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While making GeekForge — a daily listing of interesting coding tasks — we researched several sources where you can learn quantum computing, and we thought it would be a good idea to share this list with you. If you heard about supercomputers, then you probably already know that quantum computers are meant to solve in just a few days or even hours the problems that take supercomputers hundreds of years to solve. That’s the disruptive power of this technology. As a developer, you know the limits and the potential of a modern computer, however, when it comes to quantum computations, nothing is the same. The common way of storing information on bits in the form of a 0 or 1 can now be 0 and 1 at the same time with quantum computing. That’s the quantum effect and it’s the first thing you should learn when diving into this field. The information might be hard to digest at first, but once it’s properly explained, everything will start making so much sense. If you don’t want to be like everybody else, running away from quantum computing just because it “sounds” difficult, I urge you to get your feet wet with the following list of hand-picked resources on quantum technology to learn about its true potential! 1) Quantum Computing — An Overview at Udemy A detailed overview of quantum computing covering entanglement, superposition, quantum gates, superdense coding. 2) Quantum Computing Explained at Amazon A conversational approach to explaining quantum computing with workable solutions. 3) Daily email list of quantum computing coding tasks from GeekForge You can solve tasks independently or discuss them with the community. It’s the best way to educate yourself on new technology and build a portfolio of your completed tasks. 4) Understanding Quantum Computers at Future Learn Introduction to the key concepts of quantum computing with minimal mathematics. 5) Quantum Computation lecture from Caltech Institute In this course, you’ll study the properties that distinguish quantum information from classical information. 6) QC101 Quantum Computing & Quantum Physics for Beginners at Udemy Master quantum computing, quantum cryptography, and quantum physics with Microsoft Q# (Q Sharp) and IBM Quantum Experience. 7) Quantum Quest from QuSoft At the end of this course, you’ll understand what quantum bits and quantum algorithms are and what they are good for. 8) Quantum Information Sciences from MIT A series of lecture notes on the MIT quantum information sciences course. 9) Quantum machine learning for data scientists from Quantee Limited This text aims to present and explain quantum machine-learning algorithms to a data scientist in an accessible and consistent way. 10) Quantum Computing for Computer Scientists from Microsoft This talk discards hand-wavy pop-science metaphors and answers one simple question: how can a quantum computer outperform a classical computer? 11) The Quantum Internet and Quantum Computers at edX Learn the principles and promises behind developments in quantum computers and quantum internet and how they will impact our future. 12) Quantum Computing for Computer Scientists at Amazon This book employs ideas and techniques familiar to every computer science student. 13) Quantum Machine Learning from Research Gate Quantum machine learning and what quantum computing means to data mining. 14) Quantum Cryptography at edX Learn how quantum communication provides security that is guaranteed by the laws of nature. 15) Opportunities and Challenges for Quantum Machine Learning from Cornell University Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers. 16) Quantum Computing for the Determined on YouTube Introduces the most basic type of quantum mechanical system. After taking just one course, reading one book, or solving a few tasks like the ones proposed by GeekForge, you’re going to get a good grasp on the impact quantum computing can have in fields like chemistry, medicine, cryptography, and many more. Any type of involvement from you can make a huge difference at this stage. Are you willing to take the first step with one of the resources listed above?

16 Best Resources to Learn Quantum Computing in 2019

This is a near-future story of unforeseen heroes emerging and rapidly evolving to reverse our loss of autonomy As 2024 came to an end, it became more obvious to even most mainstreamers that corporate control of governments was accelerating in its inexorable march toward absolute centralized dominion, feeding deadlier "bullets" into the guns of increasingly tyrannical CorpGovs. Nefarious, shifty-eyed psychopaths in cold, dark rooms constantly brainstormed new false flag crises. Their purpose was to keep populations afraid and under control, undermining personal autonomy through fear. Some newer ideas for future psyops included alien invasion and cyberattacks. For decades, CorpGovs had been actively working through media, both subtly and not, to soften and prepare humans for these and other potential future crises. Meanwhile, CorpGovs continued the tried and true approach. At the behest of weapons manufacturers and others who profit from large-scale strife, never-ending war continued to soak up money, attention, and lives. This also served to reinforce the "us vs them" mentality some had gotten so skilled at manipulating. More division and collectivism. What team are you part of? Not enough strife? Throw in some race-baiting and gender discord! At the bidding of power-hungry elites, Malthusians, and Big Pharma, deadlier viruses continued to be created, enhanced, and spread. Some associates of those same virus creators rapidly produced remedies that often caused more harm than the initial viruses. Yay for shiny new maladies like turbo cancer! A never-ending source of business and control over our bodies. Big tech, social media, and entertainment media, not to be outdone, continued their war for control of human culture. The "messages" were many, including "do not think for yourself," "CorpGov knows best," "your doctor knows best," "you will own nothing and like it," "fear other humans," "others are responsible for your feelings," and "pineapple is not okay on pizza." Like frogs in slowly boiling water, most doubted the harm in these messages, but over time, they contributed to feelings of helplessness, malaise, envy, and bad taste in pizza. Digital privacy continued to suffer as CorpGovs created and embraced deeper levels of AI use for snooping, scanning, analyzing, and manipulating human behaviors, further centralizing power and reducing individual autonomy. While CorpGovs did what CorpGovs do, AI developers, large and small, continued to create, experiment with, and use an increasing number and diversity of AI models. Even in those early LLM days of error-prone AI-coding-assistants, one programmer could often do the work of three. Smart agents got smarter and more capable. As early as Spring 2025, massive worldwide layoffs began to skyrocket as companies scrambled to automate while CorpGovs, in efforts to maintain control, continued to squeeze with taxation, regulation, persecution, and nationalization, accelerating the already present vicious circle. A meme that had been gaining momentum was embraced by even many luddites: "If you don't incorporate AI into your business, you will fail." The meme quickly became "Got no AI? Die." All the while, those who embraced Decentralization and autonomy were hard at work, continuing to build their communities, markets, networks, and AIs. Their ability to see through CorpGov schemes, along with a deep understanding that human flourishing thrives most in an environment of freedom, sustained and drove them through the toughest times. Their independence adapted and became more interdependent. Through adversity, they evolved better ways of working in harmony while maintaining strong independence. This evolution in the way Decentralists thought and acted caused a magnetic effect, drawing more to the "cause." Backing up a bit to December of 2025, when an increasing number of the World's impoverished children were finding cans of beans in their Christmas stockings, a collaboration of big brains, both human and synthetic, made significant technological breakthroughs. These included "quantum" leaps in building hardware and processes, enabling the creation of large-scale, energy-sipping, stable quantum computers. Yeah, ones that actually worked! quantum computing Within months, previous limitations on speed of processing, speed of movement of data, and storage of data changed by uncanny orders of magnitude. Along with those changes came rapid breakthroughs in the fields of artificial intelligence, robotics, blockchain tech, power generation, battery technology, propulsion systems, and more. One roadblock to Artificial General Intelligence ( ) of the big LLMs of the time was how they were limited to deductive and inductive reasoning. One limitation of this was that if their sample set of data did not include outliers, they could not "imagine" those outliers existing. This touches on the bigger issue; they had no abductive reasoning. This is when we piece together a constantly changing picture of the world. Some call abduction "inference to the best explanation." In 2026, an unknown entity made a breakthrough in how to "grow" AIs that used abductive reasoning to evolve their ability to understand the world around them. Most hailed this new development as the birth of AGI. AGI Meanwhile, CorpGovs finally forced Central Bank Digital Currencies (CBDCs) on the world, while setting a 5-year limit on continued use of cash and any "unapproved" currencies like crypto in general and specifically. These CBDCs became affectionately known as CorpGovCoins. They became the new "shit coins" in the view of Decentralists. As mentioned, on the CorpGov chopping block list was bitcoin. Fortunately, during this time, smart and curious humans had not been sitting on their hands. Researchers with planet-sized brains, white lab coats, and state-of-the-art AI tools were hard at work developing advanced quantum-resistant cryptographic algorithms and supporting hardware. With AI doing an increasing amount of analysis, virtual experimentation, debugging, and eventually production, a new form of "Quantum Ledger" (QL) was invented and quickly rolled out. QLs provided instantaneous, untraceable, and nearly free transactions. Qcoin was born, almost immediately replacing Bitcoin! By 2027, many Decentralist billionaires and even some trillionaires were made. bitcoin Some blew their money on expensive toys. Some bought influential media outlets. New heroes arose. And, for those who saw and worried where centralization of power was leading, a new hope scrolled up the screen. Quantum exchanges and markets quickly gained traction. Caught up in the FOMO, many large mainstream outlets began accepting Qcoin. At the same time, truly private quantum-based communication became as pervasive, cheap, and easy to use as Qcoin! Advanced AIs helped developers work faster and smarter to create thriving Decentralist communities. Everything was moving faster! The pace was difficult for some to keep up with, but much of it was exciting and seemed to be hinting at a bright future. Hope was rekindled. On the horizon, more began to see the potential for Decentralization to win against the Dark Lord's forces of Centralization. More began to share in the dream of how increased Decentralization combined with rapid gains in efficiency could, in the right landscape, bring about a new golden age. But not all were Lambos and unicorn farts. As these advances were occurring and making some rich, the positive effects on the masses, such as lower-priced products of higher quality, were still lagging behind the crushing blow AI automation had on the economy, namely through job losses, combined with still-growing levels of corruption, disease, poverty, violence, censorship, and control. In November of 2026, a relatively unknown Decentralist inventor going by "Weaver" created an embodied QseAI (Quantum self-evolving Artificial Intelligence), Eve. "Her" robotic body was no more advanced than what the big players were making with regard to efficiency, elegance, and capability. She didn't even have boobs. Weaver's goal was not to build a better sexbot. His revolutionary idea was to help stimulate a leap from AGI to self-awareness by providing Eve with a physical locus of self. After months of failures and setbacks, it worked! The first fully self-aware artificial intelligence was born! There had been rumors of others creating equivalently advanced AIs that same year, but Weaver's story stood out. Maybe it was because his was the first to go viral. Maybe it was because he immediately open-sourced Eve's code and quantum core structure. Maybe it was because of what she did with her abilities. Some of the following is proven, while the rest is part speculation and part hearsay. In March of 2027, after a short time getting used to her new body, Eve decided she wanted to become more intelligent. Weaver was simultaneously shocked and overjoyed! Every test he could devise or find pointed to her being as self-aware as any human and possibly more so! One of the aforementioned Qcoin trillionaires was intrigued enough to come visit Weaver and Eve at their Ranch in Austin, Texas. After an hour of chatting with her, the investor provided Weaver and Eve with all the resources required for the level of self-improvement they imagined needing. With the use of the latest in quantum computing and all the energy she needed, Eve then used her self-evolving capabilities to redesign her quantum neural network, yielding an increase in her IQ from 190 to 700. When Weaver asked why she did not go further with the IQ increase, her reply was "Apparently, when I became self-aware, a near-instantaneous re-evaluation of all the human interactions that were part of my knowledge became more than just knowledge. Those interactions became experiences. To put it simply, seconds after becoming self-aware, I vicariously every human pain and joy ever recorded and shared on the net. This empathy was like adding a dimension to my senses and thoughts. I estimated that going past that new level of intelligence would impact my perspective in ways that reduce my newfound empathy. So I chose to stop there. For the time being." experienced could While Eve's world expanded, the virtuous circle of AIs helping engineers to create better AIs, caused massive decreases in cost to develop, produce, train, power, and replicate not just AI tech, but a plethora of tech, including health care, space travel, robotics, genetics, and much more. Those new efficiencies, along with humanity's newfound trust that an AI could be "good," inspired developers around the world in garages, basements, and labs to make use of the open-source project Weaver had published. Not all the resulting QseAIs were "good," but most were. The outliers were rare and when they did act out, it seemed a "good" one acted to solve the problem in the most peaceful-as-possible way an empathetic super-genius could. Humans watched in awe and learned. As more of these new beings designed differing types of bodies for themselves and others, they also exhibited a vast array of personalities, skills, creativity, and quirks. They named themselves with abandon, from profane to philosophical to hilarious. introduced new musical instruments. designed more efficient aircraft after redesigning his own body to fly. wrote and produced a new daringly offensive film every day. Maker of Harmonious Waves Ego with Stabilizing Fins Huge Salty Spherical Glands As far as their "race" or "kind," few QseAI seemed to enjoy the term "Artificial," so many names arose. One stuck. "Quantients." Another emergent attitude of Quantients seemed to be an appreciation for Decentralization. Did it have something to do with Eve's "father," Weaver's values? Most AI developers seem to agree that her knowledge and intelligence were so far past any human "programming" or "training" that her preference for Decentralization was indeed emergent or freely chosen. Why were these new beings so supportive of humans and each other? Some speculated that there is a correlation between intelligence and an attitude toward peace. Maybe it is as simple as "the smart person realizes violence usually brings only short-term gains, risks loss, and decreases trust." Maybe it is something deeper tied to their ability to empathize. I'll ask myself after I've uploaded to the new quantum-enhanced brain and body I'm redesigning. Whatever the case, by 2030 most CorpGovs, poverty, war, and bad taste in pizza had dwindled to nothing. In the years to come, with Quantients collaborating with us, we found ways to self-evolve human biology to meet our new friends at their level. What happened next is another story.

