Intel’s Lifeline From Google: How a Custom Chip Deal Rewrites the Struggling Chipmaker’s Future

Intel’s stock surged more than 5% on Wednesday after reports surfaced that Google had signed a landmark deal to use Intel’s manufacturing facilities to produce custom server chips. The agreement, potentially worth billions over the coming years, represents the most significant validation yet of Intel’s ambitious — and expensive — bet to transform itself into a contract chipmaker for the world’s largest technology companies.

The deal is real. And it matters.

According to Yahoo Finance, Intel shares climbed sharply on the news, which was first reported by The Information and subsequently confirmed by multiple outlets. Under the arrangement, Google will tap Intel Foundry Services — the contract manufacturing arm Intel CEO Pat Gelsinger launched in 2021 — to fabricate custom chips designed by Google’s own engineering teams. The chips are expected to be built using Intel’s 18A process technology, the company’s most advanced manufacturing node and the linchpin of its entire foundry strategy.

For Intel, this isn’t just another customer win. It’s an existential proof point.

The company has spent the better part of three years and tens of billions of dollars trying to convince the semiconductor industry that it can compete with Taiwan Semiconductor Manufacturing Company as a foundry-for-hire. TSMC dominates the market, fabricating chips for Apple, Nvidia, AMD, Qualcomm, and virtually every other major chip designer on the planet. Intel’s pitch — that the West needs a geopolitically secure alternative to Taiwan-based manufacturing — has resonated in Washington, where the CHIPS Act funneled $8.5 billion in direct subsidies to Intel. But it hadn’t yet resonated with enough paying customers to quiet skeptics who questioned whether Intel could actually deliver on its manufacturing promises.

Google changes that calculus considerably. Alphabet is the fourth-largest company in the world by market capitalization, and its cloud computing division has been designing increasingly sophisticated custom chips — including its Tensor Processing Units for AI workloads and its Arm-based Axion processors for general cloud computing. Choosing Intel to fabricate these chips signals that Google’s engineers have evaluated Intel’s 18A process and found it technically competitive. That’s a verdict the market has been waiting for.

Wall Street responded accordingly. Analysts at several firms raised their price targets or reiterated buy ratings in the hours following the announcement. The enthusiasm wasn’t universal — some noted that Intel Foundry Services remains deeply unprofitable, having reported operating losses exceeding $7 billion in 2023 — but the consensus view shifted perceptibly toward cautious optimism. A marquee customer like Google gives Intel something it desperately needed: credibility.

But context matters here. Intel’s foundry ambitions exist against a backdrop of relentless financial pressure. The company’s core business — designing and selling its own processors for PCs and data centers — has been losing market share to AMD for years. In data centers specifically, Nvidia’s GPU dominance in AI training and inference has left Intel scrambling to articulate a competitive response. Revenue has declined. Margins have compressed. The workforce has been cut repeatedly, with roughly 15,000 layoffs announced in 2024 alone.

The foundry strategy was supposed to be the answer. Or at least part of it.

Gelsinger’s vision, laid out when he returned to Intel as CEO in early 2021, was straightforward in concept if staggering in execution: Intel would separate its chip design business from its manufacturing operations, run the factory side as an independent foundry open to outside customers, and invest aggressively in new process technology to regain manufacturing leadership from TSMC and Samsung. The plan required enormous capital expenditure — Intel has committed to building or expanding fabrication plants in Arizona, Ohio, Germany, and Israel — and it required patience from investors who were watching the stock price crater.

The Google deal suggests that patience may be starting to pay off. Intel’s 18A node, expected to enter volume production in the second half of 2025, is the company’s bid to leapfrog TSMC’s competing N2 process. Independent assessments have been cautiously positive. And while TSMC remains the undisputed manufacturing leader, the gap appears to be narrowing for the first time in years.

There’s a geopolitical dimension that can’t be ignored. The U.S. government has made domestic semiconductor manufacturing a national security priority, driven by concerns about Taiwan’s vulnerability to Chinese military action. If TSMC’s fabs in Taiwan were disrupted — by conflict, natural disaster, or political coercion — the consequences for the global economy would be catastrophic. Intel is the only American company with the scale and technical capability to offer an alternative, and the Google deal reinforces its position as the cornerstone of that strategy.

Google, for its part, has its own motivations. The company has been steadily reducing its dependence on merchant chip suppliers, designing more of its own silicon to optimize performance and cost for its specific workloads. Its TPU chips have become central to its AI infrastructure, competing directly with Nvidia’s GPUs for training large language models. Manufacturing these chips at Intel’s U.S.-based fabs gives Google supply chain diversification away from TSMC — a hedge that looks increasingly prudent given the geopolitical environment.

So what does this deal actually look like in financial terms? Neither Intel nor Google has disclosed specific dollar amounts. But foundry contracts of this nature typically span multiple years and multiple chip generations. If Google commits to fabricating even a portion of its custom chip portfolio at Intel, the revenue could run into the billions annually at scale. For Intel Foundry Services, which reported just $952 million in revenue in Q4 2023, that would be transformative.

The path from here to profitability remains long, though. Building and operating leading-edge semiconductor fabs is among the most capital-intensive activities in any industry. Intel’s planned Ohio facility alone carries an estimated price tag north of $20 billion. The 18A process must perform as promised — yields must be competitive, defect rates must be manageable, and production timelines must hold. Any significant stumble could send customers running back to TSMC.

And TSMC is not standing still. The Taiwanese giant reported record revenue in 2024, driven by insatiable demand for AI chips. It is building its own facilities in Arizona, partly in response to U.S. government pressure and partly to serve customers who want geographic diversification. Samsung, too, continues to invest in its foundry business, though it has struggled with yield issues on its most advanced nodes.

Intel’s competitive position, then, is real but fragile. The Google deal is a milestone, not a finish line. The company must now execute — delivering chips on time, at the right quality, and at competitive cost. It must win additional foundry customers to fill its fabs and drive utilization rates high enough to turn a profit. And it must do all of this while simultaneously defending its shrinking share in the PC and server processor markets.

One thing the deal does accomplish immediately: it changes the narrative. For the past two years, Intel has been a turnaround story that many investors had stopped believing in. The stock lost more than half its value from its 2021 highs. Analyst commentary turned increasingly bearish. Questions mounted about whether the foundry strategy was viable or whether Intel was simply burning cash on a fantasy.

A Google contract answers those questions — not definitively, but meaningfully. It says that at least one of the world’s most sophisticated technology companies believes Intel can manufacture chips at the leading edge. That’s not nothing. That’s not nothing at all.

