It’s been several months since we returned from Hawaii, and surprisingly, my FOMO about the AI tech boom has faded. Sure, I still don’t have a job paying me gobs of money as AI CapEx surges higher, but that’s OK. Instead, I’ve allocated enough money to AI investments to where I no longer feel the need to chase the industry from the inside.

You see, my real fear isn’t missing out on another AI unicorn. It’s raising kids in a crueler and harsher world—one where, partly because of their identities, they get rejected from every top-50 university they apply to. Then, by the time they graduate from a so-so university, entry-level jobs have largely been automated away by AI.

This is not some far-off dystopia. CEOs of every major company are openly exploring or adopting AI. They’re implementing hiring freezes, slashing jobs, and reducing headcount by the thousands. Accenture cutting 11,000 jobs and Lufthansa cutting 4,000 jobs due to AI aren’t outliers, they’re harbingers. Anyone paying attention can extrapolate how dire things could be 15–18 years from now, when my children are entering the workforce.

As an investor, it’s key to forecast the future. As a parent, it’s key to forecast potential misery for your children. In both cases, if you forecast even halfway properly, you’ll likely end up wealthier, calmer, and better prepared.

Jobs Are Vanishing Due To AI

Take a look at the S&P 500’s recent performance in red compared to Total Job Openings in white. Notice the inflection point: investor optimism as AI promises profitability due to increased productivity, while job openings continue to crater.

As an investor, my hope is the S&P 500 keeps climbing—history suggests it will over the long run. As a parent, my fear is that Total Job Openings will continue to collapse to 2009 levels or worse. I clearly remember the 2008-2009 Global Financial Crisis—that’s when I launched Financial Samurai after the seventh round of layoffs at Credit Suisse. Fear was my motivator then too.

At the pace we’re going, by 2032 we could easily see a scenario where the S&P 500 is at a record high, but job openings match the lows of the last crisis.

And yet, after privately consulting with dozens of readers this year, I don’t think most Americans realize what’s coming. Sure, I may sound fatalistic, but a large part of my wealth has come from recognizing and investing in long-term trends. And the AI bulldozer is real.

Find Your Minimum AI Investment Comfort Point

Just as there’s a “Minimum Investment Threshold” where work becomes optional and you can stop stressing about office politics, there’s also a “Minimum AI Investment Threshold” where you can stop worrying quite so much about AI wrecking your career or your children’s livelihoods.

This Minimum AI Investment Threshold is conceptually similar to your Coast FIRE number. But unlike Coast FIRE, which is too dangerous for most people to rely on, the Minimum AI Investment Threshold is an active hedge, not a passive hope.

Here’s how to calculate yours:

Plug into an AI tool. Use a compound interest calculator or your favorite AI LLM to crunch the numbers for you.

Forecast the timeline. Estimate when your job will be eliminated due to AI, or when your children will graduate high school or college and enter the job market.

Estimate future living expenses. Take today’s basic living expenses and project them forward using a reasonable inflation rate (2%–4%).

Choose your cushion. Decide how many years of basic living expenses you’ll want saved in AI investments—pick anywhere from 1 to 10 years.

Discount to today’s dollars. Use a discount rate of 2%–8% (lower if conservative) to calculate how much you’d need to invest now.

Example Using Our 8-Year-old Son

Let’s take my 8-year-old son. In the year 2040, 15 years from now, he’ll be 23 and a new college graduate from a regular university.

An income that could cover his basic needs is $40,000 a year in today’s dollars—equivalent to $62,319 at a 3% annual inflation rate in 2040.

I estimate it may take him 2–4 years of job searching to realize that his dreams of clicking buttons to optimize ads for big tech companies are out of reach. At that point, he’ll probably have to take a trades job to make ends meet. (Electricians, plumbers, and general contractors should be in huge demand given all the datacenters being built.)

So, I need to have about $125,000–$250,000 ($62,319 X 2 – 4 years) set aside for him by the year 2040 to give him that cushion.