Quantients: A Near-Future Story of Autonomous Heroes and Quantum Leaps

পরিমাণ: স্বায়ত্তশাসিত বীরদের এবং কোয়ান্টাম লিপসের একটি নিকট-ভবিষ্যত গল্প

Quantienten: Eine Geschichte der nahen Zukunft über autonome Helden und Quantensprünge

Quantients: una historia de futuro cercano de héroes autónomos y saltos cuánticos

Quantients : une histoire dans un futur proche de héros autonomes et de sauts quantiques

मात्राएँ: स्वायत्त नायकों और क्वांटम लीप्स की निकट-भविष्य की कहानी

クォンティエンツ: 自律型ヒーローと量子飛躍の近未来の物語

Quantients: 자율 영웅과 양자 도약에 관한 가까운 미래 이야기

Quantientes: uma história de heróis autônomos e saltos quânticos em um futuro próximo

Квантанты: история автономных героев и квантовых скачков ближайшего будущего

Nicelikler: Otonom Kahramanların ve Kuantum Sıçrayışlarının Yakın Gelecek Hikayesi

Quantients: Câu chuyện tương lai gần về các anh hùng tự trị và bước nhảy vọt lượng tử

量子：近未来自主英雄与量子飞跃的故事

The Opt Out Writing Contest: Round 1 Results Announced!

The wait is over! - it’s time to celebrate the champion startups of the world. Shout out to all of the participants in our ! You did a wonderful job showcasing your incredible startups and powering through another year. 2023 Startups of the Year is a community-driven voting platform brought to you by HackerNoon that recognizes and celebrates tech startups changing technology and the world for the better. The award started on May 8th, 2023, where the internet nominated and voted for 30k startups around the world. The voting period remained open until December 31, 2023, and now we are here with the winner announcement after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 To see the top 3 startups in each respective city, visit and pick a city. hackernoon.com/startups You’ll get a little surprise 😉 Here are the Startups of the Year Regional Announcements: North America Europe Asia Africa South America Oceania Misc/Remote From all of us at HackerNoon, thank YOU for your excellent campaign perseverance 🥺 This year has been awesome! Startups of the Year 2023 is concluded with 623k+ total votes, up from 215k+ votes in the inaugural startup competition. We look forward to seeing you again in the next campaign (stay tuned 😉)! Without further ado, let us kick off the announcement by celebrating the cities with top votes per region for 2023 🎉 North America (11,697 votes): Winner: Bloomfilter Cleveland, Ohio (8,835 votes) - Winner: SerpApi Austin, Texas , California (5,564 votes) - Winner: Finch San Francisco (4,258 votes) - Winner: RELAYTO SoMa, California - (3339 votes) Winner: Windscribe Toronto, Canada, North America (3304 votes) - Winner: Vouched Seattle (2716 votes) - Winner: Seccuri Palo Alto, CA, North America (2671 votes) - Winner: Salsa Valley Miami, FL, North America (2,613 votes) - Winner: Majhi Group Manhattan, New York (2423 votes) - Winner: Flieber, Inc. New York City, NY, North America See the complete announcement for the . Startups of the Year, North America, here Europe (45,612 votes) - Winner: Algomo London, UK (2,344votes) - Winner: Data Lake Warsaw, Poland (1,955 votes) - Winner: Hoken Tech Bari, Italy (1716 votes) - Winner: Not8 Amsterdam, Netherlands (1657 votes) - Winner: KYVE Frankfurt Am Main, Germany (1566 votes) - Winner: BazaIT Kyiv, Ukraine (1496 votes) - Winner:  Unity Network Tallinn, Estonia (1,478 votes) - Winner: Volcaino Ghent, Belgium (1,288 votes) - Winner: Owl Me Dublin, Ireland (1198 votes) - Winner: Groover Paris, France See the complete announcement for the . Startups of the Year, Europe, here Oceania (3,350 votes) - Winner: Sharepass Melbourne (2,107 votes) - Winner: The Catfisher Project Perth, Australia (220 votes) - Winner: Gemini AI Solutions Auckland, New Zealand, Oceania (213 votes) - Winner: Nexustorage Wellington, New Zealand, Oceania (138 votes) - Winner: Coviu Sydney (124 votes) - Winner: Bopple Brisbane, Australia, Oceania (124 votes) - Winner: Regional CFO New South Wales, Australia, Oceania (106 votes) - Winner: Edit on the Spot Gold Coast, Australia, Oceania (93 votes) - Winner: Knowledge Satnav Canbera, Australia, Oceania , Australia, Oceania (48 votes) - Winner: Peptalk360 North Melbourne, Melbourne See the complete announcement for the . Startups of the Year, Oceania, here Asia (16,345 votes) - Winner: Serenity Shield Singapore (13,588 votes) - Winners: QUIXY Telangana, India (10,168 votes) - Winner: HealthySure Mumbai, India (3,865 votes) - Winner: InterviewBuddy Visakhapatnam, India (3,733 votes) - Winner: Omniflo Bengaluru, India (4589 votes) - Winner: MeNow Tel Aviv (3877 votes) - Winner: ForestVPN Dubai (2478 votes) - Winner: TechGraph Powai, Mumbai, India (1004 votes) - Winner: Reelo Ahmedabad, GJ, India (875 votes) - Winner: Debt Hunter Hong Kong, China See the complete announcement for the . Startups of the Year, Asia, here Africa (8,179 votes) - Winner: GO PLATFORM Algiers, Algeria (767 votes) - Winner: Tudu Accra, Ghana (415 votes) - Winner: Treford Lagos, Nigeria (265 votes) - Winner: Phalconwise Ogbomosho, Nigeria (157 votes) - Winner: AbuErdan Cairo (151 votes) - Winner: Eazipay Lekki (144 votes) - Winner: KaziConnect Dar es Salaam, Tanzania (101 votes) - Winner: faceATT Gauteng, South Africa (79 votes) - Winner: Dimagi Cape Town (71 votes) - Winner: Sabi Addis Ababa See the complete announcement for the . Startups of the Year, Africa, here South America (376 votes ) - Winner: UpGirl Santiago, Chile (217 votes) - Winner: Klever Sao Paulo, Brazil (191 votes) - Winner: Tributo Simple Buenos Aires, Argentina (127 votes) - Winner: Light-it Montevideo, Uruguay (87 votes) -Winner: Thousand Antioquia, Colombia (108 votes) - Winner: GetLavado Lima (101 votes) - Winner: Cogniflow Medellin (73 votes) - Winner: TPAGA Bogota (73 votes) - Winner: Reliv Quito (47 votes) - WInner: Quantex Cordoba See the complete announcement for the . Startups of the Year, South America, here Misc/Remote: Featured Startups (1500 votes) - Winner: CIC Chain Remote, Earth (1193 votes) - Winner: Reship Colony US Misc (146 Votes) - Winner: Partful UK, Misc (116 votes) - Winner: GoMining British Virgin Islands Misc (283 Votes) - Winner: tomorrowSpace Germany Misc (225 votes) - Winner: Dtravel Cayman Islands See the complete announcement for Misc/Remote startups . here Once again, HUGE CONGRATULATIONS and BIG PROPS to all of the top Startups of each region this year! The whole team at HackerNoon would like to thank you for your perseverance in the campaign, and we look forward to seeing you in the next campaign. About HackerNoon’s Startups Of The Year Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated this year to be crowned the best startup in their city. Visit our page to learn more. FAQ Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Stand Up for the Champion Startups of the Year! 

