Category: 3. Business

On this episode of The Long View, Callie Cox, chief market strategist at Ritholtz Wealth Management, discusses how she helps investors suss out signal from noise, how AI is affecting the market and economy, the role of social media on investor behavior and psychology, and how she herself has learned to become the investor she is today.

Here are a few highlights from Cox’s conversation with Morningstar’s Christine Benz and Ben Johnson.

How Market Concentration Around AI Stocks Could Be Affecting Your Portfolio

Ben Johnson: Callie, I want to stick with the topic of AI and maybe just more broadly investors’ enthusiasm for all things AI and by extension, technology, the Mag Seven tech stocks. We’re recording this conversation on Oct. 29, Nvidia has just become the first-ever $5 trillion market-cap company. I checked it’s actually in and of itself bigger than the market cap of the entire Japanese stock market at this point, which is interesting. But is this an area where maybe the spend has gotten a little too loose? Expectations have gotten a little too lofty? You wrote about this recently on your own outlet, where your prolific OptimistiCallie and finished that piece with what I thought is really the money chart in this area, which just shows the increasing gap between the representation of these big firms with respect to their price representation in big indexes and then their contribution from an earnings perspective. And generally speaking, those things have tended to move in lockstep historically, but that gap indicates that maybe investors are getting ahead of themselves. What are you worried about, or maybe why should we not be worried?

Callie Cox: So, here I think you have to think about AI in concept and in theory and in practical ways to apply to your portfolio. So obviously, AI, again, a compelling story, I’m not an AI doomer. I think AI is going to have a lot of benefits for society and is already injecting those benefits into society, even if we’re not seeing it come through in economic data and profits just yet. But I think that’s what investors are struggling with right now. We hear all these exciting things about AI, all these exciting projects that seem to be happening among the tech hyperscalers, among infrastructure firms and data centers. But we’re not seeing the payoff there yet. It’s really easy to hear about a story and then dream about where it could go. But there isn’t much data to show what this could mean.

And right now, the data that we’re getting is how much these companies are spending on these projects, which I want to be clear: Tech companies are supposed to spend money on ambitious projects. They are tech companies. You’d rather them do that than pay you back in a dividend, which some tech companies do. But that’s not their main strategy. That’s not their main strategy. They are money spenders.

But at this point, we’re seeing spending ramp up among the biggest tech companies so quickly at a time when profit expectations are high, and valuations, think price/earnings ratio are also quite high. So, you have to wonder what the give and take is there. And I explain this in my newsletter. If these companies are spending so much money on AI projects that have yet to flow into profits and free cash flow, then your perception of these companies as Wall Street’s golden child of profitability and these big spenders that are trying to establish their next business strategies don’t really fit with each other. High spending, spending at these levels will ultimately cut into free cash flows. For some companies more than others, they’ll cut into cash on hand. They’ll force these companies to raise debt and then suddenly you can’t call tech the quality part of the market anymore. And it’s really hard to suss out how much of this valuation or how much of the prices they trade at are because they’re considered the quality profit generators in the market. So that’s the theory.

Practically, when we have clients who say, OK, well, what are you going to do about that? Like, interesting idea. Why does it matter to me? Practically, this is a sign for investors to look at value. It’s a sign to take profits, and I’m not talking about every tech stock you hold here. I’m talking about very gradual moves. But it’s a time to think about taking profits within tech and other highly valued stocks, especially knowing that underneath these tech companies we’re contending with a slowing economy that’s flashing some worrying signals at the moment. Take some profit in your tech stocks, rotate them into other value stocks, don’t divest completely from the stock market because that’s your engine to building wealth over time. Just be smart and practical about where you’re allocating your money. Maybe set some sector targets, for example, that help keep your portfolio looking like the amount of risk that you’re comfortable taking for your goals. And just be grounded about where we are right now. AI, again, incredibly compelling. You want exposure to it. But maybe things have gotten a little out of hand, and you can adjust and bubble-proof your portfolio to respond to that.