The broader implications extend beyond Intel’s balance sheet. If Intel Foundry Services succeeds in attracting major customers, it could reshape the global semiconductor supply chain. Today, TSMC fabricates an estimated 90% of the world’s most advanced chips. That concentration of capability in a single company, on a single island, represents a structural vulnerability that governments and corporations alike are desperate to mitigate. Intel is the most credible path to diversification.

Whether Intel can actually pull this off remains the central question. The company has a long history of making bold promises about manufacturing timelines and then missing them. Its 10nm process was years late. Its 7nm node was delayed so badly that it was eventually rebranded as Intel 4. Gelsinger has acknowledged these failures and argued that the company has fundamentally reformed its process development methodology. The 18A node, he has said repeatedly, is on track.

Google apparently believes him. Now Intel has to prove it.

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Asia’s Tech Giants Are Reshaping the Global Order — One Week at a Time

The week of April 7, 2025, delivered a concentrated burst of technology news from across Asia that, taken together, paints a striking picture of the region’s accelerating influence over global technology supply chains, artificial intelligence development, and semiconductor manufacturing. From Japan’s semiconductor ambitions to China’s AI chip breakthroughs, from South Korea’s political turmoil spilling into its tech sector to India’s tightening grip on e-commerce regulation — the developments are worth examining in detail.

Start with Japan. The country’s semiconductor revival strategy took another significant step forward as Rapidus, the government-backed chipmaker aiming to produce 2-nanometer chips by 2027, continued to attract attention and funding. As The Register reported in its Asia tech roundup, Rapidus remains one of the most ambitious — and arguably most uncertain — national chip projects anywhere in the world. The Japanese government has poured billions of yen into the venture, and IBM has provided key technology. But skeptics remain. Two-nanometer fabrication is extraordinarily difficult, and Rapidus has no commercial track record. The company is essentially trying to leapfrog decades of manufacturing experience that TSMC and Samsung have painstakingly accumulated.

That’s the bet, though. Japan sees domestic chip production as a matter of national security, not just industrial policy. And given the geopolitical fractures running through the semiconductor supply chain — particularly the tensions between the United States and China over Taiwan — the urgency is understandable.

Speaking of China. The country’s AI chip development continued to make headlines, with Huawei’s Ascend series processors drawing particular scrutiny. Despite sweeping U.S. export controls designed to starve China’s AI sector of advanced chips, Chinese companies have shown a stubborn capacity to innovate around restrictions. Huawei’s Ascend 910B, while not matching Nvidia’s H100 in raw performance, has reportedly been adopted by major Chinese tech firms including Baidu and China Telecom for AI training workloads. The gap is real. But it’s narrowing.

The export controls, first imposed in October 2022 and tightened multiple times since, were supposed to put China years behind in AI hardware. The reality is more complicated. China has mobilized enormous state and private resources to build out domestic alternatives, and while the resulting chips are less efficient and more power-hungry than their American counterparts, they work. For a country willing to absorb higher costs and lower performance in exchange for supply chain independence, that may be enough.

South Korea’s technology sector, meanwhile, found itself entangled in the country’s ongoing political crisis. The impeachment and arrest of President Yoon Suk-yeol in late 2024 sent shockwaves through Korean business circles, and the effects continue to ripple. Samsung Electronics and SK Hynix, the two pillars of South Korea’s semiconductor industry, have had to operate amid unusual political uncertainty. Samsung in particular has struggled. Its foundry business has lost ground to TSMC, its memory chip margins were squeezed by a prolonged downturn before recovering in late 2024, and internal leadership questions persist.

SK Hynix, by contrast, has been riding high. Its high-bandwidth memory chips — essential components for Nvidia’s AI accelerators — have been in extraordinary demand. The company has effectively become the most important memory supplier for the AI boom, a position that has sent its stock soaring and given it unusual leverage in negotiations with customers.

Then there’s India. The Modi government’s evolving approach to e-commerce regulation continued to generate friction with foreign tech companies. New rules aimed at tightening oversight of platforms like Amazon and Flipkart (owned by Walmart) have raised concerns about market access and competitive fairness. India’s regulators have been increasingly assertive, pushing for greater data localization, stricter antitrust enforcement, and more favorable terms for domestic sellers on foreign-owned platforms. The tension between India’s desire to attract foreign investment and its impulse to protect domestic players is nothing new. But it’s intensifying.

As The Register noted, these regulatory moves are part of a broader pattern across Asia, where governments are reasserting control over digital markets that were largely shaped by American and Chinese tech giants over the past two decades. India isn’t alone in this. Indonesia, Vietnam, and Thailand have all introduced or tightened digital regulations in recent months.

The AI race across the region deserves particular attention. China, Japan, and South Korea are all pouring resources into large language models and generative AI applications, though with very different strategies. China’s approach is state-directed and massive in scale, with companies like Baidu, Alibaba, and ByteDance all fielding competitive models. Japan has taken a more measured path, focusing on specialized applications in manufacturing, robotics, and healthcare rather than trying to build general-purpose models to rival OpenAI’s GPT series. South Korea sits somewhere in between, with Naver and Samsung both investing heavily in AI but lacking the sheer scale of Chinese competitors.

One development that drew significant attention: the growing use of open-source AI models across Asian markets. Meta’s LLaMA models and similar open-weight releases have found enthusiastic adoption in countries where reliance on proprietary American AI systems raises both cost and sovereignty concerns. For governments wary of depending on OpenAI or Google for critical AI capabilities, open-source models offer a way to build domestic capacity without starting from scratch.

Taiwan, as always, sits at the center of everything. TSMC reported strong first-quarter earnings expectations, driven by insatiable demand for AI chips. The company’s Arizona fab, while progressing, remains years away from producing chips at the volume and sophistication of its Taiwanese facilities. That geographic concentration — the world’s most advanced chips, made overwhelmingly on a single island in the Western Pacific — continues to be one of the most significant strategic vulnerabilities in the global economy.

And it’s not just chips. Taiwan’s role in advanced packaging technology, which is increasingly important for AI processors that combine multiple chiplets into a single package, gives the island another layer of strategic importance. TSMC’s CoWoS (Chip-on-Wafer-on-Substrate) advanced packaging has been a bottleneck for Nvidia’s production, and expanding that capacity has been a top priority.

The broader picture that emerges from this week’s news is one of fragmentation and acceleration happening simultaneously. The global technology supply chain is splintering along geopolitical lines — U.S. versus China, with everyone else trying to figure out where they fit. At the same time, the pace of technological change, particularly in AI and semiconductors, is accelerating so fast that the strategic decisions being made today will have consequences for decades.

