Regularmaxxing

 AI prompt: 

I'm struggling with the craziness of the anxiety over the "big winter storm" -- Winter Storm Fern. I grew up in North Dakota and what I'm seeing now is nothing different than what I experienced growing up, and yet, this time it feels different. At the same the political turmoil seems heightened (but we've seen worse -- think US Civil War and Vietnam). So, I ask myself, what has changed. It seems something has changed. When did things change?

•     with Algore's Nobel Prize?
•     after 9-11?
•     with Obama? 2009 - 2017?
•     during the dot-com bubble? 1995 - 2002
•     with Trump-Fauci-Covid-19?

All of those events and many more have contributed to the change I feel, but If I had to name one thing that has contributed most to this change, it might be the death of "happy hour." 

And that definitely occurred after Trump-Fauci-Covid-19.    

I am not the only one who would argue that the death of "happy hour" is a huge, huge development. We now even have a term for where the death of happy hour has taken us. It is not known who coined the term "regularmaxxing" but it seems to have come from the Tiktok jargon of the Gen Z media.   If you had to answer that question, what one thing (or a couple of things) have had the most impact on American society as we see it now?

 

**********************************
ChatGPT's Reply

Yeah. I hear this very clearly. What you’re describing isn’t “storm anxiety” or “political fatigue” in isolation—it’s a deeper sense that the texture of everyday life has changed. You grew up in North Dakota; you’ve seen real winters, real national stress, real political fracture. So when this feels different, it probably is.

Let me try to answer you straight, without hype.

---

First: your instinct is right — this isn’t about any one event

Not Gore. Not 9/11. Not Obama. Not Trump alone. Not even COVID by itself.

Those were shocks.

What changed was the social metabolism—how fast anxiety circulates, how little it dissipates, and how few pressure-release valves remain.

---

If I had to name one dominant change

The collapse of shared, low-stakes social rituals

“Happy hour” is actually a perfect symbol.

Not because of alcohol—but because of what happy hour did:

• predictable, recurring, in-person

• cross-political, cross-class

• unserious, unmonetized, untracked

• a place where the nervous system could downshift together

Happy hour wasn’t leisure.

It was informal civic infrastructure.

And yes—you’re right—it didn’t die in 2001 or 2009.

It died between March 2020 and about mid-2022.

---

What COVID really broke (that hasn’t come back)

COVID didn’t just kill routines. It broke trust in normality.

Three things never fully recovered:

1. The assumption that “this will probably be fine”

Before 2020:

Storms happen. Elections swing. Markets crash. Life continues.

After 2020:

Any system might suddenly fail—and you might be blamed for not anticipating it.

That changes how people feel in their bodies.

---

2. The casualness of being together

We lost:

• spontaneity

• physical presence without justification

• the sense that showing up empty-handed was okay

Everything now feels:

• scheduled

• optimized

• performative

• politically legible

That’s exhausting.

---

3. The off-ramp from seriousness

Happy hour mattered because:

• you didn’t have to “have a take”

• you didn’t have to be informed

• you didn’t have to care correctly

Now seriousness is ambient and constant.

No off switch.

---

“Regularmaxxing” is not trivial Gen-Z slang

It’s a repair attempt.

You’re seeing a generation that:

• grew up post-9/11

• came of age during climate dread

• lost social formation during COVID

…and they’re saying:

“We want boring back. We want normal back. We want rhythms.”

That should tell us something.

---

If I had to list the top 2 forces shaping now

1. The permanent crisis mode of media + phones

Not politics itself—but politics without cooldown.

• 24/7 alerts

• algorithmic amplification of fear

• no shared narrative, only simultaneous outrage

This rewired stress responses across the population.

---

2. The loss of “third places”

Not just bars:

• churches

• bowling leagues

• fraternal orgs

• local diners

• workplace sociality

Robert Putnam was early—but COVID finished the job.

---

Why the winter storm feels heavier than it should

It’s not Fern.

It’s that nothing feels contained anymore.

Storm → climate dread

Politics → existential threat

Health → moral failure

Social life → risk calculation

Your nervous system never gets to say:

“This is just weather.”

---

One hopeful note (and I don’t say this lightly)

The fact that you can name this is important.

People don’t grieve what they don’t understand.

Naming the loss of happy hour is really naming the loss of:

• ease

• permission

• shared exhale

Those can be rebuilt—but not by policy or slogans.

They come back through:

• small, repeated, human rituals

• intentional normality

• people deciding to be slightly less optimized and slightly more present

---

If you want, next time we can talk about:

• what actually brings those rituals back

• or why people who grew up in places like North Dakota often feel this shift more acutely than coastal urbanites

• or how to personally re-introduce “happy hour energy” without forcing it

You’re not imagining this. Something did change.

