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I’ve spent 10 years of my life while working as a stylist and fashion editor in the international fashion magazine . I've also just finished a fullstack program, and my friends are confused. L'Officiel I can admit that being the fashion editor eventually became my dream job. Why? Because you get to meet absolutely any woman you would like to meet. In one issue, you could be talking about sports and the Olympic Games with the women who have trained all their lives to participate in their dream athletic event. In another issue, you could grind the subtle art of pattern making. So, yes, this was the best gap year I've ever had when I also started my own online magazine ! Abstract Stylist At this point, you might be surprised to learn I work in cybersecurity communications now. Partly, because women in tech is still (not) a stereotype, and I love (not) breaking stereotypes! Starting in the tech industry For some women of my age, tech is still a man's world. Well, it's nice if you're from a place where girls have been playing with robots for many years, but in the Baltics, we had had a long time tradition of girls well... being girls. It was only a couple of years ago when the Baltics actually started to teach tech. I mean coding schools, kids' activities, tech programs, etc. This was the first time I felt tired of being called . just a girl in fashion I desperately needed to prove something. So I started learning how to code. And now, I have finished a full-stack program - leaving my friends confused. (In the circle of artists, musicians, and creative minds, this is something that we can't really even talk about now.) Are there really no women in tech? Half of my classmates in full-stack programming were women. Later, in my UX/UI , we all were women. Currently, I am even participating in the initiative with 200 women. You would say this is great! But how about finding a job and actually working in the field of tech? courses studies "Women Go Tech" According to the , in 2019, globally, only 33.2% of all hired people were women. In 2018, global women tech hires increased to 25.7% (+1.1 ppts). In four years, women tech hires have increased from 22.1% to 25.7% (+3.6 ppts). Google annual diversity report Not a full class, you might say. Where are all those women who passionately want to learn and work in tech? It all comes down to stereotypes. From my personal experience, I shocked a lot of people when I said I was going to pursue a career in tech. First, I was doing great in fashion, and everyone seemed to think that you do what you do forever. Secondly, how could anyone without any history of real sciences education do that? I have good news for you. You can do whatever you want with your life! There are plenty of women who broke that (and many more) stereotypes and pursued their careers in tech. Women in tech Where to start if you don't know anything or anyone in tech? Here are some extraordinary women from the Baltics I suggest you to follow: Estonia: (Founder and CEO of Funderbeam) Kaidi Ruusalepp (Founder and CEO of Testlio) Kristel Kruustuk (Founder and CEO of Jobbatical) Karoli Hindriks Latvia: Alise Semjonova (Co-founder of Infogr.am, co-creator of Riga Tech Girls) (Founder and CEO of Vividly) Gunita Kulikovska (CEO of TechChill) Marija Rucevska Lithuania: (CEO of 3D model marketplace CG Trader) Dalia Lasaite (Founder of bit&Byte & Teachers Lead Tech) Monika Katkute Gelzine (COO of MailerLite) Ilma Nausedaite

Baltic Women In Tech To Watch

It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change. - Charles Darwin When somebody talks about the tech startup industry, the majority of people mentally imagine worldwide famous tech hubs, such as San Francisco and the Bay area - Silicon Valley, New York, London, Amsterdam, Singapore, Berlin, and other megacities in most developed countries. And this is not surprising - the startup industry critically relies on access to venture capital, collaboration with other market participants and legislation regarding emerging technologies, such as blockchain, AI, AR/VR, and others. If you establish your startup in right place, you would get all necessary pieces to build a successful company - venture capital firms and angel investors that can write huge checks, best accelerators will help to sharp your product, regulatory “sandboxes” as well as tens of thousands of smart people, cool events, and possibilities to collaboration. Twenty years ago during the dotcom bubble and rising of the Internet, it looked like real innovations and high-tech businesses can develop in a quite limited number of places. Now it is evident, that such a view is blinkered: situation significantly changed. There are a lot of brand new places to create something cool. Making a decision regarding jurisdiction of your own company, it is important to keep in mind necessary success factors for any global startup: Direct access to at least one huge market As low operating expenses as it is possible to have more time to test your idea using VC funding Legislation, that can supports your business and not ban you from using emerging tech, that can disrupt the market Mature startup ecosystem - events, meetups, conferences, accelerators, and VCs It looks like that in 2020 you can get all of this and even more without a presence in world-famous startups capitals. How did the former Soviet republics become innovation hubs? Approximately thirty years ago Baltic states - Latvia, Lithuania, and Estonia were poor ex-Soviet republics. But, after they gained independence they got a fresh start - according to the USSR dissolution agreement, Russian Federation inherit all ex-USSR external debts, so all ex-Soviet republics start their bookkeeping from the blank page. Besides this, they got an infrastructure, human capital, and neighborhood with the European Union, which was forming at