CIFAR10: 10 classes of images of 32x32 pixels

This blog post:

• shows the results of running a deep learning network on a set of images provided by CIFAR10 (10 classes of 6000 images of 32x32 pixels).
• demonstrates the duration of running a deep learning network on my own computer.
• demonstrates the impact on accuracy when running the model with dropout, data augmentation and batch normalisation.

The example is provided from the book of Jason Brownlee “Deep Learning for Computer Vision”.

Scope

I ran on the CIFAR10 dataset basically two different models of the CNN (Convolutional Neural Network):

• The baseline model
• The baseline augmented model with dropout, data augmentation and batch normalisation.  Data augmentation involves making copies of the example in the training dataset with small random modifications.

Results

You have an overview of the results in the screenshot below with code in Python:

Cross entropy and accuracy loss:

The above result shows the cross entropy and classification accuracy for the baseline model

The above diagram shows the cross entropy and classification accuracy for the augmented model

CPU load:

You can observe that GPU load is 0%, which is a bad usage in Neural Network computation.

A CFIFAR 10 example written in JavaScript has been created here and is very much visualising the ConvNetJS deep learning network.

Epilogue

This test clearly indicates the necessity to use an other mean of training deep neural network other than my own computer: either Amazon Web Services, Google Colab or a personal computer with big GPU capacity.

Running VGG16 on my own images

The aim of this post is to give you an idea of the capability of a CNN pre-trained model to transfer his knowledge for the discovery of your own photos. You will have a simple overview and make your own ideas about a model being able to assign its description of the photo.

I decided to use the pre-trained model VGG16 on my own images. The suggestion comes this excellent book from Jason Brownlee, "Deep Learning for Computer Vision".

After downloading the model, I tried it with my own photos taken this afternoon in a natural reserve, at home for the lady bird and the jay, and in the museum Charles de Gaulle fo the Solex.

The results are below, and the legend is the model result.

daisy (98.72%)

monarch (39.78%)

picket_fence (17.62%)

ladybug (64.89%)

jay (34.68%)

tricycle (18.96%)

Apart from the orchid, which the model associates to a "picket fence", and the solex, which the model associates with a "tricycle", all other images are correctly identified.

Crop and Animated gif: using the Pillow library

Deep Learning - Convolutional Neural Network

The usage of Convolutional Neural Network (CNN) is mainly for image processing, and can be used for example to read checks or to recognize objects in photos. In this post I explain my own experience on the usage of CNN for two use cases:

• The MNIST dataset will figure out the case of capturing written numbers.
• The CIFAR-10 dataset address the case of recognizing objects in photos.

There are plenty of articles for understanding CNN, here it's simply my understanding through one example.

An image is a story of pixels

The decomposition of a numeral picture into a network of neurons can be represented like this:

In the above image, the numeral "8" is an image of 28 * 28 pixels. This equals to to 784 input features for the network. The simplest way to recognize the numeral is to use a simple Multilayer Perceptron neural network without convolution. Even with a simple MLP, you can achieve less than 2% error rate.

Convolution

Understanding Convolutional Neural Network (CNN) is a challenge, but working with the MNIST dataset as an example helped me. Either in KERAS or with MXNET (from the Apache framework) you have code examples.

Convolution is defined as a mathematical operation describing a rule for how to merge two sets of information. Does it help you? Me not really :=(

An image is worth a thousand word:

In the image processing with CNN, it's like photography when you are applying different filters to the same picture, you get different results. In CNN, you apply different filters and then you pool them together to produce your classification.

In the above image the filter helps the processing at emphasizing part of the image. For example the first filter is spotting the upper part of the image by putting a specific weight on the first row of the matrix. There are other ways to enhance the performance with "image augmentation" techniques, as for example using the Keras Image Image Augmentation API. You can implement a concrete example with the book of Jason Brownlee.

With a CNN on a pre-trained model you get a very good accuracy:

Of the importance of pre-training the model

If you compare the two images above, you will remark that two types of network have been experimented: Resnet20 and Resnet56. The CNN have been running in the first case without pre-training and and in the second case with pre-training data. The conclusion is that you get a much better accuracy with pre-training. The importance of pre-training was demonstrated in this paper. You have an explanation about pre-training. Pre-training quickly defined: you compute the weights of your CNN network on a first set of data, and then you "transfer" this knowledge to the new set of data, that means without starting from scratch for the second set of data.

During that day we worked on a CNN with "transfer learning": that means that the CNN model was trained  on different but correlated problems. We have been using Amazon Sage Maker built-in algorithms to train our model incrementally.
Once the model was trained, we prepare the model for inference using an Amazon SageMaker endpoint.

Training the model

In the above image you will notice that the autograd (MXNET) function is used.

Two paradigms: imperative programming vs declarative programming

• Numpy is one library used in Python which is a type of imperative programming.
• Tensorflow is of type declarative programming ("compile" key word)

This distinction is important for the construction of your neuronal network: in the first stage you declare the different layers, and in a second phase you compile after adding them all.

Inference and deployment

All the screenshots of this post were extracted during a one day training at AWS, and the models were executed and deployed on AWS EC2 instance, using Jupiter Notebook and Amazon Elastic Container Service. 

Every application is now deployed in containers, the most important artefact being the Container Registry which is operated with Amazon SageMaker. You only pay (6cents to $27/hour for a 64 cores) for execution when you are using Amazon Lambda. You upload your static website to Amazon S3 (Amazon Simple Storage Service)  containing your model.

With Amazon lambda you don't have to manage infrastructure, you are managing services. It's server less and provides a fully managed highly available services.

Amazon SageMaker Ground truth is a capability that helps you because it reduces the time of preparation of the data.

Final result

The final result is a static website in which you can upload your picture and the CNN will detect for you the objects in the image.

The dog was the first example as a candidate for classification. Then I added the photo of the cat, taken out from the internet. For both the dog and the cat, you can see that the objects are well identified. Then I uploaded an image of my own photos library, a lady bird on leaf, and here you remark that the classification is far from being satisfying.

My conclusion is that images from the internet are already known and trained, but when it comes to the discovery of new images, the CNN has more difficulty to find out. Hence the need for still pre training a CNN network. And the conclusion of my conclusion, keep your private images safe.

Les Misérables de Victor Hugo à la sauce Intelligence Artificielle

Sur une idée et un code source issu du livre de Jason Brownlee, j'ai exécuté un réseau de neurone récurrent sur le livre "Les Misérables Tome V : Jean Valjean" de Victor Hugo.

Le but de l'exercice est que la machine apprenne les différentes séquences du livre afin de pouvoir générer elle-même de nouvelles phrases.

Pour cela, j'ai du récupérer le texte de l'oeuvre de Victor Hugo. Le texte est disponible sur le site Gutenberg.

