Tariff Curve Ball….Dan Niles Says to Forget About Valuations……Another Successful SPAC IPO…..AI Power Executive Order…..CRNC vs. SOUN….Checking in on the Magnificent 7….Crypto Treasury Goes Global

On the way to all time highs this came out of left field on Friday….

The market ended up shrugging it off after an initial drop though. We will see whether Marco is right here, we are due for some sort of pullback……

🔥 HEAT Formula Playbook: Themes

This is one of the reasons I think you should focus on themes, not value, growth, garp, etc.

🔥 HEAT Formula Playbook: Asymmetry

Another strong SPAC IPO, it was a Trump theme also…..

Full Disclosure: We own YORKU in SPCX

🔥 HEAT Formula Playbook: Themes

Part of the Trump’s Inner Circle theme is investing based on Trump’s executive orders…...


Long time readers should already be in the AI power stocks—-CEG, OKLO, VST, VRT etc. This should also be a positive for GSRT which has the benefit of the SPAC NAV floor. This also came out on Friday…..

I had GPT rate the big players in AI power from 1-10…..

🔌 AI Power Infrastructure: Rankings (1–10)

Company

Role in AI-Power Buildout

Score

Constellation Energy (CEG)

Leading nuclear operator; reopening Three Mile Island for Microsoft; supplying baseload to AI data centers

10

NextEra Energy (NEE)

Major renewables & growing mix including nuclear; top-tier capacity for grid scale-up

9

Duke Energy (DUK)

$83B capex plan targeting gas capacity + grid modernization; pursuit of AI-specific PPAs

9

Dominion Energy (D)

Nuclear generation + pipeline/gas footprint; well-positioned for hybrid baseload & peakers

8

Entergy

Building new natural-gas plants to power Meta and Amazon data centers

8

Williams (pipeline)

Provides behind‑the‑meter gas power for Meta’s 200 MW AI data center

8

Chevron / Exxon

Natural gas infrastructure and power supply partnerships for this sector

7

AEP / Southern / Vistra

Regional utilities expanding capacity but less scale or advanced tech

6–7

Other SMR developers (Oklo, NuScale)

Promising but face regulatory/financial hurdles

6

Williams (WMB) stands out a bit. I’m not in it, unfortunately, but I have seen some people who are good with options flow talk about this name and unusual option buying…..

🔥 HEAT Formula Playbook: Themes

This caught my eye yesterday. I’m familiar with SOUN, which I’m currently out of, not nearly as familiar with this name…

I asked GPT to look at it vs. SOUN…..

🚗 1. Cerence (CRNC) – Positioned for OEM Embedded Voice AI

  • Core Offering: Voice assistant platforms embedded in vehicles’ infotainment systems, with capabilities like CaLLM™ Edge, voice cloning, and emotional tuning.

  • Scale & Moat: ~500 million cars shipped across 60+ OEMs—flagship brands like Mercedes, BMW, VW. Longstanding OEM partnerships make it “sticky.”

  • Technology Leadership: Specialized neural speech recognition, natural-language understanding, offline LLMs, avatar interfaces. Deep automotive domain mastery.

  • Financials: ~$331 million in 2024 revenue (+12% YoY); still unprofitable due to R&D but poised for leverage with scale.

  • Downside Risks: OEMs developing in-house AI systems; reliance on auto cycle; profitability lag.

  • Score: 8/10 – High-quality embedded focus, scale, domain expertise—profit eventual as adoption grows.

🗣️ 2. SoundHound (SOUN) – Multi-Industry Voice AI

  • Core Offering: Conversational voice AI platform (“Houndify”), spanning automotive, restaurants, enterprise agents, drive-thru, healthcare, and finance.

  • Scale & Moat: 10,000+ restaurants (Chipotle, White Castle, Torchy’s); in-vehicle Installations in Hyundai, Kia, Stellantis, Lucid; major AI partnerships (Nvidia).

  • Technology Leadership: Multilingual deep meaning understanding; Polaris LLM; generative AI assistants; voice commerce ecosystem.

  • Financials: Q1 ’25 revenue $29.1 M (+151% YoY); raised 2025 guidance to $157–177 M; still unprofitable.

  • Downside Risks: High market volatility; unprofitable; shorter OEM tenure; intense competition; exposure to cyclical enterprise spending.

  • Score: 7/10 – Broad platform, strong growth and partnerships, but thinner domain concentration and profitability lag.

🧠 Head-to-Head Summary

Feature

Cerence (8/10)

SoundHound (7/10)

Automotive-Centric Fit

Deep OEM integration, embedded off‑line AI.

Strong in-vehicle presence, but shared with other industries.

Scale & Moat

500M+ pre-installed vehicles; lasting relationships.

Multi-industry installations; newer OEM deals.

Tech Leadership

Specialized automotive voice LLMs, voice cloning.

Broad conversational AI; generative and enterprise agents.

