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Founder, Software Analyst Cyber Research | Tweets on Cybersecurity & AI/ML | Catholic. Distance Runner. | Ex Cyber Research | Ex AI PM.

Apr 17, 2021, 27 tweets

Primer on How Investors can build an AI Portfolio to capture the $13T Opportunity from Artificial Intelligence by 2030.

Mega Thread //

• A Framework for evaluating AI Companies
• Top Companies that will continue to dominate
• First Principles basics on AI

Let's Review⬇️🧵

* Disclaimer: Not advice

1/Some context - This is a follow-up to a Twitter spaces with some brilliant folks:

Thread Outline:
• Foundational elements
• Debunking AI
• My framework for structuring an AI portfolio
• My Top Companies to watch
• Market Opportunity
• Summary
🔽

2/ What's AI?

Debunking it - AI simply involves training a complex system with huge amounts of data using algorithms (instructions), then using that trained system to make predictions about new data it has never seen.

Below is a break-down of the types (ML & NLP are common)

3/ Types of AI:

a) Weak AI: For tasks such as automation of repetitive tasks such as Virtual assistants, auto check-outs at McDonalds etc

b) General AI: For more complex brain-like tasks such as advanced robots, Adv deep-learning.

ML is still the common form in organizations.

4/ Basics of building an AI machine learning model

Stages broken down into:
• Gathering Data
• Clean + Process Data
• Preparation + Formatting of data
• Train + Deploy model
• Visualize through Graphs to drive decisions.

This is a very 'basic' process whenever you hear AI

5/ Why would almost all company benefit from AI?
or improve them? The key ways are:

• Improve decision-making within an organization
• Personalization and customized consumers products
• Automate tasks and drive down costs

The list below are more benefits based on a survey:

6/ So as an Investor - I use this foundational conceptual framework for building an AI Investing Strategy.

Why? -

Every organization in the world that will adopt an AI strategy by 2030 will have to undergo this maturity model by 'paying' these tech companies along the curve.

7/ How do I build my portfolio to capture this opportunity? [my structural framework]

i) Horizontal AI Companies: They provide the back-bone & Infrastructure
ii) Cloud Enablers Companies: They are the SaaS enablers
iii) Vertical AI Companies: Provide consumer product with AI

8/ Horizontal AI Companies (Slightly levered toward Hardware)

• Databases: $MDB $ESTC $ORCL $CLDR $SAP
• Storage/Transformation/Integration: $CLDR $SNOW $IBM $TDC
• Semi-Conductors: $NVDA $AMAT $NVDA $MU $AMD $TSM $KLIC $INTC $ON

[Many more private companies not listed]

9/ Cloud AI Enablers Companies:

• Cloud Providers: $MSFT $GOOGL $AMZN $SAP
• Web performance/Edge: $NET $FSLY
• Security: $CRWD $ZS $PANW $FTNT
• Visualization: $SPLK $DOMO $MSTR
• Observational monitoring: $DDOG $DT $SUMO $PD
• Data Governance: $OKTA $SAIL

10/ Vertical AI Companies:

• Insurance: $LMND
• Consumer Lending: $UPST
• Fashion: $SFIX
• Autonomous driving: $TSLA FSD
• RPA: $PATH
• Communication/NLP: $TWLO
• Enterprise AI: $AI $APPN $PLTR

You've also got companies like $UBER $ABNB that embed, but not directly.

11/
5⃣ - My Top Picks: Companies that I believe could play a big role in the next decade:

My Criteria:
✅They provide the foundation (sticky)
✅Technological Optionality
✅Platform cuts across multiple verticals
✅Platform's ability to scale
✅TAM
🛑 Not looking at valuation

1⃣ Databricks (Yet to IPO):

• They support most of the data pipeline.
• They have a Unified data Platform (foundation)
• They provide data exploration, data processing, model management and cloud storage
• They enable data processing from their combined Data lake + Warehouse

2⃣ Snowflake $SNOW

They provide:
• Cloud Storage,
• Database services
• Computational abilities
• Cloud Services through Data Marketplace- fosters data sharing & collaboration
• Snowflake gives everything an AI company needs in one package/solution (ridiculous!, I'll stop)

3⃣ Palantir: $PLTR

• Provide Gotham + Foundry
• Data Integration, AI modelling + Visualization
• They have all-in-one, full-stack analytics product (moat)

I've written multiple analysis:

i) A foundational piece:
ii) Below is a piece analyzing Foundry
investianalystnewsletter.substack.com/p/palantir-tec…

4⃣C3 AI $AI
• Ex Machina enables easy application of data science/AI to everyday business problems.
• Easy integration and allows developers to build enterprise AI without having to write lengthy code.
• UX data visualization
• Industry agnostic/ addresses multiple use-cases

5⃣ UI Path (vertical AI) - $PATH (IPO Soon)

• Enables robotics process automation
• Their software and AI monitors user activity to automate repetitive front and back-office tasks across an organization
• Leads to big cost savings

[I will be sharing a thread by end of April]

17/ Future Investing opportunities to watch out for:

1. Advanced deep-learning to write software; GPT-3 AI understands language and can write emails, perform human tasks.
2. Deep-mind and Open AI's research
3. Advanced Robotics capabilities
4. Quantum computing

And many more!

18/ Why should all this matter? -Market Opportunity.

Over the last decade, due to the digitization, the volume of Data has grown to 59ZT grown over 100x! The average teen has 800+ digital interactions

Data is the new gas that fuels AI-based product to make them better products!

19/ Market Opportunity (2): We're in early innings:

+ Over $13 - $15.7 Trillion will be contributed to the global economy by AI by 2030, according to PwC. Today, US Economy is $20T.

Ark forecast (c:@summerlinARK) over $30 Trillion will be added to MC's!

Think about the impact!

20/ Best Resources to growing/learning:

First, on Horizonal-like AI Companies Resources:

Chris puts great research on the Semi-conductor and hardware players leading $AI Race
• He has a four part series into breaking down Artificial Intelligence.

seifelcapital.substack.com

21/ Cloud AI-Enablers Resources:

• Muji puts together some great in-depth research exploring the technologies
• Some of the best the depth of $AYX $NET and $SNOW

hhhypergrowth.com

22/ @jaminball is the person for both Vertical AI Companies/Cloud companies

• Analytics companies and SaaS metrics, earnings announcements, and highlight any significant news.

• SaaS metrics, earnings announcements, and highlight any significant news

cloudedjudgement.substack.com

23/ Occasionally, I put together in-depth research on a mix of both companies (cloud or mostly vertical companies like $UPST or recently $PLTR Foundry on my newsletter.

However, the guys listed above⬆️ and people like @publiccomps do a better job!

investianalystnewsletter.substack.com/p/optional-rea…

24/24 Summary ⬇️

✅AI/Analytics will make a big impact on society by 2030
✅Structure your portfolio strategically based on the technology's optionality and scalability.
✅This was only a primer, we could have discussed much more!

I hope this thread helps you develop a frame.

25/ If you have questions, I'll be happy to answer sharing my experience, but the guys I listed above are experts.
Thanks for reading.

I'll like to hear from you -what industry group of companies are you excited about & believe has the biggest potential?

Feel free to comment.

I'll just cc some of the organizers/speakers from the Twitter Spaces:
@MaxTheComrade & @SeifelCapital @WOLF_Financial
@dhaval_kotecha @StockMarketNerd @fiducia_invest.

My bad, I forgot to tag/CC @hhhypergrowth when I mentioned Muji above!

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