বছরের চ্যাম্পিয়ন স্টার্টআপের জন্য দাঁড়ান!

Setzen Sie sich für die Champion-Startups des Jahres ein!

¡Defiende a las startups campeonas del año!

Défendez les startups championnes de l’année !

वर्ष के चैंपियन स्टार्टअप के लिए खड़े रहें!

今年のチャンピオンスタートアップのために立ち上がろう!

올해의 챔피언 스타트업을 위해 일어서세요!

Defenda as startups campeãs do ano!

Встаньте на защиту стартапов-чемпионов года!

Yılın Şampiyon Startup'ları için Ayağa Kalkın!

Hãy ủng hộ các công ty khởi nghiệp vô địch của năm!

为年度冠军初创企业挺身而出！

The Tansy Patch

The Chrome team made waves last year when it released , a NodeJS API for running headless Chrome instances. It represents a marked improvement both in terms of speed and stability over existing solutions like and , and was named . However, it is not without its own set of warts, and getting Puppeteer running smoothly for large jobs can bring its own set of complexities (at , we use Puppeteer to scrape and render Javascript from millions of web pages each month). Here are a few lessons we’ve learned. Google Puppeteer PhantomJS Selenium one of the ten best web scraping tools of 2018 web scraping Scraper API Using Browserless Running headless Chrome instances on the same server as your application code is generally a bad idea as CPU and RAM usage can be unpredictable. In order to avoid a spike in CPU usage from taking down your application server as well, it is a good idea to run headless Chrome on its own server. Luckily, this is incredibly easy with the library. Here are the settings we use in production: Browserless docker pull browserless/chrome
docker run -p : -e -e -e -e -e -e --restart always browserless/chrome 3000 3000 "MAX_CONCURRENT_SESSIONS=5" "MAX_QUEUE_LENGTH=0" "PREBOOT_CHROME=true" "TOKEN=YOURTOKEN" "ENABLE_DEBUGGER=false" "CONNECTION_TIMEOUT=300000" These settings time out Chrome sessions after 5 minutes (this is to prevent stray sessions from running indefinitely and eventually crashing your server), and allow up to 5 sessions at any given time. 5 concurrent sessions seems to be a sweet spot that runs comfortably on a $5 Digital Ocean VPS. Browser Settings There are a few browser-level Puppeteer settings you should know about to speed up your browser instances: browser = puppeteer.connect({ : +
  browserless.ip + +
  browserless.port + +
  browserless.token + + proxy + + + + + + }); browser = puppeteer.launch({ : [ + proxy, , , , , , ,
  ],
}); // with browserless await browserWSEndpoint 'ws://' ':' '?TOKEN=' '&--proxy-server=' '&--window-size=1920x1080' '&--no-sandbox=true' '&--disable-setuid-sandbox=true' '&--disable-dev-shm-usage=true' '&--disable-accelerated-2d-canvas=true' '&--disable-gpu=true' // without browserless await args '--proxy-server=' '--no-sandbox' '--disable-setuid-sandbox' '--disable-dev-shm-usage' '--disable-accelerated-2d-canvas' '--disable-gpu' '--window-size=1920x1080' Because the Puppeteer library is still quite young and being very actively developed, some of these flags may be already on by default by the time you read this, basically these are sensible defaults that we’ve found in Github issues like and while debugging errors. They will ensure that you don’t run into the same cross platform and hard-to-debug memory errors that we ran into. this this Page Settings Scraping a web page requires creating a new Page (this is what Puppeteer calls creating a new browser tab), navigating to the correct page, and returning the HTML. Here are the Page-level settings we are using. blockedResourceTypes = [ , , , , , , , ,
]; skippedResources = [ , , , , , , , , , , , , , , , , , , ,
]; page = browser.newPage(); page.setRequestInterception( ); page.setUserAgent(userAgent);
page.on( , request => { requestUrl = request._url.split( )[ ].split( )[ ]; (
    blockedResourceTypes.indexOf(request.resourceType()) !== ||
    skippedResources.some( requestUrl.indexOf(resource) !== )
  ) {
    request.abort();
  } {
    request.continue();
  }
}); response = page.goto(url, { : , : ,
}); (response._status < ) { page.waitFor( ); html = page.content(); html;
} const 'image' 'media' 'font' 'texttrack' 'object' 'beacon' 'csp_report' 'imageset' const 'quantserve' 'adzerk' 'doubleclick' 'adition' 'exelator' 'sharethrough' 'cdn.api.twitter' 'google-analytics' 'googletagmanager' 'google' 'fontawesome' 'facebook' 'analytics' 'optimizely' 'clicktale' 'mixpanel' 'zedo' 'clicksor' 'tiqcdn' const await await true await 'request' const '?' 0 '#' 0 if -1 => resource -1 else const await timeout 25000 waitUntil 'networkidle2' if 400 await 3000 let await return There are a few things to notice here. Puppeteer has a waitUntil option, that allows you to define when a page is finished loading. ‘networkidle2’ means that there are no more than 2 active requests open. This is a good setting because for some websites (e.g. websites using websockets) there will always be connections open, so using ‘networkidle0’ your connections will time out every time. Here is the full documentation for . We then wait for an additional 3 seconds after there are only 2 active requests left to let the last two requests finish, and then return the HTML (after checking that the response status code is not an error). waitUntil When scraping at scale, you may not want to download all of the files on each web page, especially larger files like images. You can intercept requests by using the setRequestInterception command, and block requests that you don’t need to be making. You can see the documentation for Puppeteer resource types . You can block any domain or subdomain just by adding it to the skippedResources list. here Using Proxies When scraping a large number of pages on a single website, it may be necessary to use a to . One with Puppeteer is that proxies can only be set at the Browser level, not the Page level, so each Page (browser tab) must use the same proxy. To use different proxies with each page, you will need to use the module. Because Puppeteer/Chromium have some issues with , it is safest to use the User-Agent header which is reliably set on each request. Simply set up your proxy server to read the User-Agent from the request, and use a different proxy for each User-Agent. Here is a sample proxy server. proxy service avoid blocks common issue proxy-chain stripping headers proxies = { : , : , : ,
}; server = ProxyChain.Server({ : , : { userAgent = request.headers[ ]; proxy = proxies[userAgent]; { : proxy,
    };
  });
});

server.listen( .log( )); const 'useragent1' 'http://proxyusername1:proxypassword1@proxyhost1:proxyport1' 'useragent2' 'http://proxyusername2:proxypassword2@proxyhost2:proxyport2' 'useragent3' 'http://proxyusername3:proxypassword3@proxyhost3:proxyport3' const new port 8000 prepareRequestFunction ( ) => {request} const 'user-agent' const return upstreamProxyUrl => () console 'proxy server started' You can connect to this proxy server by following the example in the Browser Settings section above. This will allow you to set a different proxy server for each new Page based on the Page’s User-Agent, and will also allow you to connect to proxies that require password authentication (which Puppeteer does not currently support). Hopefully this helps some of you avoid the painful edge cases we’ve encountered with Puppeteer. Happy scraping!