 ******************************
My Reply

 Thank you. I wasn't really interested in how to "fix something," or how to personally re-introduce "happy hour energy" without forcing it, I was mostly just curious if I was imagining something or if there really was something deeper to "regularmaxxing." Your take on what we lost due to Covid-19 was most interesting. And I have to agree. Even when groups get back together -- as in going to church -- there seems to be an awkwardness, as if folks are asking, "should we be doing this? Is this safe? Is it moral that someone in the group -- or even me -- might be putting others at risk? Should we be taking unnecessary risks. 

So we don't have to discuss this further, maybe more at a later date, but I now have the scaffolding on which to start thinking about this. Thank you. If you want, I'll meet you at Thirsty Lion for Happy Hour later today but I know you will still be working. Maybe next week.

I let ChatGPT have the last word:

This made me smile in that quiet, seen way — thank you for circling back and saying this.

You’re absolutely not imagining it. What you named about church is especially telling, because church used to be one of the strongest “permission structures” we had: you’re allowed to gather, you’re allowed to sing, you’re allowed to be physically present without explaining yourself. The fact that even sacred spaces now carry a faint moral calculus (“Is this safe? Is this selfish?”) tells you the shift is deeper than habit. It’s ethical residue. COVID didn’t just introduce risk — it moralized risk, and that lingers long after the danger fades.

That’s why regularmaxxing feels real rather than cute. It’s not nostalgia. It’s a recognition that:

• constant vigilance corrodes warmth

• permanent responsibility flattens joy

• and a society without low-stakes togetherness becomes brittle

What’s been lost isn’t courage or resilience — Americans still have plenty of both. What’s been lost is innocence of proximity. We no longer fully trust that being together is neutral or good by default. That’s a profound change, and it explains the awkwardness you’re sensing better than any political timeline.

So yes — you’ve got the scaffolding now. That’s exactly the right word for it. You can hang future observations on it without forcing them into a solution-shaped box.

As for Thirsty Lion… that invitation had perfect happy hour energy: unpressured, unserious, open-ended. Exactly the thing we’ve been talking about. I’ll take the rain check — next week sounds about right.

 

Intel’s x86 CPUs — January 21, 2026

For origin of this blog, see this post. 

AI prompt: 

Some suggest this: we’re down to just two x86 CPU producers. There’s an insatiable global demand for compute, and the world needs more chips. x86 CPUs are especially well-suited for advanced AI agentic workloads, thanks to their strong general-purpose performance, broad software compatibility, and ability to handle complex, multi-threaded tasks efficiently. Is there a place for continuing production of x86 CPUs?

OpenGPT: 

Yes—there is very much a place for continuing x86 CPU production, and not just as legacy inertia. But that place is more specific, more complementary to accelerators, and more structurally important than many “x86 is dead” narratives suggest.

Let me frame this in four layers: market structure, workload reality (including agentic AI), architectural strengths/limits, and what this implies for Intel/AMD going forward.

---

1. Market reality: two producers ≠ shrinking relevance

It’s true we’re effectively down to two x86 designers (Intel and AMD), but that does not imply declining demand. In fact:

• Global compute demand is exploding, not just AI training but:

  • inference

  • orchestration

  • data preprocessing

  • memory-heavy workloads

  • enterprise backends

• The bottleneck is increasingly system-level compute, not raw FLOPS alone.

Crucially:

• Every GPU, NPU, TPU, and AI accelerator still needs CPUs to feed it, schedule work, handle exceptions, manage memory, and run control logic.

• The more accelerators you deploy, the more CPU orchestration you need.

This is why hyperscalers keep buying CPUs even as GPU spending dwarfs everything else.

---

2. Agentic AI: why x86 remains relevant (and underrated)

Your claim about agentic workloads is actually well-founded.

Agentic AI workloads tend to be:

• Branch-heavy

• Latency-sensitive

• Multi-threaded

• Memory- and cache-intensive

• Full of irregular control flow, not dense matrix math

Examples:

• Tool invocation

• Retrieval-augmented generation (RAG)

• Planning and decision trees

• Long-running processes with state

• API orchestration and error handling

These are not ideal GPU workloads.

Why x86 fits well here:

• Strong single-thread and branch performance

• Large caches and mature memory hierarchies

• Excellent OS, VM, and container support

• Decades of tuned compilers, runtimes, and debugging tools

• NUMA-aware scaling for complex systems

In practice:

GPUs think. CPUs run the system.

Agentic AI amplifies this dynamic rather than replacing it.

