Analysis The disclosure of a critical security hole in Log4j last week has renewed calls to rethink how open-source software gets developed, paid for, and maintained, not that the long-simmering issue ever really went away.

The Log4j bug, an unauthenticated remote code execution flaw (CVE-2021-44228) in Apache's open-source Log4j Java-based logging library, is particularly serious and far-reaching because exploitation is not difficult and the software is widely used and buried deep within many programs.

Annoyance with the handful of project maintainers for failing to catch the bug prompted one, developer Volkan Yazici, to voice indignation about all the people bashing the maintainers for their unpaid, volunteer labor without offering any financial support or contributed code fixes.

The exploitation of open-source software by companies that use freely available works without giving back to the community has been a sore spot among open source project maintainers for years.

It's sometimes referred to as the open source sustainability problem, a characterization that downplays corporate determination to minimize costs and maximize profits.

Among open-source projects that aspire to become profitable companies and to avoid having their uncompensated labor co-opted by more established rivals, the issue has been described in adversarial terms predatory tech giants strip-mining open source instead of ecological euphemisms that avoid assigning blame.

Weighing in on the current state of affairs, Filippo Valsorda, a Google cryptographer and security lead of the internet giant's Go programming language, on Saturday called for open source maintainers to engage with companies using their software on a more professional level, in order to get paid and make open source more sustainable.

"Maintainers need to be legible to the big company department that approves and processes those invoices," he wrote in a personal blog post. "Think about it: no company pays their law firm on Patreon."

Think about it: no company pays their law firm on Patreon

Dan Lorenc, who left Google in October after almost nine years to found security startup Chainguard, said that in terms of Google's interactions with open-source projects, the problem was distribution rather than funding.

"Corporations have a budget and are willing to spend, but it takes too much time," he said via Twitter. "Finding projects that need help and maintainers willing to help in exchange for money is hard."

Yet the notion that companies will ante up if just asked nicely using corporate vernacular, rather than gig economy tooling, doesn't sit well with everyone. For one thing, there is little enthusiasm, among individual users as well as Big Tech, for paying for open-source software at the heart of larger products, projects, and services.

"I've had this kind of conversation with people before and I've gotten a surprising amount of resistance to the prospect of actually making sure that the random smattering of volunteers that LITERALLY MAKE THEIR COMPANY RUN are able to make rent," said developer Christine Dodrill in a blog post. "There is this culture of taking from open source without giving anything back. It is like the problems of the people who make the dependencies are irrelevant."

Others participating in the discussion contend funding isn't the issue. David Crawshaw, CTO of Tailscale, in a blog post said while Yazici's post about lack of support for Log4j has been receiving attention "because highly profitable companies are using infrastructure they do not pay for," funding "would not clearly have contributed to preventing this bug."

Curl creator and WolfSSL developer Daniel Stenberg seemed to be in alignment with that, reminding us of the goto fail bug in Apple's encryption code: "The Log4j case is not a showcase for bad open-source software funding. It is a showcase for naive and cheap users not doing their due diligence, code review, and testing before using components. Remember goto fail? Silly bugs are shipped even with the greatest funding."

Developer Gabriella Gonzalez elaborated on that point, arguing that the Log4j vulnerability underscores the problem of catering to big business because the bug arose from a feature maintained to appease companies concerned about backward compatibility LDAP/JNDI URLs.

"The maintainers of the log4j project knew that one of the lesser-known features was potentially problematic (although perhaps they underestimated the impact)," Gonzalez wrote in a blog post. "However, [they] did not remove the feature out of concern for breaking backwards compatibility."

Gonzalez argues that Log4j is a symptom of a larger problem: that public companies are exploitative and abusive toward open-source projects.

But the self-interested behavior of large companies extends beyond software. Whenever money or power are at issue, companies try to shape the rules to their advantage.

Uber and Lyft managed to get Californians to vote for an exemption to a law (found by a judge to be unconstitutional) that would have required drivers to be classified as employees, so they could avoid paying for benefits and reduce costs. Amazon and Google, among many other mega-corporations, fight unions for fear they will negotiate better pay and benefits for workers, thereby increasing costs. Companies like Oracle and IBM have been accused of capping or withholding sales commissions owed to their own salespeople. Employment contracts routinely impose onerous terms that benefit employers and disadvantage workers.

Businesses are simply not in the business of fair dealing. Those prioritizing their own concerns are simply doing what the law or the software license allows. The problem is not payment; it is permission many popular open-source licenses are extremely permissive while lacking the reciprocity requirements of copyleft licenses. Licenses like the Apache license and the MIT license offer a lot and ask very little.

"Open source maintainers create massive amounts of value and capture almost none of it," said Feross Aboukhadijeh, an open-source developer who runs Socket, in an email to The Register. "Many of the most important open source projects that power the Fortune 500 are maintained by volunteers in their spare time, after work hours.

The software industry needs to find a way to help maintainers start capturing at least a portion of the value they create so they can continue to write new features, fix bugs, improve documentation, and most importantly, fix critical security issues in a timely manner

"The software industry needs to find a way to help maintainers start capturing at least a portion of the value they create so they can continue to write new features, fix bugs, improve documentation, and most importantly, fix critical security issues in a timely manner.

"I expect to see more maintainers explore alternative licensing options, restricting the ways and types of organizations that can use their software or decide to let their projects stagnate which will only increase the number of security incidents that we'll continue to face."

Aboukhadijeh added that the Log4j incident also illustrates how almost no company using open-source code in their applications bothers to review it.

"At the end of the day, companies are responsible for ensuring the code they ship to production is safe, secure, and reliable," he said.

Sooner or later someone's going to pay for open-source software, if not in goodwill then in damage control.

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Log4j doesn't just blow a hole in your servers, it's reopening that can of worms: Is Big Biz exploiting open source? - The Register

What is common between Netflix, Google, Uber, Spotify, Apple and Microsoft? All these giants of their industries believe the answer to the question "What is the future of Python?" is that it is extremely bright. In 2021, Python celebrated the 30th anniversary of its launch and showed no signs of slowing down in developing as the most preferred programming language in the contemporary world.

With more than 25 million amateur users and more than 8 million professional developers trusting Python as their go-to language, it seems to be in the lead position going into the third decade of the 21st Century. In this blog post, we will look at what the future has in store for Python and what Python has in store for us in the future.