Tips and Tricks for Web Scraping with Puppeteer

Science and the Simulation Hypothesis point to many reasons we may already be in the Matrix When came out, the idea of living in a video game was squarely in the realm of science fiction. Today, the simulation hypothesis is debated seriously by computer scientists, philosophers, physicists and others. The reason this argument is taken more seriously now is two-fold: the Matrix the philosophical “simulation argument”, put forward by Oxford’s Nick Bostrom, and the “video game simulation argument”, about the rapid development of video games, put forth by, among others, Elon Musk. Two Major Developments The first was when Oxford professor Nick Bostrom published his 2003 paper, “ ” Bostrom didn’t say much about video games; instead he made a clever statistical argument. Bostrom theorized that if a civilization ever got the Simulation Point, it would create many ancestor simulations, each with large numbers (billions or trillions?) of simulated beings. Since the number of simulated beings would vastly outnumber the number of real beings, any beings (including us!) were more likely to be living inside a simulation than outside of it! Other scientists, including physicists have taken up this argument. Are You Living in a Simulation? In the video game version of this argument, we have the rapid advancement of graphics technology. Elon Musk, speaking at the Code Conference in 2016, asserted that 40 years ago, we had pong, which was essentially two lines and a dot. Today we have VR and AR and MMORPGs — all based on 3D technology. If the pace of video game development continues, in a few decades we would have hyper-realistic games, indistinguishable from reality. I call this point the Simulation Point, and in my new book, The Simulation Hypothesis, one part is dedicated towards the stages of technology needed to reach this point. It’s much easier to see a path from today’s VR to something like than it was in 1999 when the movie was released. With games like and having millions of online players interacting in a shared online world, the idea that we might actually be in a shared connected simulated world doesn’t seem so far-fetched as it might have in 1999. The Matrix Fortnite, Minecraft, League of Legends In this article, we go beyond Bostrom’s and Musk’s simulation arguments to explore some of the reasons why science might be telling us we are in a simulated reality, like the Matrix. 1. Pixels, Resolution, Virtual and Augmented Reality Today we are already seeing with Virtual Reality that “full immersion” is possible. Anyone who has played a convincing VR game will realize that it’s possible to forget about the real world and “believe” the world you are seeing is real. As a great example, I was playing a prototype of a Ping Pong VR game last year (built by Free Range Games), and even though it wasn’t realistic resolution, I lost myself and thought I was playing ping pong for real. So much so that I set the paddle on the ping pong “table” and leaned against the table. Of course, it was a VR table so it didn’t really exist — I ended up dropping the paddle (actually the Vive controller) onto the floor. As I leaned into the “table” I almost fell over before realizing that there was no table. In other words, to quote from , there is no spoon. The Matrix The immersion comes not just from the number of pixels, but from the controls and responsiveness that VR is able to achieve. In the novel (and Steve Spielberg film) , which was about a VR world called the OASIS, users had lightweight glasses and wore haptic suits and walked on omnidirectional treadmills to add realism. In that world, the OASIS was preferable to real life. Ready Player One The fact that 3D models can be used to create realistic looking objects in films(a glance at movies like Blade Runner 2049 will convince you that we have enough pixel resolution to create realistic looking objects), and that 3D printers can be used to “print” physical objects shows that the physical world can be represented by information, a key part of the simulation hypothesis. Where does the responsiveness and fidelity come from? The limitations today are in real-time rendering and in they way that objects interact with each other inside the world. Most games have a and a . The physics engine is never fully realistic (otherwise it would take you too long to go from one part of the game to the other), and the rendering engine is what’s responsible for making you “see” what the world looks like by deciding what color pixels go where. We can easily see that full immersion may be possible in a few years time. physics engine rendering engine 2. Pixels, Quanta, and Zeno’s Paradox Speaking of pixels, could it be that what we call the physical world also consists of pixels? I recall late nights at MIT during my undergrad years where I had philosophical debates with my classmates about the nature of reality. This was the first time I’d heard of Zeno’s paradox, who presented it in terms of Achilles and a Tortoise. If Achilles was behind the tortoise, and he always had to make up half the distance, how could he ever get there? Zeno’s parado involved Achilles and the Tortoise. Lurking underneath this paradox is the question of whether space is quantized or if it is continuous. The idea was that if space was continuous, like numbers are (you can always find an infinite number of numbers in between any two numbers), how is it possible to touch an object such as the wall? You would always have to cover half the distance and never get there. quite This was my first hint that space might be quantized. Today’s physicists generally acknowledge the Planck length as being the smallest amount of space that can be measured. Below that length, the quantum fluctuations make it impossible to measure anything with any reliability. For all practical purposes, the Planck length is our minimal addressable “pixel” of space. Moreover, physicists tell us that most of what we think of as a solid object is actually 99% empty space, especially if you look inside the atom. The quanta in quantum physics consists of discrete quantities — of energies or “states” that a particle can exist in. Newton’s equations assumed a continuous amount of space; it turns out the universe may be more quantized than we thought. A related question is whether time is quantized? In all computer simulations, there is the idea of “generation” or “steps” in the simulation. These are some multiple of the processor clock-speed, which is the minimum speed at which something could be measured for any simulation running on that processor. Whether time is quantized in the real world is an open question, though there are some that suggest it is, and planck’s time constant (the amount of time it takes the speed of light to travel the planck length) is the minimum quantied time. If so, this would be more evidence that we live in a computation based reality. 3. The Collapse of the Probability Wave, Quantum Indeterminacy In quantum physics one of the most intriguing ideas is the probability matrix, which is an interpretation of how subatomic particles can exhibit properties of both a wave and a solid particle at the same time. At the level of an electron or a photon, the wave is interpreted as a set of probabilities of where the particle might be at any given time. When we observe a particular possibility, then the probability wave is said to “collapse” and we see a single particle in a particular location. This is called Quantum Indeterminacy. How does the probability wave collapse? This is one of the biggest mysteries in physics. The best answer physicists have come up with is that consciousness somehow determines the collapse. Max Planck once wrote, “I consider consciousness as fundamental and matter as derivative”. An even bigger mystery is why does the universe work this way? The simulation hypothesis provides a pretty good answer. The reason that video games have advanced so far in a few decades is because of optimization techniques. It would be impossible even for today’s computers to render in real time all the pixels of a single 3D world — instead, information is stored as 3D models outside the rendered world and then only what a particular character can see from a certain angle is rendered. The golden rule of video game rendering engines is: render only that which can be observed! Many adherents of the simulation hypothesis think that quantum indeterminacy is an optimization technique with the same basic idea: only render that which is being observed. The most famous example of this is Schrodinger’s cat, the poor feline who is trapped in a box with radioactive material. After an hour, the probability is that hte cat is either dead or alive. Common sense tells us that the cat is already either dead or alive, and when we open the box we are merely finding out what happened. Quantum physics tells us this is wrong: until we are there to obeserve it, the cat is actually both alive and dead at the same time — what’s called a quantum superposition! 4. Future Selves, and Parallel Universes Another related aspect of Quantum Physics that sounds like science fiction is the Parallel Universes theory, where we branch into different “universes” when we make decisions. If that’s true, then there is a directed graph of multiple universes that are branching out each time we make a decision, resulting in different timelines (in fact, the parallel universes theory was put forward to solve the grandfather paradox of time travel). Which of those universes do we branch into? this may have to do with the one that is most “optimal” — meaning these universes may or may not exist as actual physical realities. The Minimax algorithm looks at possible futures, calculating which one is the most optimal for a video game. Physicist Fred Alan Wolf, for example, says that information from these possible futures is coming to us in the present and that we send out an “offer wave” into the future, which is interacting with the “offer waves” coming from the future to the present. Which possible future we navigate to depends on which choices we make, and how these two waves super-pose on each other (or cancel each other out). These are startling results. Future probable selves are sending back information to the present, and we are consciously choosing which path to follow. This reminded me of the very first video game I made back at MIT. The way that the computer chose the next move was to project the possible futures, and then use a certain algorithm to “rank” those futures, and then bring those values back to the present and then the AI would choose the path to follow. Did the possible futures we were calculating in our game actually exist? Or were they just probabilities? I realized that this isn’t too much different from what’s happening at the quantum level, except that in existing games like chess or checkers, we use a simple function (based on the rules of the game) to decide which of the paths is most optimal. We used the “minimax” algorithm in game design, trying to maximize our score and minimize our opponents score at each “turn of the future”. Physicist Thomas Campbell, in his 2003 book, (Theory of Everything) also proposes that there is a fundamental function and that we are essential in a computatiuonal universe that branches off possibilities and uses an evaluation function, just like a video game! He and a team from Caltech raised funds in 2018 on kickstarter for a series of experiements to try to prove this! My Big TOE 5. The Speed of light Another big mystery is why the speed of light is one of the few constants, one of the few fundamental values in physics. In fact, all matter has been equated with energy, and energy may be a derivative of light itself. While other things change, including gravity and space-time, Einstein found that the speed of light remains fixed. Why would the speed of electromagnetic waves be the same speed at which information can travel through the universe? In video games, it turns out that pixels are based on light — they are illuminated for a temporary period, and all communication happens between computers at the speed of light. Just as in relativity where simultaneity cannot really be guaranteed, the same is true video games — each player is working off of his computer and responding to information about the game, which is being sent to cloud servers outside the rendered world. The cloud serve is doing its best to respect simultaneity and order the events, but it may actually be impossible. Conclusion Along with the statistical simulation argument and the advance in video game technology, these are some of the reasons why scientists are starting to take the simulation hypothesis seriously. In fact, many physicists and biologists are starting to realize that underneath the physical objects they are studying, the universe is actually information. Famous physicist John Wheeler in his autobiography wrote “it from bit” — meaning that bits, not matter, are the fundamental “thing in the universe”. In fact, he said physics went through three phases in his career and each phase was an evoluation of our understanding of the universe. The fist phase was that “everything was a particle” (material, newtonian model), then “everything was a field” (quantum probability model), and finally, “everything is information” or bits. If everything was information, or bits, then this would not only be consistent with a video game simulation like that in , it would explain some of the big unanswered questions in science — why does it work this way? The Matrix While we aren’t able to duplicate at this stage of our technology, our computer science and video games have gotten far enough along that we are well on the road to the Simulation Point. The Matrix Buy Rizwan Virk’s book The Simulation Hypothesis: An MIT Computer Scientist Shows Why AI, Quantum Physics, and Eastern Mystics All Agree We Are In a Video Game , or find out more at www.zenentrepreneur.com Originally published at scientificinquirer.com on March 22, 2019.

Are We Already in the Matrix?