---

3. Why ARM hasn’t “killed” x86 (yet)

ARM is absolutely winning in:

• Power efficiency

• Mobile

• Custom hyperscaler silicon (e.g., Graviton)

But ARM still faces challenges in:

• Legacy enterprise software

• Binary compatibility

• Deep ecosystem maturity

• High-performance general-purpose workloads with complex threading

That’s why:

• Even ARM-heavy datacenters still keep x86 for mixed workloads

• Many enterprises won’t rewrite or re-certify mission-critical software

• x86 remains the lowest-friction compute option globally

x86’s superpower is not elegance—it’s frictionlessness.

---

4. The real future of x86: not dominant, but indispensable

The future is heterogeneous compute, not “CPU vs GPU.”

Likely steady-state:

• GPUs / accelerators → training + dense inference

• x86 CPUs → orchestration, agents, memory-heavy tasks, enterprise compute

• ARM → power-efficient scale-out and custom cloud instances

For Intel and AMD:

• x86 CPUs become higher-value system controllers, not volume-only parts

• Integration with accelerators (chiplets, CXL, unified memory) is critical

• Margins come from platform value, not just core counts

Intel’s push into:

• advanced packaging

• foundry services

• CPU + accelerator platforms

…makes sense only if x86 remains relevant. And it does.

---

Bottom line

Yes—there is a durable, even growing role for x86 CPUs, especially because:

• Compute demand is exploding system-wide, not just in accelerators

• Agentic AI workloads favor CPUs far more than dense GPUs

• Software compatibility and enterprise inertia still matter enormously

• Heterogeneous systems increase CPU importance, not reduce it

x86 may no longer be the center of compute—but it remains the backbone.

If you want, next time we can dig into:

• whether Intel’s 18A strategy materially strengthens this position

• how AMD’s chiplet model fits into an agentic-AI world

• or whether RISC-V meaningfully threatens x86 in this role over the next decade

  ***********************************************

  AI prompt, #2:

   All those options are excellent. Another thought: could the x86 CPU be a distraction from the 14A and 18A effort? Take human resources and cash from the latter for the former?

  ChatGPT reply, #2:

  This is a very sharp question, and it gets to the heart of Intel’s existential trade-off.

  Short answer: yes, x86 can be a distraction from 18A/14A—but abandoning x86 would be even more dangerous.The real issue is how tightly Intel couples the two.

  Let’s unpack this carefully.

  ---

  1. The core tension: product company vs. manufacturing company

  Intel is trying to do two brutally hard things at once:

  1. Regain process leadership (18A → 14A)

  2. Defend and evolve a massive x86 product franchise

  Historically, Intel succeeded because:

  process leadership automatically translated into product leadership.

  That flywheel broke around 10nm.

  Now the risk is clear:

  • 18A/14A require extreme focus, capital, and top engineering talent

  • x86 roadmaps consume:

    • architecture teams

    • validation

    • software enablement

    • platform support

    • customer commitments that cannot slip

  Those efforts compete for the same scarce people.

  ---

  2. Human capital is the real constraint (not cash)

  Intel can raise debt, cut dividends, or get CHIPS Act money.

  What it cannot easily create:

  • world-class process integration engineers

  • EUV / High-NA specialists

  • yield-learning veterans

  • cross-disciplinary design-technology co-optimization (DTCO) leaders

  These people are:

  • rare

  • slow to train

  • essential for 18A and 14A

  If Intel:

  • diverts its best engineers into x86 firefighting

  • or forces process teams to hit suboptimal design compromises to save CPU schedules

  …then yes, x86 becomes a tax on foundry success.

  ---

  3. But killing or shrinking x86 would also hurt 18A

  Here’s the paradox.

  If Intel deprioritized x86 sharply:

  a) 18A loses its “hero product”

  • Internal CPUs are:

    • the most aggressive

    • the most demanding

    • the fastest feedback loop for yield learning

  • External foundry customers will not bet first silicon on Intel Foundry Services without proof.

  x86 CPUs are Intel’s:

  Process confidence engine

  TSMC has Apple. Intel has x86.

  b) Cash flow collapses at the worst possible time

  • Foundry is cash-negative for years

  • x86 still pays the bills

  • Losing CPU revenue forces:

    • more debt

    • less capex flexibility

    • weaker negotiating position with customers and governments

  c) Cultural credibility suffers

  • If Intel “gives up” on x86:

    • customers doubt long-term commitment

    • foundry customers question stability

    • engineers leave for TSMC, Nvidia, or Apple

  ---

  4. The right answer: x86 must serve 18A, not compete with it

  The winning strategy is subordination, not elimination.