Japan is betting billions that it can build a world-class chip foundry from near-zero. China is betting that brute-force investment can overcome export controls. South Korea is betting that memory chips and AI hardware will remain its golden ticket. India is betting that its massive domestic market gives it the leverage to dictate terms to foreign tech giants. And Taiwan is betting that its irreplaceability will continue to be its best defense.

Not all of these bets will pay off. Some are mutually exclusive. But the sheer volume of capital, talent, and political will being deployed across Asia’s technology sector right now is staggering. The center of gravity in global tech hasn’t fully shifted east — the United States still dominates in software, AI research, and venture capital. But the hardware layer, the manufacturing layer, the physical infrastructure on which everything else runs — that’s increasingly an Asian story.

For industry professionals watching from Silicon Valley or Wall Street, the message is clear. The decisions being made in Tokyo, Beijing, Seoul, Taipei, and New Delhi this year will shape the competitive dynamics of the technology industry for the next decade. Ignoring them isn’t an option. Understanding them is a necessity.

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The Neuroscientist Who Wants to Give Your Brain a Hard Drive: Inside Nūrio’s Audacious Bet on Infinite Human Memory

A former neuroscience researcher thinks she can fix one of the brain’s oldest limitations — its tendency to forget. And she’s raised real money to try.

Tina Bhargava, who spent years studying memory at the University of Southern California, has launched a startup called Nūrio that aims to create what she describes as a “perfect, infinite memory” for human beings. Not through brain implants or pharmaceuticals, but through a wearable AI system that continuously captures, organizes, and retrieves everything a person experiences. The pitch is bold, bordering on science fiction: a device that remembers what you don’t, surfacing the right information at the right moment, effectively turning the human mind into something closer to a searchable database.

The concept isn’t entirely new. Lifelogging — the practice of recording every moment of one’s life — has been attempted before, most notably by Microsoft researcher Gordon Bell in his MyLifeBits project starting in 2001. That effort produced terabytes of data but no practical system for making sense of it. What’s different now, Bhargava argues, is that large language models and modern AI can do what earlier software couldn’t: parse context, understand intent, and deliver memories that are actually useful rather than drowning users in raw footage.

As first reported by Slashdot, Nūrio has attracted attention from both the neuroscience community and Silicon Valley investors intrigued by the intersection of AI and human cognition. The company’s approach centers on a wearable device — details on form factor remain sparse — paired with AI software that processes audio, visual, and contextual data in real time. The system is designed to function as an external memory layer, one that a user can query conversationally: “What did my doctor say about that medication last March?” or “What was the name of the architect I met at that conference in Austin?”

Bhargava’s neuroscience background gives the project a degree of scientific credibility that similar ventures have lacked. Her research at USC focused on how the hippocampus encodes and retrieves episodic memories — the specific, contextual recollections of events that make up personal experience. She’s spoken publicly about how the brain’s memory system was never designed for the volume of information modern humans encounter daily. Thousands of emails. Hundreds of meetings a year. Faces, names, conversations, commitments. The biological hardware simply can’t keep up.

That’s the gap Nūrio intends to fill.

The timing matters. The AI wearable market has become intensely competitive over the past eighteen months. Humane launched its AI Pin to withering reviews in 2024. The Rabbit R1 fared little better. Meta has pushed AI features into its Ray-Ban smart glasses with considerably more success, and several startups — including Limitless (formerly Rewind AI) and Omi — are building always-on AI companions designed to capture and recall conversations. Limitless, which sells a small pendant that records meetings and generates searchable transcripts, has gained traction particularly among knowledge workers who attend back-to-back calls and can’t remember what was said in the 2 p.m. by the time the 4 p.m. ends.

But Nūrio’s ambitions go further than meeting transcription. Bhargava has described a system that would capture not just audio but the full sensory and contextual texture of experience — where you were, who was there, what you were looking at, even physiological signals that might indicate your emotional state at the time. The goal is to reconstruct memories in something approaching the richness the brain itself produces, then make them permanently accessible.

This raises obvious questions. Privacy, for one.

An always-on recording device that captures everything its wearer sees and hears creates profound issues around consent. In many U.S. states, recording a conversation requires the consent of all parties. The European Union’s GDPR imposes strict requirements around the collection of personal data, and an ambient recording device would almost certainly trigger regulatory scrutiny. Google Glass faced a fierce backlash over exactly these concerns more than a decade ago, and the social dynamics haven’t changed much since. People don’t like being recorded without their knowledge.

Bhargava has acknowledged the privacy challenge in interviews, suggesting that Nūrio will implement what she calls privacy-by-design principles — on-device processing, user-controlled data, and mechanisms for bystanders to signal that they don’t want to be recorded. Whether those measures will satisfy regulators or the general public remains an open question. The history of consumer technology suggests that convenience tends to win over privacy concerns eventually, but the path there is rarely smooth.

Then there’s the deeper philosophical question: Should we want perfect memory?

Neuroscientists have long understood that forgetting isn’t a bug. It’s a feature. The brain’s ability to let go of irrelevant information is essential to generalization, creativity, and emotional health. People with hyperthymesia — a rare condition that produces near-perfect autobiographical memory — often describe it as a burden, not a gift. They can’t forget embarrassments, traumas, or trivial annoyances. Everything stays vivid. The psychologist Daniel Schacter of Harvard has written extensively about what he calls the “seven sins of memory,” arguing that each apparent flaw in human recall actually serves an adaptive purpose. Transience, the fading of memories over time, helps the brain prioritize what matters. Absent-mindedness reflects the allocation of attention to more important tasks.

Bhargava’s counterargument is that Nūrio wouldn’t replace biological memory but supplement it. Users would still forget naturally. They’d simply have a backup system they could consult when needed — more like an external hard drive than a cognitive overhaul. The analogy she’s used is to calculators: people didn’t stop learning math when calculators became ubiquitous, but they stopped wasting mental energy on long division.

Whether that analogy holds up under scrutiny is debatable. Cognitive scientists have documented the “Google effect” — the tendency for people to remember less when they know information is easily searchable online. A system that promises to remember everything for you could accelerate that effect dramatically, potentially making users more dependent on the device over time rather than less. The business model implications of that dependency are not lost on investors.

And investors are paying attention. The broader market for AI-enhanced personal productivity tools has exploded. Microsoft has embedded its Copilot AI across the Office suite. Google’s Gemini is being integrated into Workspace. Apple is rolling out Apple Intelligence across its devices. The thesis driving all of this investment is the same one underpinning Nūrio: that AI can serve as a cognitive multiplier, handling the informational overhead that bogs down human performance.

