2024-September

Substack

Shopify has been acquisitive, but not like Broadcom or Salesforce with their jumbo acquisitions. Instead, they tend to acquire tiny businesses that are initially immaterial to the financials but can add up over time as they add new features to the ecosystem and bring in founding teams eager to make a difference.

― Shopify: Back On Track - App Economy Insights [Link]

Business performance highlights: 1) Post-COVID hangover rebound, 2) GMV = Gross Merchandise Volume grew 27% outside North America and 32% in Europe, 3) Shopify gained market share, 4) Shopify Payments penetration rate hit an all-time high of 61%, 5) Unified commerce platform, 6) Expansion into new markets, 7) Enterprise adoption, 8) Improved profitability, 9) Temporary operating margin boost.

Strategic Partnerships: 1) App and channel partners: Google, Meta, Microsoft, Amazon, etc, 2) Product partners: PayPal and Stripe, etc, 3) Service and technology partners: Oracle, IBM, etc.

Beat your Bot: Building your Moat against AI - Musings on Markets [Link]

AI’s strengths lie in mechanical, rule-based, and objective tasks, while it struggles with intuitive, principle-based, and bias-prone work. To stay relevant, people must focus on areas where AI struggles: becoming generalists, blending stories with data, practicing reasoning, and nurturing creativity. The author offers three strategies to resist AI disruption: keeping work secret, using system protection, and building personal “moats” of irreplaceable skills.

New LLM Pre-training and Post-training Paradigms - Ahead of AI [Link]

How Costco Hacked the American Shopping Psyche - New York Times [Link]

This article provides an in-depth look at Costco’s rise as one of the largest and most influential retailers globally, from its humble beginnings in Anchorage, Alaska, in 1984 to its current status as a retail giant.

The keys to success mentioned in the article: 1) Costco’s membership model ensures customer loyalty and steady revenue, 2) Offering high-quality products at low markups creates a sense of trust and value for customers, 3) Costco encourages impulse buying through a limited-time, high-value product offering that creates a “treasure-hunt atmosphere.”, 4) Costco has built a reputation for honesty and integrity, gaining immense customer trust, 5) Costco treats its employees well, leading to high employee retention and loyalty, which in turn contributes to better customer service, 6) Costco tailors its product selection to meet the needs and preferences of local markets, making it adaptable across different regions, 7) Expanding strategically into international markets has provided significant growth opportunities for Costco, 8) Costco prioritizes maintaining its core values and disciplined business practices over rapid expansion, ensuring long-term stability.

Dealing with aging: The Intel, Walgreens and Starbucks Stores Updated! - Musings on Markets [Link]

How should companies handle aging and decline?

Until the liabilities and responsibilities of AI models for medicine are clearly spelled out via regulation or a ruling, the default assumption of any doctor is that if AI makes an error, the doctor is liable for that error, not the AI.

― Doctors Go to Jail. Engineers Don’t. - AI Health Uncut [Link]

An insightful analysis by Sergei Polevikov on one of the biggest challenges to AI adoption in clinical diagnosis. Doctors are under risk for using AI while AI developers are not.

NVIDIA: Full Throttle - App Economy Insights [Link]

Huang shared five critical points about the opportunity ahead: 1) Accelerated computing tipping point, 2) Blackwell AI infrastructure platform, 3) NVLink Game-Changer, 4) Generative AI Momentum, 5) Enterprise AI Wave.

“The biggest news of all was signing a MultiCloud agreement with AWS—including our latest technology Exadata hardware and Version 23ai of our database software—embedded into AWS cloud datacenters.”

― Oracle: Riding the AI Wave - App Economy Insights [Link]

The new agreement will enable customers to connect data in their Oracle Database to apps running on AWS starting in December. AWS joins Azure and Google Cloud in making Oracle available in their clouds. Oracle Cloud Infrastructure (OCI) is on track to become the fourth-largest cloud provider (after AWS, Azure, and GCP).

Oracle Cloud Infrastructure (OCI) does 1) multi-cloud integration, 2) public cloud consistency, 3) hybrid cloud solutions, 4) dedicated cloud. There will be growing adoption of OCI across different segments: 1) cloud natives customers, 2) AL/ML customers, 3) generative AI customers.