Le texte comprend pas moins de 625332 caractères pour un vocabulaire composé de 65 caractères différents.

Une fois le texte rapatrié en local, le réseau de neurone de type LSTM (Long Short Term Memory) en fait l'analyse sur 20 époques. Sur ma machine l'analyse a duré 6 heures et 33 minutes.

Une fois l'analyse exécutée, on va récupérer de cette analyse l'époque ayant eue la plus faible perte. En l'occurrence dans mon exécution, il s'agit de l'époque 20/20 :

L'activité du CPU pendant les 6h33 est intense:

Puis on va faire générer au modèle des nouvelles phrases cette fois sans avoir à entrainer le modèle (ouf, pas 6h 33 d'attente). Ceci est possible par récupération du modèle précédemment entrainé.

Le modèle permet de générer autant de phrases que l'on souhaite. Ci-dessous un extrait de quelques phrases générées par le programme :

" il se dit qu'il était probablement dans l'égout des halles; que, s'il

choisissait la gauche et suiva "

" est-à-dire braves. quand on est amoureux comme un tigre, c'est bien le

moins qu'on se batte comme un "

" il y aura des nuages de pourpre et d'or au-dessus

de leur tête, se déclarent contents, et qui sont d "

"  voir. je vais lui dire que

monsieur fauchelevent est là.

--non. ne lui dites pas que c'est moi. di "

"  être

réprimés. l'homme probe s'y dévoue, et, par amour même pour cette foule,

il la combat. mais co "

" vait pas à refuser. pourtant celui qui avait la clef parlementa,

uniquement pour gagner du temps. il "

" tait arrivé avec cosette, le portier n'avait pu

s'empêcher de confier à sa femme cet aparté: je ne s "

Je trouve personnellement que le résultat est impressionnant pour un modèle de base.

Le modèle prend du temps à s'exécuter sur mon iMac, car la machine ne possède pas de carte graphique NVIDIA. NVIDIA utilise CUDA qui est non disponible sur MAC. 

La solution pour augmenter la performance serait soit matérielle en achetant une machine spécifique Machine Learning comme le fait le constructeur AIME ou une solution logicielle de type PlaidML qui est un cadre logiciel qui exécute KERAS sur un GPU utilisant OpenCL au lieu de CUDA. Cette dernière solution est une bonne alternative pour exécuter du Machine Learning sur MAC sans carte NVIDIA.

Deep Learning With Python Jason Brownlee

• In this post, I write my feedback on this again excellent book "Deep Learning With Python" from Jason Brownlee. I would recommend this book if you want to progress on this Deep Learning topic with real examples and not complex math.

You will need a minimum of 15 days to read and run through the different examples that are provided alongside the book.

This book help me to progress at the understanding of important concepts such as Multilayer Perceptron, usage of the KERAS library, Convolutional Neural Networks, Recurrent Neural Networks.

• I particularly appreciated the chapter related to the predictions of sentiments. It's about the word representation which are part of Natural Processing language (NPL). Jason reference an interesting link about the model used in NPL: "Learning Word Vectors for Sentiment Analysis".
• The more I was progressing along the book, the more I was needing to run the code on an external computer. Indeed some program takes more than an hour. For example the classification of images provided with CIFAR10 run in one hour on my iMAC whereas it took only six minutes on Google Colab using GPU. The Colab platform is easy to access and you can use your own data file stored in Google Drive. Here is the link on howto to upload your own files.
• This kind of experience help at understanding the notion of Tensors: a generalization of matrices and are represented using n-dimensional arrays. A vector is one-dimensional or first order tensor and a matrix is two dimensional or second order tensor. Python together with numpy and pandas libraries are perfect for managing matrix.
• I learned the different techniques of using Keras, the library that wraps TensorFlow. The KerasClassifierWrapper class takes a function that creates and returns your neural network model.
• I was also made aware of how to reduce overfitting, tuning hyper parameters such as batch size, number of epochs, learning rate decay, usage of momentum, choosing a Time-based learning rate schedule or a Drop-based learning rate schedule. All these notions are clearly explained and demonstrated with the code examples.
• I was reading the book and in parallel I am also subscribing to the email of Jason as there is always some corollary subjects that helped me understanding subjects such as Discretization, Time series prediction, Whitening, Principal Component Analysis (PCA) and Zero-phase Component Analysis (ZCA).
• I am using the Anaconda container which comes with Sypder, a Python editor. This environment is perfect for me as it provides a stable environment with up to date libraries. Setting up Anaconda is explained in the annex of the book.

• I will certainly explore the Google seed-bank for other examples of deep learning.

maschinelles Lernen

Das Hintergrund

Wenn wir über künstliche Intelligenz sprechen, ist das Thema sehr breit. Das Thema enthält Roboter mit Sensoren verbunden mit dem Gehirn, Datenmengen Untersuchungen, Sprachassistenten, Autonom fahrende Autos, Gesicht-Identifizierung, Übersetzung, Entscheidungshilfe usw... Je breiter das Thema breit ist, desto mehr Leute wollen diskutieren.  Ich habe auch bemerkt, dass viele Leute gegenüber künstlicher Intelligenz sehr skeptisch sind. Je mehr die Leute über künstliche Intelligenz informiert sind, eine desto bessere Meinung über künstliche Intelligenz haben sie.

Maschinelles Lernen
Das Thema « maschinelles Lernen » ist nicht einfach zu erklären. Aber ich glaube, es zu verstehen, ist wichtig, weil « maschinelles Lernen » das Herz von künstlicher Intelligenz ist.
Mit verschiedenen Methoden, z.b. mit Hilfe von Internetsuche, oder mit Rechner Geschichte seit 1950, mit Beispielen, können wir dieses Thema klären. Für die heutige Erklärung, werde ich mit meine eigene Geschichte probieren.

Meine Geschichte
Als ich im vorigen Jahrhundert ein junger Ingenieur war, programmierte ich die Rechner mit einem besonderen Ziel. Der Rechner musste, mit meinen Programmen, mehrere Aktionen ausführen. Jetzt, mit maschinellem Lernen, ist das Ziel komplett anders: der Rechner lernt mit Daten, die Nahrung der Rechner, was er ausführen muss. Was sehr wichtig ist zu erinnern, ist dass die Daten am wichtigsten sind. Die Daten sind wichtiger als die Algorithmen, die sind seit mehr als 20 Jahren bekannt. Zunächst muss der Rechner die Daten analysieren und es gibt mehrere Stufen: Daten aufladen, Model festlegen, Model kompilieren, Model passen, Model bewerten und die letzte Stufe ist Prognose oder Einstufung. Zum Beispiel habe ich meine eigenen Daten über Wettlauf, Herzfrequenz, Blutdruck analysiert. Diese erste Stufe ist die wichtigste beim maschinelles Lernen. Für die Datenanalyse gibt es mehrere Techniken die aus der Statistik kommen. Nach der Datenanalyse muss der Computer, mit der Hilfe des Algorithmus, Vorhersagen machen. Und dann kommt « tiefes Lernen », eine Technik die Neuronnennetzwerk aufgebaut ist. Ich arbeitete and trainierte jetzt über « tiefes Lernen » und das ist mein Projekt Heute.
Was bedeutet das für mich? Kann ich mit meine eigenen Daten Vorhersage machen? Kann ich zum Beispiel eine Vorhersage über verbleibende Lebensjahre machen? Das ist nur möglich wenn ich Daten von anderen Leuten habe, die ähnlich wie ich leben. Leider habe ich diese Daten nicht.