Here’s how much I’d need to invest today to reach $125,000–$250,000 in 15 years, depending on the discount rate:

Based on a realistic worst-case scenario—him taking 4 years to realize his hopes and dreams won’t materialize—at a 2% discount rate I’d need about $185,754 invested today. That way, by the time he’s 23, I’ll have secretly set aside $250,000 in AI investments alone to help him survive.

It is vital all parents NOT tell their children exactly how much they are saving and investing for them. You don’t want them to become soft and develop an entitlement mentality.

AI Investing as a Psychological Hedge

Some of you may be scratching your heads: why invest in AI at all if I’m only assuming 2%–8% annual returns? With such modest expectations, I could just invest mostly in Treasury bonds yielding 4%–5% sprinkled with some stocks.

I hear you. But the point isn’t just the math. It’s the psychology.

Will you diligently invest for your or your children’s future specifically to hedge against AI? Maybe, maybe not. Further, I’m trying to be conservative in my assumptions.

By specifically investing in the very companies that may make your life and your children’s lives harder, it becomes easier to actually save and invest for the future. You now have a clear why behind your delayed gratification. And when you have a why, almost anything is possible.

When you start viewing AI as an unstoppable beast that could run you and your children over, you get more motivated to invest in AI companies.

Fear and Responsibility Drive Me to Invest

In 2025, driven by fear of a dire future and a strong sense of responsibility to protect my kids, I embarked on a new quest. I decided to invest the Minimum AI Investment Threshold so I could reduce my worry and even start rooting for the very technology that could harm my children.

The first step was opening a new Fundrise Venture account earmarked for my children with $26,000 in early August. (There was, and still is, a promotion where if you invested over $25,000, you got $500 for free invested in their Flagship real estate fund.)

Then, as my Treasury bills matured, I kept funneling between $15,500–$50,000 at a time into Fundrise Venture to hit my Minimum Investment Threshold. Every transfer I made into my account made me feel better.

Hedged Against Whatever Happens

Only time will tell whether investing $190,000 in 2025 in names like OpenAI, Anthropic, Databricks, Anduril, Canva, Ramp, and dbt Labs will pan out. If they do, I’ll be thrilled. The $190,000 could grow to anywhere from $256,000 to $2.87 million, based on a 2%–20% annual return.

That means one child will either have all his or her expenses covered for four years of job-hunting or perhaps be set for life. They can pursue careers they want rather than careers they need.

Alternatively, I could potentially lose 80% of my money and end up with just $38,000 after 15 years because AI turned out to be an overhyped dud. Maybe CapEx spend is too high for the profits. Maybe the world realizes human oversight is more essential than ever—Jevons’ Paradox at work.

In that scenario, I’d be even more thrilled if both my children found livable-wage jobs they enjoyed. Because as parents, it is our responsibility to raise children to be self-sufficient adults. Needing to still depend on your parents after age 25 slowly chips away at your sense of worth.

Without the mission of protecting my kids from AI, there’s no way I would have invested $190,000 in risk assets like the S&P 500 in just two months. Most of the money came from risk-free Treasury bonds after I sold my old house earlier in 2025. In the past, I’ve dollar-cost averaged more slowly, or invested in structured notes with downside protection when valuations are high.

But once I reallocated the money from me to my children, I extended the investment time frame from “right now” to 15 years in the future. And when you have such a long runway to invest, it becomes easier to stomach risk assets.

Asset Allocation Matters Too

Finally, when deciding your Minimum AI Investment Threshold, compare that target number to your overall asset allocation. The comparison can be to your total investable capital or total net worth.

Personally, I have a target of investing up to 20% of my investable assets in alternative investments such as venture capital. Not only am I in an open-ended venture fund that invests in AI, I’m also invested in four other closed-end VC funds, and I’m considering two more that all have AI investments.

Sure, the Yale and Harvard endowments have ~40% of their assets in private equity or alternatives. But you don’t have the size, influence, or edge of a multi-billion-dollar endowment. For the average DIY investor, allocating up to 20% in alternatives is plenty.

The older (and hopefully wealthier) you get, the more important proper asset allocation becomes to ride out volatility. Review your goals, run new financial projections, and stay disciplined. It’s easy to get caught up in hype, especially in a bull market. But nothing good lasts forever.

