Saturday, October 4, 2025

Polaris of Enlightenment

A Bell Labs for privacy

What Bell Labs taught us about orchestrating breakthroughs, and how we can use those lessons to push back against surveillance today.

Published 13 September 2025
– By Naomi Brockwell
9 minute read

I’ve been reading The Idea Factory by Jon Gertner, and it’s fascinating. It tells the story of Bell Labs, the research arm of AT&T, and a singular moment in history when a small community of scientists and engineers played a huge role in inventing much of the modern world. From the transistor to information theory, from lasers to satellites, a staggering number of breakthroughs can trace their origins from this one place.

The book asks: what made this possible?

It wasn’t luck. It was a deliberate design. Bell Labs proved that invention could be engineered: You can create the right environment to deliberately make breakthroughs more likely. With the right structure, culture, and incentives, it’s possible to give technological progress its best possible chance.

And this got me thinking: what’s the most effective way to move privacy and decentralized tech forward? Perhaps the internet itself taken on the role Bell Labs once played, and become the shared space where ideas collide, disciplines mix, and breakthroughs emerge? If so, how do we best harness this potential?

A factory for ideas

After World War II, Mervin Kelly, Bell Labs’ president, asked a radical question: could invention itself be systematized? Instead of waiting for breakthroughs, could he design an environment that produced them more reliably?

He thought the answer was yes, and reorganized Bell Labs accordingly. Metallurgists worked alongside chemists, physicists with mathematicians, engineers with theorists. Kelly believed the greatest advances happened at the intersections of fields.

There were practical reasons for cross-disciplinary teams too. When you put a theorist beside an experimentalist or engineer, hidden constraints surface early, vague ideas become testable designs, bad ideas die faster, and good ones escape notebooks and turn into working devices.

Bell Labs organized its work into a three-stage pipeline for innovation:

  1. Basic research: scientists exploring fundamental questions in physics, chemistry, and mathematics. This was the source of radical, sometimes “impractical” ideas that might not have an immediate use but expanded the frontier of knowledge.
  2. Applied research: engineers and theorists who asked which discoveries could actually be applied to communication technology. Their role was to translate abstract science into potential uses for AT&T’s vast network.
  3. Development and systems engineering: practical engineering teams who built the devices, refined the systems, and integrated them into the company’s infrastructure so they could work at scale in the real world.

This pipeline meant that raw science didn’t just stay theoretical. It became transistors in radios, satellites in orbit, and digital switching systems that powered the modern telephone network.

Bell Labs’ building architecture was designed to spark invention as well. At the Murray Hill campus, famously long corridors linked departments to trigger chance encounters. A physicist might eat lunch with a metallurgist. A chemist might bump into an engineer puzzling over a problem. And there was a cultural rule: if a colleague came to your door for help, you didn’t turn them away.

Causation is hard to prove, but the lab’s track record in the years that followed was remarkable:

  • The transistor (1947): John Bardeen, Walter Brattain, and William Shockley replaced bulky vacuum tubes and launched the electronics age.
  • Information theory (1948): Claude Shannon created the mathematics of communication, the foundation of everything from the internet to data encryption.
  • And much more: semiconductor and silicon device advances; laser theory and early lasers (including a 1960 continuous-wave gas laser); the first practical silicon solar cell (1954); major contributions to digital signal processing and digital switching; Telstar satellite communications (1962). The list goes on.

The Secret Sauce… it’s not what you think

Some people may argue that Bell Labs succeeded for other reasons. They point to government protection, a regulated market, defense contracts, and deep pockets. Those things were real, but they are not a sufficient explanation. Plenty of money is poured into research that goes nowhere. And protected monopolies often stagnate, because protection reduces the incentive to improve.

What Bell Labs’ resources did buy was proximity. Kelly’s goal was to gather great talent under one roof, and strategically try to increase the chances they would interact and work together. He built a serendipity machine.

The real lesson to take away from Bell Labs isn’t about money. It’s about collaboration and chance encounters.

By seating different disciplines side by side, they could connect, collaborate, and share insights directly. Building on one another’s ideas and sparking new ones led to a staggering array of advances at Bell Labs in the post-war decade.

Now in Kelly’s day, the best ways to give cross-pollination a real chance was to get people together in person, and that took a large amount of money from a behemoth corporation like AT&T.

If we wanted to manufacture the same kind of world-changing collaboration to push the privacy movement forward today, would we need AT&T-level resources?

Not necessarily. The internet can’t replicate everything Bell Labs offered, but it does mimic a lot of the value. Above all, it gives us the most powerful tools for connection the world has ever seen. And if we use those tools with intent, it’s possible to drive the same kind of serendipity and collaboration that once made Bell Labs extraordinary.

A decentralized Bell Labs

Kelly emphasized that casual, in-person encounters were irreplaceable.

A phone call didn’t suffice because it was usually scheduled, purposeful, and limited.

What he engineered was serendipity, like bumping into someone, overhearing a problem, and having an impromptu brainstorm.