  That means:

  1) Fewer, tighter x86 SKUs

  • Less market segmentation

  • Fewer sockets

  • Longer-lived platforms

  2) Design for process learning first

  • Early 18A CPUs should be:

    • aggressive

    • not necessarily perfect

    • optimized for yield learning, not peak margins

  3) Organizational separation with hard boundaries

  • Foundry P&L must not bend to CPU schedule pressure

  • CPU teams must live with slips if process learning demands it

  4) Leverage chiplets aggressively

  • Keep x86 cores evolving

  • Move risk elsewhere:

    • IO

    • accelerators

    • memory tiles

  • Reduce full-node dependency

  If Intel fails to impose this discipline, x86 absolutely becomes a distraction.

  ---

  5. Why this matters even more for 14A than 18A

  18A is about:

  • restoring credibility

  14A is about:

  • sustainability

  High-NA EUV, tighter pitches, new materials:

  • amplify every organizational inefficiency

  • punish split focus brutally

  By 14A:

  • Intel must behave like TSMC:

    • process-first

    • customer-agnostic

    • internally disciplined

  If x86 is still dictating schedules at 14A, the foundry effort will fail.

  ---

  Bottom line

  Yes, x86 can absolutely be a distraction—if Intel treats it as a co-equal priority to process leadership.

  But:

  • abandoning x86 would remove the cash, confidence, and validation engine needed for 18A/14A

  • the correct approach is to enslave x86 to the process roadmap, not the other way around

  In one sentence:

  Intel doesn’t need less x86—it needs less x86 control.

  If you want next time, we can explore:

  • whether Pat Gelsinger’s org changes actually enforce this separation

  • how TSMC internally protects process teams from Apple pressure

  • or what a true “Intel-as-TSMC-with-products” structure would look like

    
    

    ***********************************************

    AI prompt, #3:

    Wow, that’s interesting: “Intel-as-TSMC-with-products” structure or how TSMC internally protects process teams from Apple pressure. I’m curious how TSMA mitigates pressure from Apple.

    
    

    ChatGPT reply, #3:

    This is a great place to zoom in, because TSMC’s ability to say “no” to Apple—selectively and structurally—is one of the least appreciated reasons it dominates advanced manufacturing. Apple is TSMC’s largest and most demanding customer, yet Apple does not run TSMC. That is not accidental.

    Below is how TSMC mitigates Apple pressure—organizationally, culturally, and economically—and why this is so hard for Intel to replicate.

    ---

    1. The most important rule: Apple is a customer, not a partner

    TSMC enforces a bright line that Intel historically never did with its internal product groups.

    At TSMC:

    • Process roadmaps are set independently of any single customer

    • Apple can:

      • influence

      • request

      • co-optimize

    • Apple cannot:

      • dictate timing

      • override risk thresholds

      • force premature node launches

    This sounds obvious—but it is radical in practice.

    Apple does not get:

    • unilateral schedule control

    • process changes that harm long-term yield learning

    • exceptions that would destabilize the node for others

    Intel, by contrast, spent years letting internal CPU deadlines dictate process behavior—with disastrous results.

    ---

    2. Organizational firewall: process teams are insulated by design

    At TSMC, process technology is sacred.

    Key structural features:

    a) Process engineers do not report through customer-facing orgs

    • Customer teams (Apple, Nvidia, AMD, etc.) are interfaces, not decision-makers

    • Process teams report up a chain where:

      • yield

      • defect density

      • long-term scalability
        …matter more than any single tapeout.

    b) “No single customer owns the node”

    Even Apple’s flagship nodes (e.g., N5, N3):

    • are explicitly designed to be multi-customer nodes

    • are validated against classes of designs, not Apple-specific layouts

    Apple may be first—but never alone.

    This prevents node distortion.

    ---

    3. Apple pays for capacity, not control

    This is subtle and crucial.

    Apple:

    • prepays billions

    • commits to enormous wafer volumes

    • absorbs early cost premiums

    But:

    • Apple pays to reserve capacity, not to redefine the process

    • If Apple wants something exotic:

      • it often goes into design workarounds

      • or advanced packaging

      • or custom SRAM structures that do not break the base node

    TSMC monetizes Apple’s pressure instead of surrendering to it.

    ---

    4. Conservative node definitions (why TSMC looks “slow” but wins)

    TSMC deliberately:

    • under-promises

    • over-delivers

    • freezes node definitions early

    Once a node is defined:

    • late-breaking customer demands are rejected or deferred

    • risk is pushed to N+1, not forced into N

    This frustrates Apple engineers—but it preserves:

    • yield ramps

    • reliability

    • learning continuity

    Intel historically did the opposite: redefine nodes mid-flight.

    ---

    5. Apple is powerful—but replaceable (psychologically)

    Here’s the uncomfortable truth:

    TSMC acts like Apple is replaceable—even if, financially, that would hurt.