Apple: There’s an AI for That - App Economy Insights [Link] [video]

What is new on iPhone 16?: 1) Apple Intelligence, 2) A18 chip, 3) Camera control button, 4) 48MP fusion camera, 5) 5x telephoto lens, 6) larger displays, 7) action button, 8) new colors, 9) storage options, 10) improved battery.

What is Apple Intelligence: 1) Context-aware Siri, 2) Enhanced writing tools, 3) on-device AI, 4) image and language generation, 5） task automation, 6) visual intelligence.

Google paid Apple north of $20 billion in 2022 to be the default search engine on Safari, so this partnership brought roughly a quarter of Apple’s Services revenue. Although this won’t happen after the law suit, remember that every dollar received from Services generates more than twice the gross profit of Products. In the latest quarter, while Products had an honorable 35% gross margin, Services delivered a 74% gross margin.

Services accounted for a substantial 45% of Apple’s gross profit in the June quarter, making it a critical driver of profitability.

Apple’s iPhone 16 Shows Apple Intelligence is Late, Unfinished & Clumsy - AI Supremacy [Link]

OpenAI o1: A New Paradigm For AI - The Algorithmic Bridge [Link]

Since 2009, the Chinese government has provided at least $231 billion to companies like BYD, including for research and development programs, consumer rebates, and infrastructure like charging stations.

But by focusing solely on subsidies, it’s easy to miss the biggest reason why China’s electric vehicle industry has been so successful: It’s incredibly innovative. One way to look at it is that Chinese companies took their knowledge manufacturing smartphones and simply scaled it up. In fact, two of China’s top smartphone makers, Huawei and Xiaomi, have already unveiled their own EVs. (Apple, meanwhile, canceled its car project.)

Overall, more than 10 million EVs will be sold in China in 2024, compared to just 1.7 million in the United States.

― What China’s Electric Vehicle Boom Looks Like on the Ground - Big Technology [Link]

YouTube and Podcasts

E165｜智能眼镜爆发前夜，与Ray-Ban Meta产品经理聊聊如何打造一款热门AI眼镜 - 硅谷101 [Link]

Donald Trump Interview | Lex Fridman Podcast #442 [Link]

Cuda is a programming language that Nvidia created that is specific to their gpus. Now these other players that he’s talking about are like Intel and AMD. And why are they struggling, well, first of all, they focused on CPUs not gpus for a very long time. Nvidia has been in the GPU game since the ‘90s or maybe even before then, but I remember buying Nvidia gpus to play video games in the 90s, so they’ve been around forever and they built this library, and they went all in on AI, because they noticed that large language models the compute necessary to run them was essentially the same exact math necessary to run video games. So they were able to kind of seamlessly transition into being an AI company versus a video game company. - Matthew

― Former Google CEO Spills ALL! (Google AI is Doomed) - Matthew Berman [Link]

Eric Schmidt interview at Stanford.

The difference for me is leading versus managing. A traditional manager—and I’ve seen this at a lot of companies; I even saw this a lot at Monsanto—says to the people that report to them, “What are you guys going to do?” Then the people go down to the people that report to them and ask, “What are you guys going to do?” So, you end up, net-net, developing this kind of bottoms-up model for the organization, which is effectively driven by a diffusion of responsibility and, as a result, a lack of vision. The leader, on the other hand, says, “Here’s what we are going to do, and here is how we are going to do it,” and then they can allocate responsibility for each of the necessary pieces. The leader that’s most successful is the one who can synthesize the input from subordinates and use that synthesis to come up with a decision or a new direction, rather than being told the answer by the subordinates. So, leaders, I think, fundamentally need to:

1. Understand the different points of view of the people that report to them,
2. Set a direction or vision—clearly saying, “This is where we are going,” and
3. Figure out how to allocate responsibility to the people that report to them to achieve that objective.