It must be mentioned that Python's future-making ability is no mere accident: years of steady corporate investments from companies like Google and Amazon Web Services have ensured that Python has the best support ecosystem it needs to thrive as a programming language. The dues seem to have paid off: Python today boasts of an extremely immersive and trustworthy community that stands by its programmers and developers by offering well-rounded peer to peer support.

Let's take a quick peek at why Python is the programming language of the future.

The Millenial Coding Language: Python's Growing Open Source Community Appeal

One of the most important reasons that Python is both already popular and still growing in terms of users is the accessibility and readability of the code it generates. Python was deliberately designed such that it would be similar to the standard English language. This has made coding and programming a simple task that anyone can accomplish as quickly as they can learn to speak English.

The Millennial Appeal: 40% of all Python users belong to the age group of 21-29 years, with an additional 10% belonging to the 18-20 years cohort.

Perfect for Beginners: Additionally, as of 2020, almost a third of all Python users have less than one year of coding experience. This statistic speaks for itself insofar as Python's mass appeal and upward trajectory in the app and web development community are concerned!

Preferred Tool for Independent Development: Not only this, almost 50% of Python users work on their projects as independent contractors or freelance creators, with estimates suggesting that the development and analytics industry is looking to hire more than 40,000 Python Developers.

The rise in Python's popularity also has to do with its community of trustworthy and acclaimed peers who leave no stone unturned in helping each other. While many other programming languages have lost their ability to accommodate evolution and facilitate smoother integration with the innovations of its time, Python has been consistently keeping in touch with the latest trends. In this respect, Python has undoubtedly succeeded, as a result of which it holds one of the keys to the future of technological progress.

Delivering Tomorrow More Efficiently: Python's Future in Data Science and Smart Analytics

As the global business and entertainment ecosystems take a giant leap through the advancements offered by big data analysis, Python is poised to enable the pivot. By making tools built specifically for tasks such as complex calculations, data visualisation problems, and traffic-based content management, Python is fast becoming the bedrock of Data Science and Smart Analytics. Let's take a closer look at how and why:

Pythons Meteoric Rise: From 2016-2018, KDNuggets and Kaggle report that Python overtook R as the most used programming language for data science-related purposes: today, more than 65% of all analytics professionals use Python as their primary language. Python has thus made itself indispensable to data scientists.

Python's rise is already visible from the use of Python by companies like Amazon Web Services, Spotify and Google, to mention a few. Therefore, Python's symbiotic relationship with Data Science is one of the essential reasons why Python is the language of the future!

Learning for the Future: AI, Automation and Machine Learning

It is no secret that we are edging closer to a time where practical applications of machine learning and automation will be introduced in the forms of self-driving cars, social administration programmes, medical diagnosis, and many more! This new reality will most certainly be written in the language of Python.

Achieve Basis Tasks Faster in the Future: Python's future growth looks like an upward curve as more and more developers and companies seek to eliminate redundancies to save both time and money lost for basic tasks.

Great for Traffic-Based Content Management: Python's libraries, such as Scikit, Pandas, and Tensorflow, provide a flexible and dynamic foundation based on which projects such as big-data processing pipelines and targeted content delivery can be effectively achieved at a minimal cost. Think of, for instance, how the Spotify algorithm decides precisely the right music to show you: this is made possible because of Python-based app development!

Flawless Compatibility with Other Languages: Python is a blessing for machine learning and robotics programmes written in C or C++ as it enables smooth integration, which can interface with almost any other programming language. Thus, Python opens up the possibility of reviving projects that might have earlier not been feasible in other languages!

Tailor-made for Neural Networking: In projects involving neural networking (to programme reactions to recurrent patterns), a language like Python, which is close to the language of speech, is essential for any probability of success. Thus, for all such projects involving deep learning and analysis of patterns in data, Python is almost a necessity.

The future of Python is thus set in stone as the go-to language for developers engaging in deep machine learning projects, companies looking to scale up by using big data analytics or efforts aimed at achieving social applications of automation!

Not Just Writing the Future, But Bringing It To You: Python's Persistence in the Rise of Web Development

We already know that human beings will spend a lot of the 21st Century on the internet. It means preparing technological innovation for social application and coming up with the tools to deliver the applications themselves. This is the place where Python has already traditionally thrived: even though it competes with other web development languages, till the late 2010s, companies used to hire python developers mainly for the task of web development services.

Today, Python Development Companies and App Developers are making a resurgence as "DevOps Managers" and are still working on the unwavering foundation of Python because:

Seamless Integration: Python further offers a smooth integration experience with other programming languages such that developers can utilise it in the creation of embedded applications. Application and web development thus consistently rank amongst the biggest tasks for which the Python database is utilised.

Rich Library Resources: The existence of frameworks such as Django, Pyramid, and Flask makes Python App and Web development particularly faster. Python Web Development Services ensure that developers don't have to start from scratch but can utilise some elements already built-in into the network through its numerous libraries and packages.

Python thus possesses versatile capabilities of withering today's storms while also preparing for tomorrow: this is what makes it the programming language of the future. In 2022, the number of data scientists and machine learning experts using Python is only slated to increase because of the investment of money and human resources into delivering applications of technological innovations. While they may be less in proportion, the absolute number of web developers and DevOps managers using Python is also sure to move upward.

Pathbreaking Python: The Democratic Future of Programming Languages

Four factors have thus contributed to the rise of bright prospects for the future of Python:

Corporate investments and dedicated developer community;

The promise of smooth integration and faultless compatibility with other languages;

Endless libraries and packages for specialised tasks such as ML and AI;

The open-source nature of the network that makes programming inexpensive.

Through Python, creating new services more efficiently and integrating these services with the aim of effectively delivering them to the end consumer has become a relatively simpler process. This is evident because, even in academic spaces, Python-based Development has become a mandatory skill to be acquired in the 21st Century. It is the primary instrument through which students can translate knowledge and information into questions and hypotheses.

Python, therefore, holds the key to the future application of technological advancements being materialised into tangible reality. Are you ready to speak in the language of Python and open the door to the new world?