Das Beispiel

COVID19 ERREGER HOT SPOT NEBEN WUHAN

Eine heutige Anwendung von maschinelles Lernen ist zum Beispiel COVID19. Zunächst mit Datenmengen Untersuchung können wir die geografische Verteilung des Erregers sichtbar machen. Sehen Sie die Karte « COVID 19 Erreger Hot Spot neben Wuhan ».
Diese Information ist wichtig für die Entscheidungsinstanzen. Aber Menschen haben kognitive Verzerrung und unter Druck oder Stress irren sie sich. Die Maschinen sind rationaler als Menschen und wenn Maschinen mit richtigen und vielen Daten gefuttert sind, ist die Entscheidung besser. Dann spielt maschinelles Lernen eine wichtige Rolle, damit die Menschen eine bessere Entscheidung treffen.

Fazit
Heutzutage ist Datenmenge entscheidend und Heute sind die Daten der Treibstoff des künstliche Intelligenz. Deswegen ist Heute die weltweite Schlacht um Daten so intensiv.
Die Verarbeitung und Analyse deren Daten mit dem Ziel Prognose oder die Delegierung menschliche Aufgaben ist jetzt möglich dank der Leistung der Computer und Datenmengen.

Machine Learning Mastery with R Jason Brownlee

• I have just finished this excellent eBook from Jason Brownlee. This was for me a constant excitation at every chapter. The learning curve is progressive and you finish with end to end projects.
• A lot of fundamentals about the metrics of Machine Learning, the algorithms of Machine Learning, how to spot the best Machine Learning algorithms, and the fundamentals of analyzing the data before using any algorithms are explained into this book. What I liked, is that it is a book on which you are not passive, but you can implement and see the results directly on your machine.
• Prior to this book, I followed the MOOC "Introduction à la statistique avec R" which gives you the basics of statistics and the basics of R language.
• You will go through the algorithms KNN(Méthode des plus proches voisins) part of the non-linear algorithms family (peu d' hypothèses sur la fonction à modéliser) together with Naive Bayes, Support Vector Machine (SVM), Classification and Regression tress (CART). You will also go through the linear algorithms (forte hypothèse sur la forme de la fonction modélisée) like linear regression, logistic regression, Linear Discriminators Analysis (LDA), regularized regression.
• You will compare the performance of Machine Learning algorithms, and you will tune the Machine Learning algorithms.
• The required metrics need to analyze you data are also explained in the book, but in plain English and not with complex mathematical equations. RMSE (Root Mean Squared Error), the average deviation of the prediction from the observation and R2, le coefficient de détermination (1 is perfect, 0 is worst), accuracy for the classification (percentage of correctly classified instances out of all instances), Log Loss used to evaluate binary classification and more common for multi class classification algorithms.
• I have been using the R language and Studio tool to copy and paste the snippets of code from the book in my environment. See below my RStudio environment with an example extracted from the book:

Tension artérielle et fréquence cardiaque - Cours de bourse

Avec le langage R et l'outil R Studio on peut assez rapidement obtenir des statistiques. Il est aussi possible grace à cet outil de créer des résultats graphiques.

Ainsi sur une base de 42 échantillons de ma tension artérielle relevés entre le dernier trimestre 2019 et le premier trimestre 2020, on obtient les résultats ci-dessous :

> round(mean(tar$Systolic))
[1] 127
> round(mean(tar$Diastolic))
[1] 87
> round(mean(tar$FC))
[1] 69

et le graphique dit "à moustaches" ci-dessous :

J'ai aussi effectué une analyse des données de course de 2014 à 2020. Après un export de Garmin Connect en fichier.csv, j'ai pu extraire les principaux éléments. Les échantillons sont mensuels.

Donc en moyenne sur les 6 dernières années, j'ai parcouru 169 km en moyenne par mois, 15h30 par mois, en fréquence cardiaque moyenne de 146 et en fréquence maximale de 180.

On le savait déjà, mais on remarque que l'analyse de corrélation (Analyse en Composante Principale) permet de confirmer que la VO2MAX est corrélée à la distance parcourue, elle même fortement corrélée au temps d'activité :

Il est aussi possible d'utiliser la librairie quantmod qui permet de récupérer les cours de bourse et d'afficher des graphiques avec les chandeliers japonais :

J'ai pu acquérir cette compétence sur le langage R, ainsi que les bases de la statistique grace au cours en ligne de type MOOC FUN.

Le code pour la tension artérielle:

Mindfulness A practical guide finding peace in a frantic world - Mark Williams and Danny Penman