What Assets Should Investors Add to Their US Equity Portfolio?

Christine Benz: Well, I wanted to follow up on that because when we look at fund flows, we see more and more investors are getting their US equity exposure through just a total market index where they are obviously very concentrated in those names that you think maybe they ought to be a little bit cautious about right now. So, what would be the other assets that you would add to a US equity portfolio? It sounds like value loud and clear, but how should investors be approaching their US equity exposure?

Cox: This is such a good question because like you mentioned, a lot of investors are passive index fund investors. I see it all the time in my work. One thing you should know, and it’s hard to put your finger on an exact number here because every ETF is different and they follow different strategies or every fund is different. But what you should know, if you’re invested in a no-fee hypothetical S&P 500 fund that just tracks the market caps of the stocks in the S&P 500, about a third of your portfolio is invested in these Magnificent Seven stocks at the moment. You are very, very tech-heavy whether you realize it or intend to be or not. And just having that piece of information can help inform you as to what you need to add in or what you need to tweak in your portfolio to make it a little more attuned to your own risk tolerances.

What you do there is ultimately up to you. There are value funds that you can look at. There are dividend stock funds you can look at. There are defensive funds you can look at. So, what that could look like in your portfolio is maybe trimming a little bit off the top of those S&P funds or those passive funds to an allocation that you pinpoint beforehand. I wouldn’t do this by feel. Maybe rotating it into more defensive and value stocks. As time goes on using calendar-controlled strategy, I’ll sell a little bit this month and rotate it into this fund. And also considering that there are assets outside of the stock market. There are bonds, there are gold, there’s cash. If you have short-term spending needs coming up, then it can’t hurt to take some chips off the table and sell a little bit of your S&P fund to move it to cash to pay for those spending needs. But just know that you have a lot of options outside of the S&P fund, and right now, the S&P by nature it’s getting riskier at a time when the economy is slowing. So, it’s probably smart to be a little more tactical and active on that front.

Saudi Arabia has invested billions to transform its economy, attract global companies, and build a high-skill, high-productivity labour force. But a new Pearson report exposes a quiet threat undermining that progress: gaps in career and learning transitions are costing the Kingdom SAR 62 billion ($16.5 billion) in lost earnings every year for Saudis alone—and SAR 196 billion ($52 billion) when including expatriates.

That’s roughly 4.2% of GDP, slipping through the cracks of inefficient education-to-work pathways, prolonged job transitions, and slow-moving reskilling systems.

For a country where 70% of the population is under 35, this isn’t just an economic issue—it’s a long-term competitiveness challenge.

The hidden cost of broken transitions

Pearson’s “Lost in Transition: Fixing Saudi Arabia’s SAR 62 billion ‘learn-to-earn’ skills gap” maps the friction points across three stages: entering the labour market, shifting roles, and adjusting to technological disruption. Each stage underscores a structural issue that necessitates resolution to sustain Vision 2030’s labor-market objectives.

1. Automation is already expensive

Automation-related disruption represents around half of total losses. With 23% of Saudi jobs at high risk, the drag on productivity is measurable: shorten reskilling time by just 20%, and you inject SAR 6.3 billion ($1.7 billion) back into the economy every year.

This is the part where labour market theory meets reality. No economy can absorb automation shocks without agile reskilling pipelines. Saudi Arabia has the demand — but not yet the speed.

2. Graduates take nearly 40 weeks to land a job

The transition from school to work remains slow and costly. High school and university graduates in the Kingdom spend almost 40 weeks searching for employment. This lag mirrors patterns in other large markets but has deeper implications for Saudi Arabia: population growth and Vision 2030’s ambitious nationalisation targets make every lost week count.

The mismatch is clear. Universities and training institutes are still producing graduates whose capabilities do not align with digital, technical, or applied roles that employers increasingly need.

