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We have 2 presenters for this month's VIRTUAL MEETING.
Attend my going at 7pm Thursday the 14th to: https://lufthans.bigbluemeeting.com/b/plu-yuk-7xx

Matt McGrae: Getting Started with Nextcloud

Description:
A brief history of Nextcloud and why you might want to use it for yourself.

der.hans: Big Blue Button Video Conferencing

Description:
Big Blue Button (BBB) is a Free Software video conferencing tool with good moderation tools.
Originally created for use with classrooms, it also has instructional options and ties into Moodle.

BBB doesn't require extra software to use with desktops, lapstops, phones or tablets as it uses the WebRTC browser standard.

BBB Presentation features include:

* video conferencing
* shared chat
* shared editing
* showing documents and video
* breakout rooms

The Greenlight project is an addon for instance administration.

It includes some necessary moderation tools including:

* password protected call
* waiting room
* presenter role
* participant sharing restrictions ( lock out microphone, video, chat, etc. )
* kickout disruptors

The presentation will cover using Big Blue Button from an attendee's perspective, including a feature list and a tour of the user interface.

AZLoCo has been using Big Blue Button on a home server for at least a decade.
Recently BBB switched to WebRTC and the LoCo has been quite happy with that upgrade.

In the Free Software community there are some community run BBB instances available for testing.
You can also install BBB on your own system and run your own instance.
Alternatively, there are a few commercial hosting options available.

The PLUG general meeting will use a hosted Big Blue Button instance.
The Free Software Stammtisch will also use the hosted BBB instance for this month's meeting on Tuesday the 19th.

Biography:
der.hans is a technology and entrepreneurial veteran.

He is chairman of the Phoenix Linux User Group (PLUG), Promotions and Outreach chair for SeaGL, BoF organizer for the Southern California Linux Expo (SCaLE) and founder of the Free Software Stammtisch. He presents regularly at large community-led conferences (SCaLE, SeaGL, LFNW, Tübix, OLF, TXLF) and many local groups.

Currently a Customer Data Engineer at Object Rocket. Public statements are not representative of $dayjob.

Mastodon - https://floss.social/@FLOX_advocate

Plume - https://fediverse.blog/~/LuftHans

1. To Microservices and Back Again: Why Segment Went Back to a Monolith — microservices came with increased operational overhead and problems around code reuse. … If microservices are implemented incorrectly or used as a band-aid without addressing some of the root flaws in your system, you’ll be unable to do new product development because you’re drowning in the complexity.
2. GNU poke — interactive editor for binary data. Not limited to editing basic entities such as bits and bytes, it provides a full-fledged procedural, interactive programming language designed to describe data structures and to operate on them. (via Kernel Recipes)
3. Blender — Facebook open sourced their open-domain (“can talk about anything!”) chatbot. Human evaluations show our best models are superior to existing approaches in multi-turn dialogue in terms of engagingness and humanness measurements.
4. CopyLeft Conf 2020 Videos — the schedule has more info on each talk.

1. podpaperscissors — From the classic “prisoner’s dilemma” to more obscure coördination games, Pod Paper Scissors takes game theory out of the dry textbook and into the real world. … Each episode will feature different kinds of games and situations. Experts in a variety of fields will casually converse with the hosts about how the particular game discussed applies to their work. Some episodes feature original music inspired by the topic at hand. The podcast is hosted by game theorist Ben Klemens and science journalist and composer Liz Landau. (via Ben Klemens)
2. Verification Handbook (3ed) — latest guide to investigating disinformation and media manipulation, covering identifying actors, investigating platforms, tracking ads, etc. (via Craig Silverman)
3. Ransomware Groups (Microsoft) — analysis of ransomware campaigns yields this report, which includes a great graphic taxonomy of ransomware payloads.
4. Bug Stories — great tales of bugs and bug-hunting from the past.