• You are not your thoughts.
• You come to profound understanding that thoughts and feelings (including negative ones) are transient.
• When you start to feel a little sad, anxious, or irritable it's not the mood that does the damage but how you react to it.
• The mind is constantly trawling through memories to find those that echo our current emotional state.
• A few sad thoughts can en up triggering a cascade of unhappy memories.
• You can't stop the triggering of unhappy memories, self-critical thoughts and judgmental ways of thinking, but you can stop what happens next.
• Most of us know only the analytical side of the mind.
• But the mind is also aware.
• Meditation creates greater mental clarity.
• The act of smiling can itself make you happy.
• The evidence is clear: brooding is the problem, not the solution.
• Pure awareness transcends thinking.
• "The real voyage of discovery consists not in seeking out new landscapes but in having new eyes." (Marcel Proust)
• Mindful awarenesses - or mindfulness - spontaneously arises out of this Being mode when we learn to pay attention, on purpose, in the present moment, without judgement, to things as they actually are.
• How to double your life expectancy: If you are thirty years old, then with a life of around eighty, you have fifty years left. But if you are only truly conscious and aware of every moment for perhaps two out of sixteen hours a day (which is not unreasonable), your life expectancy is only six years and three months. If you could double the number of hours that you were truly alive each day then, in effect, you would be doubling your life expectancy.
• The seven characteristics of "Doing" and "Being" modes of mind:
1. Automatic pilot versus conscious choice
2. Analysing versus sensing
3. Striving versus accepting
• The Doing mode involves judging and comparing the "real" world with the world as we'd like to be in our thoughts and dreams
4. Seeing thoughts as solid and real versus treating them as mental events
• Mindfulness teaches us that thoughts are just thoughts; they are events in the mind. They are often valuable but they are not "you" or "reality".
5. Avoidance versus approaching
6. Mental time travel versus remaining in the present moment
7. Depleting versus nourishing activities
• When people are emotionally upset - wether angry, anxious or depressed - a part of the brain known as the right pre-frontal cortex lights up more than the equivalent part of the brain on the left. When people are in positive mood - happy, enthusiastic and bubbling with energy - the left pre-frontal cortex lights up more than the right.
• The insula and the empathy
• The longer the person has meditated, the more highly developed is the insula.
• Scientific research using brain imaging (fMRI) has shown that the insula energized through meditation.
• Control, commitment and challenge.
• A sense of coherence: comprehensibility, manageability and meaningfulness.
• They found that their lives had more meaning and that challenges should be seen as opportunities rather than threats.
• By meditating on the sounds around you, you'll come to learn that "the mind is to thought what the ear is to sound."
• The habit releasers break down the habits that can trap you in negative ways of thinking.
• You won't find the time, you have to make it.
• It's tremendously liberating to realize that your thoughts are not "real" or "reality". They are simply mental events. They are not "you".
• "Whatever you can do, or dream you can, begin it. Boldness has genius, power, and magic in it." W.H. Murray

Mindfulness week one: waking up to the autopilot

• The first stage of regaining your innate mindfulness involves returning to basics. You need to relearn how to focus your awareness on one thing at a time.
• Firstly, you need a way to train the mind to focus.
• Secondly, you need to find ways of dissolving the habits that drive much of your routine behavior.
• Seeing her mind like as a lake, Hannah saw how often it had become disturbed by a passing storm.
• Hannah was discovering something profound: that none of us can control what thoughts rampage through our minds, or the "weather" they can create. But we do have some control over how we relate to it.
• We confuse the mind's thoughts with reality and we identify ourselves far too closely with our minds.

Mindfulness week two: keeping the body in mind

• The body is acutely sensitive to even the tiniest flickerings of emotion that move constantly across the mind.
• It's clear - far more so than any of us would like to admit - that the judgments we make from moment to moment can be significantly affected by the state of our bodies at the time that we make them. For some, this will make disturbing reading, but it's also heartening because it means that simply altering your relationship to your body can profoundly improve your life.
• To cultivate mindfulness truly, we need to become fully integrated with our body once more.
• The process of building a capacity for sustained mindful concentration and awareness.
• Although you can't stop the unsettling thoughts from arising in your mind, you can stop what happens next.
• The characteristics of “Doing” mode: they include judging everything, comparing the ways things are with the way you want them to be and striving to make them different to how they actually are.
• The elegant shift from Doing to Being.

Mindfulness week three: the mouse in the maze

• The spirit in which you do something is often as important as the act itself.
• Compassion - particularly for yourself - is of overwhelming importance.
• Steve Jobs, the chief executive of Apple and a keen meditator, learned this after a brush with cancer: “Remembering that I’ll be dead soon is the most important tool I’ve ever encountered to help me make the big choices in life almost everything - all external expectations, all pride, all fear of embarrassment or failure - all these things just fall away in the face of death, leaving only what is truly important.”
• Your current state of mind is not a solid fact, but is instead governed by interlinked thoughts, feelings, physical sensations and impulse to act.

Mindfulness week four: moving beyond the rumor mill

• We don't see the world as it is, but as we are.
• We often give far more credence to emotionally charged stories than to logic, no matter how rational are the arguments.
• Our thoughts are like rumors in the mind. They might be true, but then again, they might not be.
• We might start to feel angry, sad, anxious, stressed or bitter, just because a thought triggered an avalanche of associations.
• The breathing space is not a break or diversion from reality, but a way of re-engaging with it.
• Approaching the next moment more mindfully may mean prioritizing your time, rather than frantically trying to do everything at once.
• Practice Interfering Thoughts (PITs): they undermine your enthusiasm for taking action.

Mindfulness week five: turning towards difficulties

• It's often far easier and more effective in the long run to live with our difficulties than to pour resources into battling and suppressing them.
• You will come to learn that everything changes: even the worst-case scenarios imagined in your darkest moments.
• Utile en cas de blessure lors des courses: Are you trying to get rid of them, or are you able to give them your full attention, breathing with them, accepting them, letting them be?
• Faire le lien entre la difficulté mentale et la sensation physique qui s'y rattache : Once the troubling thought or situation has been brought to mind, allow it to rest on the workbench of the mind, then let your attention drop into the body, and tune in to any physical sensations that the difficulty is evoking.
• It's the sensing of your body's reaction that's of importance. You are learning how to dissolve the first step in the chain that drives negative spiral.
• Leaving it on the workbench of the mind.
• I was exploring the sensations, not wanting to make them go away.
• It was a fear and not a fact.
• Cross-checking thoughts with reality is a powerful antidote to negativity in all its form.
• You should gently and seamlessly 'drop into' the body to explore any physical sensations that arise as difficulties appear in the mind.
• Your awareness should follow the usual hourglass shape.
• Nurturing a plant, or sowing some seeds, are among those very simple things in life that can have a surprisingly big benefit. It might even save your life.
• I am alive. I am well. I continue to challenge myself to be fully here for now. What about you?

Mindfulness week six: trapped in the past or living in the present?