Author Bio:

Mahipalsinh Rana is a CTO of Inexture Solutions, he has more than 15 years of experience in software development with a strong focus on mobile app development for all kinds of platforms including iOS and Android. Along with his guidelines, many agencieshire python developersto build their online presence & complete complex project. He loves to write and share about technology, startups, entrepreneurship, and business

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Python: The Programming and Development Language of the Future - Finextra

Programmer's glasses show code lines

As the year draws to a close, it is a good time to consider where different technologies are going and what we can expect not just next year but in the years that follow. As part of my recent adventures in EdTech, I have had a chance to consider where the world of coding is going, how the industry sees coding, how it compares to how the education world sees coding, and how both are likely to change in the coming years. With that in mind, here are 7 trends I see in the world of coding, that much of the industry and the educational world will likely want to consider and adapt to.

What is Coding anyway?

Most of us know generally what coding means. However, since the nature of coding itself is changing, it may be good to revisit this briefly. Coding has classically been defined as the process of creating computer programs (or programming). It is also the process of specifying a solution to a problem in a language that computers can understand (which by definition needs to be precise).

Trend 1: Coding for everyone

Coding is no longer just for computer scientists or those looking for jobs in the IT industry. In 2020, India made coding mandatory for all students of 6th grade and above. In the US, discussions have been ongoing for several years about whether coding should be considered equivalent to a foreign language requirement (with strong support and opposition). Such legislation made it to a state government proposal earlier in 2021, indicating that the idea is not going away and may even be gaining some momentum.

Trend 2: NoCode, LowCode and CodeGen

Oddly enough, while the world is setting up for everyone to learn coding, the industry is seeing growth in NoCode, Low-Code and CodeGen. What are these things? They are a recognition that not all coding tasks are equally important uses of an individuals time. These tools enable automation of the low level tasks of coding, freeing up the user to focus on higher level tasks such as code design, user experience and algorithm choices. Some of these solve problems (like analyze data), some generate apps, and others generate code that the user can run themselves - such as auto-generated AI code in a Google colaboratory notebook.

Is this in conflict with Trend 1? I don't think so. If you see coding as mastery of a computer language - yes this can be conflicting. However, coding, in my opinion, should not be seen that way. Coding is about specifying a solution to a problem and describing that solution and its constraints and outcomes in a logical and specific way. Put this way - automating the lower levels of coding is a natural part of making coding accessible to all.

Trend 3: AI that Codes

While Trend2 is more about straightforward automation in a constrained environment, the natural extension of this is AI that can take even higher level instructions and generate code, drawing from many sources. We are seeing this already in OpenAIs Codex. Over time, the distinction may become less relevant. As the algorithms inside LowCode/NoCode/CodeGen tools become more sophisticated, the distinctions between these two trends will disappear.

Trend 4: Open Source

This is not a new trend by any means, but I decided to include it here since its impact on the world of coding cannot be overstated. The last few years have seen the growth of not just open source but the growth of open source monetization models. However, what does any of this have to do with coding? While in the early days we would think of open source examples that are large powerful software bases like Linux, or MySQL, these days - open code is everywhere and in every possible size. Say that I wanted to learn sorting algorithms? A quick Google search will turn up countless examples, each with their own pros and cons (and bugs!). Open source has gone beyond individual apps to a sea of code with growth that shows no signs of stopping - it is in itself a form of content.

Trend 5: APIs

Developers now have another powerful resource in addition to code snippets all over the internet - and that is APIs. The Software as a Service (SaaS) boom now means that many powerful services (from databases to AIs that can detect objects and read OCR) can now be accessed with a few lines of code. This makes it not just simpler to build powerful solutions, but also makes it easier to create elastic and scalable solutions. Want to build an app that scales to thousands of users? You still need to think about how parts of the solution will accommodate that scale, but common services like databases can now accommodate that scale for you automatically, removing the need for you to become a database expert.

Trend 6: Apps and Websites

Where Trends 1-5 provide people with the foundation for coding, Trend 6 provides a destination. The worldwide app ecosystem has grown rapidly in recent years, for example with Apple demonstrating robust growth of the AppStore even during the pandemic. Where democratization of coding makes it easier for people to learn how to code, apps and websites provide a way to package up their creations for use by others. The synergy between coding and apps is further driven by governments, such as the US with the Congressional App Challenge, which encourages high school students to create unique and impactful apps. These trends are not independent either - app development is also benefiting from NoCode/LowCode/CodeGen tools as well as declarative programming approaches that make coding easier - like SwiftUI from Apple.

Trend 7: Creativity and Community

The world has known for quite a while that coding fosters logical thinking and provides a way to express creativity in the form of problem solving and solution creation. Trend 6 further reinforces this, but we can expect more outlets for creative expression with code. Musicians are already using AI programs to augment their own creativity. Is this a form of coding expression? I think so. Environments like Roblox allow users to create code for the platform, thereby injecting their own creativity into the virtual. The emerging metaverse promises more of this, with examples like Nvidias Omniverse.

Takeaways

So, what do these trends suggest? While some may seem contradictory, they are not really. What they imply are two fundamental things in 2022 and beyond.

Happy Coding!

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Where Is Coding Headed? 7 Trends For 2022 And Beyond - Forbes

By midnight on December 1, 2015, when Eric Wastl first launched his annual Santa-themed puzzle-a-day programming challenge Advent of Code, 81 people had signed up. That pretty much matched his capacity planning for 70 participants. Wastl figured this amusement might be of interest to a few friends, friends of friends, and maybe some of their friends as well.

But Wastl, a software engineer who works as a senior architect for TCGPlayer, an online marketplace for trading card games, had failed to anticipate how social medias recursive contagion might overwhelm these modest expectations. He jokes that the technical term for what happened next is: OH NO! Within 12 hours there were about 4,000 participants. The server nearly crashed. At 48 hours, there were 15,000 people, and by the end of the event, on December 25, the grand total was 52,000. The following year, he moved the operation to Amazon Web Services, and numbers have since continued to grow.

Last year, perhaps due to the pandemic, the event saw a 50% spike in traffic, with more than 180,000 participants worldwide.

And now again this year, thousands of coders from San Francisco to Sloveniastudents and software engineers and competitive programmers alikeare counting down to Christmas with Advent of Code (AoC). While traditional advent calendars deliver daily gifts of chocolate or toys (and some alternative versions deliver dog treats, Jack Daniels, Lego figures, or even digital delights via apps), Advent of Coders unwrap playfully mathy problems and then write computer mini-programs that do the solving.