that moment. During the last 30 years, they hugely moved forward - became the EU members, adopt Euro, e-government, modern legislation, focused on fostering innovative entrepreneurship and created a stable political and banking system. It is important to note, that in the postindustrial economy you don’t need large territory or abundance of natural resources such as oil and gas anymore to be successful. The good examples to support this statement are small, but very high-developed countries such as Luxembourg, Liechtenstein, Singapore, Sweden, Denmark, and many others. All you need in the new “game” is to attract financial capital, smart people and build innovations. All of this is going in accordance with the citation of Charles Darwin - if rules change, change your game strategy. These countries changed, and what they got? I am convinced that the best answer to this question is the practical experience, which is much more relevant than ratings of any kind. So, I invited several successful blockchain companies from Baltic states to share their opinion and experience regarding the business landscape they are operating on. So, let’s going on to some insider stuff. Let's start with Latvian startup Mission Tech . They provided a comprehensive comment regarding the conditions for innovation entrepreneurship. At the end of 2017, Latvia finally adopted Startup Law (special legislation for tech companies) with startup visas for non-EU founders. Just in 4 weeks non-EU founders could get a residency permit (startup visa), establish a new company & open bank account. It’s the fastest solution in the whole EU. According to , only one in three managers in the EU is female. However, in Latvia, this figure is in the majority, with 53% of leading positions going to women. Eurostat data It is important to note that Latvia takes 3rd place in the OECD ranking for the attractiveness of the tax system and has the lowest requirements for founders in terms of finances. Since the start of the business, you need to pay a minimum salary of only 460 euros. For example in Finland, this amount is approximately 2500 euros half of which goes to taxes. Moreover, Riga is one of the cheapest European capital. For example in Riga, you can live for 1000 euros for 30 days, while in London it is only 10. For venture capital funds, a startup set up in Latvia is an absolute advantage, because the cost of living in London, Paris, and Berlin is 82, 75 and 50% higher than in Riga. Latvia has the lowest EU rates on capital gains, and dividends received from other countries are taxed in Latvia at a 0% rate. Also, Latvian startups can receive tax benefits in the amount of 200,000 euros, if only 30,000 euros are raised from accelerators or venture funds. Unlike Estonia, you don’t need a special license for any related crypto activity. It’s 100% legal to operate crypto exchange without any special requirements (except let know local tax authorities). If you are thinking, where to move to the EU to start a crypto company, we definitely recommend Latvia. We’ve participated in the process of more than 40 companies relocating to Latvia, and we know stuff we talking about. The other, more restrained opinion regarding doing business in Latvia was provided by trading platform Hodlhold , which is one of the most known blockchain companies from Baltic states. It is not a secret that a lot of international companies transport workers and offices to Latvia. It is connected mainly with high-quality workers, relatively low salaries and other operational costs. The location is perfect and immigration authorities are very friendly to startups and entrepreneurs - it is easy to get startup visas and residency. Unfortunately, the legislation for crypto is not finally developed now, and in fact, we have no clear rules, how to work with crypto here. The government support for fintech and crypto companies is also limited. In our opinion, Latvia, as well as Lithuania and Estonia have good chances to become ones of world crypto leaders. But, to achieve this we need to complete the puzzle with crypto-friendly legislation - for example, Estonia made it several years ago and the results are amazing. I hope, it will be done soon. The view on the Estonian business landscape was provided by Itez , a startup that made successful business on providing crypto-fiat exchange services for EU residents. Due to the fact that we have a rather specific type of business, we have been precisely choosing the most suitable jurisdiction. As a result, we established our company in Estonia, as it suited us both in terms of costs and the convenience of legislation. In addition, it allows us to acquire the necessary licenses for our type of activity. Regarding the rules of operation for crypto companies, it is not a secret that they are tightened across the EU and Estonia is not an exception. However, we stay compliant with all of them. The advantages of this jurisdiction outweigh this tendency, such as low costs and very efficient e-government - we can make almost all business-related operations online. Talking regarding the advice for crypto companies which plan to establish a crypto business, Itez points out the following: First of all, be honest with the law. Do not save on lawyers for the preparation and subsequent maintenance of a package of operational documents for the company. Do not forget that the attention of the regulator and lawmakers is especially riveted to cryptocurrencies, so you should not be cunning. It will be better for everyone. For example, our activity requires licensing and we have two licenses - for the exchange of cryptocurrencies and for storage of cryptocurrencies of third parties. In order to fully comply with the law, we have implemented an adequate AML policy that is consistent with EU directives. In addition, we have a special AML officer who constantly monitors the work of our company. And