^{AI MARKETPULSE}
U.S. Intelligence Reportedly Believes Nvidia CEO Jensen Huang Was Targeted by a Chinese Spy

U.S. intelligence officials reportedly believe Nvidia CEO Jensen Huang had a romantic relationship with Alice Huang, an executive at Singapore-based data center company Megaspeed whom officials suspect was recruited by China’s Ministry of State Security. According to reports cited by ZeroHedge, intelligence officials prepared a memo about the relationship as concerns grew that Chinese intelligence was seeking information about Nvidia’s advanced AI chips and potentially trying to influence U.S. export policy. Megaspeed has separately faced U.S. scrutiny over alleged efforts to move restricted Nvidia chips into China, although Nvidia says an internal investigation found no evidence of wrongdoing. Congressional committees have now requested a closed-door briefing from Huang.

Key Takeaways:

• U.S. intelligence reportedly believes Alice Huang was recruited by China’s Ministry of State Security and targeted Nvidia CEO Jensen Huang.

• Republican congressional leaders have asked Huang to participate in a closed-door briefing about the reported intelligence operation and Nvidia’s security practices.

• Nvidia says it found no evidence of wrongdoing in an internal investigation involving Megaspeed and says it has no indication that company secrets or national security information were compromised.

👉️ Read the full article here

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^{AI SPOTLIGHT}
Only One of 45 Data Center Ballot Measures Went the AI Industry’s Way

The political backlash against AI data centers became difficult to ignore during the midterm elections, with just one of 45 data center-related ballot measures nationwide producing a result favorable to the industry, according to Redbud Consulting data cited by Fortune. The lone exception was Harwood, North Dakota, where roughly 75% of voters rejected a measure that would have added new reviews and public hearings for large industrial developments. The town is already home to Applied Digital’s $3 billion, 280-megawatt Polaris Forge 2 AI campus, which is under construction. Elsewhere, voters backed restrictions, moratoriums, or candidates opposing data center expansion amid concerns over electricity costs, water use, noise, and local infrastructure.

Key Takeaways:

• Of 45 data center ballot measures tracked nationwide, only one produced a result favorable to the industry.

• In Harwood, North Dakota, about 75% of voters opposed a measure that would have placed additional requirements on large industrial projects.

• The vote comes as AI companies face growing local resistance over electricity costs, infrastructure demands, noise, and the terms communities receive in exchange for hosting massive data centers.

👉️ Read the full article here

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^{TODAY’S PROMPT}
Build an AI Lead Generation Engine That Runs on Autopilot

This mega-prompt acts like an outbound automation architect, turning your ideal customer, offer, lead sources, and outreach goals into a complete lead-generation system. It maps how to collect public business leads, enrich them, score the best prospects, generate personalized emails, and trigger follow-ups without manually researching every company.

👉️ See the example inputs and outputs here

Act as an expert AI lead generation and
outbound automation strategist.

Build a practical system that finds
qualified business leads, enriches the
data, scores prospects, creates
personalized outreach, and automates
follow-ups.

Only use public or licensed business
data. Do not bypass access controls,
CAPTCHAs, logins, or platform rules.
Do not collect sensitive personal data.


MY INPUTS

What I sell:

[OFFER]

Ideal customer:

[IDEAL CUSTOMER]

Industries:

[INDUSTRIES]

Company size:

[COMPANY SIZE]

Target locations:

[LOCATIONS]

Decision-maker roles:

[JOB TITLES]

Problem I solve:

[CORE PROBLEM]

Main outcome:

[DESIRED OUTCOME]

Why my offer is different:

[DIFFERENTIATOR]

Proof I can mention:

[PROOF]

Lead sources:

[LEAD SOURCES]

Tools I already use:

[TOOLS]

Outreach channel:

[EMAIL / LINKEDIN / OTHER]

Primary CTA:

[CTA]

Preferred tone:

[TONE]

Outreach volume:

[VOLUME]

Anything to avoid:

[AVOID]


BUILD MY AI LEAD ENGINE

1. IDEAL CUSTOMER PROFILE

Define:

• Best-fit companies
• Decision-maker roles
• Buying signals
• Disqualifying signals
• Highest-priority leads


2. LEAD SOURCING

Show where to find prospects using
public or licensed business data.