The fun of it, partly, is simply in the time-honored magic of a holiday ritual. But its also in submitting to pleasurable puzzlement. Peter Norvig, a research director at Google, finds it fun because he trusts the creator, Wastl, to make it worth my timein a similar way, Norvig says, to how New York Times crossword puzzlers trust Will Shortz to do right by them. There will be some tricks that make it interesting, says Norvig, but there are bounds on how tricky.

At midnight US Eastern time (Wastl is based in Buffalo, New York), every night from December 1 to 25, a new puzzle lights up at adventofcode.com, embedded within a cleverly composed Christmas-caper narrativeone player described the story as an Excuse Plot if there ever was such a thing.

This years event got off to a fine start when Santas elves lost the keys to the sleigh. The first problem set the scene as follows: Youre minding your own business on a ship at sea when the overboard alarm goes off! You rush to see if you can help. Apparently one of the Elves tripped and accidentally sent the sleigh keys flying into the ocean!

Luckily, the Elves had a submarine handy for just such emergencies, and from there participants set off on a 25-day underwater quest. They try to solve two puzzles daily (the second adding a twist, or more difficulty), each worth a star and some praise: Thats the right answer! You are one gold star closer to finding the sleigh keys.

Every player earns a star for solving a problem, but if youre the first to get a star, you receive 100 points; if youre second, you receive 99 points; and so on, with the 100th place earning one point.

In order to save Christmas, the puzzle master explains, youll need to get all fifty stars by December 25th.

MS TECH | ADVENT OF CODE

The object of Advent of Code is to solve the puzzles using your programming language of choice (Python is the most popular). Participants also use by-hook-or-by-crook strategiessuch as Excel madness, as Wastl describes it, or reams of graph paper, and a surprising number solve the puzzles in Minecraft.

But the broader motivation varies from player to player. Some treat it as an annual tune-up for their programming skills; others see it as the perfect opportunity to learn to code or try a new language. Jos Valim, creator of the Elixir programming language, is live-streaming his AoC solutions on Twitch.

At the top of the global leaderboard, which ranks the 100 players with the highest total score, competitive programmers like Brian Chen (his handle is betaveros) and Andrew He (ecnerwala) are out for speed. A security software engineer working on end-to-end encryption at Zoom, Chen placed first last year (and the year before), while He came a close second.

Going fast is fun, Chen says, just like optimizing anything where you can get fairly immediate feedback. There are lots of little knobs to tweak, and lots of little moments to be proud of where you made the right choice or prepared something that came in useful.

Both MIT computer science alums who live in the Bay Area, Chen and He are friendly rivals whove competed together in programming challenges over the yearson the same team at the International Collegiate Programming Contest (ICPC) and as competitors at Codeforces and Googles Code Jam. This year again, Chen is beating He. To be honest, its cause hes a little better than mebetter at various tricks and implementations that optimize speedbut I dont like admitting that, says He, a founding engineer at the startup Modal, which builds infrastructure and tooling for data teams.

The leaderboard is out of reach for the majority of participantsespecially as puzzles get harder by the day. Kathryn Tang, who runs an engineering operations team at Shopify, placed 36th on day one and was still hanging on to 81st by day three, but she knew her leaderboard status wouldnt last long. Im doing this for fun using Google sheets, she says.

The element of contest, however, is replicatedat Shopify and Google and many companies big and smallwith private leaderboards, as well as dedicated chat channels where players share solutions and kvetch about the problems in post-mortems.

The competitiveness helps commitment, said the engineer Alec Brickner, commenting in a Slack channel at Primer.ai, a natural-language-processing startup in San Francisco (Brickner has made the leaderboard on a couple of days so far).

Meh, replied his colleague Michael Leikam. The payoff for me is the joy of coding.

John Bohannon, Primers director of science, seconded that with an emoji: SAME.

Bohannon also loves the silly story that sets up the problems, but the plot has little to zero utility. The speed-demon solvers completely ignore the story, focusing on the variables of the problem to solve and just getting to it, he says.

Nora Petrova, a data scientist and engineer at Primers office in London, UK, is there for the beauty, not the sport: I love the drama thats unfolding in every puzzle, she says. For instance, on day four, a giant squid attached itself to the submarineit wanted to play bingo, of course. The puzzle input was a random set of 100 bingo boards, and the challenge was to predict the winning board and give it to the squid.

Wastls main motivation in creating Advent of Code was to help people become better programmers. Beginners who are just getting into programming are the people I want to get the most out of this, he says. The success metric for most people should be How many new things did I learn?not Was I one of the very, very fastest people in the world to solve this puzzle?

Russell Helmstedter, a middle school teacher at the De Anza Academy of Technology and the Arts, in Ventura, California, is using Advent of Code to teach Python to his students in sixth, seventh, and eighth grades. They tackled the first two problems together as a class. From a teaching perspective, the problems are effective exercises because if you fail, you can simply try againvery much in the spirit of test-driven software development.

Helmstedter found that some of his students were a bit overwhelmed with the two-pronged challengedeciphering the problem and coding a machine to solve itbut most embraced the struggle. I like that it is hard to do, one student said on a survey. And another said, There is honestly no downside. I really like how you start working progressively toward a goal. Although the surveys multiple-choice question ranking feels elicited one Hate it, 41 respondents chose Like it (to varying degrees) and eight Love it.

MS TECH | ADVENT OF CODE

At the University of Ljubljana, in Slovenia, the computer scientist Janez Demar uses the AoC problems both as a professor and to hone his own skills (hes on the core team of Orange, an open-source machine learning and data visualization toolbox). I need to have some regular practice, like a violinist who plays in an orchestra and does some teaching but still needs some small pieces to practice, he says. So these are my etudes. Demar teaches Programming 101 to a heterogenous group of more than 200 students. My greatest concern, he says, is how to keep those who already know some (or a lot) of programming interested and occupied. AoC tasks are great because they require various skillsfrom pure coding to algorithms.

Gregor Kikelj, a third-year mathematics undergraduate at the university, first tried Advent of Code in 2019. He did well enough to land himself an internship at Comma.ai (working on Openpilot, its software for semi-automated driving systems), since the founder of the company was also competing. And Kikelj boosted his grade in the programming course (with another professor), since every problem solved was worth extra points on the final examplus bonus points for placing on the leaderboard.

