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Sebastian Tuchband: How B.A.T.M.A.N. Advanced Networking!

Description:
B.A.T.M.A.N. advanced is a decentralized mesh networking protocol that has existed with the Linux kernel for a while, now.
The presentation is on what is being done with it in reality, the ups, downs, and usage demos.

About Sebastian:
A systems engineer that has been working with Linux to create decentralized mesh networks for the city of Phoenix with the Arizona Blockchain Initiative.

Karen and Bradley discuss the end to Microsoft's e-book platform and generally the dangers and disasters that Digital Restrictions Management (DRM) cause for software users and developers.

Show Notes:

Karen and Bradley discuss the end to Microsoft's e-book platform and generally the dangers and disasters that Digital Restrictions Management (DRM) cause for software users and developers.

Segment 0 (00:35)

• Bradley mentioned that Microsoft ended their e-book platform. He said this was “last month” but we ended up releasing this show late, so it was in August 2019 (01:31).
• Bradley mentioned the analog hole. (09:50)
• Karen discussed the exception process under DMCA, which Conservancy participated in regarding “Smart” TVs. (12:30)
• Bradley mentioned this historical burning of the Library of Alexandria as a Roman weapon, comparing it to DRM. (15:07)
• Bradley talked about how Netflix and Microsoft used Silverlight initially as the method of DRM, and that Microsoft was a leader in the entertainment industry in providing DRM (20:00)

Segment 1 (26:31)

• Bradley and Karen discuss how DRM and other lock-down of devices, including medical devices, are creating problems in society generally.
• Karen noted that the role of for-profit companies is not to safeguard the public interest. (41:10)
• Bradley mentioned you can turn off DRM on the Google Play store for your book (as the publisher). (43:04)

Send feedback and comments on the cast to <oggcast@faif.us>. You can keep in touch with Free as in Freedom on our IRC channel, #faif on irc.freenode.net, and by following Conservancy on on Twitter and and FaiF on Twitter.

Free as in Freedom is produced by Dan Lynch of danlynch.org. Theme music written and performed by Mike Tarantino with Charlie Paxson on drums.

The content of this audcast, and the accompanying show notes and music are licensed under the Creative Commons Attribution-Share-Alike 4.0 license (CC BY-SA 4.0).

1. Quantum Supremacy: The Gloves are Off (Scott Aaronson) — Google demonstrated a quantum system that will be exponentially faster, as the number of qubits increases, than a classical system simulating the problem. IBM proposed a way of using the world’s most powerful classical supercomputer (Summit) to brute force a solution faster than the method listed in Google’s paper—but the classical computer solution will still be exponentially slower, as the number of qubits increases linearly. If Google, or someone else, upgraded from 53 to 55 qubits, that would apparently already be enough to exceed Summit’s 250 petabyte storage capacity. At 60 qubits, you’d need 33 Summits. At 70 qubits, enough Summits to fill a city … you get the idea. Amusingly enough, Google made a particular engineering choice purely to extend the gap between quantum and the classical simulations they foresaw (missing IBM’s “just brute force it, bro” solution).
2. VisibleV8 — mods for a V8 JavaScript engine that instruments JavaScript and logs a ton of stuff about function calls, property access, etc. See the paper.
3. All Carrots and No Sticks: A Case Study on Social Credit Scores in Xiamen and Fuzhou (Berkman-Klein Center) — the most detailed look at the social credit system, and it’s a long way from Black Mirror. The introduction of these city-level scores by city governments marks the entry of the government in the business of scoring citizens; however, implementation so far reveals a very basic attempt with numerous gaps and question marks, but a far cry from the Western media picture of an all-encompassing score enabled by mass surveillance.
4. Schmelvetica — the original Smelvetica was a copy of Helvetica that had its kerning messed with, which made the originally very elegant font look … awful. The creator got a take-down notice. So here’s a Python program that’ll similarly abuse any font you give it. I don’t know why I’m attracted to this horror.