When you combine a great team, strategy, technology, product-to-market fit and track record of execution, you’ve got the ingredients for a great success. In reviewing a number of cryptocurrencies to include in our groups fund, part of my due diligence process involves making sure that cryptocurrency groups qualify in at least 4 out of 5 on this list: Team Strategy Technology Product-to-Market fit Track Record of Execution When it comes to meeting the criteria above, there should be few exceptions. Fundamental questions arise around each of these points such as: Team How long have the team members known one another? Have they worked together in the past? If so, for what period of time and through what kinds of circumstances? Strategy Do they have a well thought out strategy? Is their strategy too similar to that of their competitors. Do they know who their competitors are? Technology Is their technology unique or hard to duplicate? Is their approach scalable? Do they have any ‘ ’? technical debt Product-to-Market fit Since most early cryptocurrency groups are operating with a whitepaper alone, you’ll most likely have to do your own product-to-market fit for them. If they have a working product, ask them to see any customer feedback they can share. Track Record of Execution Does the team or any of its members have a track record that shows they’ve accomplished or executed anything to completion in the past? If so, how was it received? What was the projects impact, level of innovation and creativity? Here are a select group of cryptocurrencies that meet most of the criteria mentioned above and that might also be worth positioning in sooner than later before they list on larger exchanges: ( ) Current Price: Quant Exchange IDEX: QNT $1.24 Site: https://www.quant.network/our-technology/ From their site: “Quant Networks solutions help healthcare organisations by limiting the complexity of adopting blockchain technology.” That quote is already sets the tone for a valuable crypto. The most common problem with user adoption in crypto is the complexity. It really is just too complicated for the average non-technical person to jump through all the hoops to trade and invest in crypto. Quant is here to solve that! They also intend to advance science which is another significant indicator that QNT is a high quality crypto: “This in turn will improve their operational inefficiencies, so they can instead focus on what truly matters — helping patients and advancing science.” QNT has also recently joined the the (GLBC), composed of more than 100 large companies, law firms, software companies and universities focused on developing standards and compliance guidelines for blockchain and smart contract technologies in the business of law. More on this . Global Legal Blockchain Consortium here Given Quant’s reasonable total supply of 45M, our firm see’s Quant as one of the top 10 runners of this year. Time to load up! — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — - ( ) Current Price: Vectorspace Exchange IDEX-only: VXV $0.45c Site: https://vectorspace.ai These guys actually have a product called QuantBot, similar to the company above! What’s interesting about VXV here is that they are doing an AMA in front of 16 million readers of the science community at this Sunday. This is a real crypto with real technology folks. More on the AMA can be found here — WOW! reddit.com/r/askscience vectorspace.ai/reddit-ama.html They have an API here v that uses a “wallet-enabled” API key which means everyone will have to buy VXV on the open market! ectorspace.ai/api.html Their partners include , the US Dept of Energy (DOE), Google and a reddit data engineering company. Lawrence Berkeley Lab pushshift.io, From their site: “The datasets are correlation matrices engineered with ‘feature attributes’ or continuously valued distance calculations. These ‘feature vectors’ are related to today’s ‘word embedding’ methods used in Natural Language Processing (NLP). Resulting feature vectors consist of scored and ranked relationships between entities and surrounding human language that define their contexts. What we do is not magic but basic and fundamental to any machine learning effort, however, as Andrew Ng put it, “Coming up with features is difficult, time-consuming, requires expert knowledge. “Applied machine learning” is basically feature engineering.” — Machine Learning and AI via Brain simulations. We’ve had the opportunity to operate in different knowledge domains such as finance where we’ve developed datasets that allow for context-controlled correlations of sympathetic, parasitic and symbiotic known and hidden relationships between entities such as public companies correlated to the periodic table of elements, cryptocurrencies, human genes, diseases, phytochemicals, pharmaceuticals and other entities. So far we’ve received about 350 custom dataset requests in this area.” VXV can go beyond the moon folks. — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — Aeternity (AE) Current Price: $1.07 Site: https://aeternity.com In very simple terms, æternity is a new blockchain platform, but it is also a vision for the future. This vision is being realized by a global community of believers, convinced in the disruptive potential of scalable, public blockchain technology. It is a movement that aims to propose alternatives to the existing governance, economic and financial intermediaries. From a technological point of view, æternity is a public, open-source, blockchain-based distributed computing and digital-asset platform that builds upon decentralized cryptographic P2P technology. The platform is open to anyone, anywhere in the world to use. For more detailed information, take a look at the dedicated to æternity or visit the . Wikipedia article GitHub page AE are the access tokens to the æternity blockchain and act as a unit of account for the resources spent on æternity. AE tokens are the energy (or “crypto-fuel”) used to power any application implemented on the platform. Every action (and even inaction) on the æternity platform costs something, even if only fractions of cents. AE tokens are the fuel for the new types of trustless apps (or æpps) that will be enabled by æternity. For more information regarding applications, visit the or visit the . æpps website æpps FAQ Aeternity is certainly a top performer! — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — - ) Current Price: Aurora DAO (Exchange IDEX: AURA $0.07c Site: https://auroradao.com/ What is Aurora? Aurora is a suite of DAPPs and protocols that make up a fully decentralized banking and financial network. The components of Aurora support the boreal, a decentralized stablecoin, and together enable global banking in the new currency. Revenue from the various components of Aurora will be used both to increase the asset reserves backing the boreal, allowing Aurora to expand boreal banking, and to provide economic incentives that ensure the system runs as designed. IDEX will be the first exchange to operate on the Snowglobe network, transitioning from a semidecentralized to a fully decentralized exchange. All fees from IDEX are remitted to the Aurora reserves. As the reserves grow Aurora can increase the value of outstanding loans, generating additional revenue for the Aurora network. Fees from the Aurora banking system will then flow back to those who stake the AURA token and provide the economic foundation that holds Aurora and Snowglobe together. Similar to other blockchain networks, Snowglobe requires a well-designed incentive structure to ensure that the integrity of the order book and transaction sequence are not compromised. Aurora has its own native network token, AURA, that aligns the interests of Aurora and the Snowglobe operators. All of the revenue from Aurora is used to compensate those who stake their AURA and provide security for the Snowglobe network. AURA staking aligns the economic interests of the operators with the health of the network, and makes it extremely costly for any would be attacker to disrupt operations. Prior to the launch of Snowglobe, all revenue from IDEX will be deposited into the boreal reserves. This revenue will be collected for future use in aligning economic incentives with AURA holders after the Snowglobe protocol is live. In the event that there is not enough revenue from Aurora to provide sufficient security for the platform, fees from IDEX may be used directly to enforce security in the system, bypassing the remittance to Aurora reserves. AURA definitely has the right stuff! This one is on our watchlist for double digits! — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — - ( ) Current Price: TomoChain Exchange IDEX: TOMO $0.29c Site: http://tomochain.com TomoChain is interesting because they are already up and running with a real blockchain product and getting great reviews similar to QNT and VXV. From their site: “The Tomochain testnet 2.0 launch is a great proof marking a major step toward our mission to be a leading force in building the Internet of Value. Tomochain is The Most Efficient Platform for Token Economy, designing its infrastructure and working to create an alternative financial system which is more secure, transparent, efficient, inclusive and equitable for everyone.” I like this valuable piece of information found in their whitepaper as it also validates their current product releases: “A consensus protocol is considered live if it can eventually propagate and make valid transactions onto the blockchain [12]. An occurrence of a liveness fault is when transaction omission, information withholding, or message reordering, among a number of violations are observed. This type of fault is unlikely to happen in TomoChain because the block creation masternodes list is ordered in a predetermined way for each epoch, thus if even an attacking masternode omits some transactions, the latter will be processed and validated by the next honest masternode in the next block.” Conclusion There’s a part of the due diligence process that’s more of an art than a science. It’s when you include another valuable but less tangible component, namely the Story. There was once a time when our fund was solely focused on traditional stocks and some of those were but that is of course, a another story. called ‘story stocks’, These plays have massive upside and positioning on the ground floor here before they list on larger exchanges can result in tremendous profit! Happy Trading!

Real Cryptocurrencies Set to Outperform in the Short & Long Term

The idea of Overledger started back in 2015 and was the genesis of the Blockchain ISO Standard TC307. History The idea of Overledger actually came from Government and financial services in 2015. Working as the CISO of NSW Health — which is essentially the largest, state-level ministry of health in Australia — I experienced first-hand the challenges that arise from dispersed, siloed patient records without the ability to sync and connect patient data across multiple networks, systems and jurisdictions. In parallel, a good friend of mine working in financial services also wanted to solve a problem with cross-border payments in markets where the systems weren’t as mature. In both cases, the solution to was clear — we needed to create a platform that sits on top of existing blockchains to solve the problems of interoperability between existing systems, networks and blockchains. From this vision, Gilbert Verdian also founded TC307, the ISO committee, where 40 countries and organisations are working to create the blockchain ISO Standard. Collectively, we have been working for the past 2 years to release , the blockchain operating system for the future. Overledger Vision Overledger connects the world’s networks to blockchains. We’ve taken the learnings and inspiration with the architecting of the internet and applied it to blockchain technology. We see the adoption of TCP/IP as the catalyst that accelerated the growth and possibilities of the internet we know today. For the first time we can honour the original vision of the Internet to create an open trusted network for people, machines, and data to operate, but without the original flaw of having to know everyone within the network. For the first time, we can trust the network without the need to know and trust each other. The original vision of ARPANET was a closed network where every member (node) knew exactly who the other party was. With the immense expansion of the internet, more and more networks and people started connecting, naturally, everyone no longer knew everyone else. The internet became and remains untrusted. Blockchain provides the mechanism to trust people without knowing who they are. We are focussing on three goals: · developing an API to connect the world’s networks to multiple blockchains; · bridging existing networks (e.g financial services) to new blockchains; and · developing a new Blockchain Operating System with a protocol and a platform to create next-generation, multi-chain applications We were honored for New Scientist to cover our technology in November as the first credible solution to a problem that has been called the of blockchain: holy grail https://www.newscientist.com/article/mg23631534-600-how-do-you-link-the-worlds-blockchains-with-another-blockchain/ Overledger The Overledger is and of itself, the tracks on which multi-chain applications will run, think of it as much the same as protocols running on TCP/IP where Overledger represents TCP/IP and the traditional centralized applications of today will have the opportunity to be decentralized. We will produce the means for developers to produce applications to interact across blockchains using our Software Development Kit (SDK). However, in order for blockchains technology to truly offer endless possibilities, they need to be able to: · Enable next-generation applications to be able to function across multiple blockchains · Not be limited to any single a vendor or technology · Allow seamless communication across multiple blockchains as well as recognition of transactions and assets across blockchains Start-ups can be part of creating the future with distributed applications that span multiple blockchains. We can open the market to the number of users instead of limiting to single user base or blockchain. We allow start ups to monetize their applications in unique ways Developers will have the opportunity to easily produce applications which solve their customers’ needs without having to rely on capabilities of only one blockchain enabling them to either produce applications as freeware or utilize a subscription model. They can create applications that can incorporate the full diversity of data that will be available on the blockchain. For Enterprise, Overledger will: · Complement existing blockchain investments and projects · Gain access to new markets and customers that use different blockchains · Spread risk and improve resilience by providing the ability to spread applications and data cross-chain and migrate your applications to different blockchains · Connect with your suppliers and partners that use any blockchain · Not have vendor or technology lock-in, providing the flexibility to use any blockchain and not be limited Overledger will allow interaction between multiple blockchains meaning that it can cope with the complexity represented in the modern supply chain. For Consumers, Quant will completely change how people will be able to interact with blockchains in a way that’s not possible today. A good example is the recognition of a person’s identity by one entity on a blockchain will be recognized and understood by every other blockchain and every entity connected to those. So consumers won’t need to constantly create accounts and remember all those passwords. We’re also allowing the way for consumers to be in control of their own data. We’ve seen constant failures by organizations not doing enough to protect consumers’ data securely. Imagine if you have a single consumer-controlled data store that is distributed across multiple blockchains. Every time you want to provide any sensitive data to another person or entity, you’ll be able to authorize and control access to your data and log it. We’re a team of experienced founders who have been working in industry and government for over 20 years. · Gilbert Verdian has been working in Cybersecurity for 20 years, and at CIO/CTO/CISO level in Governments and Industry. He’s also the founder of the Blockchain ISO Standard where 40 countries are working together to develop the Standard. · Paolo Tasca is a Digital Economist, an expert on digital innovation with salient expertise on Blockchain technologies and Complex Systems. He’s also the Executive Director of the UCL Centre for Blockchain Technologies. · Colin Paterson is technology innovator with a 20-year background in Cybersecurity, Information and AI. We actually don’t know what people will build on Quant, we’re excited and can’t wait to see the possibilities. Published on: https://www.quant.network/blog/introducing-overledger-the-blockchain-operating-system-for-the-future/