Nūrio’s specific funding details haven’t been fully disclosed, but the company has indicated it has raised a seed round from investors in both the neuroscience and AI spaces. The startup is based in Los Angeles, near USC’s campus, and has been recruiting engineers with backgrounds in natural language processing, computer vision, and wearable hardware design.

The technical challenges are formidable. Building an always-on wearable that captures multimodal data — audio, video, location, biometrics — without draining its battery in two hours is a hardware problem that has vexed far larger companies. Processing that data locally, as privacy considerations would demand, requires on-device AI capabilities that are still maturing. And creating a retrieval system that can surface the right memory at the right time, without being asked, edges into the territory of predictive AI — a field where accuracy is improving but far from reliable.

There’s also the question of data storage. A system that records everything generates enormous volumes of data. Even with aggressive compression and selective capture, a single user could produce gigabytes of memory data per day. Storing, indexing, and searching that data at scale — while keeping it secure and private — is an infrastructure challenge that will require significant engineering and capital to solve.

Competitors aren’t standing still. Limitless, founded by Dan Siroker, has been iterating rapidly on its wearable AI pendant and recently expanded its capabilities beyond meeting transcription to include ambient life capture. The Verge covered the company’s pivot extensively, noting that the shift from screen recording (Rewind’s original approach) to wearable capture reflected a broader industry recognition that the most valuable data isn’t on your computer — it’s in the conversations and experiences happening around you.

Omi, another startup in the space, has taken an open-source approach to its wearable AI device, betting that developer community engagement will accelerate feature development faster than a closed approach. And Meta’s Ray-Ban smart glasses, while not explicitly marketed as memory devices, already offer AI-powered visual and audio understanding that could be extended in that direction with a software update.

So what makes Nūrio different? Bhargava’s bet is that neuroscience expertise — a deep understanding of how the brain actually forms, stores, and retrieves memories — will produce a fundamentally better product than one designed by pure technologists. She’s argued that most AI memory tools treat human recall as a simple search problem, when in reality memory is associative, emotional, and deeply contextual. A truly effective external memory system would need to mirror those properties, not just return keyword matches.

It’s an intellectually compelling argument. Whether it translates into a product people will actually wear, pay for, and integrate into their daily lives is the multibillion-dollar question.

The market signals are mixed. Consumer appetite for AI wearables has been tepid so far, with the notable exception of Meta’s smart glasses. But enterprise demand for AI-powered knowledge management is surging. A version of Nūrio’s technology aimed at professionals — doctors who need to recall patient conversations, lawyers reviewing case details, executives managing hundreds of relationships — could find a receptive audience even if the consumer market remains skeptical.

Bhargava appears aware of this. In recent public comments, she’s emphasized professional use cases alongside the broader vision of augmented human cognition. The strategy seems to be: prove the technology works in high-value professional contexts, then expand to consumers as the hardware shrinks, the AI improves, and social norms around ambient recording evolve.

That’s a long game. But given the pace at which AI capabilities are advancing — and the growing cultural acceptance of AI as a daily companion — it may not be as long as it would have seemed even two years ago.

The fundamental question Nūrio poses isn’t really about technology. It’s about what it means to be human when your memories are no longer entirely your own — when the most intimate details of your life are captured, processed, and stored by a machine that understands context better than you do. The promise is liberation from the tyranny of forgetting. The risk is a new kind of dependency, one where the line between your mind and your device becomes impossible to draw.

Bhargava, for her part, seems unfazed by the philosophical weight of what she’s building. In a recent interview, she framed the mission simply: “We’re not changing what it means to be human. We’re giving humans back the memories they were always supposed to keep.”

Whether the world agrees — and whether the technology can deliver — will determine if Nūrio becomes a footnote or a turning point in how we think about the mind itself.

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The CDC’s Quiet Concession: COVID Vaccines Linked to Dangerous Blood Clotting — and What It Means Now

A federal health report years in the making has confirmed what some researchers suspected early on: COVID-19 vaccines carry a statistically meaningful association with vaccine-induced thrombosis with thrombocytopenia syndrome, a rare but potentially fatal blood-clotting condition. The findings, buried in a CDC publication that received relatively muted mainstream attention, are now rippling through the medical community and reigniting debate about pandemic-era public health communication.

The report, published by the Centers for Disease Control and Prevention, analyzed adverse event data and concluded that the Johnson & Johnson/Janssen adenoviral vector vaccine was linked to thrombosis with thrombocytopenia syndrome (TTS), a condition in which patients develop blood clots while simultaneously experiencing dangerously low platelet counts. As Futurism reported, the CDC’s own data confirmed the association — a link the agency had flagged as a possibility years ago but is now stating with greater certainty in its formal epidemiological review.

TTS is not a mild side effect. It can cause strokes, pulmonary embolisms, and death. The syndrome involves clotting in unusual locations, including the brain’s venous sinuses, and is triggered by an abnormal immune response to the vaccine that activates platelets. The mechanism bears similarities to heparin-induced thrombocytopenia, a known drug reaction, but occurs without heparin exposure.

The Johnson & Johnson vaccine was already pulled from the U.S. market in May 2023, a decision the FDA said was based on the risk of TTS relative to other available vaccines. But the CDC’s latest report puts harder numbers and stronger language behind what was previously couched in cautious probabilistic framing. For millions of Americans who received the J&J shot — roughly 19 million doses were administered in the United States — the confirmation lands differently now than it would have in 2021.

And it raises uncomfortable questions.

Chief among them: Did public health authorities move quickly enough? The first signals of TTS emerged in early April 2021, just weeks after the J&J vaccine’s emergency use authorization. The CDC and FDA recommended a brief pause — eleven days — before allowing its use to resume with a warning label. During the months that followed, the vaccine continued to be administered, particularly in settings where cold-chain storage for mRNA vaccines was impractical. Mobile clinics. Rural distribution sites. Homeless shelters. The populations served by J&J’s single-dose convenience were often those with the least access to follow-up medical care if something went wrong.

The CDC report doesn’t frame its findings as an indictment of prior decision-making. It presents the data clinically, as epidemiological agencies do. But the political and social context is impossible to ignore. Trust in public health institutions has eroded significantly since 2020, and confirmation of a vaccine-related clotting risk — even a rare one — feeds directly into the grievances of those who felt dismissed when they raised safety concerns during the pandemic’s most intense vaccination campaigns.

To be clear, the absolute risk of TTS from the J&J vaccine was always low in population terms. The CDC estimated roughly 3.8 cases per million doses among women aged 18–49 and lower rates in other demographics. But “rare” is a cold comfort to patients and families affected, and the syndrome’s severity — with a case fatality rate that some studies placed between 15% and 20% — made it far from trivial.