3. Workers who lose jobs stay out of work for almost a year

On average, displaced Saudi workers remain unemployed for 11.3 months, and 40% remain without work for more than a year. These long unemployment spells aren’t just personal setbacks — they erode skill relevance and widen the reskilling gap, compounding the SAR 62 billion annual loss.

4. Youth unemployment remains stubborn

Youth unemployment sits close to 15%, and demographic pressure is intensifying. The population aged 20–24 is projected to rise from 2.69 million in 2025 to 3.22 million in 2030.

More young people entering the market + slow transitions = escalating structural friction.

What this really means for Vision 2030

The Saudi labour market is undergoing one of the fastest transformations globally. However, the system connecting education, employers, and industry remains fragmented. The Kingdom is racing to localise jobs in tourism, logistics, manufacturing, creative industries, and tech—but the pipeline feeding these roles is not synchronised with real market demand.

The SAR 62 billion figure is not a result of low ambition. It’s the cost of misalignment.

If Saudi Arabia wants to meet its productivity and employment targets, the country must shift from qualification-centric learning to skills-centric learning, from reactive recruitment to predictive workforce planning, and from linear education models to continuous upskilling ecosystems.

Five moves that can close the gap fast

Pearson’s recommendations align with what labour market analytics and regional employers have been calling for. Here’s what must happen next:

1. Diagnose skills needs with precision

Saudi Arabia has the chance to lead globally in skill intelligence. Identifying priority roles, tasks, and competency gaps — at scale — will allow educators and employers to co-design targeted programmes instead of generic curricula.

2. Accelerate transitions with applied learning

Internships, apprenticeships, and industry mentorships should be the norm, not the exception. Early work exposure shortens job search durations and creates immediate pathways into hiring pipelines.

3. Update curricula to reflect real-world demands

Technical, vocational, and university programmes need tighter integration with industry, especially in AI, data, cloud, logistics tech, advanced manufacturing, and hospitality. The half-life of skills is shrinking; curricula can’t move on multi-year cycles.

4. Expand structured work placements

Well-governed partnerships between universities, colleges, and employers can reduce frictions between graduation and hiring. Applied training matters more to employers than theoretical mastery.

5. Build a national labour market intelligence engine.

Investing in platforms that give real-time visibility into job openings, skill requirements, and market demand will significantly reduce mismatches. Matching supply to demand is a data problem — and Saudi Arabia is well positioned to solve it.

A generational opportunity

Naseem Tuffaha, Chief Business Officer at Pearson, captured the crux: “Saudi Arabia’s youth-driven economy holds tremendous potential, but inefficient transitions are costing SAR 62 billion annually while nearly a quarter of jobs face automation risk.”

That potential is real. The Kingdom has the demographic advantage, government momentum, and investment power to build one of the most dynamic labour markets in the world.

But achieving that requires a realistic mindset: transitions matter as much as qualifications, and skills matter more than titles. Fixing the learn-to-earn pipeline is not a policy exercise — it’s a productivity strategy.

Final thought

Saudi Arabia is not facing a skills problem. It’s facing a timing problem. People are learning, but not at the right moments or in ways that match what employers need. Repairing this disconnect could unlock tens of billions in productivity and give young Saudis the career mobility that Vision 2030 promises.

The Kingdom is building one of the world’s most ambitious economic transformations. Closing the transition gap is how it makes that transformation stick.

News publishers just cleared a key hurdle against Cohere in a copyright fight over AI-generated “substitutive summaries” of their reporting.

If you’re only keeping a loose eye on the fifty-plus AI copyright lawsuits now crawling their way through federal courts, you may have missed an important new ruling last week out of the Southern District of New York. It didn’t feature photorealistic superheroes, deepfaked celebrities, or anything bright and shiny enough to rack up shares on social media. Instead, it involved something far more mundane—but no less consequential for media organizations: AI-generated reproductions of news articles. And in a case that may help shape how freely AI companies can repackage internet news content, Judge Colleen McMahon held that “substitutive summaries”—outputs that mirror not just the underlying facts but the expressive structure and journalistic storytelling choices of the originals—may plausibly infringe copyright. That was enough to let the claims move forward.