1. Learning a Language — this list of questions facing anyone taking a new language for a test run just burns with truth. (Also: encouraging to see how many of these questions are answered by the Cookbook format)
2. OpenVAS — Open Vulnerability Assessment Scanner, aka “what a cheap external security assessment vendor will run and then mail you the report from.”
3. Paxos vs Raft: Have we Reached Consensus on Distributed Consensus? — We find that both Paxos and Raft take a very similar approach to distributed consensus, differing only in their approach to leader election. Most notably, Raft only allows servers with up-to-date logs to become leaders, whereas Paxos allows any server to be leader provided it then updates its log to ensure it is up-to-date. Raft’s approach is surprisingly efficient given its simplicity as, unlike Paxos, it does not require log entries to be exchanged during leader election. We surmise that much of the understandability of Raft comes from the paper’s clear presentation rather than being fundamental to the underlying algorithm being presented.
4. Google Research Football — a novel Reinforcement Learning environment where agents aim to master the world’s most popular sport—football. Modeled after popular football video games, it provides a physics based 3D football simulation where agents control either one or all football players on their team, learn how to pass between them, and manage to overcome their opponent’s defense in order to score goals.

1. Teleforking a Process onto a Different Computer — a working proof of concept (I just don’t replicate tricky things so that I could keep it simple, meaning it’s just a fun tech demo you probably shouldn’t use for anything real) of a telefork() function call that spawns a process on another machine and returns the instance ID.
2. Consistency Maps — Jepsen analyses the safety properties of distributed systems–most notably, identifying violations of consistency models. But what are consistency models? What phenomena do they allow? What kind of consistency does a given program really need? In this reference guide, we provide basic definitions, intuitive explanations, and theoretical underpinnings of various consistency models for engineers and academics alike.
3. wasmachine — wasmachine is an implementation of the WebAssembly specification in a FPGA. It follows a sequential 6-steps design.
4. Expert Twitter Only Goes So Far: Bring Back Blogs (Wired) — we’re surrounded by opinion machines (because opinion is cheap to produce and make inflammatory, it’s a natural fit for engagement-driven businesses), so it’s nice to find knowledgeable people sharing their expertise. I see The Syllabus and newsletter systems like substack as part of the response to this dearth of high-alpha content. More please!

1. The Suddenly Remote Playbook — I just want to note that if you have to look after kids when you’re supposed to be working, you’re not working from home. Not everyone’s getting a glorious introduction to the delights of working from home.
2. taichi — a programming language designed for high-performance computer graphics. It is deeply embedded in Python, and its just-in-time compiler offloads compute-intensive tasks to multi-core CPUs and massively parallel GPUs.
3. The Cost of Training NLP Models — We review the cost of training large-scale language models, and the drivers of these costs. The intended audience includes engineers and scientists budgeting their model-training experiments, as well as non-practitioners trying to make sense of the economics of modern-day Natural Language Processing (NLP).
4. Killing Net Neutrality Did Not Save the Pandemic Internet — there’s no evidence that European networks have fallen apart during the COVID-19 crisis. Or that any differences in performance have anything to do with deregulation or net neutrality. Netflix’s decision to throttle back its bandwidth usage by 25% was done entirely pro-actively. There was no underlying network data provided by regulators to justify the move. It was just EU regulators being cautious (perhaps overly so). Indeed, similar steps have been taken here in the States. YouTube for example has downgraded video quality to conserve bandwidth. So has game platform Steam, which is slowing some game downloads. You can’t selectively highlight the EU’s efforts on this front then ignore the US ones because it supports your flimsy narrative. Well I guess you can, but you should be laughed at.

1. Moloch — Large scale, open source, indexed packet capture and search.
2. 3Dify Instagram Photos — open source toolset for adding a 3d effect to photos on Instagram’s web site. It uses 3d-photo-inpainting running in Colab (free GPU) and Cloud pubsub/storage for communication. A glimpse of the future: we could augment all our apps with deep learning-based services, but we still need to conquer paying for the GPUs and making it easy to use.
3. xkcd 2295 — data science in a nutshell.
4. Spotify Doesn’t Use “the Spotify Model” and Neither Should You (Jeremiah Lee) — I no longer work at Spotify, so I am sharing my experience to set the record straight. The Spotify squad model failed Spotify and it will fail your company too. EXTREMELY well-written. Full of killer points like Every responsibility a team cedes to increase its focus becomes a new cross-team dependency.

Three months ago, Apple released a new credit card in partnership with Goldman Sachs that aimed to disrupt the highly regulated world of consumer finance. However, a well-known software developer tweeted that he was given 20x the credit line offered to his wife, despite the fact that they have been filing joint tax returns and live in a community property state. The story went viral on Twitter, and led to an official government investigation for bias.