No More AI FOMO

I’m no longer bummed I don’t have a job at a hot AI startup growing triple-digits a year. It felt like a waste not grinding it out while living in AI central, San Francisco. I’m also less bummed that AI is stealing my content on Financial Samurai and not providing a proper link back.

But now that I’ve reached the Minimum AI Investment Threshold for both kids, I’m more at peace.

It feels great to invest in hungry founders and employees working 60+ hours a week for fortune and glory, while I play pickleball during the day and write on Financial Samurai. I’m grateful to be investing in AI near the beginning of the revolution. Our young children aren’t as lucky, which is why it’s up to us to invest for them.

So, for all you AI employees out there, keep grinding and enjoy the ride. You could make enormous fortunes over the next ten years, and I’ll be grateful if you do!

Readers, how are hedging against AI destroying the livelihoods of your children? Do you think most people are aware of the risks AI poses for their job security? What are some other things we are doing to help our children thrive in an AI world?

Easy Ways To Invest In AI

If you want exposure to private AI companies, consider Fundrise Venture. The platform owns stakes in names like OpenAI, Anthropic, Anduril, and Databricks. AI is poised to reshape the labor market, eliminate millions of jobs, and dramatically boost productivity. Since private companies are staying private much longer than in the past, it makes sense to allocate some capital to them if you want to capture potential upside before they go public. Fundrise has been a long-time sponsor of Financial Samurai, and I’m personally an investor in their funds.

For public exposure, you can also just buy QQQ or shares of the Magnificent 7—Apple, Microsoft, Google, Nvidia, Meta, Tesla—plus Oracle, which has become a stealth AI play. The beauty of investing is that you don’t need to live in Silicon Valley to participate. From anywhere in the world, you can buy a piece of these companies leading the AI revolution.

That said, don’t forget: there are no guarantees when investing in risk assets. Fast-growing companies can be extremely volatile when downturns hit. For example, Meta lost more than half its value during the 2022 bear market before recovering. Always stay diversified, keep an eye on your asset allocation, and make sure your portfolio matches your risk tolerance.

On Monday, chipmaker Advanced Micro Devices (AMD 23.61%) announced a huge artificial intelligence (AI) strategic partnership with OpenAI, the AI model developer best known for its ChatGPT chatbot. Not only did this news send shares of AMD up a whopping 23.7%, but it also gave a boost to many other AI stocks and the market in general.

AMD’s news came exactly two weeks after its rival Nvidia (NVDA -1.10%), whose graphics processing units (GPUs) dominate the AI chip market, announced a massive deal with OpenAI.

Image source: Getty Images.

Advanced Micro Devices-OpenAI strategic partnership

The AMD-OpenAI strategic partnership involves AMD supplying 6 gigawatts of its Instinct series GPUs to power OpenAI’s next-generation AI infrastructure. The first 1 gigawatt deployment of AMD Instinct MI450 GPUs is set to begin in the second half of 2026. That’s the same time frame involved in the Nvidia-OpenAI deal.

Moreover — and this is big for AMD — “AMD has issued OpenAI a warrant for up to 160 million shares of AMD common stock, structured to vest as specific milestones are achieved,” according to the press release. AMD has a total of about 1.62 billion shares outstanding, so 160 million shares is about 10% of total shares.

For context, before the deal was announced, AMD had a market cap of about $267 billion. Ten percent of that is $26.7 billion.

Putting 6 gigawatts in context

Six gigawatts equates to a ton of computing power. Here are a couple of stats to put 6 gigawatts of power in context:

• New York City’s average power demand is about 6.5 gigawatts, and its peak power demand in the summer is roughly 10 to 11 gigawatts.
• Six large-scale nuclear reactors have a power output of about 6 gigawatts.

Recap of the Nvidia-OpenAI AI deal

On Sept. 27, Nvidia announced its massive deal with OpenAI. The highlights of this strategic partnership:

• The companies plan to deploy at least 10 gigawatts of Nvidia systems for OpenAI’s next-generation AI infrastructure.
• The announcement stated that the systems will be used to “train and run [OpenAI’s] next generation of models on the path to deploying superintelligence.” [Emphasis mine.]
• The first phase is targeted to come online in the second half of 2026 using the Nvidia Vera Rubin platform.
• Nvidia plans to invest up to $100 billion in OpenAI as the new Nvidia systems are deployed.