finally, here is rather interesting material, which allows  to understand the intricacies of doing business in Latvia. This comment was provided by Startuplatvia.eu , a government-supported initiative aimed on support of the Latvian startup ecosystem. First of all, Latvia is part of the EU, which in terms of regulations and investment opportunities is a good starting point. The business climate is rather good, especially for startups that deal with cryptocurrencies. In Latvia, crypto is being regulated by the tax office and not the Financial and Capital Market Commission (local financial regulatory authority). You don’t have to acquire any additional licenses if you plan to open up a crypto exchange or any other crypto-related business in Latvia (opposite to Estonia, laws of which require to get a special license). Profits from crypto trading are considered to be capital gains in Latvia, which is taxed as 20% for physical persons and 0% for companies. Right now Latvia is moving in the right direction, especially for foreigners that plan to start a new business in Latvia. One can apply for a startup visa which technically provides temporary residence permits for up to 5 founders. That is a huge opportunity for people who want to kickstart in the EU. Taking about our advice to start your startup journey would be to study to better understand whether this jurisdiction and benefits it provides suits your goals. https://startuplatvia.eu/ If you have your own funds and want to work from a country that has a friendly and well-developed legislation framework then Latvia is a good place to start. If you plan to do fundraising in Europe, the UK or Germany would probably fit your needs better. Regarding the crypto business, there are a lot of opportunities. You can make a fully legal and operational crypto business in Latvia. Speaking about the future, my opinion is that Eastern Europe will develop faster in terms of blockchain and crypto adoption. It is mostly connected with the fact that existing financial systems here receive less trust from people than in Western European counties like Sweden or the UK. In fact, Baltic states are at the initial stage of building their innovation hubs in comparison with such big players as Silicon Valley. But, despite the youngness and limited economic resources (note that the amount of capital in the economy of Baltic states is tiny being compared to the US or UK ones), they got a huge success. So, what is possible to conclude from provided comments? This success is based on a simple principle of efficient usage of all the strong points that you have. These strong points are presented by, but not limited to low operational costs and cost of living, integration in the EU market, low taxation and flexible immigration laws. It is exciting when you can hire three developers instead of one in Silicon Valley or New York on the same budget to test your idea and ensure a longer runway for the company. The achieved success of these three countries on an innovation market is nothing but the confirmation that the adaptiveness of the system to external conditions is often more important than other features. It looks like that this principle is working for both - for countries, that offer good conditions to modern entrepreneurs and for companies, that choose efficient jurisdiction to build business. I do not have any vested interest in any of the mentioned companies. The views, descriptions and opinions expressed are those of the author and the companies, that provided comments. Do your own research.

Will Baltic states Embrace Crypto Startups and Blockchain Companies?

Let's learn about via these 53 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Machine Learning Uses /Learn Repo 1. Use Cascade Models to Get Better Speed and Accuracy in Computer Vision Tasks Great way to improve your Computer Vision models metrics 2. The Four Types of Machine Learning | Part 2 In the previous post, we saw the first two types of machine learning. In this post, we will discuss the other two types of machine learning. These are — Semi-su 3. The Convergence of AI + IOT is Imminent & Your Competitor is Already Preparing for It With the emergence of ever-cheaper and robust hardware, 5G connectivity around the corner, and most importantly, a growing list of real world use cases, we can all agree that IOT projects are here to stay. But is that where it ends ? 4. Adversarial Examples In Machine Learning Explained There are easy ways to build adversarial examples that can fool any deep learning model and create security issues no matter how complex the model is. 5. Reimagining Customer Behavior Through Machine Learning Here what you need to know about Machine Learning in business market strategy 6. Machine Learning: Santa’s little helper He’s making a list and checking it… well… once, because his model has a 98% accuracy 7. How AI Is Transforming The Field Of Education Artificial Intelligence (AI) is one of the wonders of the modern world, which isn’t going to cease to amaze the most intelligent of human beings. Like other fields, the field of education is also gaining the maximum amount of benefits out of the promises of the AI-powered technology. 8. Artificial Intelligence on Making Court Decisions In Estonia, artificial intelligence will play a crucial role in the future of human beings. It will play a crucial role in the functioning of judicial institutions, which is a great innovation. According to the authorities in this Baltic country, they are empowered to arbitrate cases of minor offenses autonomously. Unbelievable but true! 9. The GPUs for Deep Learning: NVIDIA vs AWS vs Azure and More Take a deeper dive into what a GPU is, when you should use it or shouldn’t for Deep Learning tasks, and what is the best GPU on-premises and in the cloud in 202 10. Debunking 4 Common Myths About Machine Learning Machine learning is a subset of artificial intelligence that involves the use of algorithms and statistical models to enable computers to improve them. 11. How Document Classification Can Improve Business Processes The process of labeling documents into categories based on the type of the content is known as document classification. It can also be defined as the process of assigning one or more classes or categories to a document (depending on the type of content) to make it easy to sort and manage images, texts, and videos. Document classification can be done using artificial intelligence, machine learning, and python. 