Even if Apple—the privacy leader—did not discriminate on gender, it experienced one of its worst product launches in recent history. 

Apple’s customer base and bankable style combined with Goldman’s knowledge of the financial industry must have seemed like an unbeatable combination. Apple is a great producer of computer hardware, while Goldman knows finance and its complex rules backwards and forwards. If anyone could launch this product right, it would be these two companies.

Ultimately, Apple learned a critical lesson from this experience. User buy-in cannot end with compliance with rules. It requires ethics, constantly asking how to protect, fight for, and empower users, regardless of what the law says. These strategies contribute to perceptions of trust.

Trust has to be earned, is easily lost, and is difficult to regain.

Compliance and ethics

Compliance is a simple concept: “we followed all applicable rules and regulations.” Compliance minimizes the possibility of being fined and gives you a defense if you’re taken to court. You can hire compliance experts to advise you, and lawyers to defend you. That said, compliance allows plenty of room for bad, unethical behavior. For example, payday lending businesses are no doubt compliant with the law, but many aren’t models for good corporate citizenship.

Ethics is much more slippery. It’s not about staying within legal boundaries; ethics is a discussion about what’s right, not a set of rules. It’s about living a “good” life, acting in a way that allows you to live with yourself and others. There aren’t simple standards and tests for ethical behavior, nor are you as likely to be called into court for acting unethically. But unethical behavior is likely to lose your customers’ or business partners’ trust; they will view your actions with suspicion.

The importance of ethics does not, however, mean companies should ignore compliance

Compliance functions are powerful because legal violations result in clear financial costs. The European Union’s General Data Protection Regulation (GDPR), for instance, imposes fines of up to 2%–4% of global annual revenue. This could mean millions, if not billions, of lost revenue. The era in which fines were merely a cost of doing business appears to be ending. Fines in the billions have been levied against Google and Facebook, and Practice Fusion (an electronic medical records company) has agreed to a $145 million settlement for using “its EHR software to influence physician prescribing of opioid pain medications.”

Because of its clear impact on the bottom line, compliance often reshapes business operations. For instance, financial companies are investing millions into using artificial intelligence to comply with anti-money laundering regulations or stricter data regulations.

Because compliance is so clear-cut, it is tempting to substitute compliance for ethics

Don’t do it. 

As the Apple case illustrates, rule-following is not sufficient for trust-building. Laws are frequently a minimum standard; they set a low bar. As a privacy leader in the technology space, Apple knows this well and has benefited from a strong reputation as a data steward.

For one, the law often lags behind technology and user expectations. Organizations that simply follow the rules will be sideswiped by rapidly changing technology and user expectations. Case in point: the public hearings after the outrage over Facebook’s Cambridge Analytica. Here, the public discovered that even highly experienced senators didn’t fully understand key technologies, like Facebook, much less their potential harm on users.

Furthermore, compliance-only companies will play a seemingly insurmountable game of “whack-a-mole” as new data regulations pass around the world. New rules will catch these organizations off-guard, especially when they use emerging technologies and face ambiguous rules.

Finally, investors from BlackStone to JP Morgan are beginning to prioritize environmental, social, and governance metrics—like ethics—into its definition of shareholder value. Legal compliance is increasingly inadequate for this powerful stakeholder.

As a result, to build trust, a company should lead with ethics

In our more global, diverse, and rapidly- changing world, ethics may be embodied by the “platinum rule”: Do unto others as they would want done to them. One established field of ethics—bioethics—offers four principles that are related to the platinum rule: nonmaleficence, justice, autonomy, and beneficence.

For organizations that want to be guided by ethics, regardless of what the law says, these principles as essential tools for a purpose-driven mission: protecting (nonmaleficence), fighting for (justice), and empowering users and employees (autonomy and beneficence).

An ethics leader protects users and workers in its operations by using governance best practices. 

Before creating the product, it understands both the qualitative and quantitative contexts of key stakeholders, especially those who will be most impacted, identifying their needs and fears. When creating the product, it uses data protection by design, working with cross-functional roles like legal and privacy engineers to embed ethical principles into the lifecycle of the product and formalize data-sharing agreements. Before launching, it audits the product thoroughly and conducts scenario planning to understand potential ethical mishaps, such as perceived or real gender bias or human rights violations in its supply chain. After launching, its terms of service and collection methods are highly readable and enables even disaffected users to resolve issues delightfully.

