires text, images, and video created by humans so that they can be mimicked. So far, the AI companies have used every book ever written, and as much of the internet as possible. But if AI destroys the sources of human text, then where would they be?

That would be the true apocalypse.

Once the purview of science fiction, automatons are getting closer to reality.

Key Points

Like something from a galaxy far, far away, robots are getting closer to their big takeover.

Once the domain of science fiction, autonomous robots—think C-3PO from Star Wars or Baymax from Big Hero 6 —are getting closer by the year. At 2025’s CES electronics conference, there were a handful of humanoids, none of which seemed to catch the world’s attention. At January’s conference, robots, including Boston Dynamics’ Atlas, a 6-foot-2-inch automaton weighing in at just under 200 pounds with a digital smiley face, were the stars. Chip companies lined up for a shot at best supporting actor, with Nvidia, Qualcomm, Intel, and Advanced Micro Devices pitching their wares as robotics solutions.

Wall Street is positively giddy. Artificial intelligence is still the market’s next big thing, and robots are the next phase of AI. Unlike the industrial models that follow fixed instructions or consumer products like the Roomba, which uses simple sensors to vacuum a floor, the new creations use AI models to “learn” their tasks. They can pack boxes, sort parts for assembly, and do household chores. Morgan Stanley’s Adam Jonas even recently ditched the auto beat for “embodied AI,” i.e., robots.

While robots are already working in factories and warehouses, home use is still a long way off. Part of the problem is scale—no robot is being truly mass-produced just yet, and cost estimates are little more than guesses. A NEO robot from 1X, meant for home use, can be reserved for $20,000. Tesla CEO Elon Musk believes that it will cost $20,000 to produce its Optimus robot, designed for commercial use, once “we reach about a million units per year of sustained production.” Even when they are available, robots still can’t do everything they should be expected to do. The NEO robot will be initially teleoperated by a human as it learns to do things on its own.

Investors might not have to wait as long for a payoff. Even with peak robot decades away, automatons will be an increasingly important part of a stock portfolio. Embodied AI will bolster trends that are already in place—the demand for AI chips, data connectivity, increasing power production, and the U.S. manufacturing renaissance, among them. It will take years for the industry to mature, but investors are looking at a multitrillion-dollar industry that can rival cars or smartphones.

Robotics will help “usher in the third Industrial Revolution, driving $25 trillion of combined robot revenues by 2050,” says Jonas.

The current industry is dominated by the likes of German-based Kuka, which is owned by China’s Midea Group; Swiss-based ABB, which is selling the business to SoftBank Group; and Japan’s Fanuc and Yaskawa Electric. These are mainly industrial robots, fixed to the ground and handling parts, cutting metal, and welding, among other tasks. These aren’t the robots you are looking for. While they make for a nice business—the companies sell about 500,000 units a year—their growth is tied to industrial production and somewhat limited by the slow-growing auto industry, the biggest customer for industrial robots.

The robots that have everyone excited can walk out of the factory. They aren’t programmed to do a carefully constrained repetitive motion. They are being programmed to complete tasks that had once been the purview of humans and have AI brains learning inside AI-created virtual worlds, with capabilities expanding exponentially. “The changes introduced by AI are absolutely real,” says Zachary Jackowski, the general manager of Boston Dynamics’ Atlas robot unit.

And now the race is on. Atlas, which is billed by Boston Dynamics as the world’s most dynamic robot, has a cartoonlike LED ring for a face and can see 360 degrees, lift 110 pounds, and operate in temperatures ranging from minus 4 to 104 degrees Fahrenheit. Boston Dynamics, which is majority-owned by Korea’s Hyundai Motor, doesn’t disclose pricing but says that customers typically save enough money over two years to justify the expense.