12. How To Get Started With Machine Learning With The Right Mindset You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club. 13. How Companies Are Actually Using AI in Everyday Practices When thinking of AI (artificial intelligence), mixed emotions often come to mind. For movie buffs, we might immediately see images of Will Smith battling it out with humanoid AI creatures in IRobot or the even more realistic looking depiction of artificial intelligence in the movie aptly called AI. In our human minds, AI is something that could potentially lead to a catastrophic apocalypse as machines take over the world. 14. Every Way Natural Language is Better Than SQL Since the dawn of time, humans have communicated through gestures, drawings, smoke, or speech. Along the way, Structured Query Language (SQL) made its way into human life so we could speak to databases. However, it’s time to revert back to our natural language and rethink how we talk to our data. 15. How Machine Learning Can Help With Fraud Prevention Technology, without a doubt, has eased up a lot of issues for us, including the likes of fraud prevention. But before we start talking about the technological inputs pertaining to the same, it is necessary to understand why fraud prevention is actually required by businesses and why this genre of functionality is wide-spread and extremely popular. Firstly, financial firms are probably the most affected ones as fraudsters are actually interested in siphoning off money more than anything else. Secondly, fraudulent activities aren’t restricted to one vertical and it is a challenge for the firms to develop newer strategies for combating evolving threats. 16. Introduction to Different Machine Leaning Tools Machine Learning is one of the emerging technologies of the present IT industry. This technology has now become the talk of the town and has seen  an abnormally high growth over the few years. 17. Deploy Computer Vision Models with Triton Inference Server There are a lot of Machine Learning courses, and we are pretty good at modeling and improving our accuracy or other metrics. 18. Basic Use Cases of AI, ML, Deep Learning and Internet of Things The world’s most influential companies and technologies are influenced by the efficiency of Artificial intelligence and similar technologies. Whether it is Facebook or Amazon, Google or Microsoft, all firms are harnessing AI techniques and algorithms to introduce high-level performance and streamlined operations. 19. How is AI-powered Software Development influencing Pet Tech Technology is revolutionizing all aspects of our lives. Let's take a look at how AI-powered software development influencing pet tech. 20. An Introduction to AI-Based Visual Inspection for Defect Detection “Why should I care about a cool new technology until it’s solving any of my problems?” – this was the exact conversation I had with the executive of a water purification plant over a warm cup of coffee. 21. Announcing ModelDB 2.0 release Since we wrote ModelDB 1.0, a pioneering model versioning system, we have learned a lot and adapting it to the evolving ecosystem became a challenge. Hence we decided to rebuild from the ground up to support a model versioning system tailored to make ML development and deployment reliable, safe, and reproducible. 22. Most Useful ML Ops Applications Many ML Ops tools allow overseeing the entire machine learning model life cycle. Here are some of the most worthwhile ones to consider. 23. Vladimir Vapnik's New Learning Model Vladimir Vapnik recently gave a talk about a new theory of learning he is working on. 24. Evaluating Regression Models in Machine Learning Model evaluation is very important since we need to understand how well our model is performing. 25. Breaking into Deep Learning: Transforming the World Without Expert Input Deep learning is a subdivision of machine learning in which Artificial Neural Networks (ANNs) learn from a huge influx of data to produce high-quality output. 26. Model Tests are Essential for Building Domain Knowledge Testing protects against regressions. But the most important product of testing is domain knowledge and powerful capabilities. 27. Can Graph Neural Networks Solve Real-World Problems? In this article, we will learn about GNNs and its structure as well as its applications 28. The Future of Artificial Intelligence: To Kill or To Heal? The evil cyber-intelligence from the Matrix and a cyborg killing machine from the Terminator movies - that’s what most people used to imagine when talking about the future of artificial intelligence. 29. What’s the Difference Between AI And Machine Learning? It’s nearly impossible to have a conversation about technology without mentioning artificial intelligence (AI) or machine learning (ML). 30. Here’s How Libratus, a Poker-Playing AI, Bluffed Four Professional Texas Holdem Players The world of technology is changing at a faster rate than we can possibly fathom. Long gone are the days when we were the sole trailblazers in a human-tech relationship when the incentive resided in our hands. 31. What's the Difference Between MLOps and AIOps An overview of the MLOps and AIOps worlds to understand what they mean, how they relate to DevOps, and how they compare in terms of benefits. 