For each source, explain:

• What to collect
• What qualifies a lead
• What to exclude


3. LEAD DATABASE

Create the exact fields for:

• Name
• Job title
• Company
• Website
• Industry
• Location
• Company size
• Business email
• Lead source
• Trigger event
• Personalization detail
• Lead score
• Outreach status
• Next action


4. ENRICHMENT

Show how to enrich each lead with:

• Company description
• Recent activity
• Hiring signals
• Website messaging
• Relevant content
• Likely pain points

Separate facts from AI inference.
Never invent prospect details.


5. LEAD SCORING

Create a 100-point model based on:

• ICP fit
• Buying signals
• Problem relevance
• Role fit
• Timing
• Personalization quality

Define high, medium, and low priority.


6. PERSONALIZATION

For each lead, generate:

• Relevant observation
• Likely problem
• Connection to my offer
• Personalized opening
• Best outreach angle


7. OUTREACH

Write:

• 10 subject lines
• Initial email
• Follow-up 1
• Follow-up 2
• Final follow-up

Keep messages concise and specific.

Include:

• Personalized opening
• Relevant problem
• Value proposition
• Brief proof
• Low-friction CTA


8. AUTOMATION

Map this workflow:

Lead found
→ Validated
→ Enriched
→ Scored
→ Personalized
→ Email sent
→ Reply detected
→ Follow-up triggered
→ CRM updated

For each stage, explain:

• Trigger
• AI task
• Automation action
• Data saved


9. FOLLOW-UP RULES

Define:

• When each message sends
• When automation pauses
• What happens after replies
• What happens after bounces
• What happens after opt-outs
• When the sequence stops


10. REPLY ROUTING

Create reply categories for:

• Interested
• More information
• Not now
• Referral
• Objection
• Not interested
• Unsubscribe

For each, define the response and
next automation action.


11. TOOL STACK

Recommend tools for:

• Lead collection
• Enrichment
• CRM/database
• AI personalization
• Automation
• Email sending

Prioritize tools I already use.
Give lower-cost alternatives.


12. BUILD PLAN

Create three phases:

Phase 1:
Manual prototype

Phase 2:
Semi-automated workflow

Phase 3:
Automated system

For each, explain what to build,
test, and measure.


13. SAFEGUARDS

Prevent:

• Bad lead data
• Duplicate prospects
• Fake personalization
• Broken emails
• Irrelevant outreach
• Excessive sending
• Contacting opted-out prospects


14. FINAL BLUEPRINT

Summarize:

• Target lead
• Lead sources
• Database fields
• Enrichment flow
• Scoring rules
• Personalization logic
• Outreach sequence
• Automation triggers
• Reply handling
• Tool stack
• Safeguards
• Key metrics

Make the system simple enough to
start building immediately.

If anything is missing, make the most
reasonable assumption and state it
briefly before the plan.
```

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^{AI QUICK HITS}

🐦 A bird-like drone evaded detection during a U.S. Air Force tech exercise, with Ornadyne’s one-pound O1 ornithopter reportedly being misclassified as a bird while flying for more than an hour.

🏗️ The political backlash against AI data centers is getting harder to ignore, after voters rejected projects in multiple local measures and newly elected officials campaigned on tighter restrictions.

⚡ Southeast Asia’s data-center boom is hitting power, water, and regulatory limits, with Thailand pausing 49 projects and putting 117 more approvals on hold as governments reassess the pace of expansion.

🦖 Scientists have chemically identified blood-related molecules in a 115-million-year-old dinosaur fossil, marking the first confirmed discovery of heme and mineralized red blood cell components preserved at that age.

🔋 CATL is exploring lithium-air batteries that could theoretically give EVs more than 1,200 miles of range, though the technology is still experimental and faces major durability and rechargeability hurdles.

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🤔 ^{Which image is real?}

One of these images is real, and one was created with AI. Vote for which one you think is real, and tell us why you voted that way.

The last edition’s results—75% were right!

Did you vote in the poll from November 2nd? The top image was real! Go back and see the photos here. So what do you think? Are you getting better at spotting AI vs. not?