BC BUSINESS
Saved by @Mollyycolllinss

Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:

1. That looks useful!
2. That's an interesting approach!
3. A business could be built around this!
4. How did they do that?!

 Argument Schemes and Dialogue for Explainable Planning

https://t.co/iI3fxAuOcF
Neural Fitted Q Iteration based Optimal Bidding Strategy in Real Time Reactive Power Market_1

https://t.co/rs7fJc8Sws
A design of human-like robust AI machines in object identification

https://t.co/m1Tfm1KYUl
Single Shot Multitask Pedestrian Detection and Behavior Prediction

https://t.co/S3tiOnHoRw
Controlling Synthetic Characters in Simulations: A Case for Cognitive Architectures and Sigma

https://t.co/mjqovCGUhj
Data Poisoning Attacks to Deep Learning Based Recommender Systems

https://t.co/FVr7Z9YiX1
Self-Attention Based Context-Aware 3D Object Detection

https://t.co/UcyP6IUr1V
L2PF -- Learning to Prune Faster

https://t.co/E1ipKSBFk3
DeepPoison: Feature Transfer Based Stealthy Poisoning Attack

https://t.co/B3beuwHBVD
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead

https://t.co/E9B8E4YZj6
Explainable AI and Adoption of Algorithmic Advisors: an Experimental Study

https://t.co/5Q98CpM89U
Multimodal Gait Recognition for Neurodegenerative Diseases

https://t.co/NkcrwgWfsT
On the Management of Type 1 Diabetes Mellitus with IoT Devices and ML Techniques

https://t.co/EGaHwpI6gC
Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

https://t.co/esweLNEoMb
A Comprehensive Study on Optimization Strategies for Gradient Descent In Deep Learning

https://t.co/DnyxRqxNRY
Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English

https://t.co/NKpQ0gntHy
Low-cost and high-performance data augmentation for deep-learning-based skin lesion classification

https://t.co/NMcnVpRZt5
StarNet: Gradient-free Training of Deep Generative Models using Determined System of Linear Equations

https://t.co/23HkZdcPKe
Adaptive Synthetic Characters for Military Training

https://t.co/5xNFThJlWK
The case for psychometric artificial general intelligence

https://t.co/w1ZJNCAj39
Artificial Intelligence Methods in In-Cabin Use Cases: A Survey

https://t.co/6kFoUSuLpJ
TextBox: A Unified, Modularized, and Extensible Framework for Text Generation

https://t.co/u62zif51D8
Off-Policy Meta-Reinforcement Learning Based on Feature Embedding Spaces

https://t.co/ugJvlG7b3t
Deep Reinforcement Learning with Quantum-inspired Experience Replay

https://t.co/9TBKAAGMmO
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges

https://t.co/58rbKCY9Ru
Internet of Everything enabled solution for COVID-19, its new variants and future pandemics: Framework, Challenges, and Research Directions

https://t.co/OgZKw3Cov6
Deep Neural Network Based Relation Extraction: An Overview

https://t.co/ISBG8c7UzQ
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks

https://t.co/MuUG6LsPUF
Theory-based Habit Modeling for Enhancing Behavior Prediction

https://t.co/UZDtp2A83a
Explainable AI for Robot Failures: Generating Explanations that Improve User Assistance in Fault Recovery

https://t.co/Fcn2uVEsIp
On the Control of Attentional Processes in Vision

https://t.co/B35B7Dk54K
Stochastic Optimization for Vaccine and Testing Kit Allocation for the COVID-19 Pandemic

https://t.co/CF6glQV2nW
Analyzing movies to predict their commercial viability for producers

https://t.co/VaEcSaIJtj
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning

https://t.co/nKBRaA6the
"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment

https://t.co/Cix2rinBob
Support Vector Machine and YOLO for a Mobile Food Grading System

https://t.co/VmiOwRZ2gV
To do or not to do: cost-sensitive causal decision-making

https://t.co/9iDr9CogRJ
Political Depolarization of News Articles Using Attribute-aware Word Embeddings

https://t.co/EsOFDI97Q5
Understanding the Ability of Deep Neural Networks to Count Connected Components in Images

https://t.co/gUPQWJ6YEM
Development of a Respiratory Sound Labeling Software for Training a Deep Learning-Based Respiratory Sound Analysis Model

https://t.co/VLdratnPjD
Learn by Guessing: Multi-Step Pseudo-Label Refinement for Person Re-Identification

https://t.co/gTK15Nmoko
Strategic Features for General Games

https://t.co/4Yt3ZTKb8N
Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering

https://t.co/44WSpjKDZd
Enhanced Pub/Sub Communications for Massive IoT Traffic with SARSA Reinforcement Learning

https://t.co/UWIa18td2P
Sentiment Analysis for Open Domain Conversational Agent

https://t.co/2EJqPRIvop
If You're Happy, Then You Know It: The Logic of Happiness... and Sadness

https://t.co/PJTcraD0K7
An Ontology Design Pattern for representing Recurrent Situations

https://t.co/7BWFJqKhBJ
DVD: A Diagnostic Dataset for Multi-step Reasoning in Video Grounded Dialogue

https://t.co/tTZKVlvrWe
Transformers in Vision: A Survey

https://t.co/liP1MJY72v
High-resolution land cover change from low-resolution labels: Simple baselines for the 2021 IEEE GRSS Data Fusion Contest

https://t.co/G5sWF4GYiY
Dynamic Knowledge Graphs as Semantic Memory Model for Industrial Robots

https://t.co/PcfTq36heO
Understanding Health Misinformation Transmission: An Interpretable Deep Learning Approach to Manage Infodemics

https://t.co/nwLiRdGkBQ
Anomaly Recognition from surveillance videos using 3D Convolutional Neural Networks

https://t.co/LU634yUAyU
Personal Privacy Protection via Irrelevant Faces Tracking and Pixelation in Video Live Streaming

https://t.co/dL4GJw3y95
Zombie Account Detection Based on Community Detection and Uneven Assignation PageRank

https://t.co/VGkZKfM4ih
How to Train Your Agent to Read and Write

https://t.co/NJJreymjby
Identifying centres of interest in paintings using alignment and edge detection: Case studies on works by Luc Tuymans

https://t.co/sahwzV0akw
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation

https://t.co/mQydI1yWtY
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events

https://t.co/GARbpQmbFA
Fusion of Federated Learning and Industrial Internet of Things: A Survey

https://t.co/ZoZD7WWSWa
A Framework for Fast Scalable BNN Inference using Googlenet and Transfer Learning

https://t.co/YC83Pv82kf
Neural Networks for Keyword Spotting on IoT Devices

https://t.co/aPwYWpM7vS
AttnMove: History Enhanced Trajectory Recovery via Attentional Network

https://t.co/qjt6g20nX9
Privacy-sensitive Objects Pixelation for Live Video Streaming

https://t.co/GwHIjWYXqJ
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier

https://t.co/ePVpLxTtsX
End-to-End Training of Neural Retrievers for Open-Domain Question Answering

https://t.co/2m9PzQnl65
A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition

https://t.co/cvKIwFmsWQ
RiddleSense: Answering Riddle Questions as Commonsense Reasoning

https://t.co/VPnK6TmMBY
Identity-aware Facial Expression Recognition in Compressed Video

https://t.co/9mNnzvWugT
Iranis: A Large-scale Dataset of Farsi License Plate Characters

https://t.co/taFXmeM6om
Reader-Guided Passage Reranking for Open-Domain Question Answering

https://t.co/2wt7nbg7ap
CIZSL++: Creativity Inspired Generative Zero-Shot Learning

https://t.co/jqsFZI6Bxa
DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledge

https://t.co/WY8fldH1Un
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

https://t.co/eDeIZrFx08
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets

https://t.co/3omOhvBIQN
Etat de l'art sur l'application des bandits multi-bras

https://t.co/0zqsbla1ZF
Binary Graph Neural Networks

https://t.co/VZnSpSWJmp
An automated machine learning-genetic algorithm (AutoML-GA) approach for efficient simulation-driven engine design optimization

https://t.co/8pAjZDl9uZ
CoachNet: An Adversarial Sampling Approach for Reinforcement Learning

https://t.co/yibeyARmL3
A Clinical Evaluation of a Low-Cost Strain Gauge Respiration Belt and Machine Learning to Detect Sleep Apnea

https://t.co/7OQTeR0cBz
MRNet: a Multi-scale Residual Network for EEG-based Sleep Staging

https://t.co/KuKpdhWhkD
Robust Text CAPTCHAs Using Adversarial Examples

https://t.co/08spXMzEji
Detecting Log Anomalies with Multi-Head Attention (LAMA)

https://t.co/qXK049ht20
Architectural Patterns for the Design of Federated Learning Systems

https://t.co/MVHtYSIWjm
Coding for Distributed Multi-Agent Reinforcement Learning

https://t.co/t0Re9BrNHd
Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models