32. Machine Learning Applications Across Different Industries 1952 witnessed the world’s first computer that could learn while it was running. It was a game of checkers developed by Arthur Samuel. It has barely been half a century since then and we’re already having a conversation about whether we should commercialize self-driving cars or not. Machine Learning gave birth to some of these great advancements in technology and we’re going to dive deep into everything it can do to make our lives much easier than ever before. 33. How AI and Machine Learning Changes Modern-day Industries It’s important to know exactly how AI and Machine Learning are transforming the industries and their role in our technological advancements. 34. Applications of Artificial Intelligence in Business Artificial Intelligence, the concept of ‘machines with brains’ has been in the spotlight around the last seven decades. A theoretical notion that started as simple rule-based automation in the 1950s' has now grown so much that now the scientists are trying to make human-like robots. The question- What AI might do to us? — has created a lot of controversies in and out of the scientific community. 35. 8 Machine Learning Trends that Impact Business in 2021 and Beyond Let’s discover the latest innovations in machine learning in 2021-2022 and go over various examples of how this technology can benefit you and your business. 36. Success With Machine Learning Projects in Python In this article, we will give you a sense of the applications for machine learning and explain why Python is a perfect choice for getting started. 37. Build A Commission-Free Algo Trading Bot By Machine Learning Quarterly Earnings Reports [Full Guide] Introduction 38. What is Machine learning and Why is it Important? Machine learning is quite an exciting field to study and rightly so. It is all around us in this modern world. From Facebook’s feed to Google Maps for navigation, machine learning finds its application in almost every aspect of our lives. 39. Is Automation Jeopardizing Our Future? Is automation jeopardizing our future? What's its impact on our future and the job market? And how can we cope up? 40. Universal Data Tool Introduction: Weekly Update 2 If you haven’t heard of the Universal Data Tool, it’s an open-source web or desktop program to collaborate, build and edit text, image, video, and audio datasets with labels and annotations. 41. An Introduction to Variational Autoencoders Using Keras In this tutorial, we’ll explore how Variational Autoencoders simply but powerfully extend their predecessors, ordinary Autoencoders. 42. How To Improve Data Quality When With Unsupervised Machine Learning There won’t be any business insights if the data quality is poor. 43. How Machine Learning is Used in Astronomy Is Astronomy data science? 44. Will Machine Learning Algorithms Encroach on Content Marketers? Since its inception, the field of online content marketing has been in a constant state of flux. This tendency is built into it — since it operates in an ever changing online world, all it can ever do is change along with the internet. For better or for worse, the rapid advent of machine learning algorithms in online processes will only lead to more change in the field of content marketing. 45. How To Identify Trees with Deep Learning Idea / inspiration 46. Pecan.ai Raises 11 Million to Bring Machine Learning to Business Analysts Pecan.ai has just come out of stealth, raising an $11M Series A, to enable business analysts to build machine learning models automatically. Dell Capital led the round, joined by S capital and bringing the total funding of the company to $15M. 47. Embeddings in Machine Learning: Everything You Need to Know Here's a deep dive into the history of machine learning embeddings, common uses, and current infrastructure solutions, including the vector database. 48. Quantum Machine Learning Using TensorFlow Quantum INTRODUCTION 49. How Data Analysis Helps Unveil the Truth of Coronavirus These days we are all scared of the new airborne contagious coronavirus (2019-nCoV). Even if it is a tiny cough or low fever, it might underlie a lethargic symptom. However, what is the real truth? 50. Big Tech Companies Need Machine Learning Engineers Machine learning is no longer a sci-fi concept, but an actual application of AI technology we use every day. 51. No Such Thing As The Intelligent Edge But it will be much bigger than the Internet. 52. Why It’s Very Difficult to Create AI-Based Slow Motion Over the last few years a number of open source machine learning
projects have emerged that are capable of raising the frame rate of
source video to 60 frames per second and beyond, producing a smoothed,
'hyper-real' look. 53. Optuna Vs. Hyperopt: Which Hyperparameter Optimization Library You Should Choose Thinking which library should you choose for hyperparameter optimization? Thank you for checking out the 53 most read stories about Machine Learning Uses on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

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Scientific American, Volume XLIII., No. 25, December 18, 1880, by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . The Collins Line of Steamers. here The Collins Line of Steamers. The breaking up of the Baltic, the last of the famous Collins line of steamships, calls out a number of interesting facts with regard to the history of the several vessels of that fleet. There were five in all, the Adriatic, Atlantic, Pacific, Arctic, and Baltic. They were built and equipped in New York. Their dimensions were: Length, 290 feet; beam, 45 feet; depth of hold, 31½ feet; capacity, 2,860 tons; machinery, 1,000 horse power. In size, speed, and appointments they surpassed any steamers then afloat, and they obtained a fair share of the passenger traffic. A fortune was expended in decorating the saloons. The entire cost of each steamer was not less than $600,000, and notwithstanding