Ethics leaders also fight for users and workers, who can be forgotten. These leaders may champion enforceable consumer protections in the first place, before a crisis erupts. With social movements, leaders fight powerful actors preying on vulnerable communities or the public at large—and critically examines and ameliorates its own participation in systemic violence. As a result, instead of last-minute heroic efforts to change compromised operations, it’s been iterating all along.

Finally, ethics leaders empower their users and workers. With diverse communities and employees, they co-create new products that help improve basic needs and enable more, including the vulnerable, to increase their autonomy and their economic mobility. These entrepreneurial efforts validate new revenue streams and relationships while incubating next-generation workers who self-govern and push the company’s mission forward. Employees voice their values and diversify their relationships. Alison Taylor, the Executive Director of Ethical Systems, argues that internal processes should “improve [workers’] reasoning and creativity, instead of short-circuiting them.” Enabling this is a culture of psychological safety and training to engage kindly with divergent ideas.

These purpose-led strategies boost employee performance and retention, drive deep customer loyalty, and carve legacies.

To be clear, Apple may be implementing at least some of these strategies already—but perhaps not uniformly or transparently. For instance, Apple has implemented some provisions of the European Union’s General Data Protection Regulation for all US residents—not just EU and CA residents—including the ability to access and edit data. This expensive move, which goes beyond strict legal requirements, was implemented even without public pressure.

But ethics strategies have major limitations leaders must address

As demonstrated by the waves of ethical “principles” released by Fortune 500 companies and commissions, ethics programs can be murky, dominated by a white, male, and Western interpretation.

Furthermore, focusing purely on ethics gives companies an easy way to “free ride” off social goodwill, but ultimately stay unaccountable, given the lack of external oversight over ethics programs. When companies substitute unaccountable data ethics principles for thoughtful engagement with the enforceable data regulation principles, users will be harmed.

Long-term, without the ability to wave a $100 million fine with clear-cut requirements and lawyers trained to advocate for them internally, ethics leaders may face barriers to buy-in. Unlike their sales, marketing, or compliance counterparts, ethics programs do not directly add revenue or reduce costs. In recessions, these “soft” programs may be the first on the chopping block.

As a result of these factors, we will likely see a surge in ethics-washing: well-intentioned companies that talk ethics, but don’t walk it. More will view these efforts as PR-driven ethics stunts, which don’t deeply engage with actual ethical issues. If harmful business models do not change, ethics leaders will be fighting a losing battle.

Yet despite these tremendous barriers, leaders must weave ethics into their strategies

Ethics must be embraced by top leaders, who must fundamentally shift corporate governance, C-suite incentives, strategic roadmaps, and daily operations to empower stakeholders. Inconsistent or wishy-washy company behavior will severely harm, not build, trust.

To move beyond narrow interpretations of ethics, ethical leaders must engage with critiques—like the Feminist Data Manifest-no. These push leaders to investigate and ameliorate power relations, marginalizing processes, and the history of injustice against vulnerable communities.

Similarly, leaders must engage with international human rights frameworks (IHRFs), such as the Universal Declaration of Human Rights and International Covenant on Economic, Social and Cultural Rights. While these have often been enforced against states (fighting, for instance, censorship, unfair trials, and torture), supporters nonetheless argue IHRFs afford a rich ecosystem of multilateral organizations, compliance approaches, shared language, and jurisprudence to help organizations balance human rights against competing interests, like innovation.

To gain more buy-in from top internal business leaders, ethics leaders can form coalitions with compliance, data, and even marketing departments. By leading programs with resources and measurable accountability, ethics leaders must articulate how ethics improves trust and loyalty. The effectiveness of such coalitions may explain the rise of chief ethics and compliance officers— as well as a host of new chief trust, social responsibility, citizenship, and data officers by technology leaders like Salesforce, Workday, and Unisys. Robert Smith, Director of Ethics and Compliance at InterContinental Hotels Group, agrees, arguing that these related teams should speak with “one voice.”