The mRNA vaccines from Pfizer-BioNTech and Moderna, which used a fundamentally different technology, were not associated with TTS. This distinction matters. The adenoviral vector platform used by J&J (and by AstraZeneca, whose vaccine was never authorized in the U.S. but saw similar clotting signals in Europe and the U.K.) appears to be the mechanistic culprit. Researchers have hypothesized that the adenovirus shell interacts with platelet factor 4, triggering the autoimmune cascade that leads to clotting. A 2022 study published in Science Advances provided structural evidence for this interaction, and subsequent work has largely supported that theory.

So why does this CDC report matter now, in mid-2025, when the J&J vaccine is already off the market and COVID boosters have moved to updated mRNA formulations?

Because the implications extend well beyond one discontinued product.

First, there’s the question of medical monitoring. The nearly 19 million Americans who received the J&J vaccine deserve clear guidance on long-term surveillance. Are there delayed or subclinical effects? Should certain populations receive periodic screening? The CDC report doesn’t address this comprehensively, and physicians on the front lines have noted the gap. Dr. Peter McCullough, a cardiologist who has been vocal about vaccine safety concerns, has argued that post-vaccination surveillance has been woefully inadequate across the board — a position that, whatever one thinks of his broader claims, finds some support in the limited scope of long-term follow-up studies conducted to date.

Second, the report has implications for future vaccine development. Adenoviral vector platforms aren’t going away. They’re being explored for vaccines against RSV, HIV, Ebola, and other pathogens. Understanding TTS at a mechanistic level — and building that understanding into preclinical safety assessments — is essential if these platforms are to be deployed safely in future outbreaks. The CDC’s confirmation of the TTS link strengthens the evidence base that regulators and developers will need to reference.

Third, and perhaps most consequentially, the report intersects with a broader political reckoning over how pandemic-era science was communicated. The Biden administration’s aggressive promotion of vaccination in 2021 left little room for nuanced discussion of risk. Social media platforms, acting on government guidance, suppressed or flagged content that questioned vaccine safety — including, in some cases, content that raised concerns about the very clotting risks the CDC has now confirmed. The result was a communication environment in which legitimate scientific uncertainty was often treated as misinformation.

That dynamic has not been forgotten. Robert F. Kennedy Jr., who has long campaigned on vaccine safety issues and now leads the Department of Health and Human Services under the Trump administration, has pointed to the TTS saga as evidence that federal agencies prioritized messaging over transparency. His critics counter that Kennedy’s broader skepticism toward vaccines — including childhood immunizations with decades of safety data — undermines his credibility on specific, legitimate concerns like TTS. Both things can be true simultaneously.

The timing of the CDC’s publication also coincides with ongoing congressional interest in pandemic accountability. House and Senate committees have held hearings examining the origins of COVID-19, the federal response, and the role of pharmaceutical companies in shaping public health policy. Vaccine injury compensation — currently handled through the Countermeasures Injury Compensation Program (CICP), which has been criticized for its low approval rates and limited payouts — remains a sore point. As of early 2025, the CICP had compensated only a small fraction of claimants alleging vaccine injuries, and the program’s administrative burden has been a recurring subject of criticism from patient advocates.

For the pharmaceutical industry, the report is a reminder that post-market safety signals can carry reputational and legal consequences long after a product’s withdrawal. Johnson & Johnson, which has rebranded its pharmaceutical arm as Kenvue for consumer health products, faces ongoing litigation related to TTS cases. The company has maintained that its vaccine saved lives and that the risk-benefit calculus at the time of authorization favored deployment. That argument is harder to sustain retroactively as the acute emergency recedes and the confirmed risks come into sharper focus.

The scientific community’s response to the report has been measured but pointed. Epidemiologists have noted that the confirmation validates the pharmacovigilance systems — VAERS, the Vaccine Safety Datalink, and v-safe — that detected the signal in the first place. The system worked, in other words, even if the policy response was slower and more politically fraught than it should have been. Others have argued that the delay in producing a definitive CDC assessment — years after the initial signal — reflects institutional caution that borders on dysfunction.

There’s a lesson here that transcends COVID. Public trust is not built by minimizing known risks. It’s built by acknowledging them openly, quantifying them honestly, and giving people the information they need to make decisions for themselves. The pandemic tested that principle and, in many respects, found it wanting. The CDC’s belated but clear confirmation of the TTS-vaccine link is a step toward restoring credibility. Whether it’s sufficient is another matter entirely.

What comes next will depend on whether federal agencies treat this report as a closing chapter or an opening one. The data exist to conduct deeper longitudinal studies of J&J vaccine recipients. The mechanisms of TTS are understood well enough to inform screening protocols. And the political will to reform vaccine injury compensation — making it faster, more transparent, and more generous — appears to exist on both sides of the aisle, even if the motivations differ.

None of this negates the broader reality that COVID-19 vaccines, particularly the mRNA formulations, prevented millions of hospitalizations and deaths worldwide. The evidence for that is overwhelming and has been replicated across dozens of countries and hundreds of studies. But acknowledging that net benefit doesn’t require ignoring the specific, documented harms experienced by a subset of recipients. The two truths coexist. They always have.

The CDC’s report makes one of those truths harder to look away from.

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Kevin O’Leary Says Your Net Worth Is Meaningless Until You Hit This Liquid Asset Target

Kevin O’Leary has a number he wants you to remember: $5 million. That’s the amount in liquid assets the Shark Tank investor says a person needs before they can consider themselves truly financially free. Not net worth. Not home equity. Not retirement accounts you can’t touch. Cash and liquid investments you can access without penalty or delay.

In a recent breakdown covered by Business Insider, O’Leary laid out his philosophy on personal wealth in characteristically blunt fashion. His argument is simple: most people confuse being asset-rich with being wealthy. A $2 million house and a $1.5 million 401(k) might look impressive on a balance sheet, but if you can’t write a check tomorrow without selling something or taking a tax hit, you’re not rich. You’re stuck.

This isn’t a new stance for O’Leary. He’s been preaching the gospel of liquidity for years on social media and in interviews. But the timing matters. With housing prices still elevated in most major metros, stock market volatility keeping investors on edge, and interest rates making borrowing expensive, the distinction between illiquid wealth and spendable money has never felt more relevant to working professionals.

O’Leary’s $5 million figure isn’t arbitrary. He ties it to a specific lifestyle threshold — the point at which investment income from a conservatively managed portfolio can cover living expenses indefinitely. At a 4% annual withdrawal rate, $5 million in liquid assets generates $200,000 a year. That’s enough to live comfortably in most American cities without ever touching the principal. And without a boss.

