import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import re
import nltk
from nltk.tokenize import word_tokenize
import sys
import gensim
from gensim import corpora
from gensim.models.lsimodel import LsiModel, stochastic_svd
from gensim.models.coherencemodel import CoherenceModel
from gensim.models import RpModel
from gensim.matutils import corpus2dense, Dense2Corpus
from gensim.test.utils import common_texts
from gensim.corpora.dictionary import Dictionary
from gensim.models.ldamodel import LdaModel # Latent Dirichlet Allocation and not 'Latent Discriminant Analysis'
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.preprocessing import normalize
from sklearn.decomposition import LatentDirichletAllocation, PCA
from sklearn.cluster import KMeans
from sklearn.random_projection import SparseRandomProjection, johnson_lindenstrauss_min_dim
from sklearn.random_projection import GaussianRandomProjection
from sklearn.metrics.pairwise import euclidean_distances
import string
from collections import Counter
from preprocess import preprocess_text
import spacy
from time import time
nlp = spacy.load("en_core_web_sm")
def remove_verbs_and_adjectives(text):
doc = nlp(text)
additional_stopwords = ["new", "like", "many", "also", "even", "get", "say", "according", "would", "could",
"know", "made", "make", "come", "didnt", "dont", "doesnt", "go", "may", "back",
"going", "including", "added", "set", "take", "want", "use",
"000", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "20", "u",
"one", "two", "three", "year", "first", "last", "good", "best", "well", "told", "said"]
days_of_week = ["monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"]
additional_stopwords += days_of_week
words = [token.text for token in doc if (token.pos_ not in ["VERB", "NUM", "ADJ", "ADV", "ADP", "SCONJ", "DET",
"X", "INTJ", "CCONJ", "AUX", 'PART', 'PRON', 'PUNCT', 'SYM'])]
# Only Noun and (PROPN) Proper Noun allowed.
words = [x for x in words if len(x) > 2]
words = [x for x in words if x not in additional_stopwords]
doc = " ".join(words)
return doc
df1 = pd.read_csv('bbc_news_train.csv')
%%time
df1['Preprocess_text'] = df1['Text'].apply(preprocess_text)
df1['Preprocess_text'] = df1['Preprocess_text'].apply(remove_verbs_and_adjectives)
CPU times: total: 2min 3s
Wall time: 2min 8s
df1[['Text', 'Preprocess_text']].head()
Counter(df1['Category'])
Counter({'business': 336,
'tech': 261,
'politics': 274,
'sport': 346,
'entertainment': 273})
from gensim.test.utils import common_texts
from gensim.corpora.dictionary import Dictionary
# Create a corpus from a list of texts
clean_corpus = [doc.split() for doc in df1['Preprocess_text'].values.tolist()]
common_dictionary = Dictionary(clean_corpus)
common_corpus = [common_dictionary.doc2bow(text) for text in clean_corpus]
%%time
NO_OF_TOPICS_FOR_TRAINING = 5
NO_OF_WORDS_IN_TOPIC = 20
lda = LdaModel(common_corpus, num_topics = NO_OF_TOPICS_FOR_TRAINING, id2word = common_dictionary)
CPU times: total: 9.39 s
Wall time: 8.27 s
ldamodel_topics = lda.print_topics(NO_OF_TOPICS_FOR_TRAINING, NO_OF_WORDS_IN_TOPIC)
for (topic_id, probabilities) in ldamodel_topics:
topic_string = "\n\nTopic Id: " + str(topic_id) + "\n Probabilities: " + str(probabilities)
print(topic_string)
Topic Id: 0
Probabilities: 0.006*"government" + 0.004*"film" + 0.004*"time" + 0.004*"labour" + 0.004*"people" + 0.004*"service" + 0.004*"election" + 0.004*"minister" + 0.003*"award" + 0.003*"blair" + 0.003*"market" + 0.003*"week" + 0.003*"party" + 0.003*"game" + 0.003*"number" + 0.003*"director" + 0.003*"brown" + 0.002*"actor" + 0.002*"company" + 0.002*"star"
Topic Id: 1
Probabilities: 0.008*"game" + 0.007*"time" + 0.006*"people" + 0.005*"world" + 0.005*"film" + 0.004*"service" + 0.003*"player" + 0.003*"bbc" + 0.003*"company" + 0.003*"home" + 0.003*"day" + 0.003*"plan" + 0.003*"show" + 0.003*"country" + 0.003*"music" + 0.003*"week" + 0.003*"team" + 0.003*"number" + 0.003*"firm" + 0.003*"party"
Topic Id: 2
Probabilities: 0.009*"film" + 0.008*"people" + 0.005*"time" + 0.005*"game" + 0.005*"phone" + 0.004*"world" + 0.004*"company" + 0.004*"month" + 0.003*"firm" + 0.003*"award" + 0.003*"market" + 0.003*"government" + 0.003*"bbc" + 0.003*"mobile" + 0.003*"day" + 0.003*"software" + 0.003*"sale" + 0.003*"director" + 0.003*"number" + 0.002*"service"
Topic Id: 3
Probabilities: 0.008*"people" + 0.006*"government" + 0.006*"country" + 0.006*"world" + 0.005*"company" + 0.005*"firm" + 0.004*"time" + 0.004*"month" + 0.004*"number" + 0.004*"market" + 0.004*"tax" + 0.004*"week" + 0.003*"way" + 0.003*"service" + 0.003*"deal" + 0.003*"group" + 0.003*"minister" + 0.003*"sale" + 0.003*"plan" + 0.003*"music"
Topic Id: 4
Probabilities: 0.006*"people" + 0.006*"game" + 0.006*"time" + 0.005*"election" + 0.004*"player" + 0.004*"england" + 0.004*"number" + 0.003*"world" + 0.003*"party" + 0.003*"music" + 0.003*"company" + 0.003*"group" + 0.003*"report" + 0.003*"bbc" + 0.003*"part" + 0.003*"service" + 0.003*"month" + 0.003*"sale" + 0.003*"government" + 0.003*"way"
Monday, June 27, 2022
Creating a Taxonomy for BBC News Articles (Part 9 - Using POS Tagging as word filter with Latent Dirichlet Allocation)
Sunday, June 26, 2022
Infosys Certified NLP Professional (Cheat Sheet)
Infosys Certified Natural Langugage Processing Professional: The test comprises of 21 questions. Five questions asked in the test are: 1. What is IDF? 2. What are Alpha and Beta in Latent Dirichlet Allocation? Among alpha and beta, which one relates to 'number of topics'? 3. Which vectorizing technique gives more weightage to 'stop' words: 3.a. GloVe 3.b. Word2Vec 3.c. TF-IDF 3.d. Bag of words 4. What is the purpose of Linear Discriminant Analysis? 5. Which of the following is a tokenization step? 5.a. getting unique words from text. 5.b. getting most undivisable unit from text 6. Does the word order matter in LDA (Latent Dirichlet Allocation)? 7. Which of the given word pairs shows stemming?Tags: Technology,Natural Language Processing,
Friday, June 24, 2022
Ciprobid 500 (Ciprofloxacin Tablet)
Ciprobid 500 Tablet Prescription Required Manufacturer: Zydus Cadila SALT COMPOSITION: Ciprofloxacin (500mg)Product introduction
