Donald Trump’s 3rd May 2019 trade war tweets on stock market index around the world

Tweet was posted in May 3rd 2019 where Chinese import tax hike to 25% from 10% was proposed.

Immediate negative effects were most prominent on Hong Kong and Straits Times stock index. An observed 4.5% drop.

Immediate effects were negligible on the Shanghai index as bad news seems like it was already factored a few days prior to the tweet. An observed 6% drop prior to the tweet.

Effects on the SnP was negligible. An observed 0.45% drop. The London Stock exchange (FTSE) seems to be humming to its own rhythm.

Book summary: The Fate of Rome

Climate is both an enabler and disruptor of human endeavors. Nature balances the population it supports. Technology enables increased rate of energy extraction from environment to further human purposes.

Conducive climate results in bountiful yield and has allowed Rome to rise. Land is cleared and trade networks flourish during the rise of the empire. Clearance of wild lands unlocked microbes into the human civilization.

Microbes evolve to utilize humans and other mammals as vectors of infection. Dense population and connected trading network serve as a multiplier. The worst pandemic is the white pestilence (Black Death). This wiped out more than half of human population.

Trading network collapse as a result of the decimated population. Military rank diminishes both as a result of population decimation. Problem is further compounded by collapse of financial system which makes it difficult to sustain an army.

Grounds are fertile for spread of monotheistic dooms day religion like Christianity. Emperor Justinian converts to Christianity. Classical Greek school of thoughts gets displaced.

Climate change for the worse force nomads with superior military power to migrate westwards into Roman territory.

Roman Empire with decimated population gets further crippled.

Insights from Klaren’s birthday

Conversations with Yi (EverString)

The forthcoming trend for engineering

Machine learning is increasingly becoming commoditized. DevOps becomes more important. Demand for specialized service where DevOps is encapsulated will further increase as demand for engineering tasks further outstrips engineering supplies.

On lead generation market

Companies in the lead generation space have need for scalable web crawlers. This helps offset the cost of retaining three in-house engineers.

Lead generation space has consolidated. There were priorly 120k such companies. There is 7k companies in operation. Majority of players are generating leads by scraping LinkedIn.

Consumer space require constant development of new features. Enterprise space requires service heavy. Enterprise space requires not just lead generation but entire channel marketing service suit (physical mail, online advertising, email marketing)

Lead gen hard to retain. The list becomes less valuable once it’s been used. 80% yearly churn is normal. One company reduces yearly churn to just 10% this by reducing second year subscription from USD800/yr to USD200/yr. further discount to USD100/yr if they don’t like. Recurring service is for grabbing fresh leads from same data source.

On Tele conference

Zoom’s product team compared with UberConference has developed a better understanding of the true conference needs of their users in various context. They have worked harder to ensure their product work seamlessly in identified scenarios. A typical example is the ability to join s conference bybthe press of a button on their mobile phone while driving instead of having to type the typical 4 pin digits.

Insights from dinner with Yuan

Conversations with Wang Ji Lei (Google)

China’s 996 practice has allowed China to close the 30 years technology gap between China and the US within the past 5 years. Some segments like cashless commerce have already surpassed US. The norm is some labor regulations are considered formalities and adherence is not necessary.

China’s distribution path starts from Beijing, 1st tier cities, 2nd tier cities, 3rd tier cities and finally remote villages. While double digits growth has been the norm over the past five years, market saturation has been achieved within the Chinese digital space and most apps are having problems growing.

Baidu’s Ads revenue model via search is increasingly being disrupted by Tic Toc. They have lost 50% ofvtheir search revenue last year. Similar trend is being observed with Google’s Ad revenue model which is bring increasingly disrupted by Amazon in the below USD75 consumer goods segment, Facebook between the USD75 and USD2000 consumer goods segment.

Tic Toc and WeChat dominate the bulk of the mobile usage bandwidth in China. Tic Toc with string positions within the short video entertainment segment while WeChat in the social conversations segment. Both companies face significant challenges encroaching into the other’s territory.

Tic Toc is the only Chinese mobile entertainment app that has made significant headway out of China. They have a well defined playbook which specialized tiger teams follow to gain traction in new territories. Maintenance is transferred to local team once penetration threshold is achieved. Due to fickle nature of users, retention remains the number 1 challenge. Position can be easily displaced by new entrants. Thebunderlyimg thesis is that city dwellers have lots of fragmented time spread across a day. Each video is restricted to 45secs to reduce anxiety that user has to stop watching between engagements. This also helps induce the habit of chipping in between engagements.

Typical engineer’s salary in Beijing is USD50,000 per year while a house cost around USD2million. While typical engineering salary in Silicon Valley is at least USD100,000 per year while house cost at least USD1 million. Wealth is mainly retained at the upper levels in China. Given the ratio of salary to house price as well as the comparative working hours, there is significant pull of talents to Silicon Valley.

Average green card waiting time for EB1 is now five since it’s been expended to include executives.

Major housing development is occurring in South Bay given huge influx of population and hiring by google (50,000 people) and other giants. Heavy recruitment is happening as Google continues to build out its cloud team.