Financial Position

$331M revenue; path to scale; losses from R&D.

$157–177M projected; high YoY growth; still unprofitable.

Competitive Risks

OEMs internalizing AI; auto cycles.

Market competition; need to sustain broad execution.

Verdict: Best-Positioned Stock

  • Better Positioned: Cerence (CRNC) – Its singular, deep focus on automotive voice AI—backed by scale and embedded partnerships—gives it a clearer, more defensible niche.

  • Score Recap: Cerence 8/10 vs. SoundHound 7/10

💡 For the Newsletter:

Cerence stands out as the stronger pure-play in-car voice AI, with entrenched OEM relationships and focused domain expertise. SoundHound is broader and innovative, with rapid growth, but lacks Cerence’s embedded scale. Both are interesting, but if you want one voice-AI pick for automotive, Cerence leads.

🔥 HEAT Formula Playbook: Themes

Friday I was on the Schwab Network talking about the Magnificent 7.

From a thematic standpoint, if you look at every possible AI theme that is likely to dominate in the future, one or more of these stocks is the projected winner.

Structurally, they are also set up for success as a big chunk of every dollar that goes into the S&P 500 or NASDAQ 100 goes into these stocks. Of course, that also makes them the obvious play. Most of them are must owns IMHO (I am currently out of AAPL and I like TSLA but can’t blame you if you don’t) but don’t forget the thematic hierarchy we teach in the webinars:

  1. Who are the obvious winners

  2. Who are the major suppliers to the winners

  3. Who are the major suppliers to the suppliers

  4. Who are the implementers of new technology

  5. Who gets hurt by the introduction of new technology

This makes me feel better about not owning AAPL…..

That being said, I had GPT give it’s take on the Mag 7 names.

🎯 The AI Theme: Dominated by the Magnificent 7

AI isn't a niche—it’s the axis around which industries are turning. Within every major AI domain—chips, cloud, consumer apps, advertising, infrastructure, autonomous vehicles—one or more of these names holds a genuine chokehold. That makes them foundational first-order winners. Smaller players can ride shotgun, but the big value lies here.

🔍 Deep Dive on Each Stock (Potential 1–10)

Ticker

AI Edge

Strengths

Risks

Rating

NVDA

AI chip king

Unmatched GPU & Blackwell lead; drives ~17% of S&P earnings growth; Chips built for agentic AI.

Sky‑high valuation; China restrictions hanging.

10/10

MSFT

Enterprise AI platform

Copilot, Azure AI, OpenAI partnership; recast as SaaS+AI powerhouse.

Competition, high expectations.

9/10

META

Consumer AI + ads

Massive AI investment ($72B capex); Meta AI and targeted ads.

Reliance on ad rev; regulatory heat.

8/10

AMZN

Cloud + AI infra

AWS leading GenAI, LLMs; logistics, retail integration.

Lower hardware‑driven margin growth; consumer slowdown.

8/10

GOOGL

Search + AI

Deep LLM integration; entrenched in ads and cloud.

Slower adoption; ad cycle issues.

7.5/10

AAPL

Consumer AI potential

AI-augmented UX in iOS/macOS; enormous install base.

Still playing catch-up; privacy limits innovation.

6/10

TSLA

Robotaxi + AI in motion

Full Self‑Driving data; Optimus robotics pivot.

FSD still unproven; timelines skeptical.

6/10

📈 Why You Need the Core First

In weighted industries like AI, glory goes to the infrastructure builders. Without Nvidia’s chips, Microsoft’s models, Meta’s platforms, and AWS/Google’s compute, the flashy startups don’t exist. Think of these seven as the basic materials, with the rest as refiners or fabricators. If you own these four or five leaders, you're pre-positioned for broad upside as AI adoption accelerates.

🎧 Strategic Guide for Investors

  1. Stay Tactically Weighted — Allocate 60–70% to Nvidia/MSFT/META/AMZN for core AI exposure.

  2. Add Secondary Plays — Names like Palantir and CrowdStrike can supplement in vertical niches.

  3. Manage Valuations — With forward P/E near 44×, multiple compression is possible—buy on dips, not chase peaks.

  4. Focus on Execution — Watch earnings for AI signal: Azure usage metrics, GPU guidance, ad‑AI margins, and FSD rollouts.

TL;DR: Verdict

  • Must‑Own Powerhouses: Nvidia (10/10), Microsoft (9/10), Meta and Amazon (~8/10) are first-order winners who weave the AI tapestry.

  • Brighter Future, But Riskier: Alphabet (7.5), Apple (6), and Tesla (6) offer potential but face adoption challenges and scaled expectations.

  • Broader Wisdom: If you want AI exposure that matters, load up on these core 4–5 names—secondarily supplement with smaller thematic opportunities.

🔥 HEAT Formula Playbook: Themes

Julian and I talked about this on Wednesday…..

I don’t think this area is dead and I think the recent correction could be a buying opportunity.

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