Ciprobid 500 Tablet is an antibiotic, used in the treatment of bacterial infections. It is also used in treating infections of the urinary tract, nose, throat, skin and soft tissues and lungs (pneumonia). It cures the infection by killing and stopping the growth of the infectious microorganisms. Ciprobid 500 Tablet should be used in the dose and duration as advised by your doctor. It may be taken with or without food, preferably at a fixed time. Avoid skipping any doses and finish the full course of treatment even if you feel better. Do not take a double dose to make up for a missed dose. Simply take the next dose as planned. You may experience nausea as a side effect of this medicine. This is usually temporary and resolves on its own, but please consult your doctor if it bothers you or persists for a longer duration. Diarrhea may also occur as a side effect but should stop when your course is complete. Inform your doctor if it does not stop or if you find blood in your stools. You should not take this medicine if you are allergic to any of its ingredients. Rarely, some people may have a severe allergic reaction which needs urgent medical attention. Signs of this include rash, swelling of the lips, tongue, or face, shortness of breath, or breathing problems. Special care should be taken in people with kidney problems while taking this medicine.Uses of Ciprobid Tablet
Treatment of Bacterial infectionsBenefits of Ciprobid Tablet: In Treatment of Bacterial infections
Ciprobid 500 Tablet is a versatile antibiotic medicine that can be used to treat many different infections caused by bacteria. These include infections of the urinary tract, nose, throat, skin, and soft tissues and lungs (pneumonia). It kills and stops further growth of the bacteria causing the infection. This medicine usually makes you feel better quite quickly. However, you should continue taking it as long as it is prescribed even when you feel better, to make sure that all bacteria are killed and do not become resistant.Side effects of Ciprobid Tablet
Most side effects do not require any medical attention and disappear as your body adjusts to the medicine. Consult your doctor if they persist or if you’re worried about them Common side effects of Ciprobid Headache Dizziness Gastrointestinal disorder Joint pain UrticariaHow Ciprobid Tablet works
Ciprobid 500 Tablet is an antibiotic. It works by stopping the action of a bacterial enzyme called DNA-gyrase. This prevents the bacterial cells from dividing and repairing, thereby killing them.Fact Box
Chemical Class Fluoroquinolone Habit Forming No Therapeutic Class GASTRO INTESTINAL Action Class Quinolones/ Fluroquinolones
Thursday, June 23, 2022
Top 7 countries with consistent growth of survival8 (2022-Jun-24)
Index of Journals
Tags: Technology,Data Visualization,Investment,Management,Journal,1. Cumulative pageviews in India
2. Cumulative pageviews in US
3. Cumulative pageviews in Germany
4. Cumulative pageviews in Russia
5. Cumulative pageviews in Kenya
6. Cumulative pageviews in UK
7. Cumulative pageviews in Uganda
Latent Dirichlet Allocation (Algorithm for Topic Modeling of Text Data)
Here is the problem: We have a collection or corpus of documents and you can think of them as news articles if you would like. Each news article has a topic. Some of them are science, some are politics or sports. Some of them are allowed to have two topics. A article may have multiple topics: science and politics, or sports and science. But the problem is we don't know the topics to begin with. We only know the text of the articles. We would like to have an algorithm that will help us sort these documents into topics. So here is a small example. Let's say our collection of documents has these four documents and each document has only five words. Vocabulary of words is: ball, referendum, planet and galaxy. Doc 1: ball ball ball planet galaxy Doc 2: referendum planet planet referendum referendum Doc 3: planet planet galaxy planet ball Doc 4: planet galaxy referendum planet ball And, we have three possibilities for topics: Science, Politics and Sports. Let me show you what I did.But I want you to ask youselves this: We are able to understand words and topics and hence able to do it. We know what words mean, but the computer doesn't. Computer only knows if two words are different or two words appear in a document or not. LATENT DIRICHLET ALLOCATION The Problem: We have a collection of documents or news articles and we want to sort them into topics. This is where LDA comes into picture. What LDA does is: it takes a geometric approach. If you have 3 topics, then it builds a triangle. Corners represent the topics. Then it puts the documents inside the triangle. The documents are close to the corner if they belong to the topic representing that corner. Question is: How do we put the documents in the triangle in a perfect way. I like to think of LDA as a machine that generates articles. This machine has some settings to play with and it also has a button. When we push the button, the machine starts and it's two gears start spinning and generate a document. Most likely, the document you would produce would be gibberish. It is just a bunch of words put together. With some very, very, very low probability, you could get a Shakespeare novel or declaration of indepedence. Let's say we have two machines and they both output two documents. We compare those two documents with the original document. The document that matches better with the original document, the one that matches better was from a machine with better settings. We do this activity to figure out the best setting that is most likely to give us our document. Those settings will give us the topics.
BLUEPRINT OF THE LDA
LET US LOOK AT THE EQUATION
On the left we have the probability of getting back the original article:
DIRICHLET DISTRIBUTIONS
Monday, June 20, 2022
Creating a Taxonomy for BBC News Articles (Part 8 - Using Latent Dirichlet Allocation for topic modeling)
import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns import re import nltk from nltk.tokenize import word_tokenize import sys import gensim from gensim import corpora from gensim.models.lsimodel import LsiModel, stochastic_svd from gensim.models.coherencemodel import CoherenceModel from gensim.models import RpModel from gensim.matutils import corpus2dense, Dense2Corpus from gensim.test.utils import common_texts from gensim.corpora.dictionary import Dictionary from gensim.models.ldamodel import LdaModel # Latent Dirichlet Allocation and not 'Latent Discriminant Analysis' from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer from sklearn.preprocessing import normalize from sklearn.decomposition import LatentDirichletAllocation, PCA from sklearn.cluster import KMeans from sklearn.random_projection import SparseRandomProjection, johnson_lindenstrauss_min_dim from sklearn.random_projection import GaussianRandomProjection from sklearn.metrics.pairwise import euclidean_distances import string from collections import Counter from preprocess import preprocess_textTags: Machine Learning,Natural Language Processing,Technology,Latent Dirichlet Allocation is a statistical technique to identify topics in textual data.