https://t.co/qzrec6IDOG
Handling many conversions per click in modeling delayed feedback

https://t.co/ZrU0uhNPHT
Teach me to play, gamer! Imitative learning in computer games via linguistic description of complex phenomena and decision tree

https://t.co/uXGXX0WLAD
Adversarial Machine Learning for 5G Communications Security

https://t.co/ScIUq3Pklz
From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation

https://t.co/R7k3hDzJ5W
Automatic identification of outliers in Hubble Space Telescope galaxy images

https://t.co/4PafKjJNJl
Learning a binary search with a recurrent neural network. A novel approach to ordinal regression analysis

https://t.co/wthbFhJAlj
RANK: AI-assisted End-to-End Architecture for Detecting Persistent Attacks in Enterprise Networks

https://t.co/Gor8YavtJq
Continuous Glucose Monitoring Prediction

https://t.co/m6ufMRn9vm
Phishing Attacks and Websites Classification Using Machine Learning and Multiple Datasets (A Comparative Analysis)

https://t.co/FFvkJsN5m5
MSED: a multi-modal sleep event detection model for clinical sleep analysis

https://t.co/Ki9FU3eCTC
A spin-glass model for the loss surfaces of generative adversarial networks

https://t.co/k0zRhKrRFh
Active learning for object detection in high-resolution satellite images

https://t.co/ildobu8RWv
RobustSleepNet: Transfer learning for automated sleep staging at scale

https://t.co/SjB1zOJe9N
Homonym Identification using BERT -- Using a Clustering Approach

https://t.co/LcHjpCT4m4
User Response Prediction in Online Advertising

https://t.co/HvZKLMliJw
COVID19-HPSMP: COVID-19 Adopted Hybrid and Parallel Deep Information Fusion Framework for Stock Price Movement Prediction

https://t.co/vqviIbd1Jb
User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics

https://t.co/2V5vFEojhL
An Odor Labeling Convolutional Encoder-Decoder for Odor Sensing in Machine Olfaction

https://t.co/geb8sFURyH
Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows

https://t.co/bEC6qAdAaS
Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

https://t.co/XE226wSV7w
Do We Really Need Deep Learning Models for Time Series Forecasting?

https://t.co/s1muXDs5NJ
Statistical learning for accurate and interpretable battery lifetime prediction

https://t.co/gqLMDxZO7D
3D Convolutional Selective Autoencoder For Instability Detection in Combustion Systems

https://t.co/CjjRuGypAO
The data synergy effects of time-series deep learning models in hydrology

https://t.co/BnQMmqfIwc
Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

https://t.co/ChMZRx6IFe
Risk markers by sex and age group for in-hospital mortality in patients with STEMI or NSTEMI: an approach based on machine learning

https://t.co/dz61KNDgri
The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases

https://t.co/tyLUSSQRM4
Model Extraction and Defenses on Generative Adversarial Networks

https://t.co/swz4ZCHmgv
Boarding House Renting Price Prediction Using Deep Neural Network Regression on Mobile Apps

https://t.co/I7U7R7uv4B
COVID-19: Comparative Analysis of Methods for Identifying Articles Related to Therapeutics and Vaccines without Using Labeled Data

https://t.co/yEir3K29sV
Comparing Classification Models on Kepler Data

https://t.co/JZoxxWvywE
Interspeech 2021 Deep Noise Suppression Challenge

https://t.co/xaU6nRRtco
Biosensors and Machine Learning for Enhanced Detection, Stratification, and Classification of Cells: A Review

https://t.co/gJMrXaPGUD
Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks

https://t.co/kD7xrRcYNu
Mesh Reconstruction from Aerial Images for Outdoor Terrain Mapping Using Joint 2D-3D Learning

https://t.co/HwjjezqQyg
A Review of Artificial Intelligence Technologies for Early Prediction of Alzheimer's Disease

https://t.co/Ak0vrmyogD
An A* Curriculum Approach to Reinforcement Learning for RGBD Indoor Robot Navigation

https://t.co/R4dy1PCIfV
Auto-Encoding Molecular Conformations

https://t.co/21BhsA7GXw
Adversarially trained LSTMs on reduced order models of urban air pollution simulations

https://t.co/u44QNP35Rb
Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization

https://t.co/PByu7o8tul
Data-Driven Copy-Paste Imputation for Energy Time Series

https://t.co/wPbr4eswsu
One vs Previous and Similar Classes Learning -- A Comparative Study

https://t.co/bCxer47W0s
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations

https://t.co/k5xeSGhXxp
Robust R-Peak Detection in Low-Quality Holter ECGs using 1D Convolutional Neural Network

https://t.co/a9uL9mJuCC
Learning the Predictability of the Future

https://t.co/Y7yz6X2MNr
CASS: Towards Building a Social-Support Chatbot for Online Health Community

https://t.co/MjmRThHMyX
WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection

https://t.co/mbpItXkjMf
Recurrent Neural Networks for Stochastic Control Problems with Delay

https://t.co/TEcyk88BDz
A Symmetric Loss Perspective of Reliable Machine Learning

https://t.co/VTARzV3bnx
Fixed-MAML for Few Shot Classification in Multilingual Speech Emotion Recognition

https://t.co/WbqicxzG1V
Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping

https://t.co/W61kqz9z7y
Advances in Electron Microscopy with Deep Learning

https://t.co/j3Z1kB4VKQ

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Kostas on FIRE \U0001f525
Kostas on FIRE 🔥...
@itsKostasOnFIRE
The Mother of All Squeezes

How Volkswagen went from being on the brink of bankruptcy to the most valuable company in the world in two days

/THREAD/


1/ At the peak of the 2008 financial crisis, Volkswagen was considered a very likely candidate for bankruptcy.

Heavily indebted and already financially struggling before 2008, with car sales expected to plummet due to the ongoing global crisis.


2/ With GM and Chrysler filing for bankruptcy in 2009, shorting the VW stock would seem a safe bet.

If you are not familiar with stock shorts and short squeezes check my thread


3/ On October 26, 2008, Porsche announced it had increased its stake at VW from 30% to 74%.

This was a surprise to many who were led to believe that Porsche wasn't planning a takeover of VW, based on the company's announcements.


4/ Before the announcement, the short interest was approximately 13% of the outstanding shares, a number considered relatively low.

Porsche had a 30% stake, the Lower Saxony government fund held 20% of the shares, and another 5% was held by index funds.
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Zikhona Valela
Zikhona Valela
@valavoosh
Should we go into the details of these 125 years?


SA is built on the exploitation of labour. That labour has functioned on alcohol unfortunately. Very few people consume liquor purely for enjoyment unfortunately. When SAB opened its doors 1895 workers were paid in alcohol- the dop/tot system. 2 years into SAB's establishment

The Prohibition Act is introduced. This means black people are barred from buying your wines, beer etc. So SAB's products are exclusively for white people. But during this period beer brewing by Black women is the norm. Ayinxilisi ncam ke this type of beer. Apparently it had some

Nutritious elements to it. Now some of the context around drinking culture during this time is migrant labour to the mines, further land dispossession, the Anglo-Boer Wars, Rhodes corruption (our first state capture commission if you will) which leads to his resignation.

This context plays a role in how our cities and small towns are constructed, how they lead to the confinement and surveillance yabantu. Traditional beer brewing is identified as a threat because buy now mining bosses have identified that there's money to be made here.
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How Amazon makes money?

[ Amazon's business model decoded😃]

@dmuthuk @unseenvalue @FI_InvestIndia @Vivek_Investor @drprashantmish6 @caniravkaria

🧵👇


1/ A person named Jeffery earns 100 dollars per month and has an expenditure of 120 dollars monthly. He has a very good reputation in the society. So, he takes a loan of 1k dollars for a month and this 1k cash is invested in new business ventures.

2/ For the next month, he pays his liability back by taking a loan from another person for 1.5k dollars. The loan of 1k is paid back and the remaining 500 dollars are invested in another business venture.

3/ By the end of the month, he earns 150 dollars through his old and new business ventures but has a total expenditure of 200 dollars. He again is in a deficit of 50 dollars. To pay back his 1.5k dollar loan, he takes a loan for 2k dollars

4/ This cycle goes on and on. Jeffery keeps on taking bigger loans to repay the previous loan and the leftover extra loan is invested in bigger ventures which produce more expense than income.
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Rohun
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If you make more than $100k per year you should have a Virtual Assistant.

If you don't, you're wasting your time on stuff that doesn't matter.

Here's the process I've created to find, interview, and manage great VA's after doing this for 5 years:

There's a lot of tasks you work on that are well below your intellectual capability.

Booking haircut appointments, ordering groceries, and finding flights is a waste of time.

First, you want to find out what tasks can you delegate.

Here's how:

Track everything you do every 15 minutes in a spreadsheet. Create 3 columns w/ the below questions

1. Do I like doing this?
2. Is it repeatable?
3. Can it be delegated?

If the answers are No, Yes, Yes -- you've found tasks to delegate!