Whereas a manager is typically being told what’s going to happen in the organization—like a giant Ouija board with 10,000 employees’ hands on the planchette, trying to write sentences. Ultimately, you just get a bunch of muddled goop. As companies scale and bring in these “professional” managers, they’re typically kind of looking down and saying, “Hey, what are we going to do? What’s going to happen next?”—and they’re not actually setting a direction. - David Friedberg

― “Founder Mode,” DOJ alleges Russian podcast op, Kamala flips proposals, Tech loses Section 230? - All-In Podcast [Link]

Donald Trump Interview | Lex Fridman Podcast #442 - Lex Fridman [Link]

Value Investing in a Changing World with Aswath Damodaran - Aswath Damodaran [Link]

# 362 Li Lu - Founders [Link]

Gavin Baker - AI, Semiconductors, and the Robotic Frontier - Invest Like the Best, EP.385 [Link] [Note]

In conversation with JD Vance | All-In Summit 2024 - All-In Podcast [Link]

In conversation with Elon Musk | All-In Summit 2024 - All-In Podcast [Link]

Anthropic CEO Dario Amodei on AI’s Moat, Risk, and SB 1047 - “Econ 102” with Noah Smith and Erik Torenberg [Link]

TIP658: Peter Lynch’s Guide to Investing in Your Expertise w/ Kyle Grieve - We Study Billionaires [Link]

Articles

Explain the role of Monte Carlo Tree Search (MCTS) in AlphaGo and how it integrates with policy and value networks. - EITCA [Link]

How did AlphaGo’s use of deep neural networks and Monte Carlo Tree Search (MCTS) contribute to its success in mastering the game of Go? - EITCA [Link]

Outlive: The Science and Art of Longevity - The Rational Walk [Link]

Boomer Apple - Stratechery [Link]

Great article about Apple’s overall product strategy and its stage in its corporate life-cycle. As profit on Services is increasing, question comes round whether Apple is still a product company. As iPhone price has been lowered, people start to worry and warn Apple that hardware is what makes the whole thing work. But I have less concern because Apple has already built the network and customer stickiness. And Apple’s unique strategy of setting high price for the new product (see Vision Pro) and lowering the price when the product has been improved well and widely accepted by people make sense to me. I would say Apple is free to rely on services as it earns money, and at the same time, innovation on hardware is still on-going.

Why was everyone telling these founders the wrong thing? That was the big mystery to me. And after mulling it over for a bit I figured out the answer: what they were being told was how to run a company you hadn’t founded — how to run a company if you’re merely a professional manager. But this m.o. is so much less effective that to founders it feels broken. There are things founders can do that managers can’t, and not doing them feels wrong to founders, because it is.

In effect there are two different ways to run a company: founder mode and manager mode. Till now most people even in Silicon Valley have implicitly assumed that scaling a startup meant switching to manager mode. But we can infer the existence of another mode from the dismay of founders who’ve tried it, and the success of their attempts to escape from it.

― Founder Mode - Paul Graham [Link]

Papers and Reports

Dissecting Multiplication in Transformers: Insights into LLMs [Link]

Introducing OpenAI o1-preview - OpenAI [Link]

OpenAI o1-mini - OpenAI [Link]

This is a huge progress.

Jim Fan highlighted the trends:

1. You don’t need a huge model to perform reasoning,
2. A huge amount of compute is shifted to serving inference instead of pre/post-training. Refer to “AlphaGo’s monte carlo tree search (MCTS)” for the process of simulation and convergence,
3. OpenAI must have figured out the inference scaling law a long time ago, which academia is just recently discovering. Two papers to read: a) Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. Brown et al. finds that DeepSeek-Coder increases from 15.9% with one sample to 56% with 250 samples on SWE-Bench, beating Sonnet-3.5. b) Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters. Snell et al. finds that PaLM 2-S beats a 14x larger model on MATH with test-time search.
4. Productionizing o1 is much harder than nailing the academic benchmarks. Research does not share much about details a) when to stop searching, b) what is the reward function, c) how to factor in compute cost, etc
5. Strawberry easily becomes a data flywheel.

Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters [Link]

This is a transition from train-compute to inference-compute. Fast inference is important.

An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models [Link]

GitHub

STORM: Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking [Link]

Mastering Reinforcement Learning - Tim Miller [Link]

News

Apple’s iPhone 16 faces rising challenges with AI delay and growing Huawei competition - Reuters [Link]

Google’s second antitrust trial could help shape the future of online ads - CNBC [Link]

This one focused on Google’s dominance in internet search and examines the company’s ads tech.

AI Startups Struggle to Keep Up With Big Tech’s Spending Spree - Bloomberg [Link]

Brian Niccol, Starbucks’s new CEO, has a “messianic halo” - The Economist [Link]