This below is a snapshot of few results we were getting till we trimmed and trimmed our words from the "probability" equations. Doing this to a great extent will lead to over-fitting. #1 Topic Id: 0 Probabilities: 0.006*"people" + 0.003*"mobile" + 0.003*"film" + 0.003*"phone" + 0.003*"music" + 0.003*"service" + 0.002*"party" + 0.002*"game" + 0.002*"time" + 0.002*"election" + 0.002*"government" + 0.002*"firm" + 0.002*"million" + 0.002*"way" + 0.002*"number" + 0.002*"take" + 0.002*"win" + 0.002*"player" + 0.002*"well" + 0.002*"next" Topic Id: 1 Probabilities: 0.004*"game" + 0.003*"time" + 0.003*"government" + 0.003*"people" + 0.003*"service" + 0.003*"company" + 0.003*"world" + 0.002*"month" + 0.002*"firm" + 0.002*"bbc" + 0.002*"phone" + 0.002*"film" + 0.002*"take" + 0.002*"home" + 0.002*"way" + 0.002*"week" + 0.002*"show" + 0.002*"market" + 0.002*"second" + 0.002*"well" Topic Id: 2 Probabilities: 0.006*"people" + 0.003*"world" + 0.003*"time" + 0.003*"game" + 0.003*"number" + 0.003*"government" + 0.003*"company" + 0.003*"firm" + 0.002*"month" + 0.002*"market" + 0.002*"many" + 0.002*"country" + 0.002*"film" + 0.002*"play" + 0.002*"sale" + 0.002*"tax" + 0.002*"take" + 0.002*"minister" + 0.002*"player" + 0.002*"award" Topic Id: 3 Probabilities: 0.005*"film" + 0.004*"time" + 0.003*"game" + 0.003*"labour" + 0.003*"world" + 0.002*"sale" + 0.002*"week" + 0.002*"election" + 0.002*"month" + 0.002*"people" + 0.002*"country" + 0.002*"show" + 0.002*"party" + 0.002*"firm" + 0.002*"want" + 0.002*"government" + 0.002*"since" + 0.002*"service" + 0.002*"many" + 0.002*"good" Topic Id: 4 Probabilities: 0.004*"time" + 0.003*"people" + 0.003*"game" + 0.003*"government" + 0.003*"world" + 0.002*"number" + 0.002*"company" + 0.002*"music" + 0.002*"win" + 0.002*"blair" + 0.002*"right" + 0.002*"labour" + 0.002*"show" + 0.002*"mobile" + 0.002*"england" + 0.002*"firm" + 0.002*"country" + 0.002*"next" + 0.002*"day" + 0.002*"plan" #2 Topic Id: 0 Probabilities: 0.005*"people" + 0.004*"time" + 0.003*"sale" + 0.003*"film" + 0.003*"mobile" + 0.003*"game" + 0.002*"company" + 0.002*"show" + 0.002*"firm" + 0.002*"million" + 0.002*"party" + 0.002*"world" + 0.002*"country" + 0.002*"labour" + 0.002*"way" + 0.002*"service" + 0.002*"week" + 0.002*"2004" + 0.002*"top" + 0.002*"music" Topic Id: 1 Probabilities: 0.004*"film" + 0.004*"time" + 0.003*"people" + 0.003*"government" + 0.003*"award" + 0.003*"game" + 0.002*"world" + 0.002*"music" + 0.002*"party" + 0.002*"player" + 0.002*"country" + 0.002*"blair" + 0.002*"labour" + 0.002*"win" + 0.002*"bbc" + 0.002*"home" + 0.002*"number" + 0.002*"service" + 0.002*"election" + 0.002*"top" Topic Id: 2 Probabilities: 0.006*"game" + 0.003*"people" + 0.003*"world" + 0.003*"time" + 0.003*"company" + 0.003*"firm" + 0.002*"phone" + 0.002*"film" + 0.002*"month" + 0.002*"number" + 0.002*"service" + 0.002*"player" + 0.002*"england" + 0.002*"market" + 0.002*"minister" + 0.002*"right" + 0.002*"home" + 0.002*"government" + 0.002*"next" + 0.002*"british" Topic Id: 3 Probabilities: 0.005*"people" + 0.004*"government" + 0.004*"time" + 0.003*"world" + 0.003*"election" + 0.002*"game" + 0.002*"week" + 0.002*"company" + 0.002*"labour" + 0.002*"plan" + 0.002*"service" + 0.002*"next" + 0.002*"minister" + 0.002*"win" + 0.002*"work" + 0.002*"technology" + 0.002*"way" + 0.002*"film" + 0.002*"day" + 0.002*"bbc" Topic Id: 4 Probabilities: 0.004*"people" + 0.003*"government" + 0.003*"firm" + 0.003*"time" + 0.003*"world" + 0.003*"market" + 0.003*"number" + 0.002*"month" + 0.002*"country" + 0.002*"price" + 0.002*"group" + 0.002*"film" + 0.002*"company" + 0.002*"lord" + 0.002*"show" + 0.002*"economy" + 0.002*"2004" + 0.002*"london" + 0.002*"report" + 0.002*"use" import re import string import nltk from nltk.corpus import stopwords nltk.download('stopwords') from nltk.stem import WordNetLemmatizer nltk.download('wordnet') from nltk.tokenize import word_tokenize nltk.download('punkt') def cleanup_text(text): # Remove tags remove = re.compile(r'') text = re.sub(remove, '', text) text = re.sub("&#[0-9]+;", '', text) # Remove special characters reviews = '' for x in text: if x.isalnum(): reviews = reviews + x else: reviews = reviews + ' ' #Convert to lower text = reviews.lower() return text def remove_punctuations(text): exclude = set(string.punctuation) exclude.remove("-") text = ''.join(ch for ch in text if ch not in exclude) return text def remove_stopwords(text): stop_words = set(stopwords.words('english')) days_of_week = ["monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"] stop_words.update(days_of_week) words = word_tokenize(text) words = [x for x in words if len(x) > 2] words = [x for x in words if x not in stop_words] return words def lemmatize_word(text): le = WordNetLemmatizer() text = [le.lemmatize(w) for w in text] return text def preprocess_text(doc): doc = cleanup_text(doc) doc = remove_punctuations(doc) words = remove_stopwords(doc) words = lemmatize_word(words) doc = " ".join(words) return doc def remove_additional_words(text): additional_stopwords = ["new", "like", "many", "also", "even", "get", "say", "according", "would", "could", "know", "made", "make", "come", "didnt", "dont", "doesnt", "go", "may", "back", "going", "including", "added", "set", "take", "want", "use", "000", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "20", "u", "one", "two", "three", "year", "first", "last", "good", "best", "well", "told", "said"] days_of_week = ["monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"] additional_stopwords += days_of_week words = word_tokenize(text) words = [x for x in words if len(x) > 2] words = [x for x in words if x not in additional_stopwords] doc = " ".join(words) return doc df1 = pd.read_csv('bbc_news_train.csv') df1['Preprocess_text'] = df1['Text'].apply(preprocess_text) df1['Preprocess_text'] = df1['Preprocess_text'].apply(remove_additional_words) print(Counter(df1['Category'])) Counter({'business': 336, 'tech': 261, 'politics': 274, 'sport': 346, 'entertainment': 273}) from gensim.test.utils import common_texts from gensim.corpora.dictionary import Dictionary # Create a corpus from a list of texts clean_corpus = [doc.split() for doc in df1['Preprocess_text'].values.tolist()] common_dictionary = Dictionary(clean_corpus) common_corpus = [common_dictionary.doc2bow(text) for text in clean_corpus] %%time NO_OF_TOPICS_FOR_TRAINING = 5 NO_OF_WORDS_IN_TOPIC = 20 lda = LdaModel(common_corpus, num_topics = NO_OF_TOPICS_FOR_TRAINING, id2word = common_dictionary) ldamodel_topics = lda.print_topics(NO_OF_TOPICS_FOR_TRAINING, NO_OF_WORDS_IN_TOPIC) for (topic_id, probabilities) in ldamodel_topics: topic_string = "\n\nTopic Id: " + str(topic_id) + "\n Probabilities: " + str(probabilities) print(topic_string) Topic Id: 0 Probabilities: 0.004*"people" + 0.003*"time" + 0.003*"government" + 0.003*"film" + 0.003*"game" + 0.003*"sale" + 0.003*"company" + 0.002*"world" + 0.002*"music" + 0.002*"player" + 0.002*"country" + 0.002*"month" + 0.002*"show" + 0.002*"2004" + 0.002*"market" + 0.002*"group" + 0.002*"next" + 0.002*"bbc" + 0.002*"second" + 0.002*"technology" Topic Id: 1 Probabilities: 0.004*"people" + 0.004*"time" + 0.003*"world" + 0.003*"game" + 0.002*"party" + 0.002*"firm" + 0.002*"day" + 0.002*"service" + 0.002*"show" + 0.002*"way" + 0.002*"think" + 0.002*"company" + 0.002*"market" + 0.002*"next" + 0.002*"music" + 0.002*"win" + 0.002*"award" + 0.002*"british" + 0.002*"still" + 0.002*"phone" Topic Id: 2 Probabilities: 0.004*"game" + 0.004*"film" + 0.004*"government" + 0.003*"people" + 0.003*"time" + 0.003*"firm" + 0.003*"sale" + 0.003*"labour" + 0.002*"number" + 0.002*"market" + 0.002*"country" + 0.002*"company" + 0.002*"service" + 0.002*"tax" + 0.002*"way" + 0.002*"plan" + 0.002*"week" + 0.002*"technology" + 0.002*"blair" + 0.002*"minister" Topic Id: 3 Probabilities: 0.005*"people" + 0.004*"time" + 0.003*"world" + 0.003*"game" + 0.003*"labour" + 0.003*"week" + 0.003*"party" + 0.002*"month" + 0.002*"election" + 0.002*"win" + 0.002*"way" + 0.002*"show" + 0.002*"company" + 0.002*"old" + 0.002*"number" + 0.002*"play" + 0.002*"music" + 0.002*"group" + 0.002*"net" + 0.002*"mobile" Topic Id: 4 Probabilities: 0.006*"people" + 0.004*"time" + 0.003*"film" + 0.003*"world" + 0.003*"service" + 0.003*"government" + 0.003*"mobile" + 0.003*"company" + 0.003*"game" + 0.002*"win" + 0.002*"firm" + 0.002*"number" + 0.002*"election" + 0.002*"month" + 0.002*"phone" + 0.002*"home" + 0.002*"party" + 0.002*"country" + 0.002*"minister" + 0.002*"england" for i in range (1, len(df1)): tagged_topic = df1.iloc[i]["Category"] text_for_inference = df1.iloc[i]["Text"].split() bow = common_dictionary.doc2bow(text_for_inference) document_topics = lda.get_document_topics(bow, minimum_probability=None, minimum_phi_value=None, per_word_topics=False) document_topics.sort(key=lambda elem: elem[1], reverse=True) document_topics_string = "\n\nArticle ID: " + tagged_topic + " : " for (topic_id, probability) in document_topics: document_topics_string = document_topics_string + " Topic ID: " + str(topic_id) + ", Probability: " + str(probability) + "," print(document_topics_string) for topic, prob in document_topics: topic_terms_string = "\n Topic ID: " + str(topic) + " : " + lda.print_topic(topic) print(topic_terms_string) Article ID: business : Topic ID: 0, Probability: 0.97704554, Topic ID: 4, Probability: 0.018701652, Topic ID: 0 : 0.004*"people" + 0.003*"time" + 0.003*"government" + 0.003*"film" + 0.003*"game" + 0.003*"sale" + 0.003*"company" + 0.002*"world" + 0.002*"music" + 0.002*"player" Topic ID: 4 : 0.006*"people" + 0.004*"time" + 0.003*"film" + 0.003*"world" + 0.003*"service" + 0.003*"government" + 0.003*"mobile" + 0.003*"company" + 0.003*"game" + 0.002*"win" Article ID: business : Topic ID: 4, Probability: 0.7235847, Topic ID: 0, Probability: 0.27315685, Topic ID: 4 : 0.006*"people" + 0.004*"time" + 0.003*"film" + 0.003*"world" + 0.003*"service" + 0.003*"government" + 0.003*"mobile" + 0.003*"company" + 0.003*"game" + 0.002*"win" Topic ID: 0 : 0.004*"people" + 0.003*"time" + 0.003*"government" + 0.003*"film" + 0.003*"game" + 0.003*"sale" + 0.003*"company" + 0.002*"world" + 0.002*"music" + 0.002*"player" Article ID: tech : Topic ID: 4, Probability: 0.9569476, Topic ID: 3, Probability: 0.040294025, Topic ID: 4 : 0.006*"people" + 0.004*"time" + 0.003*"film" + 0.003*"world" + 0.003*"service" + 0.003*"government" + 0.003*"mobile" + 0.003*"company" + 0.003*"game" + 0.002*"win" Topic ID: 3 : 0.005*"people" + 0.004*"time" + 0.003*"world" + 0.003*"game" + 0.003*"labour" + 0.003*"week" + 0.003*"party" + 0.002*"month" + 0.002*"election" + 0.002*"win" ... ... ...