We'll jump back into these tasks later.

Before we learn how to find them, let's understand the types of VA's:

1. Individual Freelancers (Low cost & High cost)
2. Agency VA's (High cost)

My experience has been with low-cost VA's (under $6/hour). I've gotten the same level of quality that I would with most US VA's.

Now, here's how we craft the right job post to attract the best ones: Be as specific as possible with what you expect. Here’s an example:

Also ask for a screenshot of their computer specs & internet speed results and a 2 min video of their background & why they want the job.
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Good news everyone, Jay Hoag gave us the simple 5 point playbook for finding Magical Companies in consumer technology.

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3. a virtuous cycle
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'Treasure Gods' - Sangha Nidhi' and 'Padma Nidhi', Tirumala, Tirupati.

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These are the two guards guarding the Wealth and Treasure of Lord Sri Venkateswara.

They are representatives of two treasures of Kubera, the God of Wealth.


One guard who is holding shangam (conch) on both the hands is known as Shanka Nidhi ('nidhi' means wealth).

On the other side, the guard who is holding Lotus flowers on both the hands is known as Padma nidhi.

Shangu is from the ocean which includes all types of wealth like pearls and corals.

Why shagam in his hand? Because shangam only gives the sound of 'omkaram'.

'Padmam' is the symbol of water sources in land like river, lakes, tanks etc. which is very important for all living beings.

As per the tradition, these guards are installed at the third entrance of the temple.

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**Thread on Bravery of Sikhs**
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Rani Jindan Kaur, wife of Maharaja Ranjit Singh had illegitimate relations with Lal Singh (PM of Ranjit Singh). Along with Lal Singh, she attacked Jammu, burnt - https://t.co/EfjAq59AyI


Hindu villages of Jasrota, caused rebellion in Jammu, attacked Kishtwar.

Ancestors of Raja Ranjit Singh, The Sansi Tribe used to give daughters as concubines to Jahangir.


The Ludhiana Political Agency (Later NW Fronties Prov) was formed by less than 4000 British soldiers who advanced from Delhi and reached Ludhiana, receiving submissions of all sikh chiefs along the way. The submission of the troops of Raja of Lahore (Ranjit Singh) at Ambala.

Dabistan a contemporary book on Sikh History tells us that Guru Hargobind broke Naina devi Idol Same source describes Guru Hargobind serving a eunuch
YarKhan. (ref was proudly shared by a sikh on twitter)
Gobind Singh followed Bahadur Shah to Deccan to fight for him.


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The Ife Primary Education Research Project (1970-1983).

aka

The Ife 6-Year Primary Project.


In 1970, as the Director of the Institute of Education of the then University of Ife (now Obafemi Awolowo University, Ile-Ife), later Dean Faculty of Education, Prof. Babs Fafunwa & his team embarked on one of the most groundbreaking research projects in education for Yorubaland.


The aim of the project was to test the hypothesis that the best instructional medium for good concept formation at a very tender age is the mother tongue.

This was bolstered by the observation that “of all the continents and peoples of the world, it is only in Africa…

…that formal education is offered in a language that is foreign to the child.”

So, Yoruba was to be used & tested as an exclusive medium of passing information or instructions to a set of pupils.

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Due to the pandemic you may not have visited your local library in a while. So come with me on a virtual library tour, courtesy of stock photography, to see what we do for a living...


Libraries are of course information resource centres, but in many ways they are so much more. To get the best out of them you need to really know your way around the stacks.


The enquiries desk is normally your first stop in a library, and this is where you will meet The Angry Librarian! Why is she angry? Because you keep asking her stupid questions!


"Are you open?"
"Do you have a toilet?"
"That chair's wobbly!"
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On and on it goes...


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👇 Thread. New deck getting published this week: "Consumer startups are awesome, and here's what I'm looking to invest in at Andreessen Horowitz." If you want to read it, subscribe to my newsletter here: https://t.co/262t8eh0wf


1/ A lot of new consumer technologies have been introduced to US households in the last 100 years. But it's taken many of them - like the telephone - more than 50 years to get to the majority of the US. Why is that?


2/ We had to literally teach people how to use phone. Which end goes to your mouth, which goes to your ear. Say "hello" when people call. The motivation of consumers to talk to their friends has always been there, but we had to teach the behavior


3/ If you compare phones to the latest technologies, there's been a huge shift. Things are being picked up much faster.


4/ Even while there's been all this innovation recently, physically speaking, we are still the same human beings from 100,000 years ago.
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