• The difficulty in letting go of the past, the brooding about things that did or didn't happen or worrying about things that haven't yet happened.
• Fear that if we relax, we'll begin to fail.
• Research has found that if we've experienced traumatic events in the past, or if we are depressed or exhausted or locked into a brooding preoccupation about our feelings, then our memory shows a different pattern. Very often, the result is what psychologists call an "over-general memory".
• Our minds are always desperately trying to make sense of the world, and they do this in the context of baggage accumulated over many years together with the mood of the moment.
• You over-generalize, especially, if you are tired or preoccupied with your own problems.
• The Raisin meditation, the breath, the Body Scan, the Mindful Movement, the learning to relate to thoughts as you relate to sounds, the exploration of the difficult by working through the body, each of these has contributed that there is, for you, a new possibility.
• May I be free from suffering. May I be as happy and healthy as it is possible for me to be. May I have ease of being.
• Loving-kindness to all beings.
• I'm harming myself. I think that I need to be busy; this is really old pattern for me.
• How can I nourish myself?
• How can I slow down in the midst of my rushing?
• Can I stand back?
• How can I make choices?
• How can I be kind to myself?
• She saw at the moment when she was lying in her bed, she was actually in bed, not at work.
• They teach us to feel guilty for not working hard enough.
• Brain research shows that part of the brain that is activated when we are feeling genuine empathy for another is the same part that we saw being activated by mindfulness meditation: a part called the insula.
• We don't have to do anything more than just be there.
• Although in the early stages, the Befriending meditation might seem a little difficult, remember that is has already begun its work. Brain-imaging research has shown that within a few minutes of beginning the meditation, the parts of brain governing the "approach" qualities of kindness and empathy begin to fire.
• How your thoughts can trap you by shouting their bad advice, often based on memories that are over-general, so that you often only get a biased summary of events that have happened to you.
• Albert Einstein, along with countless scientists and philosophers throughout the ages, always emphasized the importance of kindness, compassion and curiosity in daily life. Although Einstein viewed such qualities as good in themselves, he also knew that they led to clearer thinking and a better, more productive way of living and working. He did not fall into the trap of being harsh on yourself and others leads to success. Einstein knew that this view arose because we all tend to mis-attribute success to the harsh, driving voices in our heads, rather than the quieter, more reasonable ones.
• Albert Einstein wrote: "A human being is a part of the whole called by us the universe, a part limited in time and space. He experiences himself, his thoughts and feelings as something separated from the rest, a kind of optical delusion of his consciousness. This delusion is a kind of prison for us, restricting us to our personal desires and to affection for a few persons nearest to us. Our task must be to free ourselves from this prison by widening our circle of compassion to embrace all living creatures and the whole of nature in its beauty. Nobody is able to achieve this completely, but the striving for such achievement is itself a part of the liberation, and a foundation for inner security."

Mindfulness week seven: when did you stop dancing?

• Those of us who continue downward furthest are likely to be those who are the most conscientious, those whose level of self-confidence is closely dependent on their performance at work, i.e. those who are often seen as the best workers, not the lazy ones.
• What pulls you down, drains away your energy, makes you feel tense and fragmented?
• When did you stop dancing?
• This was one of the most annoying part of the job: waiting for someone else to reply.
• Take a tea break every two hours.
• Eat one less takeaway each week and cook a meal instead.
• Or you might decide to finish work in a different way, turning off your computer a quarter of an hour earlier to give you time to consider what is on the agenda for tomorrow, rather than answering emails up to the last minute, then suddenly realizing you are late for whatever it is you planned to do after work. 
• If you know which activities nourish you, you can do more of them should you start to feel unhappy or unduly stressed or tired.
• When mood is low, motivation follows action, rather than the other way around. When you put the action first, motivation follows.
• Do something pleasurable.
• Do something that gives you a sense of mastery, satisfaction, achievement or control.
• Act mindfully.
• Tiny actions can fundamentally alter your relationship to the world for the better.
• Everyday life offers endless opportunities for you to stop, to focus, to remind yourself to be fully awake and present to what is happening right now.

Mindfulness week eight: your wild and precious life

• From 'Hokusai says', Roger Keyes:
• It matters that you care
• It matters that you feel.
• It matters that you notice.
• Anxiety, stress, unhappiness and exhaustion are often symptoms of a wider and deeper malaise. They are not free-floating affections, but symptoms arising from the way we relate to each other, ourselves, and to the world itself. They are signals that there is something wrong in our lives. They are signs to which we need to pay attention.
• Well, here it is: now is the future that you promised yourself last year, last month, last week. Now is the only moment you'll ever really have. Mindfulness is about waking up this.
• But what we really need to weave is a parachute to use when life starts to become difficult or begins to fall apart.
• Week eight is the rest of your life.
• Weaving your own parachute: using mindfulness to maintain your peace in a frantic world:
• Start the day with mindfulness.
• Use breathing spaces to punctuate your day.
• Maintain your mindfulness practice.
• Befriend your feelings.
• When you feel tired, frustrated, anxious, angry or any other powerful emotion take a breathing space.
• Mindful activities.
• Increase your level of exercise.
• Remember the breath.
• What is it that is most important to me in my life that this practice could help with?
• Body Scan and Exploring Difficulty meditation.
• "Meditation" actually means "cultivation" in the original pali language.
• Practise as if your life depended on it, as in many ways, it surely does. For then you will be able to live with the life you have, and live it as if it truly mattered.