What are the broader implications for the AI space?

This seems like a win-win deal for both AMD and OpenAI. OpenAI secures a large supply of AI-enabling GPUs over multiple years. This is no small thing, as GPUs are in great demand, so supply has been tight. That’s especially true of Nvidia’s GPUs, but no doubt, also true to some extent for AMD.

On AMD’s part, it secures a huge multiyear customer for its GPUs, and it is poised to get a hefty inflow of cash as OpenAI buys up to 10% of AMD’s shares. The partnership “is expected to deliver tens of billions of dollars in revenue for AMD,” CFO Jean Hu said in the release. Moreover, it’s “expected to be highly accretive to AMD’s non-GAAP [generally accepted accounting principles] earnings per share, ” she added.

Taken together with the recent Nvidia-OpenAI humongous AI deal and other big deals in the space, there are positive implications for the broader AI market.

The main implication, in my opinion, is that these massive AI chip and infrastructure deals should accelerate the race to move beyond generative AI to achieve artificial general intelligence (AGI) and then artificial superintelligence (ASI), as I wrote about after the Nvidia-OpenAI deal was announced. Nvidia and AMD should be two of the big beneficiaries of this race, as companies rush to buy even more of their AI-enabling GPUs.

The lack of growth capital in Europe is such a persisting issue that some early-stage firms have taken the matter into their own hands. London-headquartered firm Notion Capital is one of them.

In 2017, Notion Capital was one of the first in Europe to close an opportunities fund to provide its portfolio companies with follow-on capital. Now, it has closed a $130 million growth fund, nearly twice the size of its previous one, that will also invest outside of its portfolio, TechCrunch learned exclusively.

U.S. VCs that used to fill the growth capital gap currently tend to focus more on their own market, said managing partner Stephen Chandler, noting that “opens up an opportunity for European firms like ourselves to make up some of that difference and be real European champions.” 

Some of the European companies Notion intends to “champion” from its new Growth Opps III fund are tied to the growing demand for more sovereignty, including those specializing in defense and supply chain logistics. But like many, the VC firm is also drawn to AI, which Chandler sees as a super cycle causing “a profound shift in the way that software is delivered and consumed.”

Notion Capital won’t invest in the infrastructure layer such as large language models. Instead, the firm sees opportunities in the application layer that will “massively increase” the size of its market, Chandler said. While Notion’s flagship fund has historically been known for its strong penchant for SaaS, cloud, and fintech, these will now be AI-infused, and joined by new verticals.

The firm expects to make a dozen investments and has already started deploying its capital from the funds. Deals, to date, include Upvest, a stock trading API out of its early-stage portfolio, as well as external companies Octopus Energy spinoff Kraken, and Nelly, a startup that builds software and financial products for the medical sector, according to Notion Capital.

To give itself some “robust objectivity,” in Chandler’s words, follow-on deals will be conducted by dedicated growth fund partners who will also “go out and source growth stage opportunities outside of the portfolio.”

One of them is existing Notion Capital partner Stephanie Opdam (on the left of the picture). She will now drive this growth strategy alongside Jessica “Jess” Bartos, formerly a principal at Salesforce Ventures. A U.S. national, Bartos is also Notion Capital’s first external partner hire (previous partners were promoted internally.)

“Because this was a new strategy, we felt we could benefit from external expertise at that growth stage,” Chandler said.

Subsequent growth funds may also be easier to raise. While Europe has suffered from a lack of pension funds investing in venture capital firms, incentives have started to change in several countries, including France with the Tibi initiative and the U.K. with the Mansion House Accord.

Despite its British roots, Notion Capital isn’t solely dependent on the U.K.’s regulatory framework; this latest Growth Opps III fund is denominated in euros and Luxembourg-based. 

To raise this new vehicle, which brings its assets under management to over $1 billion, the firm relied on its existing relationships with limited partners from across continental Europe, the U.K., MENA and the U.S.

“Something like 85% of our money comes from institutions; and within that, we’re very well geographically dispersed,” Chandler said.

