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

More from Business

balajis.com
balajis.com
@balajis
A solo media founder like Rogan or Mr Beast can make as much money as a strong tech founder, with significantly less managerial stress.

Tech created this ecosystem but there’s a historical cultural bias in tech towards media as unprofitable. That changed a long time ago.

Many more angels that invest in people will invest in media founders. Many traditional media people will *become* media founders.

But not necessarily big companies. Just solo individuals or small groups doing content, like Notch doing Minecraft. Because media scales like code.

Increasingly feeling like “keeping the team size as small as possible, even to one person” is the unarticulated key to making media profitable.

Substack and all the creator tools are just the start of this ecosystem.


The process of converting social influencers into media founders (a trend that has been going on for 10+ years at this point) will be increasingly streamlined.

V1 is link-in-bio, Substack, and sponcon.

V2 likely involves more angels & tokenization a la @tryrollhq. What else?

Why lack of awareness? Influencer monetization numbers are not as public as tech numbers.

There isn’t a TechCrunch & CrunchBase for media founders, chronicling the valuations of influencers.

But that’d be quite valuable. If you are interested in doing this, please DM with demo.
BUSINESS
Vijay Patel
Vijay Patel
@vijaygajera
Sarad Pawar was a director in a shell company, which have done transaction of 7 Lakh crore in cash in UK.
Company Name was SGFX FINANCIALS CO UK LIMITED. (What could be full Name of SG? Any Guess?)
Thread


According to the UK company filing database, Mr Pawar was appointed as board member of SGFX Financials Co on 13 December 2010 and left the company on 5 January 2011. The filing also notes Mr Pawar's occupation as Minister, Government of India.

This company was incorporated on 13 December 2010 and dissolved on 27 November 2012. Nature of business was ‘Other business activities’!


There were two more directors when company was incorporated
1 is Mr Sarvesh Narendra Gade and 2nd is Mrs Shahanaz Ashraf Bharde


But when this details came out in 2015, Sarad Pawar has filed a case against this couple for using his name without his knowledge! Like really?
Please see below document, which have clearly mentioned that it was authenticated!
BUSINESS
Advertisement
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.
BUSINESS
Romeen Sheth
Romeen Sheth
@RomeenSheth
I love Twitter.

It’s truly the Town Square of the Internet.

But finding the diamond in the rough voices can be tough.

Here are 20 of my favorite people to follow:

1. Alex Lieberman - @businessbarista

Alex writes extensively about the Founder journey.

The cool part is he’s lived everything he talks about - starting from $0 and selling for $75M with hardly any outside capital raised.

My favorite piece:


2. Ryan Breslow - @ryantakesoff

Ryan is a Top 1% founder.

This guy is a machine - he’s built 2 unicorns before the age of 27.

Ryan spells out lessons on fundraising, operating and scaling.

My favorite piece:


3. Jesse Pujji - @jspujji

Jesse is who I think of when I think “bootstrapping.”

He bootstrapped his company to an 8-figure exit and now shares stories about other awesome bootstrappers.

He’s also got great insight into all things growth marketing:


4. Post Market - @Post_Market

Post puts out some of the most thoughtful investment insights on this platform.

It’s refreshing because Post cuts through the hype and goes deep into the business model.

Idk who he/she/it is, but the insights are 💣.
BUSINESS
Andrew Finn
Andrew Finn
@finnscave
Young, early stage founder asked for any hiring thoughts - figured worth sharing with the twitter-verse if they can be helpful.

1a) Make people do the work they are going to do for you during the interview process.

1b) People talking about work and experience is basically useless, except to evaluate whether this job "makes sense" for someone at this stage of their life - do the dots connect or not? If you can convince people to do a contract project for a month first, even better.

2) Optimize for IQ/horsepower. Talent overruns experience in like 3-6 months and never looks back. If you love someone, but they are missing a skill, you're better off getting them to learn it than hiring someone more skilled but with less upside.

3) Optimize for low drama and ease to work with, in all ways. You want people who just want to get shit done and enjoy themselves, not people who want to bring their personal drama into the workplace.

4) People who went to the best state school in the state they are from, and were overqualified for that school, tend to be undervalued and have a great low ego/high execution/high IQ ratio. They have ivy league brains with middle class values.
BUSINESS

You May Also Like

Andrew Chen
Andrew Chen
@andrewchen
👇Thread.