To further bolster support, leaders should consider participating and learning from new cross-sector coalitions. These include those focused (a) on specific technologies like AI, such as The Partnership on AI, (b) on specific industries, such as health (All-in), government (Civic Data Privacy Leaders Network), and cities (Cities Coalition for Digital Rights or the Right to the City Alliance); or (c) on a general set of emerging issues, such as IEEE, WEF, Metrolab, or Data Collaboratives Research Network. Due to the wide variety of community, academic, and nonprofit leaders, these coalitions also provide invaluable opportunities for leaders to diversify their networks and challenge their assumptions.

While incorporating human rights and ethics into business strategies may be costly in the short run, over the long term, Paul Barrett, deputy director of New York University’s Center for Business and Human Rights, argues that “companies will benefit financially from operating humane, efficient supply chains and employing motivated workers proud of their jobs.”

Ultimately, organizations that discard ethics may find themselves on the wrong side of history. They risk becoming the redlining banks that excluded communities of color from loans due to perceived financial risk, or the government agency that denied treatment to African Americans suffering from syphilis due to a desire to for innovative research, or the billion-dollar company whose planes killed 346 people, after placing “undue” pressure for safety approvals of new algorithms to improve take-off performance.

In the next decade, leaders—from Apple to the next venture-financed startup— will use cutting-edge technologies in a fight for competitive advantage and better operations. But those that succeed in our history books protect, fight for, and empower their users, including the most vulnerable.

Leaders must not give up.

1. Posthog — open source product analytics.
   
2. Into the Mainframe (Recurse) — the interviews with two mainframe programmers are a great reminder of how much things have changed. And how they haven’t. For instance, later in my career I kept a weighted punching clown in my office. As programmers, we liked our users, but we also sort of hated them. They would make all these unreasonable requests, give us bad data, stuff like that. So all my staff could come by my office when they were mad at their users and punch the clown to feel better. It was fun. I had two doors in my office, and one time some guy I’d never seen before in my life walked into my office without knocking, punched the clown, and walked out the other door. Never saw him again.
   
3. NetLogo — a multi-agent programmable modeling environment. For simulations/modeling.
   
4. Things I Wished More Developers Knew About Databases (Jaana B. Dogan) — really good points, hard won from experience. You are lucky if 99.999% of the time network is not a problem.

1. It’s Time to Learn (Scott Berkun) — a strong response to Marc Andreessen’s It’s Time to Build. It feels like we are in a disrupted time when anything is possible, and folks are wondering where the levers are to pull.
2. pygraphistry — a library to extract, transform, and visually explore big graphs.
3. Desert Island Devops — a single-day virtual event, to be livestreamed on twitch.tv/oncallmemaybe on April 30th, 2020. All presentations will take place in the world of Animal Crossing: New Horizons.
4. MSFT’s Machine Learning-Powered Bug Sorting — Since 2001 Microsoft has collected 13 million work items and bugs. We used that data to develop a process and machine learning model that correctly distinguishes between security and non-security bugs 99 percent of the time and accurately identifies the critical, high priority security bugs, 97 percent of the time. This is an overview of how we did it. Part of the ongoing augmentation of developers by (ML-powered) software.

1. CastleDB — a structured static database […]. CastleDB looks like any spreadsheet editor, except that each sheet has a data model. […] stores both its data model and the data contained in the rows into an easily readable JSON file. […] allows efficient collaboration on data editing.
2. Mainframes Are Having a Moment (IEEE Spectrum) — Although many college and university computer science departments have cut back or dropped mainframe programming curriculum to focus on more modern languages and technologies, faculty and staff at others report an uptick in interest in Cobol and related classes. The increase began well before pandemic-related layoffs inundated state unemployment agency computer systems, causing government officials to put out the call for programmers who know Cobol to step in and help.
3. swimOS — a complete, self-contained distributed software platform for building stateful, massively real-time streaming applications. swimOS implements a distributed microkernel, called the Swim Kernel, that is persistent without a database, reactive without a message broker, autonomous without a job manager, and which executes general purpose stateful applications without a separate app server.
4. Using a Self-Rewriting README Powered by GitHub Actions to Track TILs (Simon Willison) — writing down what you’ve learned how to do keeps it fresh. I’ve been doing it for years, as have other people — check out this person’s astonishing collection.