Tesla’s Optimus, which stands about 5 feet 8 inches tall and weighs 125 pounds, has evolved from dancing in a suit, to serving drinks while controlled remotely, to learning kung fu. Tesla is working on generation three of Optimus and hopes that it will autonomously perform simple repetitive tasks, while making life easier for humans. Tesla recently announced that it would discontinue its Model S and X electric vehicles, converting the capacity to a robot manufacturing line.

“Optimus 3 really will be a general-purpose robot that can learn by observing human behaviors, so you can, like, demonstrate a task or literally verbally describe a task…and it will be able to do that task,” Musk said on Tesla’s January earnings call. “It is awesome.”

Other entrants include Figure AI’s F.03 robot, introduced in October, which stands about 5 feet 8 inches tall and weighs about 135 pounds, with a carrying capacity of 44 pounds. The company positions it a little like Rosie from The Jetsons, taking “care of household tasks like laundry, cleaning, and doing dishes, all autonomously.” CEO Brett Adcock hopes to test F.03 in homes by the end of the year.

Agility’s Digit robot, with its rectangular eyes and pincers for hands, looks a little more like science fiction and a little less like a human replacement. Standing about 5 feet 9 inches tall, it can carry 35 pounds and is already in use at select warehouses, including those operated by GXO Logistics and Amazon.com. The company can produce some 10,000 robots per year at its manufacturing facility in Salem, Ore.

China isn’t sitting still. It hosted the first World Humanoid Robot Games in Beijing last August, and its brands, including Unitree Robotics and UBTech Robotics, provide serious competition for U.S. manufacturers. “This is the first time since the 20th century where the U.S. is facing stiff competition from another power that has formidable strengths not only in technology, but also in terms of economic strength and military strength,” says Maria Vassalou, head of the Pictet Research Institute.

Wall Street sees an enormous opportunity in robotics. RBC analyst Tom Narayan projects some 350 million robots sold annually, at an estimated $25,000 each, by 2050, pointing to a $9 trillion market. Morgan Stanley’s Jonas projects a $25 trillion market by 2040, though his estimate includes cars, drones, humanoids, and other form factors. Even one of the least optimistic analysts, UBS’ Phyllis Wang, projects a global population of 300 million humanoid robots by 2050, implying an addressable market of $1.4 trillion to $1.7 trillion. The potential is obvious. “Robots looking and behaving like humans is no longer sci-fi fantasy,” says Wang.

The numbers are wild and, to some extent, pie-in-the-sky. But the same could have been said of other new technologies, including EVs and robo-taxis. It took about 20 years to go from the U.S. Department of Defense’s initial 2004 Darpa Grand Challenge to a surprisingly smooth ride around San Francisco or an easy morning commute using Tesla’s Full Self-Driving product. It won’t take 20 years for fully operational robots to arrive. Self-driving cars are, as Musk puts it, robots on wheels. And the same technology that Tesla and Alphabet’s Waymo use to train AI drivers will power the new robots.

No one has created a robot equivalent to a Tesla Model 3—a product that is useful, affordable, and desirable. They are coming, though. The Model 3 was introduced five years after the lower-volume Model S, which came four years after the very-low-volume Roadster. The AI already works. Before large language models, robots were trained by very smart people telling the robots exactly what to do. Now, the robots train themselves in virtual worlds. The smart people now work on how to improve training. That mode of operation has already yielded “physical” AI that interacts with the real world.

The biggest holdup is cost and manufacturing. The current generation of humanoid robots costs roughly $100,000 to $200,000 each, and the ability to manufacture at scale doesn’t exist. To go from the equivalent of a 2008 Roadster to a Model 3 in robotics, the cost of AI computing needs to fall, and the entire supply chain needs to be built up. Boston Dynamics has relationships with Alphabet’s DeepMind and Nvidia, while Hyundai, its owner, is an expert at high-volume, high-precision manufacturing and coordinating far-flung supply chains. As a result, Atlas should be available for the home and workplace sooner than many others.