their quick passages, the subsidy received, and the high rates of freight paid, the steamers ran for six years at great loss, and finally the company became bankrupt. The Atlantic was the pioneer steamship of the line. She sailed from New York April 27, 1849, and arrived in the Mersey May 10, thus making the passage in about thirteen days, two of which were lost in repairing the machinery; the speed was reduced in order to prevent the floats from being torn from the paddle-wheels. The average time of the forty-two westward trips in the early days of the line was 11 days 10 hours and 26 minutes, against the average of the then so called fastest line of steamers, 12 days 19 hours and 26 minutes. In February, 1852, the Arctic made the passage from New York to Liverpool in 9 days and 17 hours. The Arctic was afterward run into by a French vessel at sea and only a few of her passengers were saved. The Pacific was never heard from after sailing from Liverpool, and all the persons on board were lost. The Atlantic, after rotting and rusting at her wharf, was deprived of her machinery and converted into a sailing vessel, and was broken up in New York last year. The Adriatic, the "queen of the fleet," made less than a half dozen voyages, was sold to the Galway Company, and is now used in the Western Islands as a coal hulk by an English company. The Baltic was in the government service during the war as a supply vessel, and was afterward sold at auction; her machinery was removed and sold as old iron. She was then converted into a sailing ship, and of late years has been used as a grain carrying vessel between San Francisco and Great Britain. On a recent voyage to Boston she was strained to such an extent as to be made unseaworthy, and for that reason is to be broken up. One cannot but remark in this connection how small has been the advance in steamship building during the quarter century since the Collins line was in its glory. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2007). Scientific American, Volume XLIII., No. 25, December 18, 1880. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/21081/pg21081-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The Collins Line of Steamers

A Treatise on Painting by da Vinci Leonardo, is part of the HackerNoon Books Series. You can jump to any chapter in this book . MISCELLANEOUS OBSERVATIONS here MISCELLANEOUS OBSERVATIONS. Chap. CCCXLIV.— Why a painted Object does not appear so far distant as a real one, though they be conveyed to the Eye by equal Angles. If a house be painted on the pannel B C, at the apparent distance of one mile, and by the side of it a real one be perceived at the true distance of one mile also; which objects are so disposed, that the pannel, or picture, A C, intersects the pyramidical rays with the same opening of angles; yet these two objects will never appear of the same size, nor at the same distance, if seen with both eyes. Chap. CCCXLV.— How to draw a Figure standing upon its Feet, to appear forty Braccia high, in a Space of twenty Braccia, with proportionate Members. In this, as in any other case, the painter is not to mind what kind of surface he has to work upon; particularly if his painting is to be seen from a determined point, such as a window, or any other opening. Because the eye is not to attend to the evenness or roughness of the wall, but only to what is to be represented as beyond that wall; such as a landscape, or any thing else. Nevertheless a curved surface, such as F R G, would be the best, because it has no angles. Chap. CCCXLVI.— Plate XXII. How to draw a Figure twenty-four Braccia high, upon a Wall twelve Braccia high. Draw upon part of the wall M N, half the figure you mean to represent; and the other half upon the cove above, M R. But before that, it will be necessary to draw upon a flat board, or a paper, the profile of the wall and cove, of the same shape and dimension, as that upon which you are to paint. Then draw also the profile of your figure, of whatever size you please, by the side of it; draw all the lines to the point F, and where they intersect the profile M R, you will have the dimensions of your figure as they ought to be drawn upon the real spot. You will find, that on the straight part of the wall M N, it will come of its proper form, because the going off perpendicularly will diminish it naturally; but that part which comes upon the curve will be diminished upon your drawing. The whole must be traced afterwards upon the real spot, which is similar to M N. This is a good and safe method. Chap. CCCXLVII.— Why, on measuring a Face, and then painting it of the same Size, it will appear larger than the natural one. A B is the breadth of the space, or of the head, and it is placed on the paper at the distance C F, where the cheeks are, and it would have to stand back all A C, and then the temples would be carried to the distance O R of the lines A F, B F; so that there is the difference C O and R D. It follows that the line C F, and the line D F, in order to become shorter, have to go and find the paper where the whole height is drawn, that is to say, the lines F A, and F B, where the true size is; and so it makes the difference, as I have said, of C O, and R D. Chap. CCCXLVIII.— Why the most perfect Imitation of Nature will not appear to have the same Relief as Nature itself. If nature is seen with two eyes, it will be impossible to imitate it upon a picture so as to appear with the same relief, though the lines, the lights, shades, and colour, be perfectly imitated. It is proved thus: let the eyes A B, look at the object C, with the concurrence of both the central visual rays A C and B C. I say, that the sides of the visual angles (which contain these central rays) will see the space G D, behind the object C. The eye A will see all the space FD, and the eye B all the space G E. Therefore the two eyes will see behind the object C all the space F E; for which reason that object C becomes as it were transparent, according to the definition of transparent bodies, behind which nothing is hidden. This cannot happen if an object were seen with one eye only, provided it be larger than the eye. From all that has been said, we may conclude, that a painted object, occupying all the space it has behind, leaves no possible way to see any part of the ground, which it covers entirely by its own circumference. Chap. CCCXLIX.