The lawsuit, Advance Local Media LLC v. Cohere Inc., was filed in February 2025 by fourteen major news and magazine publishers including Forbes, Condé Nast, the Los Angeles Times, and The Atlantic. They allege that Cohere—a Canadian AI company behind the “Command” family of large language models—reproduces substantial portions of their works, sometimes near-verbatim, while bypassing publisher paywalls. They also claim that Command generates “hallucinated” content falsely attributed to their brands. Altogether, the complaint identifies more than 4,000 allegedly infringed works and includes 75 output examples that, the publishers say, closely track the structure, sequencing, tone, and expressive choices of the original reporting.

Last Thursday, Judge McMahon denied Cohere’s motion to dismiss (read order here), holding that the publishers had adequately alleged direct infringement, secondary infringement, and Lanham Act violations. Cohere didn’t challenge—at least not at this stage—allegations about training-data copying, retrieval-augmented generation (RAG), or outputs that reproduce verbatim or near-verbatim excerpts of the publishers’ works. Instead, the company zeroed in on the plaintiffs’ “substitutive summary” theory, arguing that any overlapping expression was minimal and that Command’s outputs were nothing more than factual digests.

Judge McMahon wasn’t convinced. “It is not possible to determine infringement through a simple word count,” she wrote; “the quantitative analysis of two works must always occur in the shadow of their qualitative nature.”

When Does a Summary Cross the Line?

The Cohere ruling comes as courts nationwide are grappling with “summary-style” AI outputs. Traditional summaries distill facts from longer works, and copyright doesn’t protect facts themselves. But it does protect the expressive arrangement of those facts: choices about structure, emphasis, pacing, and narrative arc that turn basic reporting into storytelling.

Long before AI, courts recognized that abridgments can infringe when they replicate those expressive elements. In 1999’s Nihon Keizai Shimbun v. Comline Business Data, the Second Circuit held that while defendants had “every right to republish the facts” contained in news articles, abstracts could still infringe when they tracked the original “sentence by sentence, in sequence” using the same structure and organization. Line drawing proved tricky even then: one abstract escaped liability by reporting the same facts “in a different arrangement, with a different sentence structure and different phrasing.” Another avoided infringement by copying only 20% of the original. Still, the court cautioned that “it is not possible to determine infringement through a simple word count”—a principle Judge McMahon invoked twenty-five years later in Cohere.

Recent AI cases show courts applying those same principles to machine-generated content. In an April 2025 ruling in New York Times v. Microsoft, Judge Sidney Stein dismissed claims by the Center for Investigative Reporting (CIR) alleging that Copilot’s bullet-point “abridgments” infringed their articles. The court found that those reorganized and skeletal summaries weren’t substantially similar, qualitatively or quantitatively, to the original CIR articles as a matter of law.

But just two weeks ago, the same judge allowed fiction authors’ output-based claims against OpenAI to proceed, finding that ChatGPT’s narrative summary of A Game of Thrones plausibly crossed into protected expression because it “conveys the overall tone and feel of the original work by parroting the plot, characters, and themes of the original.” In a blog post, copyright scholar Matthew Sag called the ruling “a fundamental assault on the idea expression distinction,” warning that if a 580-word ChatGPT summary infringes a 694-page novel, “thousands of Wikipedia entries” could find themselves in copyright crosshairs.

News articles present a unique challenge: they’re much shorter than novels—making wholesale copying easier—but contain far more unprotectable factual content. The question isn’t whether plot and characters were copied, but whether the journalist’s particular way of presenting facts—the structural choices, emphasis, and narrative flow that distinguish reporting from a police blotter—was appropriated. When summaries adopt those expressive choices, they may cross into infringement territory. Still, determining when exactly that’s happened isn’t always an easy task.