Today, the internet in many ways mimics similar chance encounters. What once required hundreds of millions of dollars and government contracts can now be achieved with a laptop and an internet connection.

  1. Open work in public: GitHub issues, pull requests, and discussions can now be visible to anyone. A stranger can drop a comment, file a bug, or propose a fix. This is the digital version of overhearing a whiteboard session and joining in.
  2. Frictionless publishing: Research papers, blog posts, repos, and demos can go live in minutes and reach millions. People across disciplines can react the same day with critiques, code, or data.
  3. Shared problem hubs: Kaggle competitions, open benchmarks, and Gitcoin-style bounties concentrate diverse talent on the same challenge. Remote hackathons add the social, time-bound pressure that sparks rapid collaboration, like at Bell Labs where clusters of scientists would swarm the same puzzle, debate approaches in real time, and push each other toward breakthroughs. At Bell Labs, Kelly deliberately grouped many of the smartest people around the same hard problem to force progress.
  4. Topic subscriptions, not just people: Following tags, keywords, or RSS feeds brings in ‘weak-tie’ expertise from outside your circle. ‘Weak ties’ comes from social network theory: ‘strong ties’ are your close friends and colleagues, and you often share the same knowledge. ‘Weak ties’ are acquaintances, distant colleagues, or people in other fields, and they’re more likely to introduce new information or perspectives you don’t already have. So when you follow topics (like ‘post-quantum cryptography’ or ‘homomorphic encryption’) instead of just following individual people, you start seeing insights from strangers in different circles. That’s where fresh breakthroughs often come from — not the people closest to you, but the weak ties on the edges of your network.
  5. Remixes and forks: On places like GitHub, instead of just commenting on someone’s work, you can copy it, modify it, and publish your own version. That architecture encourages people to extend ideas. It’s like in a Bell Labs meeting where instead of only talking, someone picks up the chalk and adds to the equation on the board.
  6. Chance discovery: Digital town halls expose you to reposts, recommendations, and trending threads you might never have gone looking for. Maybe someone tags you in a post they think you’d find useful, or you have cultivated a “list”, where you follow a group of accounts that consistently have interesting thoughts. These small nudges can create a digital form of the ‘hallway collision’ Kelly tried to design into Bell Labs.
  7. Cross-linking and citation trails: Hyperlinks, related-paper tools, and citation networks help you move from one idea to another, revealing useful work you did not know to look for. It’s like walking past ten doors you didn’t know you needed to knock on.
  8. Lightweight face time: AMAs, livestream chats, and open office hours give people a simple way to drop in, ask questions, and get unstuck, and are the digital equivalent of popping by someone’s desk.

Now, anyone can tap into a global brain trust. A metallurgist in Berlin, a cryptographer in San Francisco, and a coder in Bangalore can share code, publish findings, and collaborate on the same project in real time. Open-source repositories let anyone contribute improvements. Mailing lists and forums connect obscure specialists instantly. Digital town squares recreate the collisions Kelly once designed into Murray Hill.

What once depended on geography and monopoly rents has been democratized. And we already have proof this model works. For example, Linux powers much of the internet today, and it is the product of a largely decentralized, voluntary collaboration across borders. It is a commons built by thousands of contributors.

The internet is nothing short of a miracle. It is the infrastructure that makes planetary-scale cross-pollination possible.

The question now is: what are the great challenges of our time, and how can we deliberately accelerate progress on them by applying the lessons Bell Labs taught us?

The privacy problem

Of all the challenges we face, privacy is among the most urgent. Surveillance is no longer the exception, it is the norm.

The stakes for advancing privacy in our everyday lives are high: surveillance is growing day by day, with governments buying massive databases from brokers, and corporations tracking our every move. The result is a chilling effect on human potential. Under constant observation people self-censor, conform, and avoid risk; creativity fades and dissent weakens.

Privacy reverses that. It creates the conditions for free thought and experimentation. In private, people can test controversial ideas, take risks, and fail without fear of judgment. That freedom is the soil in which innovation grows.

Privacy also safeguards autonomy. Without control over what we reveal and to whom, our decisions are subtly manipulated by those who hold more information about us than we hold about them. Privacy rebalances that asymmetry, letting us act on our own terms.

At a societal level, privacy prevents conformity from hardening into tyranny. If every action and association is observed, the boundaries of what is acceptable shrink to the lowest common denominator. Innovation, whether in science, art, or politics, requires the breathing room of privacy to flourish.

In short, privacy is not just a shield. It is a precondition for human flourishing, and for the breakthroughs that push civilization forward.

If we want freedom to survive in the digital age, we must apply the Bell Labs model to accelerate privacy innovation with the same deliberate force that once created the transistor and the laser.

Just as Bell Labs once directed its collective genius toward building the information age, we must now harness the internet’s collaborative power to advance the lived privacy of billions across the globe.

The call to build

Kelly’s insight was that breakthroughs do not have to be random. They can be nurtured, given structure, and accelerated. That is exactly what we need in the privacy space today.