But while recent initiatives to mobilize long-term institutional capital  “[weren’t] really a feature in this fund,” he added, “the signs are extremely positive, and that’s great [for] addressing that fundamental problem we started with, in terms of some of the gaps in growth capital we have in Europe.”

“If this finally works out and more LPs participate in growth stage investing, this could translate into more competition for Notion Capital. At least at the growth stage, where it is less established than at the early stage. However, Chandler sees both as a continuum.

“Our real competitive advantage in this growth strategy is leveraging the reach that we have in our early stage strategy,” Chandler said. “Most growth funds don’t have that. They’re out there trying to do all of their sourcing at the growth stage once they put their head above the parapet in terms of scale and momentum.”

In contrast, he said, Notion Capital has many touch points with founders over the years, including through its very active platform team, and is flexible in terms of its check size.

Despite its expanded scope, Growth Opps III’s main asset arguably remains Notion Capital’s portfolio. The firm has invested in more than 150 startups since its inception, including Currencycloud, GoCardless, Mews, Paddle, and Quantum Systems. While some are pre-AI or have been exited, the remaining companies likely include future champions — a track record that should make external companies more willing to take their growth checks, even if growth capital becomes less scarce in Europe.

Google’s parent, Alphabet, reached a $3 trillion market valuation for the first time on Monday, entrenching its place in the ranks of the world’s most valuable companies and signaling the central role of artificial intelligence (AI) in propelling Big Tech’s dominance. In Google’s case, some legal clarity around its monopoly status also helped.

Billionaire Steve Mandel and his hedge fund Lone Pine Capital have been a great one to follow for individual investors. Although some hedge funds have a poor record of underperforming the broader market, Mandel has substantially outperformed the market over the past three years. So, when he makes a move in his portfolio, investors should pay attention.

One thing Mandel did during Q2 was sell off some of his Microsoft shares. Although it wasn’t a massive move, the hedge fund reduced its position by about 5%. Then, Mandel used some of those funds to invest in another promising AI stock that has increased in value by nearly 800% over the past decade.

That stock? Amazon (AMZN -1.16%).

Image source: Getty Images.

AWS is the best reason to invest in Amazon right now

Amazon may not be the first company that comes to mind when you think about AI. Instead, it probably seems more like an e-commerce investment. While that sentiment is true for the consumer-facing portion, the reality is that a large chunk of Amazon’s profits comes from AI-related revenue streams.

The biggest is from Amazon Web Services (AWS), its cloud computing arm. Cloud computing firms are having a strong year, thanks to the massive demand generated by AI workloads. Because more companies can’t justify spending millions (or even billions) of dollars on a data center dedicated to training AI models, it’s far more reasonable to rent computing power from a firm that already has the capacity. That’s the idea behind cloud computing, and it has translated into strong growth for the business unit.

In Q2, AWS’s sales rose 17% to $30.9 billion. That’s strong growth, but it is a bit slower than its peers, Microsoft Azure and Google Cloud, which each grew revenue by more than 30% in Q2. However, AWS is much larger than both of these units, so it shouldn’t surprise investors that AWS is growing at a slower rate. AWS accounted for about 18% of Amazon’s total revenue in Q2, but it made up 53% of its operating profit. That’s because AWS has far superior margins compared to its commerce business units, making AWS a critical part of the Amazon investment thesis.

AWS is experiencing a significant boost from AI, making it a strong stock pick in this space.

But Microsoft is also a solid AI pick, so why is Mandel moving from Microsoft to Amazon?

Amazon’s stock looks more promising over the long term

From a valuation perspective, both companies trade at fairly expensive levels for their growth. However, they’re both priced about the same from a forward price-to-earnings (P/E) standpoint.

AMZN PE Ratio (Forward) data by YCharts

One thing Amazon has going for it that Microsoft doesn’t is the steady upward pressure on Amazon’s margins. Thanks to AWS and its advertising service business units being the fastest growing in Amazon, its margins are steadily improving. Although Amazon’s revenue growth rate appears to be somewhat slow, its operating income growth rate is actually quite rapid.