Why Cohere Matters

Cohere is one of the first major decisions to sustain a text-based output copying claim involving non-verbatim news summaries. For months, AI companies have pointed to Judge Stein’s dismissal of the CIR claims as proof that summary theories were DOA. Judge McMahon just showed the door is still very much open.

More broadly, Cohere continues a trend away from the abstract fight over AI training data to the more concrete issue of outputs. Whatever happens with fair use defenses around training, AI companies face real exposure when their outputs too closely mirror protected expression. For developers marketing news-oriented applications or research assistants, the message is clear: “summaries” aren’t a safe harbor but a fact-specific minefield requiring careful navigation.

A Tale of Two McMahon Rulings

It’s worth noting that Judge McMahon has now ruled on both ends of the AI-news spectrum. Last year I wrote about her dismissal of Raw Story Media v. OpenAI, where digital news outlets sued under the DMCA for removal of copyright management information. Without registered copyrights, they couldn’t bring infringement claims, only DMCA claims for CMI removal. And without evidence that ChatGPT actually disseminated their articles, they couldn’t show concrete harm for Article III standing. The case was dismissed.

The Cohere publishers learned from that failure. They came to court with registered copyrights, allowing them to bring full infringement claims. They also brought concrete examples of allegedly infringing outputs, and it was enough to allow their claims to proceed.

The Bottom Line

To be clear, the publishers haven’t won anything on the merits. They’ve simply lived to fight another day. Cohere will have ample opportunity to push back at summary judgment, where substantial similarity becomes an evidentiary question rather than a pleading exercise. Fair use will also loom large, especially for outputs that are shorter, more factual, or meaningfully transformative. But for now, Judge McMahon has made one thing clear: expressive news retellings aren’t immune from copyright scrutiny.

And in an era where AI companies want to position their models as replacements for traditional news consumption and search engines, the question of when a summary becomes a substitute—and when a substitute becomes infringement—is only going to get more pressing.

As always, I’d love to know what you think. Drop a comment below or @copyrightlately on social. And if you prefer verbatim reproductions over “substitutive summaries,” here’s a complete copy of Judge McMahon’s ruling in Cohere.

View Fullscreen

Former U.S. Secretary of State Mike Pompeo has joined the advisory board of Ukraine’s leading defense company, renowned for its long-range drones capable of striking targets deep inside Russia, as a corruption investigation continues.

In an effort to enhance its international reputation, Fire Point is establishing a new factory in Denmark and bringing prominent industry figures on board. It also aims to expand its operations to produce battle-tested cruise missiles, with plans to more than double its current capacity.

However, public scrutiny remains intense during an ongoing corruption investigation. Fire Point’s executives insist they have nothing to hide and are operating under strict martial law protocols, even commissioning an independent audit to appease investigators. Critics, however, question the company’s opaque origins and the monopoly of its contracts with the Defense Ministry, and point to alleged links to President Volodymyr Zelenskyy’s notorious associate Tymur Mindich, who is implicated in a major corruption scandal.

“In general it’s good they are working on this,” said Iryna Terekh, Fire Point’s chief technology officer of the investigation. “We completely support, as a company, the fact that this investigation is happening.”

Terekh said Fire Point has commissioned a major international firm to conduct an independent audit of its pricing and production to quell concerns. The investigation by anti-corruption organizations, launched a year ago, is still ongoing, she said. “We will be waiting for the results to come.”

The Associated Press was given exclusive access to a factory in Ukraine where its cruise missile, known as the Flamingo or FP-5, is assembled. The AP was given access on the condition the exact location is not named, due the risk of Russian attacks.

Fire Point, which rose to prominence after initially being relatively unknown following Russia’s full-scale invasion of Ukraine in February 2022, now reports around $1 billion in revenue this year. It is also constructing a factory in Denmark to manufacture essential rocket propellent.

In the meantime, the company is forging ahead with plans to expand.