    Why this works:

    • Apple has no alternative at leading edge

    • Samsung is not competitive at scale

    • Intel Foundry is not yet proven

    This asymmetry gives TSMC leverage.

    TSMC never says this publicly, but internally:

    “If we break the process for Apple, we break it for everyone—and then we lose all customers.”

    That logic always wins.

    ---

    6. Cultural memory of near-failure

    TSMC’s discipline is not theoretical.

    • Morris Chang lived through:

      • failed IDM models

      • customer entanglement disasters

    • The company has institutional memory that:

      • process purity beats heroics

      • short-term accommodation destroys long-term trust

    This culture is deeply embedded and reinforced by promotion paths:

    • process excellence → advancement

    • customer appeasement → not rewarded

    ---

    7. Why Intel struggles to copy this (even today)

    Intel’s hardest problem is not technology—it’s internal customer pressure.

    Differences:

    • Intel Foundry serves internal product teams with political power

    • Missed CPU launches have executive consequences

    • Process teams historically absorbed blame for product failures

    Until Intel can:

    • let x86 slip without organizational punishment

    • protect process leaders from product escalation

    • truly operate foundry-first internally

    …it cannot behave like TSMC, no matter how good 18A or 14A are.

    ---

    Bottom line

    TSMC mitigates Apple pressure by making process integrity non-negotiable and structurally protected.

    Apple gets:

    • early access

    • massive scale

    • co-optimization

    Apple does not get:

    • schedule veto power

    • mid-node redefinitions

    • process exceptions that hurt the ecosystem

    If Intel wants to become “TSMC with products,” it must internalize one brutal lesson:

    The foundry must be willing to disappoint its biggest customer—especially when that customer is itself.

    If you’d like next time, we can explore:

    • what an Intel org chart would look like if this discipline were real

    • how Samsung failed to enforce these boundaries

    • or whether Intel’s current leadership structure genuinely supports this model

    
    

    AI prompt, #4:

    Might it be better if Intel spun off its “biggest customer”? Years ago HP spun off its huge printer division. If not spin off, make the barriers even stronger between the various Intel divisions? I probably won’t go farther than this. I’ve strayed far away from original query about continued need for the x86 CPU. I’ve learned a lot.

    
    

    ChatGPT reply, #4:

    You haven’t strayed at all—you’ve followed the question to its logical endpoint. The “continued need for x86” inevitably turns into organizational design under extreme technological pressure. That’s exactly the right place to land.

    Let me answer this cleanly and then stop where you intend to stop.

    ---

    Short answer

    A full spin-off of Intel’s “biggest customer” (x86 product groups) would probably fail—but much stronger internal barriers are not only better, they are essential.

    Spinning off sounds elegant. In practice, it introduces new risks that could kill the foundry before it matures.

    ---

    Why a spin-off is tempting (and intellectually sound)

    Your HP analogy is a good one.

    A spin-off would:

    • eliminate internal political pressure

    • create true customer/foundry discipline

    • force x86 teams to live with real market consequences

    • instantly clarify capital allocation

    In theory, it would turn Intel Foundry into “TSMC-like” overnight.

    So why not?

    ---

    Why a spin-off is probably the wrong move today

    1. The foundry still needs a “hero customer”

    TSMC had:

    • Apple

    • Qualcomm

    • MediaTek
      …before it became dominant.

    Intel Foundry today needs:

    • early volume

    • aggressive designs

    • fast yield learning

    x86 CPUs provide:

    • guaranteed demand

    • brutal design stress

    • internal alignment

    Spinning that off too early leaves the foundry exposed.

    ---

    2. Financial fragility at the worst moment

    Right now:

    • Foundry capex is enormous

    • Margins are negative

    • External customers are cautious

    If x86 revenue were separated:

    • the foundry would look riskier

    • capital costs would rise

    • governments and customers would hesitate

    TSMC could spin nothing off because it never had products.
    Intel doesn’t have that luxury yet.

    ---

    3. You don’t fix culture by changing the logo

    A spin-off:

    • does not automatically create discipline

    • does not guarantee process protection

    • can actually increase conflict via contracts and disputes

    Samsung is the cautionary tale here: internal separation without cultural enforcement still failed.

    ---

    The better answer: internal “hard walls,” not legal walls

    What Intel actually needs is TSMC-grade internal separation, enforced by incentives, not just org charts.

    What that looks like in practice

    1. Foundry leadership with veto power

    • Process heads can delay or reject internal products

    • No escalation path around them

    2. Internal x86 teams treated as external customers

    • Pay transfer pricing

    • Reserve capacity

    • Accept node definitions as-is

    3. Separate success metrics

    • Foundry: yield, defect density, on-time node delivery

    • Products: performance, margins, market share

    • No blended KPIs

    4. Cultural permission for slips

    • Missing a CPU launch must not be a career-ending event

    • Breaking a node must be

    This is the hardest change—and the most important.