AMZN Revenue (Quarterly YoY Growth) data by YCharts

This trend still has years to unfold, which is a solid reason to transition from Microsoft to Amazon. I believe this will be a winning trade over the long term, as Amazon’s profits are expected to grow at a significantly faster rate than Microsoft’s, resulting in the stock outperforming its peer over the long term due to their similar valuations.

However, both stocks are still solid AI picks, and you can’t go wrong with either one.

Markets are coming off a monster rally on Friday, when Federal Reserve Chairman Jerome Powell opened the door to a rate cut next month.

Futures tied to the Dow Jones Industrial Average rose 24 points, or 0.05%. S&P 500 futures were up 0.05%, and Nasdaq futures added 0.06%. On Friday, the Dow hit a new all-time high, while the S&P 500 and Nasdaq closed in on their records.

The yield on the 10-year Treasury was flat at 4.256% after diving Friday on rate-cut expectations. The U.S. dollar was down 0.02% against the euro and flat against the yen.

Gold fell 0.13% to $3,413.80 per ounce. U.S. oil prices rose 0.2% to $63.79 per barrel, and Brent crude added 0.15% to $67.83.

Friday’s stock surge came after a big selloff that was led by tech giants, as doubts have grown about the AI boom and how much it will actually help companies.

That’s after a recent report from MIT found that 95% of AI pilot programs at businesses are failing to produce much of a return.

Adding to those concerns were remarks from OpenAI CEO Sam Altman, who drew a parallel between today’s AI frenzy and the 1990s dot-com bubble.

Wall Street’s faith in the staying power of AI as an investment thesis will be put to the test when Nvidia reports quarterly earnings after the close on Wednesday.

The report also comes after Nvidia and AMD agreed to an unprecedented deal where they give the federal government a 15% cut of their chip sales to China.

For now, demand from U.S. companies remains high as so-called hyperscaler tech giants Alphabet, Microsoft, Amazon, and Meta Platforms alone are expected to deploy $400 billion in capital expenditures this year, and most of that is going to AI.

On Friday, the Fed’s preferred inflation gauge is due as policymakers wait and see how much of an effect on inflation President Donald Trump’s tariffs are having.

Earlier updates on the consumer price index and the producer price index were mixed, and analysts expect the personal consumption expenditures index for July to rise 0.2% on a monthly basis and 2.6% on a yearly basis, the same annual rate as June.

But the core PCE is seen climbing 0.3% on a monthly basis and 2.9% on a yearly basis, accelerating from June’s 2.8% annual rate.

Still, some Fed officials, including Powell, have indicated that tariff-related impacts on inflation may be short term and that more attention should go to the labor market, which has shown signs of weakening.

I was not invited to Sam Altman’s cozy dinner with reporters in San Francisco last week (whomp whomp), but maybe that’s for the best. I have trouble suppressing exasperated eye rolls when I hear peak Silicon Valley–ironic statements.

I am not sure I could have controlled myself when the OpenAI CEO said that he believes AI could be in a “bubble,” with market conditions similar to the 1990s dotcom boom. Yes, he reportedly said, “investors as a whole are overexcited about AI.” 

Yet, over the same meal, Altman also apparently said he expects OpenAI to spend trillions of dollars on its data center buildout in the “not very distant future,” adding that “you should expect a bunch of economists wringing their hands, saying, ‘This is so crazy, it’s so reckless,’ and we’ll just be like, ‘You know what? Let us do our thing.’”

Ummm…what could be more frothy than pitching a multi-trillion-dollar expansion in an industry you’ve just called a bubble? Cue an eye roll reaching the top of my head. Sure, Altman may have been referring to smaller AI startups with sky-high valuations and little to no revenue, but still, the irony is rich. It’s particularly notable given the weak GPT-5 rollout earlier this month, which was supposed to mark a leap forward but instead left many disappointed with its routing system and lack of breakthrough progress.

In addition, even as Altman speaks of bubbles, OpenAI itself is raising record sums. In early August, OpenAI secured a whopping $8.3 billion in new funding at a $300 billion valuation—part of its plan to raise $40 billion this year. That figure was five times oversubscribed. On top of that, employees are now poised to sell about $6 billion in shares to investors like SoftBank, Dragoneer, and Thrive, pushing the company’s valuation potentially up to $500 billion.