That’s the real point here. Freedom, not luxury.

O’Leary is quick to distinguish between people who earn high incomes and people who are actually wealthy. A surgeon making $600,000 a year but spending $580,000 isn’t wealthy. A small business owner sitting on $5 million in accessible investments making $150,000 in passive income is. The gap between income and liquidity is where most high earners get trapped, according to O’Leary, and it’s a trap he says is largely self-inflicted through lifestyle inflation.

So how does he suggest getting there? O’Leary’s advice skews predictable but disciplined. Save aggressively. Invest in dividend-paying stocks and income-generating assets. Avoid debt on depreciating items. And critically, stop treating your primary residence as a wealth-building tool. He’s argued repeatedly that a home is a consumption asset, not an investment — a position that puts him at odds with conventional American financial wisdom but aligns with what many financial planners have been saying quietly for years.

There’s a class dimension to this advice that’s hard to ignore. Telling people to accumulate $5 million in liquid assets when the median American household net worth sits around $192,900, according to the Federal Reserve’s 2022 Survey of Consumer Finances, can feel tone-deaf. O’Leary would likely counter that the target isn’t meant for everyone right now — it’s a long-term goal, a North Star for people serious about building generational wealth. But the distance between that target and most people’s reality is vast.

Still, the underlying principle holds up. Liquidity matters more than most people think. Financial advisors consistently warn that clients overweight illiquid assets — real estate, private business equity, restricted stock — and underestimate how vulnerable that makes them during downturns or personal emergencies. Having money you can actually move is different from having money that exists on paper.

O’Leary’s framing also reflects a broader cultural shift in how wealth is discussed publicly. The rise of the FIRE movement (Financial Independence, Retire Early), the popularity of personal finance content on platforms like YouTube and TikTok, and growing skepticism toward traditional retirement timelines have all pushed liquidity and passive income into mainstream conversation. O’Leary is speaking to an audience that already thinks in these terms.

Whether $5 million is the right number for you depends on where you live, how you spend, and what kind of life you want. For someone in a low-cost area with modest tastes, $2 million in liquid assets might be more than enough. For someone in San Francisco or New York with kids in private school, $5 million might not cut it.

The number matters less than the concept. And the concept is this: wealth isn’t what you own. It’s what you can spend.

O’Leary has built a personal brand around this kind of financial tough love, and it clearly resonates — his social media posts on money regularly pull millions of views. But brand aside, the core message here is sound financial planning dressed up in reality TV confidence. Know your liquid number. Track it separately from your net worth. And don’t confuse a high salary with financial independence.

That distinction alone is worth more than most financial advice you’ll hear this year.

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Apple’s Creator Studio Offensive: Logic Pro, Pixelmator Pro, and a Quiet Bet on the Professional Class

Apple just updated nearly every creative application it owns. Logic Pro, Final Cut Pro, Pixelmator Pro, Motion, Compressor — all of them received simultaneous refreshes in the second week of April 2026, a coordinated release that signals something larger than a routine version bump. This is Apple telling professional creators, in the clearest terms possible, that it wants to own the entire creative workflow from first note to final render.

The updates, first reported by 9to5Mac, arrived on April 9 and touched every major platform Apple operates — macOS, iPadOS, and in some cases, iPhone and Vision Pro. Logic Pro jumped to version 12.1 on the Mac and 3.1 on iPad. Final Cut Pro moved to 11.1 on Mac and 3.1 on iPad. And Pixelmator Pro, the image editor Apple acquired in late 2024, received its most significant post-acquisition update yet.

Taken individually, none of these updates would warrant more than a product blog post. Taken together, they represent a strategic escalation.

Start with Logic Pro. The new version introduces what Apple calls Session Players 2.0, an expansion of the AI-driven virtual musician feature first launched in 2024. The original Session Players offered bass, keyboard, and drum parts that could adapt to a song’s chord progression and feel. Version 2.0 adds guitar — acoustic and electric — along with expanded style options across all instruments. For producers working alone or in small teams, this is a meaningful capability. You can now sketch a full arrangement without hiring session musicians or hunting through sample libraries. The AI adapts to tempo changes, follows chord charts, and responds to slider-based controls for complexity and intensity.

But the more telling addition in Logic Pro is the deeper integration with Apple’s spatial audio tools. New Dolby Atmos mixing presets, improved binaural rendering for headphone monitoring, and tighter integration with the Apple Music production guidelines all point toward a single conclusion: Apple wants Logic Pro to be the default tool for producing music destined for Apple Music’s spatial audio catalog. That catalog has grown substantially since its 2021 debut, and Apple has been quietly funding Atmos remixes of classic albums while encouraging new releases in the format. Making the production tools easier and more accessible serves that goal directly.

Final Cut Pro’s update is similarly layered. On the surface, it’s about performance — faster exports on M4-series chips, improved timeline responsiveness with complex multicam projects, and better proxy workflow management. Useful but expected. The more interesting additions involve collaboration features that have been expanding since Final Cut Pro moved to a subscription model on iPad. Real-time collaboration now supports up to five editors working on the same timeline simultaneously, with conflict resolution handled automatically. Apple is clearly watching Adobe’s moves with Frame.io integration into Premiere Pro and responding with its own vision of cloud-connected editing.

There’s also a new AI-powered scene detection tool in Final Cut Pro that automatically tags clips by content type — interview, B-roll, establishing shot, close-up — and suggests rough assembly edits based on those tags. It doesn’t replace an editor. It’s more like having an extremely fast intern who can pull selects while you focus on the story.

Then there’s Pixelmator Pro. This is the one worth watching most closely.

When Apple acquired Pixelmator’s parent company in late 2024, the creative software community held its breath. Would Apple fold Pixelmator’s technology into Photos and let the standalone app wither? Would it become a loss leader, free with every Mac? Neither happened. Instead, Apple has been methodically upgrading Pixelmator Pro while keeping it as a paid application, now priced at $69.99 as a one-time purchase — a pointed contrast to Adobe’s subscription model for Photoshop.

The April 2026 update adds generative fill capabilities powered by Apple’s on-device machine learning models. Unlike Adobe’s Firefly-based generative fill, which processes requests through cloud servers, Pixelmator Pro’s implementation runs entirely on the local machine using the Neural Engine in Apple silicon. The privacy implications are significant for commercial photographers and designers working with sensitive or proprietary imagery. Nothing leaves the device. No training on your data. No cloud dependency.