Kikelj (grekiki) got up every morning for the puzzle drop6 a.m. in Sloveniaand ranked 52 overall on the leaderboard, accumulating a total of 23 extra exam points. After that year, they put the cap on the amount of points you can receive to 5, he recalls. But hes still rising with the sun to pounce on the puzzle. This year his best ranking, on day five, was 25thhes aiming to stay in the top 100. Well see how it goes as the problems get harder, Kikelj says.

If the leaderboard is your game, competition is fierce and the daily countdown is keyplayers wait like a hawk for the puzzle to drop, and then click lickety-split to download. Last year, this giant burst of traffic synchronized to a single second (as Wastl describes it) troubled even Amazons load balancers.

The AoC Subredditone of many communities around the internetis full of inside-baseball banter about how to prevail (with solutions and help threads, as well as self-satire and memes). But the best resource is perhaps Brian Chens blog post on how to leaderboard.

Original post:
This puzzle challenge brings joy to the world of code - MIT Technology Review

The open-source, artificially intelligent prosthetic leg designed by researchers at the University of Michigan will be brought to the research market by Humotech, a Pittsburgh-based assistive technology company.

The goal of the collaboration is to speed the development of control software for robotic prosthetic legs, which have the potential to provide the power and natural gait of a human leg to prosthetic users.

We developed the open-source leg to foster the study of control strategies for robotic prosthesesone of the most prominent barriers hindering their public impact, said Elliott Rouse, assistant professor of mechanical engineering and core faculty at U-Ms Robotics Institute.

The open-source leg is now being used by over 10 other research groups to develop control strategies on a common platform, but we noticed some research groups would rather not build it themselves. To maximize the benefit to the public, a product-like solution was needed.

First released in 2019, the open-source legs free-to-copy design is intended to accelerate scientific advances by offering a unified platform to fragmented research efforts across the field of bionics. Now, for labs that need an off-the-shelf robotic prosthesis for research and development, Humotech will provide an assembled version of the open-source leg, including warranty service and technical support.

We see many benefits to standardizing the hardware and software used by the research community, said Josh Caputo, president and CEO of Humotech. The fully contained and powerful open-source leg is a natural expansion of what we can do to support our mission to transform the way the world develops wearable robotics.

By offering a preassembled version with professional support, we hope to improve access to this platform for studying the control of robotic prosthetic legs. Were extremely excited to partner with the University of Michigan on this strategic initiative and together help accelerate research and innovation in the field.

Alejandro Francisco Azocar, Mechanical Engineering Graduate Student Research Assistant puts the finishing connections together before testing an open-source robotic leg designed by Elliott Rouse, Assistant Professor of Mechanical Engineering, and his research group in the G. G. Brown Building on May 28, 2019. Image credit: Robert Coelius, Michigan Engineering

Humotech, originating from Carnegie Mellon University, develops tools for the advancement of wearable robotic control systems and other wearable devices. Using its own research community, Humotech will further build and support a development community around the open-source leg and seek to incorporate the leg into Humotechs Caplex platform. Caplex is a hardware and software testbed that enables researchers to emulate the mechanics of wearable machines, including prostheses and exoskeletons.

In collaboration, Rouses lab and Humotech will also iterate on new versions of the open-source leg to meet the needs of prosthetic wearers and researchers.

The original prosthetic leg was designed to be simple, low-cost and high-performance. Its modular design can act as a knee, ankle or both, with an onboard power supply and control electronics that allow it to be tested anywhere. Rouse collaborated with Levi Hargrove, director of the Center for Bionic Medicine at the Shirley Ryan AbilityLab in Chicago, to develop this first model.

Rouse hopes Humotechs partnership will expand the capabilities of other labs, and enable them to conduct high-impact research. An example of such research that Rouse notes is a Nature Biomedical Engineering article, Design and clinical implementation of an open-source bionic leg, by former mechanical engineering doctoral student Alejandro Azocar.

For researchers looking to build the leg on their own, the prosthetics parts list, assembly instructions and programming remain freely available online.

This collaboration furthers the mission of our open-source leg project, Rouse said. The translation of an open-source research prototype to a commercial product is rare for our field, but our partnership can continue to lower the barrier to research, speed technical advances, and in the end, positively impact lives.

Written in collaboration with Danielle Commisso of Humotech.

Excerpt from:
U-M, Humotech partner to bring open-source bionic leg to research labs - University of Michigan News

Some of the top names in global venture capital have invested more than $100-million in a Toronto startup named after the city of Buffalo with 18 employees, no revenue and big plans to transform how software is developed.

Buf Technologies Inc. said last week it had raised US$93.4-million in four separate financings since its founding 22 months ago, including a US$68-million funding last month co-led by New York funds Lux Capital and Tiger Global.

Other investors include U.S. venture capital firms Amplify Partners, Lightspeed Venture Partners, Addition, Haystack Ventures, Abstraction Capital, Greenoaks Capital Partners and Canadas Garage Capital.

Its the fourth investment this fall in Canada led or co-led by Tiger Global, one of the worlds largest and most prolific early stage investors, known for offering big dollars at rich valuations to young, growing companies with fast closing times and no requests for board seats or other conditions usually set by VC firms.

Bufs early success attracting money is in sharp contrast to Canadas startup scene a decade ago, when many founders here were told by U.S. funders they would have to move south as a condition of receiving funding. Many did.

By contrast, Buf was founded and built in Toronto by an American, software engineer Peter Edge, after leaving his previous job with Uber Technologies in the city, which has seen a huge influx of global tech giants and a proliferation of startups that have flourished without having to move. The team could have built this company anywhere, said Mike McCauley, managing partner of Waterloo, Ont.-based Garage Capital. But theyve chosen to build it in Toronto because its where they believe its the best place to attract the best global talent.

Mr. Edge named the company as both a nod to both his hometown of Buffalo (which is technically the companys headquarters) and also the area of software development it focuses on, known as protocol buffers (or Protobuf) built on top of open-source tools first developed by Google.

In plainer language, Buf is working to make it easier for machines and software programs to communicate with one another. Developers typically create and use software tools known as APIs (application programming interface) that enable different digital technologies to interact. While some of the largest digital companies have adopted technologies such as Protobuf to streamline the development process, much of that work is done by everyone else using less advanced open-source programming tools. Its a laborious process that Mr. Edge said in an interview previously ate up 20 per cent of his engineering working time.