1. How Not to Rewrite it in Rust — A much better alternative is to reuse the original library and just publish a safe interface to it. As this comment on Lobsters says, Rust can add safety guarantees even to C code! When using a C library, you may need to know things such as “if I pass a pointer to the library, who will free it and when?”, “can this be NULL?”, “is this thread-safe?”, “can I call this function more than once?”. In C, these things are in the manual, but Rust can express them in the type system. When writing Rust wrappers, I literally copy prose from the documentation into Rust type system and have the compiler enforce RTFM!
2. A Study on the Prevalence of WebAssembly in the Wild — we examine the prevalence of WebAssembly in the Alexa top one million websites and find that as many as one out of 600 sites execute Wasm code. Moreover, we perform several secondary analyses, including an evaluation of code characteristics and the assessment of a Wasm module’s field of application. Based on this, we find that over 50% of all sites using WebAssembly apply it for malicious deeds, such as mining and obfuscation.
3. Userland — an integrated dataflow environment for user applications. Very cool idea! Very early and docs not everywhere, but see this video for demos and explanation of philosophy. (via Twitter)
4. Bigslice — a system for fast, large-scale, serverless data processing using Go.

Technology does not make a market. People make a market. It’s only when millions of people make individual decisions to use a new product or service that a technology takes hold. That is why it’s critical to examine broader social forces when trying to understand how quickly a new technology will be adopted—and to understand why blockchain technology is building momentum at this particularly potent time.

In the 1980s, scientists at European physics lab CERN were struggling to share and collaborate on their research. Tim Berners-Lee, a contractor with the lab, provided an answer: he created the World Wide Web. He designed this new platform to be permission-less and free, an open space for creativity, innovation, and free expression that transcended geographic and cultural boundaries.

Our world is now 30 years into its internet-driven, digital-centric life. This has reshaped us, from how we run a household to how we do our jobs. It’s changed the architecture of our expectations—of what we expect a friend, colleague, or a business to be able to do. And it has given us unprecedented capability. This power has shaped markets, as businesses clamored to respond to the new customer we have become. Since the dawn of the web, it has moved us to a steadily escalating desire for more accountability, transparency, participation, inclusion, and openness.

But something else also happened, and we are increasingly aware of the implications of what we have created. Power has become concentrated in the hands of a few internet giants, who now wield undue influence. Our digital lives generate heaps of data that propagate beyond our intent and control. Malicious actors have found they can leverage our inability to distinguish real from fake in the digital world, to doctor our perception of reality with ease. How did this happen? A key driver: there was nothing in the internet’s original specs to code direct trust between two participants.

Enter blockchains

In this moment of increasing discontent, we’re entering the dawn of the blockchain era. While we are still in the very early days, pioneers—both in the enterprise and in blockchain-first startups—are looking to leverage the technology to address this shortcoming in trust. Blockchains show potential to address key concerns of our digitally driven lives, such as a lack of transparency, accountability, verifiable identity, and control of data. Themes emerging in the work of the early pioneers seeking disruption include:

• Deeper transparency
  Not only are consumers demanding more transparency, but there are two business reasons for it: transparency can help optimize operations, and it can increase customer preference. Blockchains enable a permanent and tamper-proof record of a good’s journey from origin to ultimate destination that anyone in the community can monitor and audit. Trust is based on code, mathematics, and cryptography, instead of having to trust in another party, or rely on central institutions to supervise or direct a relationship. This could ensure sensitive pharmaceuticals are kept at the right temperature, verify the provenance of intellectual property, identify whether fish came from a sustainable source, or find the point at which components “disappeared.” There is even work to explore whether this functionality could help fight fake news.
• Self-sovereign data
  There is an assumption today that organizations that collect data own it, and have unfettered access to its use, as long as it’s within the realm of privacy policies (which are rarely read by users). In the vision of many pioneers in the blockchain space, the “ownership” of data would switch from the organization that gathers it to the individual or organization that contributed it. In this vision, data essentially would be “vaulted” (as in a black box) and decisions to use or sell that data would be controlled by the contributor. Access could be rescinded at any time. There are projects that are exploring versions of social media, ride-sharing, and other platforms that use this approach. But the story extends beyond the individual. With new cryptographic techniques that can enable analysis on the data without actually “seeing” it, data may one day be accessible outside of the corporate silos in which it currently resides. Imagine how our concept of big data could get bigger, for example, if the health care industry could safely share data across organizations, or how many more organizations could benefit from AI if more training data were available.
• More equitable sharing of value
  Today, we freely give data, content, and other forms of value in exchange for the use of “free” products. In the vision of blockchain pioneers, the technology can be used as the plumbing to facilitate a shift to a more collaborative relationship between business and customer. We can verify a contribution has come from a specific identity, track how it’s used over time, and then compensate accordingly. This represents a paradigm shift—these (unproven) business models are no longer a zero-sum game, but about creating value together. As the space evolves, innovators are likely to eventually identify viable alternatives that embody this paradigm. As consumers are exposed to these alternatives, they will be trained to recognize the true value of their contribution and will be influenced by which brands or businesses compensate them most fairly for the value they help create.