Google cloud’s market share continues to lag with Amazon leading, Microsoft Azure in Second and AliCloud 3rd. Google cloud organization is facing an inflection point as upper management faces difficulties with zeroing in on a clear strategy. The symptoms are the dilemma between engineering culture (Google Default) versus customer culture (Amazon) and SMB versu Enterprise. Google’s traditional engineering culture has the effect of causing company to drift towards heavy engineering solutions which might be an overkill for SMB needs coupled with a lot of wastage which no one needs. This opens up a gap for customer focused companies.

Tesla autonomy

https://www.youtube.com/watch?v=tbgtGQIygZQ

The Mission

Building and optimizing the entire infrastructure (hardware and software) from ground up with autonomous self driving as the mission

Mission and decision making

Design decisions are made with trade off between functionality and cost to achieve the mission while keeping cost in control

  • Lidar is not useful when cameras are available
  • driving cars with HD mapping makes the entire operation brittle since actual road conditions can change

Operating structure

  • Data Team
  • Hardware Team
  • Software Team

The Data model

  • Cars on roads are constantly collecting new data
  • New data is being utilized to train and improve neural network model
  • New improved model is constantly being deployed back to the car to improve self driving
  • Real world data provides visibility into long tail scenarios that simulated data cannot. Simulating long tail scenario is an intractable problem
  • Balancing between data model and software
    • Neural network is suitable for problems that are hard to solve by defining functions / heuristics
    • Simple heuristics are better handled through coding in software

Future revenue model

Robo-taxi that will disrupt the ride-sharing space.

  • Consumer car – USD0.60 / mile
  • Ride sharing – USD 2-3 / mile
  • Telsa Network – USD 0.18 / mile

Main challenges:

  • Legal – need more data and processing time to get approved
  • Battery capacity
  • Social norms around robo taxi

Societal comparison between our current day and age versus the era of communism’s rise

In Karl Marx’s Das Kapital, I see huge similarities between the society during his time of writing and our current day. Corporations well optimized for profitability while workers work long hours without making enough to sustain themselves.

Currently, blue collared workers are either unemployed or getting paid close to minimal wage. With the growing prevalence of trend 996, where overworking gets glorified, even knowledge workers are working increasingly long hours while stuck living in areas paying ever increasing rent.

The only distinct between what is observed now and then is the promise of upward mobility through hard work, some call it the “American Dream”. Based on my observation even that is getting slaughtered.

Based on the current trajectory, I foresee a day majority of our population wakes up to realize the dream is in fact just a dream and a set of ideology similar to Karl Marx’s gain widespread popularity amongst the masses.

Related references

Blitzscaling with Microsoft

  • At scale, making sure everyone knows and adheres to mission, vision and values is very important
  • Handling Technological disruption is easy, handling business model disruptions are hard as it requires slaughtering your current cash cow
  • Need to set some ground rules that are baked into the core to mitigate against negative societal impact when operating at scale.
  • Ask permission from investors to use a different set of leading indicator metric when exploring into new terrain to help show progress every quarter

Book summary: The Nature of Technology

The Nature of Technology
  • Each technology exploits a natural phenomena thereby exposing a functionality to further human purpose
  • Principal – the idea of how a phenomena is captured
  • One technology builds on another (or a collection them) – recursion
  • Components – components and practices
  • functionality assumes modularity simplifies design
  • Types of phenomena
    • Physical – what goes on in the physical environment
    • Behavioral – what goes on in a human brain
    • Organization – the emergent dynamics when a group of human brains interact
  • Science is the practice of probing Nature to identify phenomena through the use of technology
  • Engineer is a process of solving the problem to create a solution by making technology work.
  • Invention is mental association of problem with principal and technology
  • A technology stack when required to perform at higher levels needs to be modified to get pass bottlenecks
    • Internal replacement
    • Structural deepening
      • can become an issue. Example
        • military organization
        • legal system
        • administrative system
      • Mechanisms
        • Lock-in – preventing easy migration to new technology
        • adaptive stretch – adopting new technology to augment existing ones
      • Opens the door for disruption
  • Technology buildout tends to be concentrated in one country or region – concentration of talents (people with deep craft) and the forming of a culture
    • who to talk to
    • how to get something fixed
    • what to ignore
    • what theories / principals to look to
  • An economy (how resources are exchanged) is the expression of its technology
    • Economy is neurons, flesh and blood
    • Technology is the skeletal structure

Insights from lunch with Manish and Ketan

  • The tech industry is cyclical
    • Consumer Tech is going out of trendy and
    • enterprise is coming into trend
  • Look up for parallels, for example case studies for how the following company grew
    • New Relic
    • Rubrik
  • Co-founder discussions
    • 4 year vesting, 1 year cliff
    • Clarify edge cases like board seat, shares and voting rights in the event of death
    • Date first before marriage
      • need to test them on smaller scope to see if they can deliver (remunerate with profit sharing)
      • if they prove themselves overtime, start exploring larger scope where they can work together (consider with shares)
  • Team configuration
    • product development
      • product management
      • engineering
      • design
    • Enterprise sales
    • Finance – much later when sales is happening

SPY – SnP index during Dec 2018 market pull back

  • The market contracted by as much as 17% (USD290 to USD240)
  • Turn around happened on 24th Dec 2018 during Christmas
    • Negative trading volume was below moving average
    • Positive trading volume was above moving average
    • RSI was in oversold territory ( <30)
  • Macro Factors
    • Trade War
    • Federal reserve interest rate hike