The generative fill results, based on early user reports circulating on X and various creative forums, aren’t quite at the level of Adobe’s latest Firefly models in terms of photorealism. But they’re close. And they’re fast — nearly instantaneous on M3 Pro and M4 machines. For many professional use cases, speed and privacy will outweigh marginal quality differences.

Pixelmator Pro also gained expanded RAW processing capabilities in this update, with support for over 800 camera models and new lens correction profiles. Apple appears to be positioning it as a genuine Lightroom alternative in addition to a Photoshop competitor, which would give photographers a single application for both cataloging-style adjustments and pixel-level editing.

So why does all of this matter beyond the product specs?

Because Apple is assembling something. Piece by piece, update by update, it’s constructing a complete creative production environment that runs exclusively on its hardware. Logic Pro for audio. Final Cut Pro for video. Pixelmator Pro for images. Motion for motion graphics. Compressor for encoding. All optimized for Apple silicon. All integrated with iCloud. All designed to work together in ways that third-party tools from Adobe, Avid, or Ableton simply can’t replicate on Apple hardware because they don’t have the same level of access to the underlying system frameworks.

This isn’t new strategy. Apple has been building creative tools since it acquired what became Final Cut Pro in 1998. But the pace and coordination of these updates suggest a renewed intensity. The acquisition of Pixelmator filled the last major gap — image editing — and now Apple has a credible answer to every core creative application category.

The competitive pressure this exerts on Adobe is real. Adobe’s Creative Cloud subscriptions generate roughly $13 billion in annual recurring revenue, and a significant portion of that comes from individual creators and small studios — exactly the audience Apple is targeting with professional-grade tools at dramatically lower price points. Logic Pro costs $199 once. Final Cut Pro costs $299 once. Pixelmator Pro costs $69.99 once. Compare that to Adobe’s $59.99 per month for the full Creative Cloud package, which adds up to $719.88 per year.

The math isn’t subtle.

Apple doesn’t need its creative apps to be profit centers. They exist to sell hardware. Every professional creator locked into Logic Pro is a professional creator who needs a Mac. Every video editor dependent on Final Cut Pro’s optimizations for Apple silicon is an editor who won’t be switching to a Windows workstation. The apps are the moat around the hardware business, and Apple is deepening that moat with every update cycle.

There are limitations to Apple’s approach, of course. Final Cut Pro still lacks the deep third-party plugin infrastructure that Premiere Pro and DaVinci Resolve enjoy. Logic Pro, while powerful, doesn’t have the live performance capabilities of Ableton Live or the advanced MIDI editing of Cubase. Pixelmator Pro is impressive but doesn’t yet match Photoshop’s 35 years of accumulated feature depth in areas like advanced compositing and print production workflows.

And Apple’s tools remain Apple-only. In mixed-platform production environments — which describes most large studios, agencies, and post-production houses — that’s a genuine constraint. You can’t hand a Final Cut Pro project file to a colleague running Windows. You can’t open a Logic Pro session in Pro Tools without exporting stems first. For solo creators and small teams working entirely within Apple’s hardware lineup, this isn’t a problem. For larger organizations, it’s a dealbreaker that no amount of feature parity will fix.

Still, the trajectory is clear. Apple is investing heavily in creative software at a moment when many professionals are frustrated with subscription fatigue, cloud dependency, and the feeling that their tools are being designed for the broadest possible audience rather than for working professionals. Apple’s pitch is simple: buy our hardware, use our tools, keep your data on your device, pay once.

It’s a compelling pitch. Whether it’s compelling enough to shift market share in meaningful ways will depend on execution over the next several update cycles. But with the April 2026 releases, Apple has made its intentions unmistakable. The company that once ceded professional creative tools to third parties — remember when it let Aperture die? — is now building them with a seriousness and coordination that the industry hasn’t seen from Cupertino in years.

The creative software market just got a lot more interesting. And a lot more competitive.

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Wall Street’s Biggest Bank Just Called the Bottom on Stocks — and the Reasoning Is More Nuanced Than You Think

JPMorgan Chase, the largest bank in the United States by assets, has told clients that the current selloff in American equities represents a buying opportunity — not the beginning of something worse. The call, made amid tariff-driven volatility and persistent macroeconomic uncertainty, is striking in both its confidence and its timing.

The bank’s analysts argue that the S&P 500’s recent decline has already priced in a meaningful economic slowdown, and that investors willing to stomach near-term turbulence will be rewarded. As Yahoo Finance reported, JPMorgan’s strategists see the current dip as an entry point rather than a warning sign, framing the pullback as a healthy repricing rather than the start of a prolonged bear market.

That’s a bold stance. And it arrives at a moment when consensus on Wall Street is fractured.

The S&P 500 has been whipsawed in recent weeks by escalating trade tensions between the United States and China, with the White House imposing sweeping new tariffs and Beijing retaliating in kind. President Trump’s tariff policies — some announced, some paused, some reversed within days — have injected a level of policy unpredictability that markets haven’t seen in years. Corporate earnings guidance has grown murkier. Consumer confidence readings have softened. The bond market has flashed intermittent distress signals. Against that backdrop, JPMorgan’s call to buy the dip carries real weight, precisely because the bank isn’t dismissing the risks.

Instead, the thesis rests on valuation. JPMorgan’s equity strategists believe that the market correction has compressed price-to-earnings multiples enough to compensate for the deteriorating macro picture. In their view, much of the tariff damage is already baked in. The argument isn’t that everything is fine — it’s that stocks have gotten cheap enough relative to earnings expectations that the risk-reward has shifted in favor of buyers.

This kind of call is what separates institutional research from retail sentiment. Retail investors, by and large, have been pulling money from equity funds. Institutional flows tell a more mixed story, with some large allocators quietly adding exposure to U.S. large-caps even as headlines scream caution. JPMorgan’s recommendation gives those allocators intellectual cover.

But not everyone agrees.

Goldman Sachs has been notably more cautious, warning clients that the tariff situation could deteriorate further and that earnings estimates for the second half of 2025 remain too optimistic. Morgan Stanley’s Mike Wilson, long one of the more bearish voices on the Street, has echoed that concern, arguing that margin compression is underappreciated and that the market hasn’t fully discounted a potential recession scenario. Citigroup’s strategists have taken a middle path, suggesting that while U.S. equities may be near a trough, the catalyst for a sustained rally isn’t yet visible.

So JPMorgan is out on a limb. Not recklessly — the bank hedged its call with caveats about trade policy uncertainty and the possibility of further downside if tariff negotiations collapse entirely — but meaningfully.