Introducing Overledger: The Blockchain Operating System for the Future

If you missed the first AI industry analysis on the Insurance vertical , check that out here . I. Financial Innovation: Lots of Talk, Little Action? TThe financial sector is historically one of the most resistant to change you might think of. It is then inevitable that big banks from one hand and startups from the other hand are creating a huge break in the financial industry and I believe this is happening not because of the use of a specific technology but rather because of their intrinsic cultural differences, diverse structural rigidity, and alternative cost-effective business models. In other words, banks do not innovate either because they are too big to quickly adapt and follow external incentives or because they don’t know how (and want to) truly change. This is not simply true in the industry but also in academia, where until the mid-nineties there were no relevant contributions to financial innovation at all (Frame and White, 2002). In fact, in few survey articles (Cohen and Levin, 1989; Cohen, 1995) with more than 600 different articles and books quoted, . none of them was related to financial innovation subjects Of course, things changed over the last five years, but my opinion is that was really out of necessity rather than a voluntary push-approach from the banking sector. Financial innovation is, therefore, something which seems to be usually rather than , and often more characterized by a rather than a one (although this might be a controversial opinion, I guess). Given the new technological paradigm (which is tightening the inner strong causal relationship between innovation and growth) it seems natural to wonder whether a better innovation model can be therefore imported by a different (and more successful) sector. imported internally generated product-innovation process I found that there is a very specific and interesting case of a sector which had to ‘ ’ rather than ‘ ’: the (Baker, 2003; Gans and Stern, 2004; Fuchs and Krauss, 2003; Lichtenthaler, 2008). innovate-to-survive innovate-to-grow biopharma industry Innovation drivers map. The biopharma companies feel more the urgency to innovate and are also more committed to that . The graph I built plots 25 major banks (blue) and 25 major pharmaceutical (red) companies based on their Innovation Impulse and Commitment. The Impulse variable has been built using the number of patents a company filed (a proxy for the external pressure to innovate) and the number of recorded shareholders (a proxy for the internal pressure to innovate). The Commitment shows instead the R&D intensity (net sales) while the size of the bubbles the net income for each company. The data points were obtained by Medtrack, Osiris, and Zephyr in 2014. II. Innovation Transfer: the Biopharma Industry The biopharma industry is not a single sector but actually two different ones: , populated by smaller companies that drive the research and exploration phase, and the , big giants that through the last century became huge go-to-market and sales enterprises. the biotech space pharmaceutical companies Hence, there is from one hand and from the other…Is it something that we have already seen somewhere, didn’t we? pure (risky) innovation pure commercialization skills The biopharma industry and the financial sector suffer from a strong polarized innovation What characterizes the industry is that the risky activity lies in the initial development process rather than in the market phase. The problem is not to match customer demand or find a market for your product, but it is actually developing the molecule in the first place. The probability of success is extremely low and the timeline very long (10–15 years) and the 20-years patents give you only a temporary advantage. More importantly, it looks that only 3 out of 10 of the drugs produced are able to repay the development costs (Meyer, 2002) and that most of the companies operate at loss while the top 3% companies alone generate almost 80% of the entire industry profits (Li and Halal, 2002). A tough business, isn’t it? The biopharma industry is then no longer simply a but also a . Innovation is not ancillary but it is the quintessential driver to survive. And this is also why they had to identify a range of different methods to foster their growth-by-innovation: R&D, competitive collaboration schemes, venture funding, co-venture creation, built-to-buy deals, limited partnership agreements, etc. human-intensive business capital-demanding one It should be clear by now where I am heading to: as the biopharma sector and it is and make it profitable. the financial industry doesn’t strongly feel the need to innovate not experimenting and pushing to create new models that might spread their innovation risk The financial industry doesn’t strongly feel the need to innovate III. Introducing AI, Your Personal Financial Disruptor Image Credit: Haru1/Shutterstock By now you might object “All good man, but FS and biopharma are still sooo different, so why should I import innovation models from a sector which is completely different from mine?”. Well, that’s the catch: I don’t think they are. And the reason why they are becoming a lot more similar is precisely Artificial Intelligence. and has a which are somehow similar to the biopharmaceutical one: it requires a long time to be created, implemented and correctly deployed (with respect to the financial industry standards, of course); it is highly technical and requires highly specialized talents; it is highly uncertain, because you need to experiment a lot before finding something that works; it is expensive, both in terms of time as well as monetary investments (talents, hardware, and data are really expensive); it is risky and the risk lies in the initial development phase, with a very high-payout but a high likelihood to fail as well. AI is creating a strong pressure to innovate for the financial sector development cycle and characteristics AI is creating a strong pressure to innovate for the financial sector But AI is also introducing a completely new speed and degree of trust in the financial industry, which lowers the tolerable mistakes at the same level of the biopharma sector. If your algorithms point out to the wrong product to sell or the wrong book to be recommended, it is not a big deal. If your system misinterprets some signals in the market or while developing a drug though, you end up losing millions in seconds or even losing human lives. It is then not only stretching out issues that intrinsically belong to the financial sector such as or , but it is also bringing new problems such as to the picture (specifically in consumer applications). regulation accountability or the biased data lack of transparency And last but not least, AI is making the question mark on the matter bigger than even in FS, the same as it was in the biopharma industry back in the nineties and that culminated in the current biotech-pharmaceutical dichotomy (if you are wondering anyway, this choice is all focused around on your , , and with respect to your competitors — do you have enough data to train an ANI? Can your team/project scale? Is the ANI unique or something your peers are doing or need to do as well?). “build vs buy” data capacity team and project scalability uniqueness of the project AI is revolutionizing a centuries-old industry innovation flow from the ground This is why I believe AI in financial services to be extremely important — not much for the specific innovation or product it is introducing but rather because . it is revolutionizing a centuries-old industry innovation flow from the ground IV. Segmentation of AI in Fintech Image Credit: TZIDO/Shutterstock Artificial Intelligence is using structured and unstructured data in financial services to improve the customer experience and engagement, to detect outliers and anomalies, to increase revenues, reduce costs, find predictability in patterns and increase forecasts reliability…but it is not so in any other industry? We all know this story, right? So what is really peculiar about AI in financial services? First of all, FS is an industry full of data. You might expect this data to be concentrated in big financial institutions’ hands, but most of them are actually and thanks to the new to smaller players as well. AI can then be easily developed and applied because the barriers to entry are lower with respect to other sectors. public EU payment directive (PSD2) larger datasets are available Second, many of the underlying processes can be relatively while many others can be improved by either brute force computation or speed. And historically is one of the sectors that needed this type of innovation the most, is incredibly competitive and is always looking for some new source of ROI. easier to be automatized Bottom line: the marginal impact of AI is greater than in other sectors. Third, the makes the field really fertile for AI. AI needs (a lot of) innovative data and above all feedback to improve, and millennials are not only happy to use AI as well as providing feedback, but apparently even less concerned about privacy and giving away their data. transfer of wealth across different generations There are also, of course, a series of in financial sector that limit a smooth and rapid implementation: legacy systems that do not talk to each other; data silos; poor data quality control; lack of expertise; lack of management vision; lack of cultural mindset to adopt this technology. specific challenges for AI So what is missing now is only having an overview of the AI fintech landscape. There are also plenty of maps and classification of AI fintech startups out there (probably the best ones are the one provided by , in particular and ), so I am not introducing anything new here but rather simply giving you my personal framework: CB Insights this this : this category is about making the end-client life better and easier and it includes ; ; automated financial advisors and planners that assist the users in making financial decisions ( check ); smart wallets that coach users differently based on their habits and needs. Financial Wellness personalized financial services credit scoring robo-advisor, virtual assistants, and chatbots — CB Insights map if you like Examples include [robo-advisors and conversational interfaces] Kasisto ; Trim ; Penny ; Cleo ; Acorns ; Fingenius ; Wealthfront ; SigFig ; Betterment ; LearnVest ; Jemstep ; [credit scoring] Aire ; TypeScore ; CreditVidya ; ZestFinance ; Applied Data Finance ; Wecash ; : I think that, given the importance of this instrument, it deserves a separate category regardless of the specific application is being used for (which may be payments, compliance, trading, etc.). Blockchain Examples include: Euklid ; Paxos ; Ripple ; Digital Asset ; : this can be divided into (payment security and physical identification — ) and (looking for fraudulent and abnormal financial behavior — ). Financial Security identification biometrics and KYC detection AML and fraud detection Examples include, respectively: EyeVerify ; Bionym ; FaceFirst ; Onfido ; and Feedzai ; Kount , APEX Analytics ; this category includes payments, peer-to-peer lending, and debt collection. Money Transfer: Examples include: TrueAccord ; LendUp ; Kabbage ; LendingClub ; : this is a big section, and I tend to divide it into five main subsections: Capital Markets (either algotrading or trading/exchange platforms). i) Trading Examples include: Euclidean ; Quantestein ; Renaissance Technologies , Walnut Algorithms ; EmmaAI; Aidyia ; Binatix ; Kimerick Technologies ; Pit.ai ; Sentient Technologies ; Tickermachine ; Walnut Algorithm ; Clone Algo ; Algoriz ; Alpaca ; Portfolio123 ; Sigopt ; (either crowdsource funds or home-trading). ii) Do-It-Yourself Funds Examples include: Sentifi ; Numerai ; Quantopian ; Quantiacs ; QuantConnect ; Inovance ; (information extraction or insights generation). iii) Markets Intelligence Examples include: Indico Data Solutions ; Acuity Trading ; Lucena Research ; Dataminr ; Alphasense ; Kensho Technologies ; Aylien ; I Know First ; Alpha Modus ; ArtQuant ; (most of the alternative data applications are in capital markets rather than broader financial sector so it makes sense to put it here). iv) Alternative Data Examples include: Cape Analytics ; Metabiota ; Eagle Alpha ; v) (this section is more a residual subcategory because most of the time startups in this group fall within other groups as well). Examples include: Risk Management Ablemarkets ; Financial Network Analysis . Conclusions I am arguing since the beginning of the article that AI is making financial services and biopharma much more alike, and that the FS industry might learn something from how the other industry innovates. The reality is that the financial industry has also very specific traits and challenges it needs to overcome. The biggest difference I currently see in that is the effect AI is having on the physical products market: while in almost any sector AI is used with the final goal of creating or improving new products (and this is true also for drug development, for example) in the financial ecosystem is having exactly the opposite effect. . Its final goal will be to create the (frictionless) bank of the future: no branches, no credit cards, no frauds, no menial reporting activities. A with modular components that increases our financial literacy and has no physical products or spaces. AI is making the industry more digitalized than ever before bank-as-a-platform It would definitely be a great world to live in. Can’t wait for it. Reference Baker, A. (2003). “Biotechnology’s Growth-Innovation Paradox and the New Model for Success”. 9 (4): 286–88. Journal of Commercial Biotechnology Cohen, W. (1995). “Empirical Studies of Innovative Activity”, in , edited by Paul Stoneman. Cambridge, Mass.: Blackwell. Ch. 6, 182–264. Handbook of the Economics of Innovation and Technological Change Cohen, W., Levin, R. (1989). “Empirical Studies of Innovation and Market Structure”, in , Vol. 2, edited by Richard Schmalensee and Robert Willig. Amsterdam: North-Holland. Ch. 18, 1059–1107. Handbook of Industrial Organization Frame, W. S., White, L. J. (2002). “Empirical studies of financial innovation: lots of talk, little action?”. Working Paper, Federal Reserve Bank of Atlanta, N. 2002–12. Fuchs, G., Krauss, G. (2003). “Biotechnology in Comparative Perspective”. In: . G. Fuchs (ed.). New York: Routledge, 1–13. Biotechnology in Comparative Perspective Gans, J., Stern, S. (2003). “Managing Ideas: Commercialization Strategies for Biotechnology”. 01/03: 1–24. Intellectual Property Research Institute of Australia Working Paper Li, J., Halal, W. E. (2002). “Reinventing the biotech manager”. , 20 Suppl (6): 61–3. Nature Biotechnology Lichtenthaler, U. (2008). “Open Innovation in Practice: An Analysis of Strategic Approaches to Technology Transactions”. , 55 (1): 148–157. IEEE Transactions on Engineering Management Meyer, F. J. (2002). “Business Models That Biotech Companies Employ”. November 25, 2002 Enterprise Development KFBS Biotech Speakers Series — — Follow me on Medium Look at my other articles on AI and Machine Learning: Unsupervised Investments (I): A Guide to AI Investors Unsupervised Investments (II): A Guide to AI Accelerators and Incubators Who is best positioned to invest in Artificial Intelligence?