The Unicorn project Gene Kim

• Always good to give more than you get - you never know who can help you in the future. Networking matters.
• You can get rid of loops entirely using iterators, it's an easier, and much safer, way to write a loop.
• Learning Clojure, her favorite programming language, was the mots difficult thing she had overdone, because it entirely removes the ability to change (or mutate) variables.
• How executives are so disconnected from the daily work. It was not helpful for Sarah to remind everyone of how "saving the universe" depends on Phoenix. And it was not helpful for John to appel to their "moral sense of correctness". The job of the bridge crew is to ensure the company strategy is viable, not to remind them of the strategy or to micromanage everyone to death. Their job should be to ensure everyone can get their work done.
• There is nothing so rewarding as providing something to someone who really needs your help. She needed help and she received it.
• The satisfaction of helping people must be reward enough, right?
• Its' such a pain to get things from Operations through normal channels.
• I remember your group. You were one of the best-prepared in the whole company.
• A different way of working, bypassing the normal organizational lines of communication.
• Incredible perseverance, focus, and never taking "no" for an answer.
• I can't believe how the bureaucracy and silos have taken over.
• And that is what an effective network is all about - when you can assemble a group of motivated people to solve a big problem, even though the team looks nothing like the official org chart.
• The lack of trust and too much information flowing around is causing things to go slower and slower.
• I really think this group can make a big difference.
• It's your job to safeguard the most important projects in the company.
• Technical debt is what you fell the next time you want to make a change.
• First ideal of locality and simplicity in our code and organizations.
• Think about the engagement scores of the technology employees versus the rest of the business and ponders the different.
• The last place we want complexity is internally in our processes.
• The first ideal - Locality and Simplicity
• The second ideal - Focus, Flow, and Joy
• The third ideal - Improvement of daily work
• The fourth ideal - Psychological safety
• The fifth ideal - Customer focus
• No one talks about the real problem. Most people aren't brave enough to say what they think or to do the right thing.
• Being able to test and push code to production is more productive, makes for happier customers, creates accountability of code quality to the people who write it, and also makes the work more joyful and rewarding.
• It can be fun to be at the center of everything, but it's certainly not sustainable. Down the road, only chronic wakeup calls, exhaustion, cynicism and burnout await.
• We're going to need a lot more clarity from leadership on this.
• Amazon likely spent over $1 billion over six years rearchitecting all their internal services to be decoupled from each other.
• It is ignorance that is the mother of all problems, and the only thing that can overcome it is learning.
• TWWADI: The Way W've Always Done It.
• The famous Andon cord is just one of their many tools that enable learning. When anyone encounters a problem, everyone is expected to ask for help at any time, even if it means stopping the entire assembly line.
• Each adds to the coordination cost for everything we do, and drives up our cost of delay. And because the distance from where decisions are made and where work is performed keeps growing, the quality of our outcomes diminish.
• For the leader, it no longer means directing and controlling, but guiding, enabling, and removing obstacles.
• Inspirational communication, personal recognition, and supportive leadership.
• Fourth ideal of Psychological safety: no one will take risks, experiment, or innovate in a culture of fear, where people are afraid to tell the boss bad news.
• The fourth ideal asserts that we need psychological safety, where it is safe for everyone to talk about problems.
• If you see something that could hurt someone, you must fix it as quickly as possible.
• Third ideal of improvement of daily work and the fourth ideal of psychological safety.
• The QA team uses a different ticketing system, we don't have access to it.
• We've been waiting almost a year for anonymized customer data.
• We're in a relay race, and we need to get the baton handed to you.
• Small batch sizes, like in manufacturing, create a smooth flow of work, with no jarring disruptions or catastrophes.
• So we need a ticketing system to manage those complex flows of work. But it's so easy for people to lose sight of what the purpose of all this work is.
• This fast and frequent feedback is such a big part of achieving the second ideal of focus, flow and joy.
• How to deliver better value, sooner, safer, and even happier.
• Knowing that you may only need the smallest nudge to buy.
• We have to synchronize with everyone else's release schedules.
• Years of over-promising and under-delivering.
• Unless, of course, there's an urgent business need with a powerful sponsor.
• What about 'don't rock the boat' and 'stay in your lane' do you not understand?
• They think that we are the bottleneck, but we 're always waiting for them.
• Long before the feature ever gets to development, it goes through the funding approval process, which often takes over a year.
• We don't have a fast value stream.
• I need product managers who are working side by side with the teams who are building what will achieve our most important business objective.
• "World as imagined" colliding violently with the "world as it actually is".
• Fostering a culture of psychological safety.
• How tenuous and fleeting the conditions that enable psychological safety can be.
• Needing a nudge to complete their work.
• In order to speak clearly, you need to be able to think clearly. And to think clearly, you usually need to be able to write it clearly.
• Including conflicting definitions of data across all the enterprise.
• Lots of unanticipated problems now that they're working directly with the data scientists and analysts.
• FAANGs: Facebook, Amazon, Apple, Netflix, Google
• Tuckman phases of team going through form, storm, norm and perform.
• And them names help create an identity for the entire group, not just for individuals, and they reinforce the notion that team goals are more important than individual goals.
• But we can't buy back the trust we lost.
• It's important to have a sustainable work pace and to limit our work in process to make sure that work keeps moving through the plan.
• Whenever you have a team of people who are passionately committed to achieving a mission and who have the right skills and abilities, it's dangerous to bet against them.
• Able to navigate the organization in a way very different than the official org chart would suggest.
• A NoSQL database won’t enforce relationnel integrity like most databases.
• It was trying to create a unified vocabulary and taxonomy that they could use, because almost every business system had different names for similar things.
• Daily engineering team standups
• With blockers being urgently handled by the team leads.
• This is what you get for waiting too long to invite the day scientists to the engineering meetings.
• 2004 Google Map/Reduce research paper was published, which described the techniques Google used to massively parallelise the indexing of the entire internet on commodity hardware. This led to the invention of Hadoop, Spark, Beam.
• This new scheme would allow a massive decoupling of services and data.
• Data is the lifeblood of the company.
• Understanding our customers and providing what they need.
• Sounds like a great plan
• Everyone, we have a plan. Let’s make it happen.
• When everyone knows what the goals are, teams will self-organise to best achieve the goals.
• Creating a culture where people felt safe to experiment, to learn and make mistakes, and where people make time for discovery, innovation, and learning.
• The future requires creating a dynamic, learning organisation where experimentation and learning are a part of everyone’s daily work.
• Suggestions were put into production to improve safety, to reduce toil, to increase quality, and to increase flow.
• The more parochial goals that they don’t care about, wether it’s your internal plans of record or how your functional silos are measured.
• Net Promoter Score to rate customer satisfaction. We ask our customers, on a scale of 0 to 10, how likely it is that they would recommend our stores to their friends. The 9s and the 10s are promoters, the 7s and 8s are neutral, and the rest are detractors from the percentage of promoters. An NPS score of thirty is considered good, and above fifty is great.
• Improvements in employee engagement and morale.
• Employee engagement and customer satisfaction are the only things that matter.
• Dr. Geoffrey Moore “Crossing the Chasm”
• Lead time from idea to market offerings matters.
• Almost all business investment now involves software.
• What if psychological safety is as much of a precondition to dynamic, learning organisations as physical safety?
• Those successful efforts that she is so proud of are now going to cause a bunch of innocent people to lose their jobs.
• Asking everyone to do more with less.
• A plan to eliminate $2 million from the IT organisation, that’s about fifteen people across all of your groups.
• Long term, we don’t want to manage our dependencies, we want to eliminate them.
• Cores are the central competencies of our organisation. Context is everything else. It’s the cafeterias, shuttles between buildings, and the thousands of things companies must do to operate. They’re often mission-critical, such as HR, payroll and email. Bu t our customers do not pay us for the great payroll services we provide to our employee.
• Fifth ideal, of being truly customer-centric instead of being silo-centric.
• Those middle managers are your interface between strategy and execution.
• The HIPPO effect (or Highest Paid Person’s Opinion), referring to people’s unhealthy tendency to only care what the highest-level decision-maker thought.
• ODB-II
• Blameless post-mortem.
• What’s needed is focus and urgency, and the modern methods of managing the value creation process.