— Universality of Painting; a Precept. A painter cannot be said to aim at universality in the art, unless he love equally every species of that art. For instance, if he delight only in landscape, his can be esteemed only as a simple investigation; and, as our friend Botticello remarks, is but a vain study; since, by throwing a sponge impregnated with various colours against a wall, it leaves some spots upon it, which may appear like a landscape. It is true also, that a variety of compositions may be seen in such spots, according to the disposition of mind with which they are considered; such as heads of men, various animals, battles, rocky scenes, seas, clouds, woods, and the like. It may be compared to the sound of bells, which may seem to say whatever we choose to imagine. In the same manner also, those spots may furnish hints for compositions, though they do not teach us how to finish any particular part; and the imitators of them are but sorry landscape-painters. Chap. CCCL.— In what Manner the Mirror is the true Master of Painters. When you wish to know if your picture be like the object you mean to represent, have a flat looking-glass, and place it so as to reflect the object you have imitated, and compare carefully the original with the copy. You see upon a flat mirror the representation of things which appear real; Painting is the same. They are both an even superficies, and both give the idea of something beyond their superficies. Since you are persuaded that the looking-glass, by means of lines and shades, gives you the representation of things as if they were real; you being in possession of colours which in their different lights and shades are stronger than those of the looking-glass, may certainly, if you employ the rules with judgment, give to your picture the same appearance of Nature as you admire in the looking-glass. Or rather, your picture will be like Nature itself seen in a large looking-glass. This looking-glass (being your master) will shew you the lights and shades of any object whatever. Amongst your colours there are some lighter than the lightest part of your model, and also some darker than the strongest shades; from which it follows, that you ought to represent Nature as seen in your looking-glass, when you look at it with one eye only; because both eyes surround the objects too much, particularly when they are small. Chap. CCCLI.— Which Painting is to be esteemed the best. That painting is the most commendable which has the greatest conformity to what is meant to be imitated. This kind of comparison will often put to shame a certain description of painters, who pretend they can mend the works of Nature; as they do, for instance, when they pretend to represent a child twelve months old, giving him eight heads in height, when Nature in its best proportion admits but five. The breadth of the shoulders also, which is equal to the head, they make double, giving to a child a year old, the proportions of a man of thirty. They have so often practised, and seen others practise these errors, that they have converted them into habit, which has taken so deep a root in their corrupted judgment, that they persuade themselves that Nature and her imitators are wrong in not following their own practice. Chap. CCCLII.— Of the Judgment to be made of a Painter’s Work. The first thing to be considered is, whether the figures have their proper relief, according to their respective situations, and the light they are in: that the shadows be not the same at the extremities of the groups, as in the middle; because being surrounded by shadows, or shaded only on one side, produce very different effects. The groups in the middle are surrounded by shadows from the other figures, which are between them and the light. Those which are at the extremities have the shadows only on one side, and receive the light on the other. The strongest and smartest touches of shadows are to be in the interstice between the figures of the principal group where the light cannot penetrate. Secondly, that by the order and disposition of the figures they appear to be accommodated to the subject, and the true representation of the history in question. Thirdly, that the figures appear alive to the occasion which brought them together, with expressions suited to their attitudes. Chap. CCCLIII.— How to make an imaginary Animal appear natural. It is evident that it will be impossible to invent any animal without giving it members, and these members must individually resemble those of some known animal. If you wish, therefore, to make a chimera, or imaginary animal, appear natural (let us suppose a serpent); take the head of a mastiff, the eyes of a cat, the ears of a porcupine, the mouth of a hare, the brows of a lion, the temples of an old cock, and the neck of a sea tortoise. Chap. CCCLIV.— Painters are not to imitate one another. One painter ought never to imitate the manner of any other; because in that case he cannot be called the child of Nature, but the grandchild. It is always best to have recourse to Nature, which is replete with such abundance of objects, than to the productions of other masters, who learnt every thing from her. Chap. CCCLV.