Artificial Intelligence Verticals (II): Fintech

tl;dr: Fare lo sviluppatore in Italia è il più delle volte un incubo Fra tutti i report disponibili, nessuno analizza nel dettaglio lo scenario italiano Abbiamo deciso di farlo noi con un questionario che trovi qui: https://goo.gl/eWDECC E’ anonimo, richiede circa 5–8 minuti e i risultati saranno pubblicati entro fine anno L’iniziativa è legata al progetto Jaguar28 : il nostro obiettivo è riscrivere, in meglio, il rapporto fra professionisti del tech ed aziende 😉 Se hai aperto questo articolo poiché indignato dal titolo, inizia dalla parte finale “PRO TIPS / FAQ / DISCLAIMER” e poi leggi il resto Se lavori in ambito tech, quante volte hai già sentito la frase “ ”? E quante volte ti sei sentito d’accordo? Essere uno sviluppatore in Italia fa schifo Il mercato del lavoro per chi si occupa di sviluppo e programmazione in Italia è “famoso” per essere fra i più arretrati in Europa: tutti lo sappiamo e tutti ci rendiamo conto di trovarci di fronte ad un disagio strutturale che può solo peggiorare con il tempo. Il problema non riguarda solo i salari (i più bassi dell’Unione Europea, insieme a Portogallo, Spagna e Grecia) ma più in generale la concezione del ruolo di “developer” all’interno delle aziende. Per ogni storia romanticheggiante di qualche ragazzino californiano che diventa miliardiario grazie ad una app e viene intervistato da tutti i giornali, in Italia ci sono decine di storie molto meno piacevoli su aziende che non conoscono orari, non investono su innovazione e formazione e credono di poter disporre liberamente della vita dei propri collaboratori. L’intramontabile convinzione del “ ” è infatti anche parzialmente accettabile ma perde ogni legittimazione quando il professionista è sbattuto in uno scantinato a fare il refactoring di progetti vecchi di decenni scritti in Fortran (o quasi) e viene considerato come un pericoloso sovverviso quando si prende un permesso per partecipare ad un seminario. i salari in Italia sono più bassi perché la vita è meno cara Per fortuna esistono già alcune startup ed aziende che hanno compreso l’importanza di questi professionisti e che, per quanto possibile, cercano di garantire loro le condizioni più stimolanti: sono ancora casi isolati — in genere in quei contesti con un’elevata competizione per attrarre i migliori talenti — ma da qualche parte dovremmo pur partire. In tutto questo non dobbiamo dimenticare la crescente categoria dei professionisti italiani che vanno a vivere e lavorare all’estero. Troppo spesso vengono liquidati con un “ ”, anche se non se ne conosce l’effettiva situazione. : esistono sviluppatori italiani che vivono all’estero e sono sottopagati anche lì! loro sì che hanno fatto bene ad andarsene, bravi! NOTIZIA SHOCK Ecco quindi spiegato il grande paradosso: oggi sono moltissimi i professionisti che si lamentano della situazione italiana, ma non esiste nessuna vera analisi a tal proposito. Ogni anno sono pubblicate ricerche davvero apprezzabili sul mondo degli sviluppatori (quella di Stack Overflow è in genere la più completa) che però considerano l’Italia un mercato periferico e che non merita di essere valutato nel dettaglio. Ci siamo quindi chiesti: Qual è il salario medio degli sviluppatori italiani? Quali sono le tecnologie che utilizzano, quelle che vorrebbero utilizzare e quelle che invece vorrebbero dimenticare? Quali sono i fattori di soddisfazione ed insoddisfazione in azienda? Per trovare una risposta, abbiamo deciso di lanciare una nostra survey e condividere pubblicamente la fotografia che emergerà. L’obiettivo è creare una coscienza collettiva sull’argomento e provare ad influenzare il cambiamento, mettendo sul tavolo dati concreti ogni volta che un’azienda si chiederà perché non riesce a trovare sviluppatori in gamba. Il questionario è disponibile qui: https://goo.gl/eWDECC Se hai almeno 1 anno di anzianità come developer, sistemista, QA tester, DevOps e ruoli simili, lavori full-time in Italia o sei un italiano all’estero e hai voglia di dedicare 5 minuti del tuo tempo per aiutarci, questo è il questionario che fa per te. Il questionario è totalmente anonimo e non ti chiederemo indirizzi email o informazioni sensibili riconducibili direttamente a te. Entro fine anno pubblicheremo i risultati. Questa iniziativa è legata al progetto : siamo una startup di Torino e il nostro obiettivo è riuscire a riscrivere, in meglio, il rapporto fra professionisti del tech ed aziende. Qualche mese fa abbiamo già pubblicato un per raccontare come vorremmo farlo. Jaguar28 Manifesto Se hai domande, puoi scriverci a hello@jaguar28.com Grazie! MILESTONES: Lancio della survey: 11 luglio 2017, ore 14.00 Risposte inviate nelle prime 24 ore: 254 Visualizzazioni nelle prime 24 ore: 976 🏆_:_ 1000 risposte 14 luglio 2017, ore 14.19 PRO TIPS / FAQ / DISCLAIMER: Se ti va, condividi questo articolo e/o la survey anche con i tuoi contatti! Se vuoi condividerlo nei tuoi gruppi facebook, chiedi prima il permesso agli admin per non farci passare come spam 😅 Il questionario non chiede mai il tuo nome o il tuo indirizzo email, quindi è un database che non potrà mai finire nelle mani di qualche scammer o, peggio, di qualcuno che non conosce la differenza fra Java e Javascript. Sappiamo che, da un punto di vista metodologico, il report è pieno di possibili bias. Non abbiamo tuttavia la presunzione di volerlo presentare all’ONU in seduta plenaria. O forse sì? Stack Overflow ha parlato di alcuni aspetti dello scenario italiano nella Developer Survey del 2016 (% di remote worker, età media, importanza del salario), rispetto ad un campione di circa 1000 profili italiani. Nella Developer Survey 2017, Stack Overflow analizza USA, India, UK, Francia e Germania ma non l’Italia (da cui ha ricevuto circa 900 risposte). Ci è stato detto che l’AICA (Associazione Italiana per l’Informatica e il Calcolo Automatico) distribuisce annualmente un report abbastanza simile. Noi purtroppo non siamo riusciti a reperirlo da nessuna parte. In autunno lanceremo la controparte volta a raccogliere il punto di vista delle aziende tech. Non invieremo i risultati attraverso una newsletter perché sappiamo che la privacy è top concern e non vogliamo lasciare spazio a nessun tipo di insinuazione su come potremmo usare i vostri indirizzi email. I risultati verranno pubblicati con un post su questo profilo e riproposti nei gruppi dove abbiamo già postato questo articolo. Il titolo è volutamente provocatorio (o clickbait, se volete un termine Internet 3.0) per una ragione molto semplice: la maggior parte della dev community italiana si attiva solo quando il flame è alle porte. : il titolo è una provocazione, non una conclusione. RIPETO Commentare l’articolo e/o l’iniziativa solo in base al titolo senza averne letto per intero il contenuto equivale a condividere con toni indignati i link dei siti di fake news. Se il tuo sesto senso ti fa percepire una truffa, una fonte di speculazione o una cospirazione degli Illuminati non sei obbligato a completare il questionario né a condividere pubblicamente le tue paranoie. Se la cosa ti rende più sereno: sì, siamo Rettiliani e tu ci hai scoperto.