Unter Druck - Jana Simon - Wie Deutschland sich verändert

• Deutschland habe sich in den vergangenen fünf Jahren sehr verändert.
• Bei Alexander Gauland, nach seiner Aussage, dass wir das recht hätten, auf die Leistungen der deutschen Soldaten in zwei Weltkriegen stolz zu sein.
• Weil das Wort "Altparteien" schon Joseph Goebbels als Propagandamittel für die Nationalsozialisten diente.
• "Die Unterwerfung" von Michel Houellebecq.
• "Wir Deutschen sind das einzige Volk, das sich ein Denkmal der Schande in das Herz seiner Hauptstadt  gepflanzt hat". "Wir brauchen eine erinnerungspolitische Wende um 180 Grad". Björn Höckes
• "Fussballfeldgrossen Albtraum im Herzen der Hauptstadt" Martin Walzer
• In Ostdeutschland ist die AfD zweitstärkste Partei.
• AfD-Spitzenfunktionäre wie Björn Hacke aus Thüringen und Uwe Junge aus Rheinland-Pfalz Seite and Seite mit Pegida-Anhängern und bekannten deutschen Neonazis zeigten.
• Gauland bezeichnete die Zeit des Nationalsozialismus im Vergleich zur "über tausendjährigen Geschichte" Deutschlands als "Vogelschiss".
• "Lazard ist eine etwas andere Bank. Lazard hat mich geholt, weil ich Brücken zwischen der Finanz-Fachwelt un der politischen Welt bauen soll" Jörg Asmussen
• Lazard bereitet weltweit Regierungen.
• "Die Franzosen findet es völlig normal, dass Menschen, die nicht für die Regierung arbeiten, trotzdem von der Regierung irgendwo hingeschickt werden, und wenn es geht, bringen die vielleicht auch zwei, drei Aufträge für französische Unternehmen mit nach Hause" Jörg Asmussen
• Fast niemand für irgendetwas Verantwortung übernimmt.
• Instagram: von allen sozialen Medien ist es vielleicht das narzisstischste.
• Wohlstand ist, wenn du Sicherheit hast, ein Haus besitzt, aus dem dich keiner rauswerfen kann.
• Bosch Standorte: das ist der Augenblick, in dem einem physisch klar wird, was für eine gewaltige Macht das ist, das ökonomische Herz der Bundesrepublik.

Vers la guerre - L’Amérique et la Chine dans le piège de Thucydide ?

• Des spécialistes modernes du comportement ont expliqué ce phénomène au niveau psychologique et remarqué que la crainte de la perte (ou le risque d’un « déclin ») l’emporte sur l’espoir du gain, ce qui nous incite à prendre des risques déraisonnables pour maintenir les choses en l’état.
• « Si tu veux la paix, prépare la guerre ». « Ce n’est qu’en se préparant à la guerre que l’on peut garantir la préservation des richesses, des ressources naturelles et du territoire de l’Etat ». Churchill.
• Les Chinois maîtrisent la stratégie de la patience : tant que le temps jouent pour eux, ils sont prêts à attendre qu’un problème se résolve de lui-même.
• Des changements progressifs mais fondamentaux.
• Les relevés de comptes de centaines de milliers de clients sont effacés pour toujours. Les clients qui souhaitent consulter leur solde en ligne constatent que leur compte a disparu : ils se retrouvent littéralement sans un sou.
• Comme les architectes du projet européen l’avaient bien compris, si les crises qui menacent la survie de l’Union sont inévitables, ce n’est nullement le cas de son effondrement.
• Il n’est pas facile d’ignorer les faits.
• Les occasions se présentent souvent de manière inattendue, pour mieux s’évaporer sans crier gare.
• La guerre économique, la guerre de l’information, les opérations secrètes, la guerre par procuration. La guerre économique que se livrent les Etats-Unis et la Chine. Pratiquement tout ce qui se vend aux Etats-Unis, de l’iPhone au Boeing, est constitué de composants fabriqués en Chine.
• Le resserrement des liens économiques a fait émerger au sein de ces deux sociétés des acteurs puissants qui ont tout intérêt à ce que cette relation productive perdure et qui joueront de leur influence pour préserver la paix.
• Nous devons anticiper des modèles récurrents dans l’histoire de l’humanité.
• Une stratégie commence par poser un diagnostic avant d’établir une ordonnance.
• L’économie de la Chine pèsera 50% plus lourd que celle des Etats-Unis en 2023 et pourrait être presque trois fois plus importante ne 2040.
• Depuis trente ans, Washington a investit bien plus dans le domaine de la défense que tous ses concurrents.
• Les différences comptent au moins autant que les similitudes.
• De plus en plus de gens se voient comme les laissés-pour-compte de la mondialisation et alimentent la montée du populisme, du nationalisme et de la xénophobie.
• La première impression n’est souvent pas la bonne et les trajectoires peuvent faire des tours et des détours imprévus.
• Le destin distribue les cartes, mais ce sont les hommes qui jouent la partie.
• « Oublier son objectif est la forme de stupidité la plus commune » Nietzsche.
• « Connaissez l’ennemi et connaissez-vous vous-même ; en cent batailles vous ne courrez jamais aucun danger. Quand vous ne connaissez pas l’ennemi mais que vous vous connaissez vous-même, vos chances de défaites et de victoires sont égales. Si vous êtes à la fois ignorant de l’ennemi et de vous-même, vous êtes sur de vous trouver en péril à chaque bataille » Sun Tzu.
• Si l’élaboration méticuleuse d’une stratégie ne garantit nullement son succès, l’absence de stratégie cohérente et envisageable sur la durée a toutes les chances d’aboutir à un échec.
• Shakespeare avait raison : notre destinée « n’est pas dans nos étoiles, mais en nous-mêmes »