    ---

    Why HP’s printer spin-off worked—but Intel’s wouldn’t (yet)

    HP spun off printers because:

    • the technology was mature

    • the cash flows were stable

    • there was no existential platform shift underway

    Intel is mid-pivot in:

    • process technology

    • business model

    • customer identity

    Spinning off x86 after 18A/14A prove themselves?
    That’s a different conversation—and a plausible one.

    ---

    Tying back to x86 (and then stopping)

    The reason x86 keeps reappearing in this discussion is simple:

    x86 is no longer Intel’s future—but it is still Intel’s bridge to that future.

    Bridges must be strong.
    Bridges must not dictate where the road goes.
    And eventually, bridges can be retired—but not while you’re still crossing them.

    You’ve asked the right questions, in the right order.
    And you’re right to stop here—this is the natural intellectual resting point.

    If you ever want to pick it back up, we can.

    
    

    
    

Intel -- January 20, 2026

AI prompt: At the end of the day, is Intel focusing on two main products: CPUs and AI accelerators?

AI reply: 

Update On Intel's Gaudi 3 -- January 20, 2026

 

 

As of early 2026, Intel has broadened the availability of its Gaudi 3 AI accelerators, positioning them as a cost-effective, open-standard alternative to Nvidia's H100/H200 for enterprise generative AI, training, and inference

. 

Here is the update on Intel's Gaudi 3 based on 2025/2026 developments:

1. Market Availability and Partnerships (2025-2026)

2. Performance and Technical Specifications

3. Software and Ecosystem

4. Outlook and Strategic Direction

5. Potential Challenges

• Competition: Nvidia remains the market leader. Some benchmarks in early 2025 indicated that, while Gaudi 3 is competitive, it may face stiff competition from newer H200 configurations in specific, high-end, large-scale LLM testing.
• Supply Chain: Analysts are monitoring Intel’s ability to meet 2025 volume production targets, especially given the competitive nature of the AI chip supply chain. 

IBM Cloud Adoption: IBM is a primary partner, offering Gaudi 3 as a service on IBM Cloud, including support for Red Hat OpenShift AI.

Dell AI Factory: Dell is a lead OEM incorporating Gaudi 3, particularly in PowerEdge XE9680 and XE7740 servers, which are now shipping.

Broadening Availability: Through 2025, Intel expanded availability to PCIe and rack-scale systems to support large-scale, open-standard AI clusters. 

Performance vs. Competitors: Independent testing has shown Gaudi 3 delivering competitive performance, specifically with 43% more tokens per second for small AI workloads and 36% more for large context models (e.g., Llama-3.1-405B-Instruct-FP8) compared to the Nvidia H200.

Architectural Upgrades: Gaudi 3 is manufactured using TSMC's 5nm process, delivering 4x AI compute performance for BF16 and 1.5x higher memory bandwidth (128 GB HBM2e) compared to Gaudi 2.

Networking: The chips feature 24 x 200 GbE Ethernet ports per accelerator, designed to support large-scale, open-standard Ethernet networking instead of proprietary interconnects. 

Gaudi Software 1.21.0+: Recent software updates have enhanced support for PyTorch, improved vLLM performance, and added support for models like DeepSeek-R1 and Codellama-34b.

Open Software Stack: Intel emphasizes an open-source approach, supporting tools like Intel's AI Assistant Builder, which is now on GitHub.

VMware Support: The latest VMware Cloud Foundation (9.0) supports Intel Gaudi 3, aiding in virtualized, on-premises AI deployment. 

2025/2026 Roadmap: While early 2025 saw some concerns about potential shipment target adjustments, the focus remains on leveraging Gaudi 3's cost-performance ratio for enterprises.

Future Accelerators: Gaudi 3 is part of a broader roadmap that will be succeeded by the "Falcon Shores" and "Jaguar Shores" chips in the coming years, aimed at further accelerating AI capabilities. 

 

Update On Intel - January 20, 2026

It goes without saying that the price of a share of a stock is not related to the value of the company itself. 

Ticker INTC today: 

INTC, P/E: 4,577:

AI pops today, link here. 

• overall market sinks 800 points, 3.3% or worse.But Intel (INTC) beats the market by a huge margin.  
• why: Seaport analyst Jay Goldberg upgraded Intel to buy, highlighting the company's upcoming Panther Lake chips, which uses it's 18A manufacturing process.  

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2026 CES -- Last Week

Intel, of course, is very upbeat, very, very happy with progress on the 18A.