None of us are really providing any business value doing that, Mr. Edge said. A lot of the industry has had a really difficult time bringing it to everyone else in an easy-to-consume way, and we think we have the world experts to actually accomplish it. If we can eliminate a large portion of that code base you need to write it effectively reduces the amount of time your engineers need to spend on all these ancillary tasks. With every company becoming a software company, if you can give back software engineering time, youre giving a company back one of its most valuable assets.

The companys head of business development, Ahron Seeman, a former management consultant, explains its approach is to build schema driven tools analogous to Lego. You know what the interface between two bricks will be, so you can build a chimney before you build a roof because you know exactly how they should connect. Google and Facebook have done that for years. Bufs value is to build software to help [other] companies do that in a more accessible way.

Mr. Edge, who studied computer science and math at Pittsburgh-based Carnegie Mellon University, has recruited at least six of his former colleagues from the ride-sharing giant Uber. Other Buffers previously worked at prominent tech firms Stripe, GitHub, Cisco and Autodesk.

Mr. McCauley said what intrigued us most about the story was that the team had experienced the exact problem they were going after at some of the most well-respected engineering companies and had realized what they were building would be useful to everyone else, but no one had built it for everyone else yet.

Guru Chahal, a partner with Silicon Valley-based Lightspeed, which led Bufs US$3.7-million seed round in September, 2020, said when he met the company it was very clear the potential here is huge, because there is an amount of pain every software team in the world goes through to take those open-source projects and make them usable for the team. If you solved that, youd get paid for it.

Buf released a free open-source program called Buf CLI last year that it says has been downloaded more than a million times. In recent months, it has focused on building its paid tool, called Buf Schema Registry. Several early customers are now testing it out; Mr. Seeman describes them as major enterprises, public companies and household names but wont disclose their identities.

I would expect very soon we will have our first revenue, Mr. Edge said, though he added: Meaningful revenues, to the point where it has a major impact on the business, isnt our primary concern as a 2022 target.

For now the focus is on staffing up to 100 people next year, accelerating development and building up the user base.

While the idea of giving away a product for years is foreign in many sectors, its commonplace in the world of software tool development; other multibillion-dollar-valued companies have deployed similar strategies, including Lightspeed-backed Grafana Labs Inc., and publicly traded Confluent Inc., Elastic NV and HashiCorp Inc.

Our experience is, if you create and provide value to engineering teams, theres enough budget that theyll pay for a version with more support and features, Mr. Chahal said.

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Toronto startup Buf Technologies raises more than $100-million with 18 employees, no revenue - but big plans to change how software is built - The...

Sunne

Admittedly, 2021 has turned out differently than most of us expected, with Hot Vax Summer giving way to "continue to social distance and exercise caution" fall. But as we evolve and adjust to the new new normal, Kickstarter's Design and Tech team continues to be inspired by the many creators and innovators who are rising to the challenge and working toward the public benefit through creativity, great design, and plenty of fun. From groups turning waste into opportunity and harnessing the power of the wind to the ascent of water-saving shower tech and the creation of a sunset you can hang on your windowsill, 2021 was filled with surprise, awe, and optimism for the ways design can enhance everyday life.

These were some of the top trends in a year that defied predictions.

One Clock

The passing of time took on a surreal quality in 2021. We no longer relied on just the minutes, hours, or even days to chart our year, and this shift was reflected in a range of unique projects. The classic clock got some creative upgrades as Author Clock charted each minute in iconic quotes from literature, and OneClock transformed the daily wake up into a less alarming experience thanks to AI-generated music from a Grammy-award-winning composer. Watches also got a reimagining, with Bangle providing open-source programming options for smartwatch users. While the Minimalist Wall Calendar visualized the passing of a year without unnecessary frills, Superlocal went granular, allowing backers to reflect the unique ebbs and flows of life via a clock face.

Motion Kit

This past year many of us took up new hobbies, learned a skill or two, or simply tried to finally assemble that IKEA furniture. For the ambitious, 2021 was great for tinkering and experimenting. From kaleidoscope legend Thea Marshall, Kaleidxscape offered backers the option of building their own fantastical 'scopes. The brainchild of two former physics and design students, MotionKit promised tinkerers the chance to create their own Rube Goldberg-style contraptions. And for those looking to make science and tech fun, PocketLab G-Force designed a STEM kit on wheels by way of a mini car packed with sensors that measure speed and motion to help teach engineering and physics, while CircuitMess Batmobile promised to illuminate the dynamics of autonomous driving in a superhero-friendly package.

Boxx

Life is far from back-to-normal, and many are looking for ways to recreate "outside world" experiences often enjoyed in public spaces into the home. Inspired by her own maternity leave exercise struggles, creator Anna Samuels launched Boxx, the smart punch bag and app for training from your living room. Nimble offered a robotically applied salon-quality manicure right on your bedside vanity, while Light Pong's interactive ping pong promised all the fun of games night at the local dive.

There also continues to be enthusiasm for virtual reality and the prospect of traveling to wherever you'd like while remaining at home. Lynx launched the latest in AR and VR with its open and versatile headset, beaming wearers into central Paris or simply into their favorite game, while Tundra Tracker promoted its Full Body tracking, cross-compatible with any SteamVR device.

Ebo Smart Robot

They don't shed, need to be walked, or have bathroom emergencies and for robot pets, 2021 was absolutely their year. Drawing clear inspiration from Boston Dynamics' Spot, MangDang's Mini Pupper is an extremely cute way to learn robotics, while the XGO Mini scampered its way into our hearts. The Ebo Smart Robot's camera and AI-equipped roaming bots utilize a speaker and advanced mobility to provide connectivity and companionship to family members (both two and four-legged), while FerroPet uses electromagnets to make alien goo (aka ferrofluid) dance.

Shine Turbine

Last year saw many of us embracing the outdoors with new zest, and that trend extends to projects that offer creative ways of capturing and storing green energy. Shine Turbine launched a powerful portable turbine small enough to toss into a backpack; EcoFlow promised energy independence with a portable home battery equipped for smart energy management; Sunne captured the sun's rays during the day to illuminate an elegant window light at night; and Solar Cow's cow-shaped solar panel, equipped with electric udders for charging portable batteries, generated electricity while helping underserved children attend school.