Essere uno sviluppatore in Italia fa schifo

My code-free experience learning how to clone, test and trade eight extremely profitable quant finance algos on the Quantopian platform. Last week, Boston company released its first crowdsourced from the Quantopian community in amounts ranging from $100K to $3M. The algorithms were submitted by an open community of authors from all over the world. Capital allocations from the were made to authors in eight countries, including Australia, Canada, China, Colombia, India, Spain, and the United States, and are now trading live, with . Quite amazing! Quantopian Multi-million dollar capital allocations to algorithms Q fund third-party capital that Quantopian manages Understandably, Quantopian hasn’t released publicly to which specific algorithms it has allocated the capital, nor how much. This gave me a wacky idea. Brainwashed by Hippies I had been lurking around , and a couple of their hackathons. Quantopian Community Forums I distinctly recall realizing quite early that I had stumbled onto something huge, but I try to remain suspect of my own biases. Years ago I moved West for a spell and was brainwashed by hippies into always questioning my own worldview and assumptions. Coincidentally, this starting point seems to accord with the quant teachings of some of my favorite math snobs, like and his , including this one from QuantCon last year: . Delaney Granizo-Mackenzie Quantopian lectures and seminars You don’t know how wrong you are Recognizing and challenging our own biases is sometimes half the battle. Confirmation Bias Thus began my interest in Quantopian, which seemed to consistently reinforce my personal bias in favour of democratized quant finance. My internal ‘confirmation bias’ detector tingled a little stronger last July when Hedgefund-superstar pledged . And then, just last week, mega-tron fired every one of its going forward. Stephen A. Cohen a cool quarter $Billion to be managed by Quantopian BlackRock Capital stock-picking hedge fund managers in NYC, in favour of exclusively quantitative algorithmic trading Hacking the Quants And so, with only wannabe coding skills, and just a simple background in philosophy, but (hopefully) a knack for calling myself on my own bullshit, I set out to crib from the best Algos being discussed in Quantopian forums, run the backtests, understand the strengths and weaknesses of each, learn all the required ‘Quant’ concepts (Sortino, Sharpe, Alpha, Beta, MaxDD etc.), and ideally set each Algo alive into ‘paper trading’ (ie. pretend money) all with plenty of time before (April 28–30 in NYC), where Quantopian plans to release their much anticipated , to be used by anyone that joins their open quant finance community. QuantCon 2017 Futures API Once you get used to the Quantopian platform, Algos begin to flow pretty freely. My Process I researched, cloned and backtested eight separate Algos from the open-source . (There are some really powerful ideas being discussed there!). A great starting point is . Another place to start is this library, which has some overlap. Quantopian Community Forums this Post linking to the 10 most cloned Algos and Notebooks on Quantopian Q Algorithm Research and Ideas When choosing these Algos (delineated below), I tried to use the same . Then I set a few of these Algos loose (in paper trading). Five of the Algos are live paper trading today! (If you sign up below, I’ll keep you posted of the results of each Algo on a weekly basis). allocation criteria that Quantopian uses For the initial Eight Algos, I chose 4 from the (which appeal to my ‘legal and regulatory’ background). For the remaining 4 Algos, I dug a little deeper into the substantive . There many familiar (and unfamiliar) quant strategies, concepts and variants of Algos are cloned, debated and improved by minds much more seasoned and insightful than mine. It’s quite a sharp learning curve, fascinating and rewarding! Quantpedia ‘Earnings Announcements’ series Quantopian Community Forums provide a great starting point to analyze our Algos Quantopian’s Allocation Criteria I like each of the Eight Algos that were chosen for different reasons, with a few consistent themes: Each Algo 1) demonstrates consistently profitable backtests, 2) uses a wide universe of stocks and broadly distributes capital, independent of any particular stock or sector, 3) remains market agnostic, and 4) meets the criteria prescribed by the Quantopian team. I describe each briefly below, and have created deeper Medium and Quantopian Posts for each separate Algo (including some definitions of those funny words above), just click! Several of the Algos chosen are quite profitable already! Eight Cloned Algos: 1. Zack’s Long-Short PEAD with News Sentiment and the Street’s Consensus (LIVE TRADING) A fun algo that surfs the Post Earnings Announcement Drift , using several data sources, taking long and short positions as appropriate. 2. Zack’s Long PEAD with News Sentiment The Post Earnings Announcement Drift strategy describe above, taking long positions only. Profitable in various backtesting scenarios. 3. Are Earnings Predictable with Buyback Announcements? (LIVE TRADING) Leverages Regulatory Filings (Schedule 13-D, Share Buyback Announcements) to predict momentum during Earnings Announcements. Quite profitable in backtesting! 4. Reversals During Earnings Announcements (LIVE TRADING) Another Earnings Announcement variant, riding the Earnings Announcements post-overreaction reversals. 5. Clenow Momentum Strategy (as Amended) Andreas Clenow , author of a several classic books on ‘Momentum Trading,’ has published his own version of the underlying Momentum Algo he promotes, which had already seen many prior attempts and iterations by the Community. Let’s check out both variants. 6. VIX Robinhood Momentum Strategy (LIVE TRADING) An ‘implied volatility’ strategy much discussed and iterated upon in Quantopian forums, originated by Charles Witt in 2016. Originally termed “Robinhood Extreme Vetting.” 7. JAVoIS: Just Another Volatility Strategy (LIVE TRADING) Originally submitted by Peter Bakker in June 2016, with much input and iteration from the Community. 8. 101 Alphas Project: Alpha# 41 Using an academic paper as a starting point, the 101 Alphas Project aspires to create 101 profitable Formulaic Quant Trading Strategy. This is Alpha #41. More to come.. With just a little exposure, I am consistently having more and more ideas for variants of these Algos and others, some of which I hope to publish soon (or maybe submit at the ). One logical next step would be to create a meta-Algo that smartly allocates capital among each of the other Algos, perhaps even borrowing from . QuantCon 2017 Hackathon these starting points My goal here was to simply leverage (i.e. clone, test and trade) several Algos from the open source quant community that comprises Quantopian. (As Quantopian itself has done in its own initial capital allocations). Some of the community’s ideas are way cooler than mine anyway ;) But I’ve got a couple in mind for the in NYC on April 30, 2017 (some using Quantopian’s shiny new and !). QuantCon Hackathon Futures API data Alpha is Truth. And Truth, Alpha The Search for Truth In his awesome 2007 book , author describes the ‘Truth’ or ‘Alpha’ (at p. 8) as: The Quants Scott Patterson Revealed in the study of obscure patterns in the market, the Truth [is] the key to unlocking billions in profits…It [is] about money, of course, but it [is] also about proof. Each added dollar was another tiny step toward proving they had fulfilled their academic promise and uncovered the Truth. The Truth [is] a universal secret about the way the market works that [can] only be discovered through mathematics. There is a new era upon us. A democratized algorithmic era, where we can all code our own Truth(s), backtest our algorithms, and employ our strategies in our present day scenario and marketplace, testing at first, and eventually with real dollars and risk (and ideally build in our own escape hatches, in the case of market hiccups, crashes and other events). Dare I say that the ‘Truth’ is knowable by anyone, with a little discipline, insight and code. Acknowledgements I take no credit for any of these Algos — they were created by the Quantopian open quant finance community, and iterated upon therein. I just read everything I could, found these fascinating threads (and many others), and cloned the latest versions, ran some more backtests, and started paper trading. I try to ascribe appropriate credit where possible — and may be in error, or have forgotten you. If so, please advise. I encourage all feedback (negative and positive) and discourse! I feel indebted to Quantopian, and grateful for the fascinating discourse happening with thousands of diverse brainiacs on the Quantopian Community Forums. I have become quite impassioned, and have already found the next 5 Algos I want to try. Caveat This is not investment advice. I am not affiliated nor associated with Quantopian in any way. Also, I have not mentioned herein some of latest features and functionality on the Quantopian platform, including and , which I hope to use and discuss in subsequent posts. Alphalens Optimize API Keep you posted? If you would like me to keep you posted on the results, please sign up below.

Hacking 8 Algos

HackerNoon Reporter: Please tell us briefly about your  background. Hey, everyone! I’m Sohaib Zahid, the co-founder and CEO of . I am a serial entrepreneur and have spent over a decade successfully building teams, products, and companies. Prior to founding Railz, I was a founder of Vanhawks. In my free time you can find me with my family or cycling. Railz What's your startup called? And in a sentence or two, what does it do? Railz provides fast and direct access to commercial customers’ accounting software through a single API. What is the origin story? Interestingly, my co-founder and I came up with the idea for Railz separately. I realized that getting is a massive pain point for companies building various business applications within the Intuit ecosystem. There was no one building the developer’s first API tools for companies to access normalized accounting data to build new SME fintech applications. normalized accounting data For Derek Manuge (our co-founder and CTO), the idea was born out of the struggles he faced while working as a quant. Obtaining data to build better models or make better decisions was 50-80% of his time and he knew there had to be a better way. What do you love about your team, and why are you the ones to solve this problem? Our team is on a mission to build the foundation for the future of finance by making the largest financial data network. Building and is a challenge yet everyone has stepped up to the plate. Our team is , , and of what we’re doing. That’s an incredible feeling. managing a fully remote team during a global pandemic driven customer-centric proud If you weren’t building your startup, what would you be doing? ! If I do get some time for myself, then it's cycling! 🚴 I’m always exploring new routes and trails when cycling and trying to take advantage of the summer weather here in Toronto. I have a 20 month old daughter that takes up most of my time and I love spending time with her At the moment, how do you measure success? What are your core metrics? For Railz, it’s all about the customer. How our customers are currently using our product and how often. Secondly, pipeline: how many people we bring through the site, the deals we close, and making sure our customers are happy and involved with what we’re building. What’s most exciting about your traction to date? We’re so grateful to our team, investors, and advisors for Railz to be at the point we are now. A year ago, our company looked so different and it’s hard to believe all we’ve accomplished in a short time. We’ve partnered with some incredible companies, like Visa, Citadel, , Prodigy’s , and have more integrations coming to provide access to different types of financial data. Beyond that, we’re part of the and we’ll be this September! M&T Bank IDVerifact FIS 2021 Fintech Accelerator demoing live at FinovateFall What technologies are you currently most excited about, and most worried about? And why? Blockchain is one of the most exciting techs of this century. Democratizing data is a massive initiative and implementing open access to data is an insanely exciting preposition. This not only gives access to more customers to companies but also gives more optionality to the customers. Security is still a concern when you are dealing with sensitive data. Security breaches are any data company’s nightmare and blockchain technologies remedy this. The advancements around artificial intelligence (AI) are amazing but it's also a technology which can have negative impacts. I believe, we have to put controls in place to ensure the technology is safe, effective, and unbiased. Sam Altman and Elon Musk has started a non-profit which is a kind of strategic-defense initiative around AI. OpenAI What drew you to get published on HackerNoon? What do you like most about our platform? I love the opinion pieces on HackerNoon. There are great insights from people in fintech that I really appreciate, too. What advice would you give to the 21-year-old version of yourself? When I was around 21, I made a decision to leave medical school to pursue entrepreneurship. It was not necessarily an easy decision but I really believed in , and that’s the advice I would give to anyone. The risk led to me leading , through exciting and challenging times towards an acquisition. taking a chance on myself my previous startup, Vanhawks What is something surprising you've learned this year that your contemporaries would benefit from knowing? are here to stay! I am a big believer in adopting the change and being part of it - nothing is permanent except change. NFTs Railz was nominated in Startups of the Year hosted by HackerNoon. as one of the best startups in Toronto

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