1. Nebula —open source distributed, scalable, lightning-fast graph database.
2. COBOL Programming Course — from the Open Mainframe Project.
3. Serverless Handbook — a resource teaching frontend engineers everything they need to know to dive into backend.
4. Novel Annealing Processor Is the Best Ever at Solving Combinatorial Optimization Problems (IEEE Spectrum) — Dubbed STATICA (Stochastic Cellular Automata Annealer Architecture), the processor is designed to take on challenges such as portfolio, logistic, and traffic flow optimization when they are expressed in the form of Ising models.

1. Kanboard — free and open source Trello-like Kanban boards.
2. Remote Work Playbook — really useful advice on the actual mechanics of working remotely, not just which tools to use but how to use them. E.g., As an individual contributor, is there something you just did that you think a colleague would have to do at some point in the future, would this have been easier and faster if you had a document to consult? If your answer to both questions is yes, write documentation for the thing and store in a common place where your team can access. Notion is a great place to store this. You should also share the link in your instant communication channel so your colleagues are aware.
3. avatarify — deep fake technology used to give you avatars of your choice for use in Zoom and Skype.
4. pstress — Database concurrency and crash recovery testing tool. (via Percona blog)

1. Coding vs Programming (John Gruber) — I’d noticed this linguistic change too. See also Engineering vs Programming vs Computer Science. Coding is shorter so it’s probably gaining in popularity because shorter is easier to say and thus more convenient.
2. micrograd (Andre Karpathy) — A tiny Autograd engine (with a bite! :D). Implements backpropagation (reverse-mode autodiff) over a dynamically built DAG and a small neural networks library on top of it with a PyTorch-like API. Both are currently about 50 lines of code each.
3. Game Cheating in Hardware — pcileech WebRadar is a browser based radar cheat for CS:GO that can be run on a different PC, connected to a PCIe card providing direct memory access to the target computer. It’s like doping for e-sports. (via Luke Weston)
4. Radar Trends to Watch: April 2020 — early weak signals of interesting developments in Ops & Infrastructure, Software Development, AI & ML, and Quantum Computing. Plus the unavoidable Coronavirus-driven changes.

1. The Science of Happiness — free enrolment in Berkeley’s MOOC to teach positive psychology. Learn science-based principles and practices for a happy, meaningful life.
2. The New Business of AI (A16Z) — many AI companies have: Lower gross margins due to heavy cloud infrastructure usage and ongoing human support; Scaling challenges due to the thorny problem of edge cases; Weaker defensive moats due to the commoditization of AI models and challenges with data network effects.
3. Group Chat: The Best Way to Totally Stress Out Your Team — Group chat is like being in an all-day meeting, with random participants, and no agenda.
4. Human Standards Project — p2p-shared international and device manufacturer standards to assist diy ventilator and masks teams.

Since early in March, technology news has been all Coronavirus, all the time. That’s a trend we expect to continue through April and probably beyond. So let’s start with Coronavirus news, and hope that we have something different for next month.

Coronavirus

• The Coronavirus pandemic is forcing reconsideration of how private data is used.  Maciej Ceglowski’s post “We need A Massive Surveillance Program” is important, particularly since Maciej has a long history as a privacy advocate. At the same time, many other privacy advocates are saying, “Be careful what you give up, because you won’t get it back,” including Edward Snowden.
• A number of organizations are using blockchains as a way of sharing coronavirus data. I don’t think this will be the blockchain killer app (it’s too specialized), but it might be the killer demo. 
• While the maker movement of a decade ago has died back, it’s worth noting that the coronavirus has spawned a lot of maker projects—from facemasks to ventilators, and many things in between. 
• 24,000 Coronavirus research papers in one archive: Now the question is how researchers will use this archive effectively. There’s really only one answer: automatic summarization and intelligent search using AI. 
• Apple has made biometrics on watches an essential feature. Other companies with smart watch products will be forced to follow–especially since doctors are now replacing in-office visits with telemedicine. A lot of cultural change is needed before doctors will accept ambient data detection, but Coronavirus may force that change to happen.

Operations and Infrastructure

• Rolling updates for Kubernetes with Kublr: Rolling updates are an essential feature for groups that are practicing continuous deployment. There have been some hackish workarounds, but Kublr attempts to provide a real solution.
• AWS has a Linux-based operating system for containers called Bottlerocket. Bottlerocket’s most important feature is that it streamlines the update process, making updating possible for container orchestrators.
• Monitoring production systems is an essential practice. m3 is an open source monitoring tool from Uber that is effective at huge scale. It is being commercialized by Chronosphere.