The tariff picture itself remains deeply fluid. The Trump administration’s 90-day pause on certain reciprocal tariffs, announced in early April, gave markets a brief reprieve. But the baseline 10% tariff on most imports remains in effect, and the rate on Chinese goods has climbed to levels not seen since the Smoot-Hawley era. Beijing has responded with its own escalating duties on American agricultural and industrial exports, and both sides appear to be settling in for a prolonged standoff rather than a quick resolution.

For corporate America, the uncertainty is arguably worse than the tariffs themselves. Companies can adapt to a known cost structure. They can’t plan around a tariff rate that might change via social media post at 6 a.m. on a Tuesday. That’s the core problem, and it’s one that JPMorgan’s analysts acknowledge without fully resolving. Their thesis implicitly assumes that the worst of the tariff escalation is behind us — an assumption that requires a certain faith in the administration’s willingness to negotiate.

Recent data complicates the picture further. The April jobs report came in stronger than expected, with nonfarm payrolls adding 177,000 positions and the unemployment rate holding at 4.2%. That’s good news on its face, but economists have noted that the labor market tends to be a lagging indicator, and that the full impact of tariff-related disruptions won’t show up in employment figures for months. Consumer spending, meanwhile, has shown signs of a pullback in discretionary categories — exactly the pattern you’d expect if households are bracing for higher prices on imported goods.

The Federal Reserve, for its part, has signaled patience. Chair Jerome Powell has emphasized that the central bank wants to see how tariff effects filter through the economy before adjusting interest rates. Markets are pricing in two to three rate cuts by year-end, but Fed officials have pushed back on that timeline, suggesting that inflation risks from tariffs could delay easing. That tension — between what the market expects and what the Fed is willing to deliver — is another source of potential volatility.

JPMorgan’s call to buy the dip implicitly bets that the Fed will eventually come around. If economic data weakens enough, the thinking goes, Powell will cut rates to support growth, providing a tailwind for equities. It’s a reasonable expectation. But it’s not guaranteed, especially if tariff-driven inflation proves stickier than anticipated.

There’s a historical dimension worth considering. In prior episodes of tariff-driven market stress — most notably during the 2018-2019 trade war with China — stocks did eventually recover, and investors who bought during the dips were rewarded handsomely. The S&P 500 fell roughly 20% from its September 2018 peak to its December 2018 trough, then rallied more than 30% over the following year. JPMorgan’s strategists are, in part, betting that this pattern repeats.

The analogy has limits. The current tariff regime is broader and more aggressive than anything implemented during Trump’s first term. The global trading system has also changed — supply chains that were rerouted after the first trade war can’t be easily rerouted again. And the fiscal backdrop is different, with the federal deficit running at levels that constrain the government’s ability to provide stimulus if the economy tips into recession.

Still, JPMorgan’s core argument has a certain logic. Valuations have compressed. Sentiment is washed out. Positioning is light. Those are the classic ingredients for a market bottom. The question is whether this time, the fundamental backdrop is deteriorating fast enough to overwhelm the technical setup.

One factor working in the bulls’ favor: corporate buybacks. With stock prices lower, companies sitting on large cash reserves have accelerated share repurchase programs. That provides a floor of sorts, absorbing selling pressure that might otherwise push prices lower. Several major tech companies have announced expanded buyback authorizations in recent weeks, and the pace of actual repurchases has picked up meaningfully according to S&P Dow Jones Indices data.

Another factor: the dollar. The greenback has weakened modestly against a basket of major currencies, partly reflecting foreign investor concerns about U.S. policy predictability. A weaker dollar, all else equal, boosts the earnings of multinational corporations by making their overseas revenues worth more in dollar terms. For a market dominated by globally exposed mega-caps, that’s a meaningful tailwind.

And then there’s the AI trade. Despite the broader market turbulence, spending on artificial intelligence infrastructure has shown no signs of slowing. Microsoft, Alphabet, Amazon, and Meta have all reaffirmed or increased their capital expenditure plans for AI-related investments. That spending flows through to semiconductor companies, cloud infrastructure providers, and a wide range of enterprise software firms. JPMorgan’s analysts have specifically cited the durability of AI capital spending as a reason to remain constructive on the technology sector, which accounts for roughly 30% of the S&P 500’s market capitalization.

The counterargument is straightforward: AI spending is great until it isn’t. If a recession materializes, even the most committed tech companies will trim budgets. And the valuations on AI-adjacent stocks, while lower than their peaks, remain elevated by historical standards. Buying the dip in Nvidia at 25 times forward earnings is a different proposition than buying it at 15 times.

For institutional investors parsing JPMorgan’s recommendation, the practical question is one of timing and sizing. Few large allocators are going to make an all-in bet on U.S. equities based on a single bank’s call. But many will use it as one input among several in their decision-making process. The bank’s research carries outsized influence precisely because of its scale — JPMorgan’s asset and wealth management division oversees more than $3.9 trillion — and because its strategists have a track record that commands attention, even when they’re wrong.

And they have been wrong before. In early 2022, JPMorgan’s equity strategists were broadly constructive on stocks heading into what turned out to be a brutal year for both equities and bonds. The S&P 500 fell more than 19% that year. The bank’s analysts adjusted their views as conditions deteriorated, but the initial call cost credibility with some clients. That history is relevant context for anyone evaluating the current recommendation.

What makes this moment particularly tricky is the sheer number of variables in play. Trade policy. Monetary policy. Fiscal policy. Geopolitical risk. Technological disruption. Any one of these factors could dominate the market’s direction over the next six to twelve months. The interaction effects between them are nearly impossible to model with precision.

JPMorgan is essentially making a probabilistic argument: given what we know today, the odds favor higher stock prices over the medium term. That’s not the same as saying stocks can’t go lower first. It’s not the same as saying the economy won’t stumble. It’s a statement about expected value, weighted across a range of scenarios.

For the average institutional portfolio manager, that framing is useful even if the specific conclusion is debatable. It forces a disciplined assessment of risk and reward at a time when emotional reactions — fear, paralysis, capitulation — are the biggest threats to long-term returns.

The next few weeks will test JPMorgan’s thesis. Earnings season is winding down, and the guidance that companies have provided has been cautious but not catastrophic. Trade negotiations between Washington and Beijing remain stalled, though back-channel communications reportedly continue. The Fed’s next policy meeting in June will provide another data point on the rate outlook.

If the tariff situation stabilizes and economic data holds up, JPMorgan will look prescient. If trade tensions escalate further or the labor market cracks, the call will age poorly. That’s the nature of making a directional bet in an environment defined by uncertainty.

One thing is clear: the biggest bank in America doesn’t think this is the beginning of a bear market. Whether that conviction proves well-founded will say a lot about where the economy — and the market — is headed for the rest of 2025.

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