OpenAI is hardly an outlier in its infrastructure binge. Tech giants are pouring unprecedented sums into AI buildouts in 2025: Microsoft alone plans to spend $80 billion on AI data centers this fiscal year, while Meta is projecting up to $72 billion in AI and infrastructure investments. And on the fundraising front, OpenAI has company too — rivals like Anthropic are chasing multibillion-dollar rounds of their own. 

Wall Street’s biggest bulls, like Wedbush’s Dan Ives, seem unconcerned. Ives said Monday on CNBC’s “Closing Bell” that demand for AI infrastructure has grown 30% to 40% in the last months, calling the capex surge a validation moment for the sector. While he acknowledged “some froth” in parts of the market, he said the AI revolution with autonomous systems is only starting to play out and we are in the “second inning of a nine-inning game.” 

And while a bubble implies an eventual bursting, and all the damage that results, the underlying phenomenon causing a bubble often has real value. The advent of the web in the ’90s was revolutionary; The bubble was a reflection of the massive opportunities opening up.

Still, I’d be curious if anyone pressed Altman on the AI paradox—warning of a bubble while simultaneously bragging about OpenAI’s massive fundraising and spending. Perhaps over a glass of bubbly and a sugary sweet dessert? I’d also love to know if he fielded tougher questions on the other big issues looming over the company: its shift to a public benefit corporation (and what that means for the nonprofit), the current state of its Microsoft partnership, and whether its mission of “AGI to benefit all of humanity” still holds now that Altman himself has said AGI “is not a super-useful term.”

In any case, I’m game for a follow-up chat with Altman & Co (call me!). I’ll bring the bubbly, pop the questions, and do my best to keep the eye rolls at bay.

Also: In just a few weeks, I will be headed to Park City, Utah, to participate in our annual Brainstorm Tech conference at the Montage Deer Valley! Space is limited, so if you’re interested in joining me, register here. I highly recommend: There’s a fantastic lineup of speakers, including Ashley Kramer, chief revenue officer of OpenAI; John Furner, president and CEO of Walmart U.S.; Tony Xu, founder and CEO of DoorDash; and many, many more!

With that, here’s more AI news.

Sharon Goldman
sharon.goldman@fortune.com
@sharongoldman

FORTUNE ON AI

Wall Street isn’t worried about an AI bubble. Sam Altman is – by Beatrice Nolan

MIT report: 95% of generative AI pilots at companies are failing – by Sheryl Estrada

Silicon Valley talent keeps getting recycled, so this CEO uses a ‘moneyball’ approach for uncovering hidden AI geniuses in the new era – by Sydney Lake

Waymo experimenting with generative AI, but exec says LiDAR and radar sensors important to self-driving safety ‘under all conditions’ – by Jessica Matthews

AI IN THE NEWS

More shakeups for Meta AI. The New York Times reported today that Meta is expected to announce that it will split its A.I. division — which is known as Meta Superintelligence Labs — into four groups. One will focus on AI research; one on  “superintelligence”; another on products; and one on infrastructure such as data centers. According to the article’s anonymous sources, the reorganization “is likely to be the final one for some time,” with moves “aimed at better organizing Meta so it can get to its goal of superintelligence and develop AI products more quickly to compete with others.” The news comes less than two months after CEO Mark Zuckerberg overhauled Meta’s entire AI organization, including bringing on Scale AI CEO Alexandr Wang as chief AI officer. 

Madison Avenue is starting to love AI. According to the New York Times, artificial intelligence has quietly become a fixture of advertising. What felt novel when Coca-Cola released an AI-generated holiday ad last year is now mainstream: nearly 90% of big-budget marketers are already using—or planning to use—generative AI in video ads. From hyper-realistic backdrops to synthetic voice-overs, the technology is slashing costs and production times, opening TV spots to smaller businesses for the first time. Companies like Shuttlerock and ITV are helping brands replace weeks of work with hours, while tech giants like Meta and TikTok push their own AI ad tools. The shift raises ethical questions about displacing creatives and fooling viewers, but industry leaders say the genie is out of the bottle: AI isn’t just streamlining ad production—it’s reshaping the entire commercial playbook.