Software Development

• Microsoft buys npm: This certainly isn’t Steve Ballmer’s Microsoft. And, along with Microsoft’s acquisition of GitHub, it makes Microsoft a dominant player in much of the open source movement. 
• Chrome has new tools to help develop for the visually impaired; they simulate what the page would look like with different vision problems. This is an important step forward for developers working on accessibility. Mozilla also has accessibility checking.

Artificial Intelligence and Machine Learning

• Realtime transcription and translation with Google Translate: This feature is rolling out to Android now, and will be delivered to iOS later. There are lots of issues that they will have to think about—for example, there are significant variations in Spanish from country to country—but it’s an impressive accomplishment for natural language technology. 
• We’ve known for some time that AI-based image classification can be tricked. Researchers have shown that it is also possible to spoof LIDAR, which could have a big effect on the development of autonomous vehicles. 
• A data set is a world view. This isn’t a new idea, but it’s important. A must-read article.
• Facebook has developed a new system called Deep Entity Classification for detecting fake accounts. It’s based on connection patterns between users and also seems to take advantage of machine-generated labeling.  

Quantum Computing

• TensorFlow Quantum integrates quantum computing into TensorFlow to jump-start research into machine learning on quantum computers. While TensorFlow does not directly support quantum computing, this makes it a tool for simulations and prepares the way for supporting real quantum computers.
• Honeywell hasn’t been part of the quantum computing picture so far, but at the beginning of March, it suddenly announced that it had built a quantum computer. They’re claiming it will be twice as powerful as IBM’s machine.

Other

• There is legislation in the US Senate that would have the effect of restricting encryption. While this is framed as a bill to combat child sexual abuse, it would have drastic effects on computer security of all kinds.

1. Introduction to COBOL — a 1999 web site (!) with slides from a University of Limerick course. IBM will offer free (presumably more modern) training.
2. zoombot — a highly advanced AI to handle Zoom calls.
3. storybook.js — open source toolkit and sandbox to build UI components in isolation so you can develop hard-to-reach states and edge cases.
4. tic-80 — a fantasy computer for making, playing and sharing tiny games.

1. FairMOT — one-shot multi-object tracking that remarkably outperforms the state-of-the-arts on the MOT challenge datasets at 30 FPS.
2. pipedream — IFTTT for coders.
3. Compiler Explorer — an interactive tool that lets you type code in one window and see the results of its compilation in another window. Using the site should be pretty self-explanatory: by default the left hand pane is the source window and the right hand has the assembly output. (via Tim Westbrook)
4. MOOM — move and zoom windows on a Mac. See also Magnet. (via Ben Gracewood and @kylehqcom)

1. The Fuzzy Edges of Character Encoding — the history, politics, and computational basics of text-based character encoding and digital representations of text, from Morse Code to ASCII to Unicode (and emoji), as well as alternative text encoding schemes. (via Everest Pipkin)
2. AutoHotkey — an automation scripting language for Windows.
3. The Electronic Nose and its Applications: A Survey — very good summary of tech, limitations, and applications of “electronic noses” aka multiple chemical sensors plus some machine learning/statistics.
4. falsisign — Make it look like a PDF has been hand signed and scanned.

1. System Design for Advanced Beginners — a friendly explanation of the what and why of systems, with acknowledgement of the real world like There are many tools out there, each with different strengths and weaknesses, and many ways to build a technology company. The real, honest reasons that we will make many of our technological choices will be “we chose X because Sara knows a lot about X” and “we chose Y on the spur of the moment when it didn’t seem like a big decision and we never found the time to re-evaluate.”
2. Lozya — Teleconferencing with an RPG map. Walk around, talk to folks, have private conversations by huddling in a corner, or drop in on other conversations. Ideal for meetups!
3. Hammerspoon — desktop automation framework for macOS. It lets you write Lua scripts that hook into operating system functionality, allowing you to interact with the keyboard/mouse, windows, displays, filesystem, and much more. (via CSAIL’s Missing Semester Potpourri)
4. The Hitchiker’s Guide to Logical Verification (PDF) — book for a course, using Microsoft Research’s Lean theorem prover.