Biography Book Covers for Camera Postures (Steve Jobs and Elon Musk)
Index of Journals
1. Elon Musk by Ashlee Vance
2. Elon Musk by Ashlee Vance
3. Steve Jobs (old)
4. Steve Jobs (young)
5. Me as Elon Musk
6. Me as Steve Jobs
Sunday, June 19, 2022
Elon Musk by Ashlee Vance (15 Minutes Long Summary)
# When I asked Elon Musk to help me write a book about him, he said, “I don’t want to do it.” # I first met Elon Musk in 2012. # On a recent visit to Elon Musk’s SpaceX factory in Hawthorne, California, I was taken aback by the scale of the operation. Musk and I talked, as he made his way around the design studio’s main floor, inspecting prototype parts and vehicles. # In our series of letters from African-American journalists, novelist, and writer Ta-Nehisi Coates reflects on his time in San Francisco during the dotcom boom and bust. # In the late 1990s and early 2000s, Silicon Valley created some of the biggest technology companies the world had ever seen. # In the late 1990s, Elon Musk, the billionaire founder of Tesla Motors and SpaceX, moved his company from Silicon Valley to Hawthorne, California. # Elon Musk, the billionaire founder of SpaceX, Tesla Motors, and the Boring Company, wants to send humans to Mars. # There are two things that make Elon Musk stand out. # When Elon Musk was growing up in South Africa in the 1950s and 1960s, the world was a very different place. # When Joshua Haldeman and his wife, Wyn, moved from Toronto to Cape Town, South Africa, in the early 1950s, the Haldemans had everything they needed: a house, a dance practice, a plane, and five children. # Maye Musk was the nerd in her family. # Elon Musk, founder and chief executive of Tesla Motors, is a master of the mind. # Elon Musk’s mother, Maye, had just divorced her second husband, Errol, and had three children of her own. # Elon Musk’s father, Errol, is a prominent South African businessman and philanthropist. # When Elon Musk was growing up, he and his friends Kimbal and Peter Rive took the train to South Africa. # When Elon Musk went to high school in South Africa in the late 1980s and early 1990s, he was among a handful of students with the grades and self-professed interest to be selected for an experimental computer program. # In the summer of 1988, 12-year-old Musk’s mother, Maye, sent him off to live with her uncle in Minnesota. # When Peter Nicholson met Elon Musk and Maye Kimbal at Queen’s University in Toronto, they were both working at the same bank. # When Elon Musk was a student at the Massachusetts Institute of Technology in the late 1980s and early 1990s, he was known as the “serial entrepreneur.” # When Elon Musk and Adeo Ressi arrived at the University of California, Berkeley, they had no idea what to expect. # In his final year at Queen’s University, Elon Musk received an award from his professor for his work on a new type of capacitor. # In the summer of 1994, Elon Musk was about to start college. # When Elon Musk moved to Silicon Valley in the early 1990s, he was working as an engineer at Pinnacle Innovations, a start-up founded by people who’d done similar work at companies like Atari and Atari 2600. # When Elon Musk and his brother Kimbal started Zip2, a turn-by-turn directions service in San Francisco in the early 1990s, they had no idea what they were getting themselves into. # John Heilman, one of Zip2’s early employees, gave up his job as a software developer to go door-to-door with Kimbal Musk, Elon Musk’s brother and co-founder of Tesla Motors. Elon Musk stopped pounding his keyboard, leaned out from behind his monitor, and said # Kimbal Musk, one of Elon Musk’s brothers and the co-founder of Zip2, told me that he and his brother had a strained relationship. # In the early days of Zip2, the car-sharing company founded by Elon Musk, the young engineers at the company were given little time to think. # In 1996, Zip2 launched a free online classified advertising service for newspapers. # Kimbal Musk, one of the co-founders of Zip2, a car-sharing service that was sold to Google for $1bn in 2004, told the BBC’s Stephen Sackur in an interview that when he sold the company to Google, he had no idea what he was doing. # In the early 1990s, Elon Musk, the founder of electric carmaker Tesla Motors, was having a bad day. # In the early 1990s, Elon Musk came up with the idea for an online bank while working at a bank in Canada. # When Elon Musk, the billionaire co-founder of Zip2 and X.com, bought a McLaren F1 racing car in 2005, he had no intention of using it for personal use. # When Elon Musk started X.com, a Silicon Valley-based online bank, he enlisted the help of Peter Fricker, Craig Payne, and Peter Ho. # When I first met Elon Musk at his start-up called X.com in the early 1990s, he was working on a payment system for Palm Pilot handhelds, so I asked him what he was up to and he said he was working on a payment system for Palm Pilot handhelds, so I asked # When Elon Musk bought X.com in 1999 for $1bn (£640m), he inherited a start-up that had become embroiled in a bitter dispute with two of Silicon Valley’s most influential investors, Peter Thiel and Peter Levchin. # In January 2002, PayPal co-founder Elon Musk met with PayPal co-founder Peter Thiel and PayPal’s other co-founder, Scott Moritz, to discuss the future of the company. # Elon Musk, the founder of Zip2 and PayPal, has died at the age of 45. # Three years ago, Elon Musk was in the midst of one of the most turbulent periods of his career. # In the summer of 2001 Elon Musk and his wife Justine were living in Palo Alto, California, running their start-up X.com. # When the Mars Society, a group of scientists working on sending humans to Mars in the 2030s, held its annual dinner in Los Angeles last year, the invitations were sent out. # In 2001, the Mars Society, a group of scientists, engineers, and celebrities that had been working on sending humans to the Red Planet since the 1960s, was in disarray. # When billionaire entrepreneur Elon Musk announced in 2006 that he was going to build a plant garden on Mars, he had no idea how much money he would need to do it. # In 2002, Elon Musk and his business partner, Griffin Cantrell, flew to Moscow to meet with the Russian government to discuss buying a fleet of intercontinental ballistic missiles, or ICBMs, for use in space. # When Russian entrepreneur Alexander Zubrin heard about Elon Musk’s plans to launch a private rocket company, he was ready to buy it. # It all started with a simple conversation between John Garvey, a rocket builder, and John Cantrell, a friend and fellow enthusiast, at Garvey’s workshop. # When Elon Musk’s private rocket company, SpaceX, opened its doors to the public in Hawthorne, California, in June of 2012, it did so with a flourish. # In the summer of 2002, Elon Musk started a company called SpaceX to develop a rocket that could launch small experiments into orbit. # When Elon Musk’s brother-in-law, Nevada, was killed in a car crash, Justine Musk told her husband: “You’re going to have to live with this for the rest of your life." # Musk also recruited Gwynne Shotwell, an aerospace veteran who started as SpaceX’s first. # In the early days of SpaceX, the company’s headquarters were located on the campus of Brown University. # When Elon Musk’s rocket company SpaceX opened its doors in Hawthorne, California, in 2006, he brought with him an army of young engineers. # At the launch pad in Cape Canaveral, Florida, SpaceX’s Kestrel and Merlin engines were put through their paces. # In an interview with the BBC, Elon Musk, founder of the private rocket company SpaceX, said: “I’m not afraid to ask questions. When the third chamber cracked, Musk flew the hardware back to California, took it to the factory floor. # When Elon Musk’s SpaceX announced plans to launch its Falcon 1 rocket from