Prendre soin de l'enfant intérieur - Thich Nhat Hanh

• Enseignements sur l'art de guérir.
• Quoi que nous fassions, qu'il s'agisse de cuisiner, de balayer, de faire la lessive, de marcher ou de respirer, nous pouvons continuer à générer l'énergie de pleine conscience ; ainsi sa graine pourra se renforcer en nous. Et si nous parvenons à la développer toujours plus, la graine de la concentration pourra émerger à son tour. C'est grâce à ces deux énergies, pleine conscience et concentration, que nous pourrons nous libérer des afflictions.
• La pleine conscience est en effet une source d'énergie puissante qui peut reconnaître, étreindre tendrement ces énergies négatives et en prendre soin.
• Alors n'hésitez pas, chaque jour, à baigner ainsi votre colère, votre désespoir, votre peur.
• "J'inspire, je sais qu'il y a de la tristesse en moi. Bonjour ma petite tristesse. J'expire, je vais prendre bien soin de toi."
• Au lieu de combattre nos émotions, nous prenons bien soin d'elles. Nous avons d'ailleurs une grande alliée que nous offre la pleine conscience : la concentration.
• Nous sommes nos ancêtres et nos descendants.
• En réalité, nous sommes la continuation de notre mère et de notre père, tout comme cell de nos ancêtres.
• Nous transmettons nos pensées, nos paroles et nos actions, c'est à dire notre karma, à nos enfants et au monde entier ; c'est là qu'est notre véritable avenir.
• Nous portons tous nos ancêtres en nous, ils nous accompagnent dans chacun de nos gestes, que ce soit en courant, en pratiquant la marche consciente ou quand nous nous établissons dans la joie du moment présent.
• Notre façon d'agir peut provenir de nos ancêtres.
• Lorsque nous sommes capables de sourire face à une provocation.
• Peur originelle, désir originel.
• Nous voulons une nouvelle relation, un nouveau travail ou davantage d'argent. Mais, une fois que nous les obtenons, nous ne parvenons pas à nous en réjouir. Désir après désir, nous restons insatiables.
• Prise de conscience que l'on peut se satisfaire de peu.
• Cessons de convoiter tant de choses, et reconnaissons que même si nous obtenons l'objet de notre désir, nous n'en serons pas plus heureux, et que nous développerons même d'autres désirs.
• Aujourd'hui adulte, il y a une multitude de situations et de choses, parmi ce que nous voyons, entendons et expérimentons, qui ont pour effet de nous ramener à ce souvenir de souffrance.
• Le son de la cloche nous rappelle d'arrêter pensées et paroles pour revenir à notre inspiration et à notre expiration.
• La véritable pratique consiste donc à apprendre à vivre pleinement chaque moment de notre quotidien.
• C'est pour cela que le sourire est excellent ; il détend notre visage, et nous pouvons ensuite l'envoyer à chacune des autres parties de notre corps.
• Il n'y a pas de chemin vers le bonheur, le bonheur est le chemin.
• La première manière de gérer notre souffrance consiste à semer et arroser nos graines de bonheur.
• La deuxième manière de gérer notre souffrance est de cultiver la pleine conscience en permanence.
• La troisième solution qui s'offre à nous pour prendre soin des afflictions qui nous accompagnent depuis notre plus tendre enfance est de les inviter délibérément à monter dans notre conscience mentale.
• Notre pleine conscience peut nous éclairer quant aux dangers d'une recherche permanente du plaisir.
• Le Bouddha nous a d'ailleurs enseigné qu'en absence de souffrance, nous n'aurions jamais la possibilité d'apprendre.
• Il est essentiel pour chacun de nous de prendre le temps de définir ce qui est nécessaire à notre bonheur.
• Nos actions prennent racines dans nos objectifs.
• Tout bonheur porte aussi en lui un goût de souffrance.
• Etre déterminé à ne pas fuir, pour examiner en profondeur notre angoisse et l'accepter pleinement.
• Transformer la souffrance ne veut pas dire la "combattre" ni se "débarrasser" d'elle. Il s'agit tout simplement de la baigner dans la lumière de notre pleine conscience.
• Rester totalement ancré dans le moment présent, ici et maintenant, est une réelle pratique, c'est un entraînement.
• Libéré de la colère, je cesserai d'agir dans l'intention de punir.
• Tolérer la douleur ne signifie pas tenter de la supprimer.
• Je suis en colère, vraiment en colère. Je souffre et je veux que tu le saches.
• Je ne comprends pas pourquoi tu m'as dit cela, pourquoi tu m'as fait cela. Je souffre beaucoup.
• S'il te plaît, aide moi.
• Exprimer notre souffrance, ne serait-ce que par écrit, nous aidera à surmonter notre fierté.
• Nous impliquer à cent pour cent dans l'acte de cuisiner, d'arroser le potager ou de faire la vaisselle.
• La réelle pratique consiste à vivre intensément chaque moment de notre quotidien avec pleine conscience et concentration.
• Nous devons pratiquer la méditation assise et marchée, de façon à prendre conscience de notre situation et voir clairement quelle action engager.
• C'est pour cela qu'il est aussi important de cultiver la pleine conscience dans notre vie quotidienne, de façon à pouvoir nous exprimer sans blesser les personnes à qui nous nous adressons.
• Pour parvenir à faire la paix, nous devons donc abandonner toute vue dualiste et quitter notre tendance à toujours vouloir punir l'autre personne.
• La vie n'est nulle part ailleurs qu'ici et maintenant.
• Nous devons apprendre à comprendre l'autre personne. Ainsi, si nous comprenons suffisamment son mode de fonctionnement, il n'ya plus ni danger ni souffrance.
• Cessons de nous laisser détruire par les projections du futur ou du passé. Ce ne sont que des fantômes. C'est pour cela que nous nous entraînons à être toujours dans le moment présent.
• Apprenons à apprivoiser notre douleur et à vivre pleinement avec elle.
• Sans souffrance, sans compréhension de cette souffrance, le véritable bonheur est impossible.
• Un jour le malentendu pourra se dissiper, simplement par la façon dont vous vivez votre vie, à travers la manière dont vous pratiquez.
• Dès que les hommes sont conscients de la souffrance engendrée par l'oppression politique et par l'injustice dans la société, ils sont en mesure d'arrêter ce qu'ils sont en train de faire et d'aider les autres à s'arrêter à leur tour pour amorcer une nouvelle direction, qui ne détruira plus notre planète.
• Ces souffrances sont aussi celles de nombreuses générations de ma famille, ainsi que celles de toute notre histoire de peuple allemand.
• Arrêter les ruminations.
• Un bouddha est quelqu'un qui est habité par l'énergie de la pleine conscience, de la compréhension et de l'amour.
• J'inspire, je sais que la douleur est là. Bonjour ma petite douleur, je sais que tu es là et je vais prendre soin de toi, sans peur.
• Qu'il s'agisse de la télévision, de journaux, de l'internet, de musique ou de conversations, tout sert le même objectif : couvrir, ensevelir, ignorer la souffrance en soi.
• Il existe un rapport étroit entre souffrance te bonheur.
• Première concentration : le vide. Méditer, c'est prendre le temps de regarder.
• "Rien ne se crée, rien ne se perd, tout se transforme"
• Deuxième concentration : la non-apparence.
• La troisième concentration : la non-poursuite. 
• Ne pas poursuivre, cela implique de ne rien convoiter.
• La non-poursuite est une condition de base pour le bonheur véritable.
• La nature impermanente de toute chose. Le non-désir.
• La toute première nourriture est la nourriture est la nourriture comestible. La deuxième source de nourriture concerne les impressions sensorielles. La troisième source de nourriture est la volition (transformer une motivation en action), ce à quoi nous aspirons le plus. C'est elle qui nous procure la vitalité dont nous avons besoin pour mener notre vie. La quatrième nourriture est la conscience, c'est à dire la conscience collective, l'énergie collective.
• Il est donc essentiel que nous examinions la qualité de notre environnement, tant pour nous que pour nos enfants.
• Selon la logique de notre esprit, mourir signifie que nous passons soudainement de "quelque chose" à "plus rien", que nous sommes quelqu'un et, d'un coup, ne sommes plus personne.
• Le nirvana signifie donc l'extinction de toutes les notions, quelles qu'elles soient, y compris les notions de naissance et de mort, d'être et de non-être.
• Notre discours est franc, mais pas destructeur.
• L'écoute compatissante est de toute première importance.
• Toute notre concentration est portée vers cette écoute et, même si nous entendons des propos qui ne sont pas exacts, nous poursuivons notre écoute afin de permettre à l'autre personne d'exprimer sa souffrance et, ainsi, d'apaiser les tensions qu'elle porte en elle.