Where does change begin?

On the cusp of surpassing baby boomers as the nation’s largest living adult generation, millennials are a massive force. In the United States, they are also becoming the wealthiest: over the next 30 years and as they are entering their prime earning years, millennials will inherit $30 trillion from their baby boomer parents and grandparents. Receptive and quick to adopt new technologies, millennials, through their influence and demands, have already played a huge role in shaping the way we shop, work, and live. They may very well be one of the first—and highly influential—major segments to adopt blockchain-fueled development. A recent Pew Research Center study found that just 19% of millennials (those born from 1981 to 1996, according to Pew Research) feel that “most people can be trusted.”

Disruption could also be spurred by an even younger generation. New York Times writer David Brooks traveled to college campuses to understand how students see the world. In a story he wrote after the experience, starkly titled “A Generation Emerging from the Wreckage,” Brooks describes a cohort with diminished expectations. Their lived experience includes the Iraq war, the financial crisis, police brutality, political fragmentation, and the advent of fake news as a social force. In short, an entire series of important moments in which “big institutions failed to provide basic security, competence, and accountability.” To this cohort in particular, blockchains’ promise of decentralization, with its built-in ability to ensure trust, is tantalizing. To circumvent and disintermediate institutions that have failed them is a ray of hope—as is establishing trust, accountability, and veracity through technology, or even the potential to forge new connections across fragmented societies.

This latent demand is well aligned for the promise of blockchains. While it’s a long road to maturity, these social forces provide a receptive environment, primed and ready for the moment entrepreneurs strike the right formula.

1. Open Library Book Sponsorship — you pay and name the book, they digitize it.
2. Public Impact Starter Kit — The diagnostic tool helps you improve the impact of a government initiative. Guiding you through an assessment of your policy against the nine elements of the Fundamentals framework, you’ll determine whether the key drivers of policy success are in place. […] The nine-sided Fundamentals Map helps you map your policy against the Fundamentals framework to illustrate areas of strength and areas for improvement. […] The Checklist for Policymakers is a useful tool when you’re developing or reviewing a policy. By checking off each of the nine elements of the Fundamentals framework, you can help maximize the likelihood of your policy being a success. (via Danny Buerkli)
3. Mantis — Netflix open sourced their platform to build an ecosystem of real-time stream processing applications. (via Medium)
4. Unshaky — discards immediate second keypresses of the type generated by defective Apple butterfly keyboards.

1. Memex — open source browser extension to full-text search your browsing history and bookmarks.
2. Competition Programming and Problem Solving, Fall 2019 — CMU course.
3. Pwnagotchi 1.0.0 — I wanted Alpha and Beta to be able to detect each other and exchange with each other very basic information—but how do you communicate anything at all from a computer when: the main and only Wi-Fi interface is in monitor mode and already being used for Wi-Fi scanning, hopping, and frames injection; you have Bluetooth, but you want to keep it free for other uses (tethering, like we’re doing today, or maybe integrating BLE attacks, too, some day); you’re using the USB ports in gadget mode, so you can’t use external USB devices, like another Wi-Fi.
4. Turbo Rascal 1.0 — Pascal IDE for C64 games, with a ton of specialized features (memory, level editing, etc). At the same time, FreePascal has a WebAssembly back end. Pascal’s a fun language for learning compilers on, but not really fully featured for building modern systems. I wonder how this new school of compiler and IDE developers can take their skills to a wider audience.

1. The NAI Suite — A prototype for automated reasoning over legal texts, called NAI, is presented. As an input, NAI accepts formalized logical representations of such legal texts that can be created and curated using an integrated annotation interface. The prototype supports automated reasoning over the given text representation and multiple quality assurance procedures.
2. Streamsheets — open source release of an open source tool for making your data immediately understandable and for creating IoT applications visually and interactively—without a single line of code.
3. Bazel Hits 1.0 — Build software from Google. Key features of the release: semantic versioning, long-term support, features supported on Android, Angular, Java, and C++.
4. Assembler Robots Make Large Structures from Little Pieces — “What’s at the heart of this is a new kind of robotics that we call relative robots,” Gershenfeld says. Historically, he explains, there have been two broad categories of robotics—ones made out of expensive custom components that are carefully optimized for particular applications such as factory assembly, and ones made from inexpensive mass-produced modules with much lower performance. The new robots, however, are an alternative to both. They’re much simpler than the former, while much more capable than the latter, and they have the potential to revolutionize the production of large-scale systems, from airplanes to bridges to entire buildings.