The challenge for investors is playing a technology that is still early in the hype cycle. While two exchange-traded funds— KraneShares Global Humanoid & Embodied Intelligence Index, or KOID, and Global X Robotics & Artificial Intelligence, or BOTZ—were created to capitalize on the trend, they aren’t ideal choices. Two large positions in KOID are the rare earth metals producers MP Materials and Lynas Rare Earths —robots need electric motors and other components that require the metals—as well as auto-parts maker Aptiv and Nvidia for its semiconductors. Nvidia is the largest position in BOTZ, followed by Fanuc and ABB, which make old-fashioned factory robots.

Nvidia is a good option because robots need chips and training, says Ivana Delevska, portfolio manager of the Spear Alpha ETF, or SPRX. Nvidia’s Groot AI robot model, Jetson Thor robot brain, and Cosmos virtual training platform put it in a pole position to supply aspiring robot makers. Robots aren’t a new growth driver, however, but an extension of its current ones. “You are pretty well protected from their base business, and then if and when robotics does materialize, you’ll get the benefit,” says Delevska, adding that she expects robotics to be a $1 trillion market in the next 10 years, with Nvidia serving as its “backbone.”

Robots will also be a tailwind for other chip companies, and suppliers of sensors, actuators, bearings, magnets, motors, batteries, and more, says Jonas. UBS analyst Amit Mehrotra points to multi-industry stocks as a possible beneficiary. He has Buy ratings on Honeywell International, Zebra Technologies, Cognex, and Teledyne Technologies, which all make industrial automation parts that would be used in robots, as well.

Mobileye Global is also worth a look. The self-driving-car technology company bought robot start-up Mentee for $900 million on Jan. 6, and the stock could use a boost. Shares declined 3.3% on Jan. 22 after Mobileye gave relatively disappointing guidance for 2026 due to concerns about the company’s autonomous-driving business. “While the acquisition introduces risk and near- to medium-term dilution, the strategic upside is significant,” says Canaccord analyst George Gianarikas, who has a Buy rating and $24 price target on the stock. “The humanoid sector is increasingly competitive, with a surge of American and Chinese start-ups; however, Mobileye’s proven autonomous technology offers a distinct advantage.”

Auto makers, though, might be the best place to look for robot bets. They have sensors, actuators, batteries, metals, and the manufacturing know-how to build robots. Tesla is the most expensive stock in the S&P 500 index —it trades for 200 times estimated 2026 earnings—and is valued at $1.5 trillion because it’s viewed as an AI/robotics stock these days, not an auto maker. While robots and robo-taxis generate little revenue and earnings, the combination of robot potential, Musk’s history, and lack of alternatives means that investors have given it the benefit of the doubt, though new money should wait for a better entry price.

Hyundai is charting a course from pure-play auto maker to an embodied-AI company. It owns 88% of Boston Dynamics, a hidden asset that isn’t yet generating earnings or cash flow. Currently valued at about $25 billion, Boston Dynamics accounts for about 25% of the company’s $86 billion market value. Excluding the Boston Dynamics stake, Hyundai stock trades for about 7.5 times its estimated 2026 earnings, above the average of six times over the past five years. A sustainably higher multiple could be in the offing if the company can go from a slow-growth auto maker in a competitive and cyclical business to a maker of robots.

Even General Motors and Ford Motor could morph from sluggish car companies into something far more dynamic. After all, GM installed the first industrial robot, Unimate, in 1961 to unload a material press. In another 65 years, robots will be building more of the car, and probably themselves, too.

Legacy auto makers won’t be responsible for the AI brains or training, but their manufacturing and supply-chain expertise will be needed to drive the robot revolution. Ultimately, it’s an opportunity that could one day dwarf the auto business—and a chance to escape the purgatory they have been in for decades.

“We do not have the right supply chain for robotics [yet]; we have pieces,” says Ayanna Howard, a senior member at the Institute of Electrical and Electronics Engineers. “The closest would be cars—cars have sensors, they have actuators, they have batteries, they have metal.”

And everything needed to be a player in the robot race.

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