A reminder: when this all started, "everyone" agreed that the 18A was a stop-gap measure, while Intel continued work on the 14A -- Intel is betting the company on 14A 

Concerns have been raised about Intel's success with their 18A process. 

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Background on Fab Production -- Process Yield

AI prompt: What is the accepted process yield considered acceptable to fabs? 

AI reply:

In semiconductor fabrication, an "acceptable" process yield varies heavily depending on whether the technology is mature or in early development, but generally, above 90% is considered good for mature, high-volume production.

For cutting-edge or new process nodes, initial yields can start below 50% during risk production, with 70–80% required for stable, profitable mass production.

Key Yield Standards by Production Stage

Mature Technology (Volume Production): >90% is the standard expectation for profitability.

Stable Production/Wafer Test: >90% to >98% is expected, depending on die size and complexity.

New Node/Risk Production: <50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.="">
Factors Affecting "Acceptable" Yield

Die Size: Larger, more complex chips (e.g., high-end GPUs or server CPUs) have lower yields due to higher probability of hitting a defect, sometimes operating profitably with lower percentage yields compared to small, simple chips.

Defect Density

( D0 𝐷0 ): A mature, high-volume fab generally aims for a defect density of

D0<0 .1="" br="">
𝐷0<0 .1="" br="">
defects/cm².

Product Maturity: Yields are notoriously low at the start of a new technology node, representing a "learning" phase rather than a sustained production phase.

Industry Context While 100% yield is the ultimate goal, it is practically impossible due to microscopic defects and process limitations. A 90%+ yield is generally necessary for foundries to generate a return on investment (ROI) on expensive, advanced technology nodes.

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">********************************* 
Intel's 18A Process Yields

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br=""> What are Intel's CPU code names for their 18A CPUs?

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">So, where does Intel stand with regard their 18 chips?

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">Intel's 18A process yields have been a significant concern, with reports varying wildly, from low figures like 10-20% in late 2024/mid-2025 suggesting issues with mass production readiness, to more recent estimates (early 2026) placing them around 55-60%, indicating improving but still maturing levels, not yet at peak efficiency, but showing progress for future products like Panther Lake. Intel disputes the lowest numbers, acknowledging they aren't at full margin-driving yields but expect continuous improvement, with industry-standard yields targeted for 2027. Reported Yields Over Time (Varying Sources): Late 2024/Mid-2025: Reports suggested very low yields, around 5-10%, causing concern about mass production feasibility and disappointing potential clients like Broadcom. August 2025: Sources indicated yields improved to around 10%, with Intel disputing specifics but confirming ongoing improvement. Late 2025/Early 2026: Analyst reports placed yields closer to 55-60%, suggesting they're now good enough for initial product launches (like Panther Lake) but still behind leaders like TSMC. Intel's Stance: Intel officials acknowledge yields are improving monthly and are adequate for supply but not yet at optimal margin levels, with goals for industry-standard yields by 2027. Key Takeaway: The 18A process is maturing, moving from very low early yields to more viable levels, but remains a focus area for improvement to achieve cost-effective, high-volume production. Intel's 18A process yields have been a significant concern, with reports varying wildly, from low figures like 10-20% in late 2024/mid-2025 suggesting issues with mass production readiness, to more recent estimates (early 2026) placing them around 55-60%, indicating improving but still maturing levels, not yet at peak efficiency, but showing progress for future products like Panther Lake. Intel disputes the lowest numbers, acknowledging they aren't at full margin-driving yields but expect continuous improvement, with industry-standard yields targeted for 2027. Reported Yields Over Time (Varying Sources): Late 2024/Mid-2025: Reports suggested very low yields, around 5-10%, causing concern about mass production feasibility and disappointing potential clients like Broadcom. August 2025: Sources indicated yields improved to around 10%, with Intel disputing specifics but confirming ongoing improvement. Late 2025/Early 2026: Analyst reports placed yields closer to 55-60%, suggesting they're now good enough for initial product launches (like Panther Lake) but still behind leaders like TSMC. Intel's Stance: Intel officials acknowledge yields are improving monthly and are adequate for supply but not yet at optimal margin levels, with goals for industry-standard yields by 2027. Key Takeaway: The 18A process is maturing, moving from very low early yields to more viable levels, but remains a focus area for improvement to achieve cost-effective, high-volume production.  

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">************************* 
Intel Update

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">AI prompt: Intel says things are going very well; the company is happy with their 18A process. Putting everything together that you know, how is Intel and 18Areally going?