People from across the AI world came together in London for the Artificial Intelligence Conference. Below you’ll find links to highlights from the event.

When flying is cheaper than standing still

Raffaello D’Andrea presents his vision of how autonomous indoor drones will drive the next wave of robotics development.

• Watch “When flying is cheaper than standing still“

When to trust AI

Marta Kwiatkowska provides an overview of techniques being developed to help improve the robustness, safety, and trust in AI systems.

• Watch “When to trust AI“

Real-time AI for entity resolution

Jeff Jonas details how you can use a purpose-built real-time AI to gain new insights and make better decisions faster.

• Watch “Real-time AI for entity resolution“

Building and deploying AI applications and systems at scale

Ben Lorica and Roger Chen review how companies are building AI applications today.

• Watch “Building and deploying AI applications and systems at scale“

The quest for high-quality data

Ihab Ilyas describes the HoloClean framework, a prediction engine for structured data with direct applications in detecting and repairing data errors.

• Watch “The quest for high-quality data“

Machine learning challenges at LinkedIn: Spark, TensorFlow, and beyond

Zhe Zhang provides an architectural overview of LinkedIn’s machine learning pipelines.

• Watch “Machine learning challenges at LinkedIn: Spark, TensorFlow, and beyond“

The power of knowledge at scale

Alexis Crowell Helzer outlines a practical approach to implementing machine learning.

• Watch “The power of knowledge at scale“

Large-scale machine learning at Facebook: Implications of platform design on developer productivity

Kim Hazelwood and Mohamed Fawzy look at how applied ML has changed the platforms and infrastructure at Facebook.

• Watch “Large-scale machine learning at Facebook: Implications of platform design on developer productivity“

Accelerate with purpose

Walter Riviera discusses three key shifts in the AI landscape.

• Watch “Accelerate with purpose“

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

1. Natron — open source compositing software for VFX and motion graphics.
2. is-website-vulnerable — finds publicly known security vulnerabilities in a website’s front end JavaScript libraries.
3. Solving Logic Grid Puzzles With An Algorithm That Imitates Human Behavior — We present in this paper our solver for logic grid puzzles. The approach used by our algorithm mimics the way a human would try to solve the same problem. Every progress made during the solving process is accompanied by a detailed explanation of our program’s reasoning. Since this reasoning is based on the same heuristics that a human would employ, the user can easily follow the given explanation.
4. Fomu — a programmable FPGA device that fits inside a USB port. It has four buttons, an RGB LED, and an FPGA that is compatible with a fully open source chain and capable of running a RISC-V core. Fomu comes in a custom plastic enclosure that slots perfectly into a USB Type-A port.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote highlight from the O’Reilly Artificial Intelligence Conference in London 2019. Watch the full version of this keynote on the O’Reilly online learning platform.

You can also see other highlights from the event.

This is a keynote from the O’Reilly Artificial Intelligence Conference in London 2019. See additional keynotes and sessions from this event on the O’Reilly online learning platform.

You can also check out more highlights from AI London ’19.

1. Searching for Alternative Facts (Francesca Tripodi) — Since Google is seen as a neutral purveyor of information, it becomes a conduit for accessing “unbiased” information. And while this quest for truth may start in good faith, significant risks follow: first, searches meant to question political reality can reinforce existing ideological beliefs; second, services like Google and YouTube can unintentionally expose individuals who consider themselves “mainline conservatives” to “far-right” and “alt-right” content through algorithmic recommendations; and third, bad actors looking to exploit an audience disillusioned with mainstream media can take advantage of such intellectual exploration. See also BoingBoing.
2. What to Do When You Get Sherlocked by Apple — as someone who worked at a company that got Sherlocked by Google, these points ring true.
3. roughViz — Reusable JavaScript library for creating sketchy/hand-drawn styled charts in the browser.
4. Programming Principles for Early-stage Startups — 1. Expect to re-write your code and do not over architecture. 2. Use consistency and agree upon the rules. 3. Solve system problems, not the immediate problem. 4. Keep sprints short and features small. 5. Focus on good database design. 6. Avoid processes that add too much overhead.