— How to judge of one’s own Work. It is an acknowledged fact, that we perceive errors in the works of others more readily than in our own. A painter, therefore, ought to be well instructed in perspective, and acquire a perfect knowledge of the dimensions of the human body; he should also be a good architect, at least as far as concerns the outward shape of buildings, with their different parts; and where he is deficient, he ought not to neglect taking drawings from Nature. It will be well also to have a looking-glass by him, when he paints, to look often at his work in it, which being seen the contrary way, will appear as the work of another hand, and will better shew his faults. It will be useful also to quit his work often, and take some relaxation, that his judgment may be clearer at his return; for too great application and sitting still is sometimes the cause of many gross errors. Chap. CCCLVI.— Of correcting Errors which you discover. Remember, that when, by the exercise of your own judgment, or the observation of others, you discover any errors in your work, you immediately set about correcting them, lest, in exposing your works to the public, you expose your defects also. Admit not any self-excuse, by persuading yourself that you shall retrieve your character, and that by some succeeding work you shall make amends for your shameful negligence; for your work does not perish as soon as it is out of your hands, like the sound of music, but remains a standing monument of your ignorance. If you excuse yourself by saying that you have not time for the study necessary to form a great painter, having to struggle against necessity, you yourself are only to blame; for the study of what is excellent is food both for mind and body. How many philosophers, born to great riches, have given them away, that they might not be retarded in their pursuits! Chap. CCCLVII.— The best Place for looking at a Picture. Let us suppose, that A B is the picture, receiving the light from D; I say, that whoever is placed between C and E, will see the picture very badly, particularly if it be painted in oil, or varnished; because it will shine, and will appear almost of the nature of a looking-glass. For these reasons, the nearer you go towards C, the less you will be able to see, because of the light from the window upon the picture, sending its reflection to that point. But if you place yourself between E D, you may conveniently see the picture, and the more so as you draw nearer to the point D, because that place is less liable to be struck by the reflected rays. Chap. CCCLVIII.— Of Judgment. There is nothing more apt to deceive us than our own judgment, in deciding on our own works; and we should derive more advantage from having our faults pointed out by our enemies, than by hearing the opinions of our friends, because they are too much like ourselves, and may deceive us as much as our own judgment. Chap. CCCLIX.— Of Employment anxiously wished for by Painters. And you, painter, who are desirous of great practice, understand, that if you do not rest it on the good foundation of Nature, you will labour with little honour and less profit; and if you do it on a good ground your works will be many and good, to your great honour and advantage. Chap. CCCLX.— Advice to Painters. A painter ought to study universal Nature, and reason much within himself on all he sees, making use of the most excellent parts that compose the species of every object before him. His mind will by this method be like a mirror, reflecting truly every object placed before it, and become, as it were, a second Nature. Chap. CCCLXI.— Of Statuary. To execute a figure in marble, you must first make a model of it in clay, or plaster, and when it is finished, place it in a square case, equally capable of receiving the block of marble intended to be shaped like it. Have some peg-like sticks to pass through holes made in the sides, and all round the case; push them in till every one touches the model, marking what remains of the sticks outwards with ink, and making a countermark to every stick and its hole, so that you may at pleasure replace them again. Then having taken out the model, and placed the block of marble in its stead, take so much out of it, till all the pegs go in at the same holes to the marks you had made. To facilitate the work, contrive your frame so that every part of it, separately, or all together, may be lifted up, except the bottom, which must remain under the marble. By this method you may chop it off with great facility. Chap. CCCLXII.— On the Measurement and Division of Statues into Parts. Divide the head into twelve parts, each part into twelve degrees, each degree into twelve minutes, and these minutes into seconds. Chap. CCCLXIII.— A Precept for the Painter. The painter who entertains no doubt of his own ability, will attain very little. When the work succeeds beyond the judgment, the artist acquires nothing; but when the judgment is superior to the work, he never ceases improving, if the love of gain do not retard his progress. Chap. CCCLXIV.— On the Judgment of Painters. When the work is equal to the knowledge and judgment of the painter, it is a bad sign; and when it surpasses the judgment, it is still worse, as is the case with those who wonder at having succeeded so well. But when the judgment surpasses the work, it is a perfectly good sign; and the young painter who possesses that rare disposition, will, no doubt, arrive at great perfection. He will produce few works, but they will be such as to fix the admiration of every beholder. Chap. CCCLXV.— That a Man ought not to trust to himself, but ought to consult Nature. Whoever flatters himself that he can retain in his memory all the effects of Nature, is deceived, for our memory is not so capacious; therefore consult Nature for every thing. THE END. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. da Vinci Leonardo (2014). A Treatise on Painting. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/46915/pg46915-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

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