The company launched an advisory board and named Pompeo as a member on Nov. 12, executives told AP. “It’s a big honor for us,” Terekh said, speaking from the factory floor. “We decided that since we are growing into a big international company, we have to ensure we are following the clearest and best corporate standards.”

Another three individuals will join the board. “We are rising as a company and we want a wise adviser board to help us establish this work,” said Terekh.

U.S. Special Envoy to Ukraine Keith Kellogg also visited one of Fire Point’s factories during his last visit, executives said, in a visit that included other Ukrainian defense technology companies as well.

Building on the success of its deep-strike drone, the FP-1, which AP was granted exclusive access to view in August, the company is now planning to ramp up production of its cruise missiles. They are also in high demand among Ukrainian forces as Western missiles remain hard to access in sufficient quantities to debilitate Russian capabilities.

Fire Point has successfully tested Flamingo on the battlefield at least four times, company executives said. In late August it was used to strike an FSB base in Armiansk in the occupied Crimean Peninsula. This week, the missile was used to strike targets in the Russian city of Oryol. The company did not provide its current production capacity, citing security concerns.

Production is going according to plans, company executives said, without elaborating on precise figures for security concerns.

On the factory floor, dozens of hollowed hulls of missile frames lay scattered. These are made with carbon fiber, a material better suited to eluding Russian radars than aluminum, Maksym, the head of design told the AP. He spoke on condition that only his first name be used for security reasons.

Fire Point is a significant beneficiary of the so-called Danish model, a financing mechanism spearheaded by Denmark, in which foreign governments directly fund Ukrainian defense companies, rather than procuring weapons from their own industries to send as aid. A factory to produce solid rocket fuel for missiles, including the Flamingo, is being established in Denmark.

“They did a great job helping us to secure production of critical components,” Terekh said of Denmark’s support. “Our factory in Denmark is dedicated to solve a bottleneck with solid rocket propellent.”

But the company’s rapid rise has been marred by an investigation by Ukraine’s anti-corruption watchdogs.

Authorities are examining whether Fire Point inflated component prices or drone quantities in Defense Ministry contracts for its main weapon, the FP-1 drone, and are also scrutinizing potential links between the company and Mindich.

Anti-corruption agencies have said they were not investigating the Flamingo missile.

Lawmakers raised an issue with Fire Point because of its apparent monopoly over deep strike drones, its ability to garner lucrative contracts despite being relatively unknown, and obscurity over its ownership. Its legally listed owner is Yehor Skalyha, who maintains connections to the entertainment industry, just like Mindich.

Anti-corruption watchdogs have not released the findings of their investigation. Company founder Denys Shtilerman told AP that he is the majority owner, with Skalyha owning 2%.

Shtilerman said he has met Mindich on several occasions, but the company denies the business owner has any links to their company.

On Sunday, engineers from the company painted a pink flamingo on one Flamingo cruise missile whose purchase had been made by a crowdfunding campaign by a Czech organization, Weapons to Ukraine. Each missile costs approximately $500,000.

The amount was raised in two days, said Jan Polak, a member of the organization. The same organization managed to fund the delivery of a Black Hawk helicopter to Ukraine’s military intelligence, Polak said. “We feel that they are fighting for us,” he said of his organization’s reasons for funding the procurement of missiles to strike Russian targets.

The current design of the Flamingo missile is a compilation of old Soviet weapons and new techniques. Engines were sourced from old Soviet jets, for example.

Testing and fine-tuning is a constant process, Maksym said. “As of now we are still doing training launching, because our rockets were manufactured just six months ago. Right now, we are training, but we are training on objects in the territory of Russia and Crimea,” he said.

Workers conducted a mock run of a launch with a missile, this one painted black, that will be used in a future mission, he said. Workers drove in a truck that concealed the weapon.

“We are studying, doing all we can to hit targets as far as we can,” he said, adding that finding ways around Russian radar systems and electronic warfare remained an ongoing challenge. “We are learning from each launch to work on mistakes.”