the White House in February, one of the engineers working on the rocket at the company’s factory in California, Scott Hollman, said, “We wanted to make it feel real... # When SpaceX needed to connect its buildings to the internet, founder Elon Musk asked his employees to do it over a weekend in the middle of the night. # In the early days of Elon Musk’s rocket company, SpaceX, employees felt like they were second-class citizens. # When Elon Musk’s private rocket company SpaceX needed to launch a satellite into orbit, it turned to a remote island off the coast of Hawaii. # In the summer of 2005, Elon Musk’s company, SpaceX, set up shop on Kwaj, an island off the coast of South Korea. # When SpaceX’s Falcon 1 rocket crashed into the Pacific Ocean off the coast of Kwaj, South Korea, in July 2006, Elon Musk, the company’s founder, was furious. # When the first stage of Elon Musk’s Falcon 9 rocket lifted off from Cape Canaveral, Florida, it looked like it was going to go well. # The Haldeman children had lots of downtime in the African bush while wild adventures with their parents. # Maye Musk’s original video-game code for Blastar, the game he wrote as a twelve-year-old and published in a local magazine. # The three children of Elon Musk, founder of the electric car company Tesla, were all born in South Africa. # Tesla co-founder and chief executive Elon Musk founded the electric carmaker in 1994. # SpaceX’s first flight from Kwajalein Atoll (or Kwaj) in the Marshall Islands was a difficult but ultimately fruitful adventure for the engineers. # Elon Musk, founder and chief executive of SpaceX, met with German astronaut Michael Mueller at the International Space Station earlier this year. # SpaceX, the private rocket company founded by billionaire Elon Musk, is developing a robot that can build spacecraft. # The private rocket company SpaceX is developing new ways to launch and land spacecraft. # Elon Musk, founder and chief executive of SpaceX, visited a Dairy Queen in El Paso, Texas, on Thursday. # Elon Musk is the founder and chief executive of SpaceX, a private rocket company based in Hawthorne, California. # Tesla Motors, the electric car maker, has announced that it is shutting down its factory in Fremont, California. # Elon Musk, founder and chief executive of Tesla Motors, is a big fan of Fidel Castro. # An unmanned SpaceX Falcon 9 rocket carrying a Dragon spacecraft is due to lift off from Florida's Cape Canaveral Air Force Station on Friday. # Elon Musk, the billionaire co-founder of electric car maker Tesla, has been in the news in the past few weeks for a number of reasons. # Tesla founder Elon Musk and his wife, Talulah Riley, are expecting their second child. # In the late 1980s and early 1990s, Bill Straubel worked nights and on the weekend doing electronics consulting for a start-up. # Bill Straubel, the inventor of the lithium ion battery, had been meeting with Elon Musk, the billionaire founder of Tesla Motors. # When Tesla Motors cofounders Jeff Tarpenning and Steve Eberhard decided to start their own car company in 2003, they had no idea what kind of reception they would get. # It all started with a phone call from Martin Eberhard, one of the co-founders of Tesla Motors. # When Tesla’s Glenn Straubel and Evgeny Berdichevsky first started working on the electric car company’s prototype, they shared a single San Carlos, California. # When Elon Musk dropped by Tesla’s headquarters in Palo Alto to test drive the company’s first car, the Roadster, on Jan. # When Tesla first unveiled its Roadster electric car in 2005, one of the company’s engineers, Peter Tarpenning, sent Elon Musk, Tesla’s co-founder and chief executive, a picture of the car. # When Tesla unveiled its first car, the Model S, at the Consumer Electronics Show in Las Vegas in 2006, the company’s chief executive, Elon Musk, and chief financial officer, Steve Tarpenning, had no idea what they were getting themselves into. # When the Tesla Roadster went on sale in 2007, Elon Musk and Martin Eberhard, Tesla’s co-founder and chief executive, were at odds. # When Tesla announced that it would open a battery factory in Thailand, founder Elon Musk had no idea how complicated the process would be. # Elon Musk, Tesla’s co-founder and chief executive, told me that Tim Eberhard, Tesla’s former chief executive, had told him that the cost of making the company’s first car, the Roadster, was too high. # When Tesla’s chief executive, Martin Eberhard, found out that the company’s chairman, Robert Watkins, had told investors that Tesla was in chaos, he was furious. # In the summer of 2007, Tesla’s founder and chief executive, Elon Musk, had a falling out with the company’s former chief executive, Roger Marks. # Tesla’s former chief engineer, Dan Popple, remembers one meeting in which Elon Musk, Tesla’s co-founder and chief executive, was angry. # Three of Tesla’s earliest employees left the company when Elon Musk took over as chief executive in 2007, according to people close to the company. # When Elon Musk and his wife, Justine, moved to Los Angeles in the early 1990s, they became part of the city’s elite. # When Elon Musk started Tesla and SpaceX in 2006, the press loved him. # In the early days of Tesla and SpaceX, Elon Musk was a very hands-on boss. # When Elon Musk filed for divorce from his wife, Justine, in May of 2007, it was the end of an era. Justine took to her blog in an entry titled “golddigger,” and said she was fighting for a divorce settlement that would include their house, alimony and child support, $6 million in cash # When Elon Musk and a group of friends went on a night out in London in the early 1990s, one of the men, Jason Lee, was determined to make the most of it. # It all started with a simple exchange of e-mails. # When Elon Musk announced that he was going to try to launch the Falcon 1 rocket for the third time in less than a year, he had a lot to live up to. # On the morning of September 27, 2008, Elon Musk, the founder of SpaceX, ordered his team to fly the body of his rocket from Los Angeles to Kwaj, a remote island in the South Pacific. # When SpaceX’s Falcon 1 rocket lifted off from Cape Canaveral Air Force Station on Saturday afternoon, SpaceX flight director Tim McLaury said, “I knew it was going to be a good day.” # In the summer of 2008, Elon Musk, founder and chief executive of Tesla Motors, learned that SpaceX, his company, had won a contract from NASA to resupply the International Space Station. # When Elon Musk, the founder of SpaceX and Tesla Motors, announced last week that his company had won a $1.6 billion contract to supply the International Space Station (ISS), billionaire investor Nelson Gracias said, “Elon Musk... # SpaceX’s Falcon 9 rocket is the most powerful rocket in the world. # On Friday morning, a Falcon 9 rocket blasted off from Vandenberg Air Force Base on the central California coast. # Elon Musk’s private rocket company, SpaceX, has announced that it will reduce the cost of sending satellites into orbit by 50% over the next five years. # Elon Musk’s rocket company, SpaceX, is looking for engineers who are passionate about their work. # Harish Singh, a former employee of Elon Musk’s rocket company SpaceX, told me he was fired from the company. # The first thing you notice when you walk into SpaceX’s factory at Cape Canaveral is how big it is. # Billionaire Elon Musk’s rocket company, SpaceX, is a pioneer in the field of making its own hardware. # Elon Musk may be best known as the founder of SpaceX, a rocket company that has become one of the world’s most successful start-ups, but he’s also one of the world’s most intimidating executives. # Elon Musk, founder and chief executive of private rocket company SpaceX, recently spoke to the BBC’s Stephen Sackur about his company’s failure to launch