Published a new essay: The red flags and magic numbers that investors look for in your startup’s metrics – 80 slide deck included!


This was a deck that I created on my (longish) interview process with @a16z. It was a long path, starting with meeting folks at the firm 10 years ago. But the purpose of the deck was to explain how I would use my superpower in an investing context

Here's what I explain in the deck. As investors (whether angel or VC) we're often confronted with an up-and-to-the-right graph. Is it going to go up? Or down?


One solution to forecast these growth curves is the Growth Accounting Framework, where you add up New+Reactivated and subtract churned users. In each time period that gives you the difference in monthly actives.


The problem with this is that it's a lagging metric, not a leading one. We need to go one level deeper and look at the underlying loops that drive these numbers, to understand the quality.
STARTUPS
Brian Armstrong
Brian Armstrong
@brian_armstrong
1/ Productivity tip: when I keep procrastinating on something I often trick myself by saying, "ok just work on it for the next 20 minutes" or some short period of time, "and then you can chill/relax guilt free" and give myself some treat (sugar, netflix, etc)

2/ Usually at the 20 minute mark (sometimes I set a timer) I'm so engrossed in what I'm doing that I don't want want to stop and end up working on it for the next hour or two. But getting started seems to be the hardest part.

3/ Key to this: you have to actually be ok with stopping after 20 minutes and being guilt free if that's how you feel. So it's not a trick, i have the option every time, I just often don't want to use it once i'm in the zone.
PRODUCTIVITY
Advertisement
Elizabeth May
Elizabeth May
@_ElizabethMay
This is NONSENSE. The people who take photos with their books on instagram are known to be voracious readers who graciously take time to review books and recommend them to their followers. Part of their medium is to take elaborate, beautiful photos of books. Die mad, Guardian.


THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN


If you come for Bookstagram, i will fight you.

In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)
FUN
Meet Shah
Meet Shah
@ms89_meet
Strong Monopolies:

IRCTC 100% Market share in Rail Network.

IEX >90% market share in power trading.

Zydus wellness >90% market share in sugar free product.

Eicher motors >85% market share in 250cc bikes category.

MCX >85% market share in commodity trading.

Coal India >80% market share in coal production in India.

ITC >75% market share in cigarettes.

Honda Siel >75% in portable power generators.

Hindustan Zinc >75% market share in primary zinc industry.

Asahi India Glass >70% market share in automotive glass.

NRB Bearings >70% market share in needle roller bearings.

Pidilite >65% market share in adhesives.

CAMS >65% market share in RTA within mutual fund industry.

Time Technoplast >65% market share in polymer based industrial packaging.

Concor >65% market share in domestic container cargo transport.

Exide >60% market share in lead batteries.

Naukri >60% market share in the Indian job market space.

Praj >60% market share in ethanol plant installing.

Indiamart Intermesh >55% market share in the online B2B Classified space.

Borosil Renewables >55% market share in Lab glass.

Vst Tillers >50% market share in
Power tillers.

Delta corp >50% in online poker games.

Vinati Organics >50% market share in IBB.
GENERICLEARNINGS , GENERAL TWEER , INTRESTING TOPIC
Vibhu Vashisth
Vibhu Vashisth
@VIBHU_Tweet
THE UNTOLD TALE OF THE LESSER KNOWN WARRIORS:JOGRAJ GURJAR & RAMPYARI GURJAR AND HOW DID THEY DEFEAT THE CRUELEST ISLAMIC INVADER, TIMUR LANG.

Timur Lang, was the founder of Timurid Empire. He was born in April 1336 CE, somewhere in central asia.


During his reign, he conquered Persia, Egypt, Central Asia and emerged as the most powerful and heinous ruler. He was a religious fanatic like the rest of the Islamic invaders who tried to invade India.

Timur Lang decided to invade India in 1398 as he heard about India's splendid wealth and had a desire to conquer India which his ancestor Genghis Khan couldn't do.


After Firoz Shah's demise in1388, Delhi Sultanate was in a state of political turmoil.During this time, Timur sent his grandson Pir Mohammad to attack Indian front. He invaded Multan&was able to defeat Iqbal Khan's brother but when he met with resistance,he asked help from Timur.


Iqbal Khan secured his hold on Delhi under Muhammad Tughluq after Firoz Shah died.
Timur provided the required back-up to his grandson with 100000 men approx. Timur sacked and plundered all the cities coming in his way &later in October 1398 reunited with his grandson.
ALL