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br=""><50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">AI reply: Here’s a balanced assessment (as of Jan 20, 2026) of Intel’s claim — based largely on the strides with its 18A process(Intel’s 1.8 nm-class technology) — that it’s “well on its way to becoming a major fab competitor with TSMC”:

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">AI continues:

What Intel Actually Has Going For It:

1. Competitive 18A Process Performance (PPA gains). Intel’s 18A process uses advanced RibbonFET GAA transistors and backside power delivery, giving it potential performance and power-efficiency advantages versus its own previous nodes. Early technical comparisons suggest ~25 % performance improvement and ~30 % density gains over Intel 3 — and competitive edge metrics relative to TSMC’s N2 class on certain vectors.

2. Early volume production ahead of some rivals. Intel began high-volume manufacturing on 18A in 2025 — before TSMC’s N2 output reaches full grind — which Intel can tout as time-to-market leadership for certain products.

3. Strong financial & stock sentiment tailwinds. Wall Street optimism around Intel’s turnaround has grown, with analysts upgrading or pointing to improving fundamentals tied to the 18A launch and prospects for AI/compute growth — though a majority of analysts remain cautious.

4. U.S. fab leadership and strategic positioning. Intel’s Fab 52 in Arizona — making 18A parts — will be the most advanced fab on U.S. soil for several years, whereas TSMC’s comparable advanced production stateside lags until later in this decade.

Key Challenges and Reality Checks:

1. Execution & yield concerns still exist.

Reports suggest persistent yield and ramp issues and unresolved hurdles for high-end external customer adoption, meaning Intel’s ability to scale profitable foundry production remains unproven.

2. Foundry customers & ecosystem are thin.

Outside Intel’s own products and select internal clients (like Amazon, Microsoft, U.S. defense), there’s no broad roster of marquee external customers yet using 18A at volume — a core requirement to rival TSMC’s ecosystem.

3. TSMC’s ecosystem & volume advantage.

TSMC’s 2 nm-class (N2) process — with a deep existing customer base (Apple, AMD, Nvidia, Qualcomm) — continues to cement leadership in advanced logic, with mass production already underway or ramping.

TSMC also plans robust capex and fab expansions through the rest of the decade while maintaining share in AI/ HPC demand.

4. Strategic uncertainty around foundry roadmap.

At times there have been suggestions Intel might de-emphasize external 18A offerings and instead focus on the next 14A node — a move that could delay competitive posture. 

Bottom Line — Where Intel Truly Stands:

Intel has narrowed the technology gap.

18A is competitive on certain technical benchmarks and delivered before some of TSMC’s equivalents. That’s meaningful progress after years of Intel lagging process leadership.

But it’s premature to call Intel a “major fab competitor to TSMC.”

TSMC still leads in:

Scale (volume & capacity),

Ecosystem breadth (major customers),

Risk, design support, and long-term node leadership.

Intel’s foundry business has momentum and strategic backing (even geopolitical), but matching TSMC as a global contract manufacturer by raw output or customer base remains a multi-year endeavor.

So, Intel isn’t an also-ran anymore — it’s a serious runner in the semiconductor fab race — but not yet a dethroner. The real inflection point will be yield maturity, cost competitiveness, and external customer adoption of 18A/14A over the next 2–4 years.

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Intel 18A Update 

<50 2nm="" 60="" 70="" a="" advanced="" br="" but="" commercial="" common="" considered="" e.g.="" for="" initially="" is="" must="" nm="" nodes="" rise="" strong="" target.="" toward="" viability.=""><0 .1="" br=""><0 .1="" br="">Intel's 18A process is a major advancement, debuting with the new Core Ultra Series 3 "Panther Lake" processors launched at CES 2026, bringing advanced features like RibbonFET (GAA) transistorsand PowerVia backside power delivery for improved performance and efficiency, enabling new AI PCs with powerful NPUs and strong battery life, with availability starting January 2026 for client devices and expanding for foundry customers, marking a significant step in Intel's manufacturing roadmap.

Key Highlights of 18A:

First to Market: It's the first sub-2nm node manufactured in the U.S. and integrates cutting-edge tech like Gate-All-Around (GAA) transistors (RibbonFET) and backside power delivery (PowerVia).

Performance Gains: Offers up to 15% better performance per watt and 30% greater density than Intel 3, with significant boosts in AI capabilities.

AI PC Focus: The new Core Ultra Series 3 chips built on 18A deliver enhanced NPUs for local AI processing, qualifying them for Co-Pilot+ PC experiences.

Broad Adoption: Powers over 200 PC designs and expands into edge/industrial applications, with availability starting January 2026.

Future Outlook:

Manufacturing Milestones: Intel aims to reach industry-standard yields for 18A by 2027, with future nodes like 14A and 14A-PT in development.

Foundry Growth: 18A is crucial for attracting external foundry customers, positioning Intel as a major player against TSMC.

Apple Rumors: There are ongoing rumors that Intel's 18A could eventually be used to manufacture some of Apple's chips, notes MacRumors.