its first rocket on time. # When SpaceX co-founder and chief executive Elon Musk was looking for engineers to work on the company’s Falcon 1 rocket, he turned to a Stanford University graduate who had worked on the Falcon 1’s predecessor. # When SpaceX co-founder and chief executive Elon Musk announced that his company would be launching the Dragon spacecraft to the International Space Station this summer, he sent an e-mail to SpaceX’s chief operating officer, Gwynne Davis. # Elon Musk’s rocket company, SpaceX, is based in Hawthorne, California, a suburb of Los Angeles, but the company’s mission is to put people on the International Space Station. # If you’re Elon Musk, the founder of SpaceX, you’ve got a problem. # Elon Musk’s treatment of former SpaceX chief engineer David Bowersox, who he called an “idiot,” has been widely reported. # When SpaceX co-founder and chief executive Elon Musk called to tell her he was looking for a new employee, Susan Shotwell had no idea what she was getting herself into. “I did, and that’s when I told him, ‘You need a good business development person.’” # In a rare interview with the press, SpaceX COO Gwynne Shotwell laid out her vision for the future of the space industry, as she sat down with interns at the company’s headquarters in Cape Canaveral, Florida. # SpaceX’s chief executive, Elon Musk, said this week that his company’s goal is to become the “premier launch company” in the world. # In March, SpaceX founder Elon Musk appeared before the Senate Armed Services Committee to pitch his company to the US Air Force as a competitor to United Launch Alliance (ULA). # When the private rocket company SpaceX launched its first Falcon 1 rocket on Kwajalein, Malaysia, in September 2005, it received a $12 million per flight option. # When SpaceX chief executive Elon Musk unveiled the company’s new Dragon 2 spacecraft at the International Space Station (ISS) last week, it was clear that he was on a mission. # It all started with a Christmas party. # If you’ve ever watched a car ad, you’ll know that they’re pretty much the same thing every time. # Tesla’s Model S was the most fuel-efficient car on the market. # When Tesla unveiled its electric car, the Model S, in July 2012, few people outside Silicon Valley had heard of the company or its founder, Elon Musk. # When Elon Musk raised the price of the Tesla Roadster from $75,000 to $100,000 in April 2007, he did so with the hope that it would attract more buyers to the electric car. # When Tesla Motors unveiled its first all-electric car, the Roadster, in 2007, it was clear that Elon Musk and Co. # Tesla’s decision to build the Model S on an all-electric platform came out of frustration with Fisker Automotive, according to Tesla’s chief engineer, Rob Lloyd. # When von Holzhausen moved to Los Angeles in the early 1990s, he had no idea what he was getting himself into. # When Tesla founder Elon Musk asked von Holzhausen to design the company’s first car, he had no idea what he was getting himself into. # In an interview with the BBC, Tesla Motors chief executive Elon Musk explained how the company had to choose between making the body panels of its Model S electric car from scratch or leaving them in the car. # When Tesla’s chief engineer, von Holzhausen, arrived at the company in 2008, he wanted the public to see the Model S. # When Michael O’Connell joined the Army in the early 1990s, he knew he wanted to be a soldier, but he didn’t know what he wanted to do with the rest of his life. # When Tesla’s chief executive, Elon Musk, and his business partner, James O’Connell, met with Daimler’s chief executive, Dieter Zetsche, in March 2009, they had a simple proposition. # When Tesla unveiled its Model S electric car at the Consumer Electronics Show in January 2010, Jalopnik was not a fan. # In the early days of Tesla’s Model S, Javidan Javidan, the company’s chief engineer at the time, would sit in Elon Musk’s lap and jot down the changes he wanted to make to the car. # When Tesla’s design chief, von Holzhausen, was asked to come up with a way to make the company’s Model X more child-friendly, he came up with one of the most radical ideas he’d ever seen. # The first thing you notice when you walk into Tesla’s factory in Fremont, California, is that it’s very different from the company’s previous facility in Hawthorne, California. # “It’s been a restful few months,” Elon Musk, the chief executive of Tesla Motors, the electric car maker, said as I watched the film, The Girl with the Dragon Tattoo. # Tesla’s chief executive, Elon Musk, once told me that one of the first problems he encountered with the company’s new Model S was that the interior of the car was “a mess.” # In the first few weeks of April 2013, Elon Musk was on a mission. # On a sweltering summer night in July, Tesla’s headquarters in Hawthorne, California. # When Tesla unveiled its first Model S car in 2007, I was sitting in a coffee shop in Silicon Valley. # Tesla doesn’t release a new Model S every year. # Tesla founder Elon Musk once said, “If I had a rabbit on every gauge for Easter, he can have that done in a couple of hours. # Three brothers from Santa Cruz, California, had always loved technology. # In a 2006 interview with the Wall Street Journal, Elon Musk said that he and his cousins, Lyndon and David Rive, had come up with a solution to the problem of rising energy costs. # When I first met Elon Musk, the founder and chief executive of SolarCity, I was struck by his sense of urgency. # It’s been a long time coming. # In an interview with the BBC, Tesla’s chief executive, Elon Musk, said the company’s next-generation electric cars will be priced between $35,000 and $50,000. # In an interview with the Wall Street Journal, Tesla chief executive Elon Musk revealed that he’s considering building a roller coaster at the company’s Gigafactory in Nevada. # Elon Musk, founder of the private rocket company SpaceX, once said, “I don’t think it’s going to happen in 10 years. # Billionaire Elon Musk, founder of the private rocket company SpaceX, has revealed his plans to send humans to Mars in the 2030s. # In January of this year, Elon Musk proposed building a Hyperloop between Los Angeles and San Francisco and between San Francisco and D.C. # Elon Musk, the billionaire founder of Tesla and the rocket company SpaceX, is known as a ruthless boss who will do anything to get what he wants. # Tesla’s founder and chief executive, Elon Musk, is a man of few emotions. # When Elon Musk talks to the media, he’s not just talking about his companies, SolarCity, Tesla Motors. # Elon Musk’s SpaceX and Tesla are “nothing but an utterly derivative overhyped toy for showoffs.” # In the late 1980s and early 1990s, Apple was the most valuable company in the country, and billions of its clever devices were spread all over the world. # Google co-founder Larry Page has been speaking to the BBC about his relationship with Elon Musk, the billionaire founder of SpaceX, the rocket company that plans to send humans to Mars. # Elon Musk, the billionaire founder of Tesla Motors and SpaceX, is the subject of a new HBO documentary, “The Tesla Chronicles.” # I’m writing a book about Elon Musk. # It was a busy week for Elon Musk, with the announcement of the Hyperloop and the launch of the space Internet. # Elon Musk, the billionaire founder of electric carmaker Tesla Motors, has been accused by a physicist of stealing his idea for an online mapping service, Zip2. # When Bill O’Reilly accused Elon Musk of lying about his time at Stanford, I reached out to some of the people who knew him best. # “I finished my physics degree in ’94, and then I went to grad school. # In the second of our two interviews with PayPal’s former chief executive, Elon Musk, we look back at his time at X.com. # PayPal co-founder and