Silicon Valley’s AI deals are creating zombie startups: ‘You hollowed out the organization.’ According to CNBC, Silicon Valley’s AI startup scene is being hollowed out as Big Tech sidesteps antitrust rules with a new playbook: licensing deals and talent raids that gut promising young companies. Windsurf, once in talks to be acquired by OpenAI, collapsed into turmoil after its founders bolted to Google in a $2.4 billion licensing pact; interim CEO Jeff Wang described tearful all-hands meetings as employees realized they’d been left with “nothing.” Similar moves have seen Meta sink $14.3 billion into Scale AI, Microsoft scoop up Inflection’s founders, and Amazon strip talent from Adept and Covariant—leaving behind so-called “zombie companies” with little future. While founders and top researchers cash out, investors and rank-and-file staff are often left stranded, sparking growing concern that these quasi-acquisitions not only skirt regulators but also threaten to choke off AI innovation at its source.

Nvidia working on new AI chip for China that outperforms the H20, sources say. According to Reuters, Nvidia is developing a new China-specific AI chip, codenamed B30A, based on its cutting-edge Blackwell architecture. The chip, which could be delivered to Chinese clients for testing as soon as next month, would be more powerful than the current H20 but still fall below U.S. export thresholds—using a single-die design with about half the raw computing power of Nvidia’s flagship B300. The move comes after President Trump signaled possible approval for scaled-down chip sales to China, though regulatory approval is uncertain amid bipartisan concerns in Washington over giving Beijing access to advanced AI hardware. Nvidia argues that retaining Chinese buyers is crucial to prevent defections to domestic rivals like Huawei, even as Chinese regulators cast suspicion on the company’s products.

EYE ON AI RESEARCH

Study finds AI-led interviews improved outcomes. A new study looked at what happens when job interviews are run by AI voice agents instead of human recruiters. In a large experiment with 70,000 applicants, people were randomly assigned to be interviewed by a person, by an AI, or given the choice. Surprisingly, AI-led interviews actually improved outcomes: applicants interviewed by AI were 12% more likely to get job offers, 18% more likely to start jobs, and 17% more likely to still be employed after 30 days. Most applicants didn’t mind the change—78% even chose the AI when given the option, especially those with lower test scores. The AI also pulled out more useful information from candidates, leading recruiters to rate those interviews higher. Overall, the study shows that AI interviewers can perform just as well as, or even better than, human recruiters—without hurting applicant satisfaction.

AI CALENDAR

Sept. 8-10: Fortune Brainstorm Tech, Park City, Utah. Apply to attend here.

Oct. 6-10: World AI Week, Amsterdam

Oct. 21-22: TedAI San Francisco. Apply to attend here.

Dec. 2-7: NeurIPS, San Diego

Dec. 8-9: Fortune Brainstorm AI San Francisco. Apply to attend here.

BRAIN FOOD

Do AI chatbots need to be protected from harm? 

AI lab Anthropic has introduced a new safety measure in its latest Claude models, which empowers the AI to terminate conversations in extreme cases of harmful or abusive interaction. The feature activates only after repeated redirections fail—typically for content requests involving sexual exploitation of minors or facilitation of large-scale violence. The company is notably framing this as a safeguard not principally for users, but for the model’s own “AI welfare,” reflecting an exploratory stance on the machine’s potential moral status.

Unsurprisingly, the idea of granting AI moral status is contentious. Jonathan Birch, a philosophy professor at the London School of Economics, told The Guardian he welcomed Anthropic’s move for sparking a public debate about AI sentience—a topic he said many in the industry would rather suppress. At the same time, he warned that the decision risks misleading users into believing the chatbot is more real than it is.

Others argue that focusing on AI welfare distracts from urgent human concerns. For example, while Claude is designed to end only the most extreme abusive conversations, it will not intervene in cases of imminent self-harm—even though a New York Times opinion piece yesterday urged such safeguards, written by a mother who discovered her daughter’s ChatGPT conversations only after her daughter’s suicide.