Nutshell Cooler

The popularity of inventive reuse and repurposed circular waste continues to produce new and innovative projects on the platform, particularly in fashion and style. The year saw the creation of caffeinated gear with Panto Coffee Boots and Baseline Midlayer's hoodies made from recycled coffee grounds, as well as jaunty headwear from Storied Hats, created with a fusion of coffee, algae, and cactus. Standouts also included grappaSac's stylish bags made from grape waste left by the international wine harvest and EcoTrek's pants knitted from recycled ocean buoys.

Bringing sustainability into home design, Welli Bins, made from sugarcane, launched a collection of sustainable plant-based storage bins, while SOAPBOTTLE crafted an entirely-sustainable home goods line. In high-end, Ohmie unveiled an elegant lamp made from recycled oranges, Gomi speakers transformed recycled e-waste and ocean plastic into portable sound systems, and Nutshell Cooler upcycled coconut waste into eco-friendly to-go insulation.

REFRAMD

To capture imaginations, designers are focusing on adding positivity to the world. Called to action by her battle with cancer, shoe designer Nelli Kim launched REDEN, a line of kicks created with orthopedic surgeons to ease foot pain; REFRAMD unveiled a series of digitally tailored glasses custom made for Black nose profiles and others underserved by traditional retailers; and EONE Switch's inclusivity-designed watches sought to help vision-impaired wearers tell time by touch. Forgoing fast fashion's environmental waste, La Guapa unveiled clothing from vintage wool blankets, the line also providing Melbourne, Australia's refugee community with work and learning opportunities.

Inclusivity was also key. In 2021, Dynasty George revealed a line of elegant, maternity-friendly dresses; Ponderosa by Alpine Parrot offered female hikers size 14-24 options for hitting the trails; and Victoria Jenkins, a garment technologist who became Disabled in her 20s, Unhidden, unveiled a series of adaptive garments that accommodate mobility challenges.

uFactory Lite 6 robotic arm

When desktop 3D printers first emerged a decade ago, they were slow, expensive, routinely failed, and we absolutely loved every second of watching a real object emerge from the digital ether. These days, 3D printing may feel less novel, but the machines themselves are much more capable. Creality's CR-30 filament printer, a follow up to their extremely popular CR-6 SE campaign from 2020, features a conveyer belt, allowing you to print a parade of identical models that would be too long for most printers to create in a single piece. The team at Elegoo were also thinking big with their Jupiter resin printer, bringing the intricate detail of SLA printing to a large format. And the Revopoint POP, a handheld 3D scanner, lets you turn the world around you into 3D models for printing or maybe showcased on the Looking Glass Portrait, a holographic display that shipped in 2021.

Beyond 3D printing, we saw quite a range of innovative tools for helping you bring your ideas to life. Carvera aims to reduce CNC mills' steep learning curve, YesWelder offers a budget-and-space-friendly entry point into the world of metal fabrication, and xTool's M1 combines laser and blade cutting technologies to let you work with a wide range of materials. For those of us who don't own a giant factory building to house industrial robots, the uFactory Lite 6 robotic arm brings the power of automated manufacturing and testing to a more manageable scale.

Keyboardio Model 100

Heading into year three of working from home, it's no surprise that we've seen a steady stream of products designed to make the experience of sitting at your computer a little more comfortable. And Kickstarter remains a hub for mechanical keyboard enthusiasts: Keychron launched three new variations on their highly-customizable designs, Mojo68 embraced quirky design and bold color palettes, and the Keyboardio Model 100 sporting a hardwood enclosure, split keyboard, and open-source firmware clicked with backers. If QWERTY alone doesn't cover your human-computer interface needs, TourBox offers a versatile controller with mappable dials and buttons to enhance film editing, music production, digital illustration, and more.

Portable displays that allow you to take your home setup anywhere are also a trend worth watching. Arovia's Splay lets you carry up to an 80" screen in your backpack thanks to a patented folding mechanism, and Espresso Display's portable touchscreen monitor earned a spot on Time's 'Best Inventions of 2021' list for giving adherents to the two-screen lifestyle a portable option.

Want to see what else is on the horizon? Browse some of our favorite projects.

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Kickstarter's Year in Design and Tech Trends - Core77.com

Gourav Singh Bais

Gourav is an applied machine learning engineer at ValueMomentum Inc. He is skilled in developing machine learning/deep learning pipelines, retraining systems and transforming data science prototypes to production-grade solutions. He has been working in the same field for the last three years and has served a lot of clients including Fortune 500 companies, which provided him the exposure to build experience and skills that can contribute to the machine learning community.

As a data professional, you may come across some datasets with few independent variables (input variables). One variable would be time, and the other can be any sort of time-dependent column, such as the number of bookings in a hotel or the number of passengers on a flight.

This type of data is referred to as time-series data, which has some type of trend and captures a point in time. There are various ways of storing this type of data, such as relational databases or files, like CSV or Excel. However, these options are not designed to efficiently store the time-series data. Enter time-series databases, which are specifically designed to efficiently and quickly store time-series data.

There are various use cases where time-series databases (TSDB) perform significantly better than other storage mechanisms. Consider a few:

Furthermore, there are several advantages to using a time-series database over other storage mechanisms for that data type. Here are a few reasons:

One widely used time-series database is InfluxDB. The company InfluxData created InfluxDB, an open source time-series database. Its written in Go for storing and retrieving time-series data for any use case, including operations monitoring, application metrics, Internet of Things (IoT) sensor data and real-time analytics.

To learn more about the benefits of InfluxDB, you can refer to the InfluxData website.

In this article, you will learn what is needed to get started in InfluxDB with R language, starting from installing, setting up, querying, writing and finally, building a simple time-series application using R.

Clients interacting with InfluxDB using any programming language must be able to connect to the database so that different database operations can be carried out. The influxdb-client-r library can be used to connect to InfluxDB using R. Its a package that supports operations, like writing data, reading data and getting the database status. This client library works with InfluxDB version 2.0.

Lets start with setting up InfluxDB using version 2.0. InfluxDB is available on different platforms, like Windows, Linux and macOS. Examples that you will see in this article are tested against macOS Big Sur, although installing it on any platform is simple.

Alternatively, you can use InfluxDB Cloud to quickly get a free instance of InfluxDB running in minutes without having to install anything locally on your machine.