chief executive Scott Thompson talks about the company’s business model, PayPal’s relationship with X.com, and how Square is doing the wrong version of PayPal. # In our series of letters from the world’s leading entrepreneurs, SpaceX founder and chief executive Elon Musk shares his thoughts on whether or not the company should go public. # It is not correct to think that SpaceX would be as bad as Tesla or SolarCity if we were publicly traded. # We have had a number of investors express interest in buying shares in SpaceX, so I thought I would share my thoughts with them. # I’m writing this on the eve of the release of my book about Tesla’s founder, Elon Musk. # On a personal front, I’d like to thank Elon Musk. # Silicon Valley is home to some of the world's most cutting-edge technology, as well as some of its most successful companies. # Almeda Haldeman was Elon Musk’s great-grandmother. # When Scott Haldeman's parents decided to emigrate from the United States to Australia, they had no idea how long it would take them to get there. # Former South African President Nelson Mandela's son Wyn has died at the age of 85, his family says. # Elon Musk, founder of electric car maker Tesla, has revealed that he once had an esoteric conversation with a bank executive. # Maye Nkosi and her family are moving from South Africa to Canada. # Tesla has raised three-million-dollar funding from venture capitalists Mohr Davidow. # Elon Musk, founder of electric carmaker Tesla, has moved into his new headquarters in Hawthorne, California. # Here’s a look back at some of the more unusual stories from the world of finance. # Harris Fricker, one of Elon Musk’s first employees at Tesla Motors, has spoken out for the first time about his time at the electric car maker. # A chronology of key events: # Elon Musk, the billionaire founder of electric carmaker Tesla Motors, says he’s lucky to be alive after being diagnosed with malaria and viral meningitis. # Buzz Aldrin, the first man to set foot on Mars, says Elon Musk’s plan to build a sewage-treatment plant on the surface of the Red Planet is “ridiculous.” # A chronology of key events: # SpaceX chief executive Elon Musk has named former Boeing executive Gwynne Hollman as his new chief of staff. # The world's tallest building, the Burj Khalifa in Dubai, is being demolished to make way for the world's tallest building, the Burj Khalifa in Abu Dhabi. # A flight from Los Angeles to San Francisco was delayed for more than two hours after a passenger tried to take his glasses off. # Former SpaceX chief executive Elon Hollman is the subject of a new book about his time at the company. # Elon Musk, chief executive of electric car maker Tesla Motors, has invested $1bn in the company. # Tesla boss Elon Musk sent an e-mail to one of his employees saying, “I want your head to hurt every night when you go to bed.” # Elon Musk has settled his divorce with his wife, Justine, for an undisclosed sum. # Justine Musk, the mother of Elon Musk’s two children, spoke to me for the first time about her relationship with the Tesla and SpaceX founder. # Tesla founder Elon Musk has revealed details of his first meeting with Saudi Arabia’s Crown Prince Talulah. # Tesla and SpaceX founder Elon Musk has revealed that he took his daughter, Riley, on a trip to the Grand Canyon. # In the summer of 2002, Elon Musk announced that he would be launching his first Falcon 9 rocket from Cape Canaveral, Florida. # Elon Musk, founder of Tesla Motors, has revealed that his company’s Falcon 9 rocket blew up during its first test flight in 2004. # Elon Musk, founder of electric car company Tesla, has revealed that one of his employees sent him a letter of resignation after he found out he was gay. # Elon Musk, the billionaire founder of SpaceX, has announced plans to build and launch rockets that can be reused. # Blue Origin, the private rocket company founded by Amazon founder Jeff Bezos, has hired former SpaceX chief executive Elon Musk as its chief technology officer. # Elon Musk, founder of SpaceX, and Jeff Bezos, founder of Blue Origin, have had a war of words about reusable rocket technology. # SpaceX founder Elon Musk has revealed how he came up with the name Dragon. # SpaceX’s Dragon capsule has been given the go-ahead to fly to the International Space Station. # In our series of letters from African-American journalists, film-maker and columnist Ahmed Rashid looks at some of the challenges and rewards of being an African-American in Hollywood. # Elon Musk's SpaceX has landed its unmanned Falcon 9 rocket and Dragon spacecraft on an ocean platform, after blasting off from Florida's Cape Canaveral Air Force Station. # Tesla boss Elon Musk has revealed the design of the company's new electric car, the Model 3. # The US space agency’s ambitious plan to send astronauts to Mars has been described as “insane” and “clueless” by a former SpaceX investor. # Elon Musk’s electric car company, Tesla Motors, has unveiled its first self-driving vehicle. # Tesla’s new Model S electric car is the most fuel-efficient car in the world. # Here’s a look back at some of the key moments that led up to the launch of Tesla’s first car, the Roadster. # Tesla chief executive Elon Musk has revealed that he tried to hire Apple co-founder Steve Jobs as his chief executive. # Here are some key details about the US government's role in the development of the world's largest solar farm, in Hawaii. # Tesla Motors has agreed to sell most of its stake in energy storage firm Calico for $3bn to private equity firm Thoma Bravo. # In an interview with the BBC, Tesla’s former chief executive, Elon Musk, and Tesla’s former vice president of manufacturing, Bob Lloyd, discuss the genesis of the electric car maker. # Tesla’s chief executive Elon Musk is keeping a low profile at the electric car maker’s factory in Hawthorne, California, according to one of the company’s investors. # Tesla’s new Model S is powered by a battery pack that’s been developed in-house by the company. # Tesla’s chief executive, Elon Musk, has revealed details of a secret meeting with Google’s chief executive, Sundar Pichai. # Elon Musk, founder of electric carmaker Tesla Motors, has admitted that the company’s plans for a network of charging stations are behind schedule. # In an interview with BBC Radio 4’s Today programme, Tesla chief executive Elon Musk discusses the company’s forthcoming Model S electric car. # Elon Musk, the chief executive of electric car maker Tesla, has defended the company’s decision to open its own stores. # Tesla’s chief executive, Glenn Straubel, says the company’s goal is to create a charging network that is free and ubiquitous. # A Canadian man has become the first person to be granted permanent residency in the United States using his skills as an underwater hockey player. # Tens of thousands of people have turned out for the annual St Patrick's Day parade in the Irish capital, Dublin. # Here’s a look at some of the key numbers behind General Motors’ (GM) decision to sell its Chevrolet brand to Fiat Chrysler Automobiles (FCA). # In an exclusive interview with the BBC, Elon Musk, founder of private rocket company SpaceX, reveals the final design of his spaceship that will send humans to Mars in the 2030s. # Elon Musk’s ex-wife, Kim Riley, has spoken out for the first time about her relationship with the Tesla founder. # Elon Musk, the founder of electric car maker Tesla, has revealed that he fired one of his employees after she refused to take a two-week vacation. # In our series of letters from African-American journalists, film-maker and columnist John Legend’s wife Tameka Riley reflects on her husband, Tesla founder Elon Musk. # Elon Musk’s former boss at PayPal, Peter Jurvetson, has compared Musk to Steve Jobs and Bill Gates.
Subscribe to:
Posts (Atom)