InfluxDB can be installed on macOS using Homebrew:

```$ brew update$ brew install influxdb influxdb-cli```

```

$ brew update

$ brew install influxdb influxdb-cli

```

Alternatively, InfluxDB can be manually downloaded here.

Once InfluxDB is installed, you can start it by using this code:

The first time you start InfluxDB, it will ask you to set up the account, which can be carried out using the UI [localhost:8086](localhost:8086) or command line interface (CLI). For a UI setup, you will have to open the localhost URL and provide the information required for the initial setup. If youre using CLI, youll need to do it with the InfluxDB client, which can be started in the terminal using the following code:

For the initial setup, note the following details:

Username: You can choose any username for the initial user.

Password: You need to create and confirm a password for database access.

Organization name: You need to choose the initial organization name.

Bucket name: An initial bucket name is required, and you can create as many buckets as you want to work with.

Retention period: The time period your bucket will store the data before deleting it. You can choose **never** or leave it empty for an infinite retention period.

To install InfluxDB on other platforms, refer to the following link.

Once you have installed InfluxDB and completed the setup, you can log in to [localhost:8086](localhost:8086). You should see a screen like this:

You can take a look through the various modules included in the dashboard, though this article will primarily focus on those through which you can connect to the InfluxDB client. Start with the data module:

Here, you can observe different sections, like Sources, Bucket, Telegraf, Scrapers, and Tokens. To interact with InfluxDB using R, youll need to check the Buckets and Tokens sections. To connect with the database, youll need to have a private token (key) generated that is only accessible to you, allowing you to connect to different buckets.

To generate this token, navigate to the Tokens tab. On the right side, you will see a Generate Tokens button. This button has two different sections:

Read/Write Token: This token provides read and write access to different buckets, which can be limited to the scope (to specific buckets) or provided to all the buckets available. With this token, you can only read and write the data in an organization.

All-Access Token: This token provides full access to actions, like reading, writing, updating or deleting each bucket. This would be the recommended token through which you can connect to any bucket available without any explicit configuration and can perform all the needed actions, like read, write, update and delete.

For the purposes of this article, youll want to generate an All-Access Token. Once the token is generated, you can access it anytime by simply logging into the localhost console.

Now that you have InfluxDB all set up, you can download R and RStudio for writing and testing the code. Installing R is pretty simple. You can download the package here, then open and install it. After the R installation, you can download RStudio, which will be the IDE that you use to write the R code. You can download RStudio here.

At this stage, you have almost all the tools and technologies needed to connect to InfluxDB. As the last step, you need to install the InfluxDB client library for R, which can be downloaded using the following line of code:

```install.packages("influxdbclient")```

```

install.packages("influxdbclient")

```

If you install it on RStudio, other dependencies will be downloaded along with the base library. However, if dependencies are not automatically downloaded, you can separately download them using the following line of code:

```install.packages(c("httr", "bit64", "nanotime", "plyr"))```

```

install.packages(c("httr", "bit64", "nanotime", "plyr"))

```

The next step will be to import the InfluxDB client library in R and create an instance of InfluxDBClient that can be used to interact with the database and perform all sets of operations. Parameters required to make a database connection include the following:

Since this connection will be made locally, the connection script should look like this:

If you are using a cloud account make sure the URL parameter matches the region your cloud account is located in, rather than using localhost. You can find the URL endpoints in the docs.

Now that you have established a connection to InfluxDB, its time to use the data to perform different database operations. To understand these operations, lets take a look at some sample data of worldwide COVID-19 casesfrom January 2020 to April 2020:

This sample data contains the following fields:

To read the data frame in R, you will need to write the following line of code:

Lets start by first inserting this data into InfluxDB. To do so, use the write() method, which accepts parameters like this:

```client$write(data, bucket, precision, measurementCol,tagCols, fieldCols, timeCol, object)```

```

client$write(data, bucket, precision, measurementCol,

tagCols, fieldCols, timeCol, object)

```

Note: The above method is simply a function definition, not part of the code.

This method takes the following parameters:

To store the COVID-19 data in InfluxDB using the write() method, you will need to make sure that your time-stamp column (Date) is in POSIXct format.

The response from the write() function can be NULL, True, or an error. To debug the write() function and check how the data is being written in the database, you can assign an object: lp.

Now that you have your time-stamped data stored in the database, lets try reading the data. For querying the data using the R client, the read() function is used, which expects a Fluxquery. For querying, you can make use of the same client that you created for writing the data or you can create a new InfluxDB client and do the same.

Lets break down the above query. Starting with the keyword from, youll need to first specify the bucket name, followed by the range of time from which you want to select the data, and finally, a set of conditions. In the above query, the condition specifies not to include the start and stop columns from the database.

The result contains a list of data frames for each entry made in the database for the specified period. To check an instance of it, you can use the following code:

Now that you have queried the data, lets make use of this data for forecasting purposes. Here, you will be training a time-series model on the data retrieved and will try to predict the next five days cases. Lets create a dataframe from the results that you have after querying:

Once the dataframe is created, there are some changes that will be required to apply the time-series model on it. Typically, this stage is data preprocessing.

After preprocessing, now its time to create a time-series representation of our data. This would be done using the following code:

Finally, lets fit the data into the forecasting model and make the predictions for the next five days:

That is how data can be accessed and used for time-series forecasting, which is just one practical use case for the time-stamp data. The whole implementation can be found here.

For more information and best practices for optimizing the performance of InfluxDB, refer to the docs.

After reading this article, you now know how to set up InfluxDB in your system, as well as how to create a client and to write and read data for your time-series use case using R language. One major advantage of InfluxDB is that it comes with support for almost all major programming languages.

There are several options for storing time-series data, but time-series databases, like InfluxDB, can do so more quickly and on a higher scale. Several use cases, such as IoT applications, automated cars or real-time application analysis, need data insertion from as little as tens of thousands to as many as hundreds of thousands of entries at a time. Time-series databases perform this task at a very high speed and in real time, allowing them to be easily adapted by any developer working on a real-time time-series application. Be sure to consider deploying InfluxDB to use these great features in your own applications.

The New Stack is a wholly owned subsidiary of Insight Partners, an investor in the following companies mentioned in this article: Real.

Featured image via Pixabay.

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Getting Started with R and InfluxDB The New Stack - thenewstack.io