The internet already gives us the structure for invention at a global scale. But privacy has lagged, because surveillance has stronger incentives: data is profitable, governments demand back doors, and convenience keeps people locked in. The internet is not a cure-all either: it produces noise, and unlike Bell Labs, there is no Kelly steering the ship. It’s up to us to curate what matters, chart our own course, and use these tools deliberately if we want them to move privacy forward.

The best future is not one of mass surveillance. It is one where people are free to think, create, and dissent without fear. Surveillance thrives because it is organized. Privacy must be too.

The future will not hand us freedom. We have to build it.

 

Yours in Privacy,
Naomi

Naomi Brockwell is a privacy advocacy and professional speaker, MC, interviewer, producer, podcaster, specialising in blockchain, cryptocurrency and economics. She runs the NBTV channel on Rumble.

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Your battery life reveals more than you think

Published today 8:21
– By Naomi Brockwell
5 minute read

I’ve been running a little experiment the past 10 days.
I carried two phones everywhere: my Google Fi device and my GrapheneOS device.

Every night, here’s how the batteries compared:
• Google Fi: about 5% left
• GrapheneOS: about 50–75% left

What’s going on here? Am I really using the Google Fi phone 2–4x more?

Actually it’s the opposite.
My GrapheneOS phone is my daily driver. That’s where I use Signal, Brave, podcasts, audiobooks, email, camera, notes, calendar, my language app, and other things.

Meanwhile, on my Google Fi phone, I’ve installed exactly two apps: Signal and Google Maps, and I also use it as an internet hotspot. I deleted as many preinstalled apps as I could without breaking the phone, but there are countless ones I can’t remove.

At first glance you might think the hotspot is what’s draining the battery. That’s certainly a factor, but for context I turn the device to airplane mode (and shutting off the hotspot) whenever I’m not using it.

Even with “aggressive battery saver” enabled and hours in airplane mode, the Google phone churned through its battery like crazy.

The fact that the Google phone’s battery still dies so quickly is revealing. Battery drain can actually be a useful indicator of how private your device is. Some of this comes down to deliberate privacy choices, and some of it comes from the inherent design of each operating system.

Why battery drain is a privacy clue

Battery life is a rough but useful proxy for what’s happening under the hood.
If your phone is dead by dinnertime even when you barely use it, something else is doing the work. And “something else” usually means:
• Background services constantly phoning home
• Analytics trackers collecting usage data
• System-level apps pinging servers even when you think they’re off
• Push notification frameworks that keep connections alive 24/7

That invisible activity not only kills your battery, it shows how much your phone is reporting back without your consent.

Your privacy choices also matter

The way I use my devices also makes a huge impact on how much background activity is happening.

On Graphene, I silo apps across six profiles. My main profile has all the functionality I mentioned before. And I’m constantly using the device, but a lot of what I do doesn’t require connectivity. I can take pictures, listen to music, write notes, and listen to audiobooks all without needing to be online.

When I want to check messages, email, or browse the internet, I simply turn WiFi on, and when I’m done I turn it off again (like turning off a light switch when I leave a room).

I also have other apps I rarely use, some of which are more privacy-invasive, like Uber or others that require sandboxed Google Play Services. These are kept in secondary profiles, and when those profiles are inactive, they’re effectively powered off. This means there’s no chance of these apps running in the background.

Meanwhile, on the Google Fi phone, even though I tried to delete as much bloatware as possible, there are countless apps I can’t uninstall and processes I can’t turn off.

Google Play Services is the biggest offender: It’s a hugely invasive process with elevated system permissions that is always on. You can think of it as a hidden operating system layered on top of Android, handling push notifications, location data, updates, and telemetry. It’s not optional.

In some cases it can actually make your battery more efficient by centralizing notifications instead of having each app run its own system. But that depends entirely on how you use your device.

For example, I don’t have a ton of apps on that device that need all their processes to be centralized in a single, more efficient system. I just have 2 apps.

And I don’t use notifications at all, which means that the centralization of push notification services isn’t helpful to me. And even if I did use notifications, Signal is capable of handling its own push notifications without Google Play Services. So for my setup, having Play Services constantly pinging servers and running countless background processes is overkill. It makes a data-minimalist setup impossible.

Why GrapheneOS performs differently

Unlike most Android phones, and especially Google Fi, GrapheneOS doesn’t come with bloatware. It doesn’t have the same preinstalled junk running in the background — it’s an incredibly stripped down OS. If you want Google play services you can install it, but it’s sandboxed just like any other app, without elevated permissions. That means it doesn’t get special system access to spy on everything you do like it does on Android.

On top of that, GrapheneOS lets you isolate apps into separate profiles, each with its own encryption key and background permissions. Apps in one profile can’t see or interact with apps in another.

This not only improves security, it massively reduces unnecessary background chatter. Most of the Graphene phone spends its day idle, instead of phoning home.

Background activity = surveillance

This comparison proved to me that even on a pared-down Google phone with limited use, there are countless processes running behind the scenes that I don’t control and don’t need.

And those processes make a huge difference in how fast the battery disappears.

Other phones show the same pattern

I compared my results with others in my travel group. Their iPhones drained quickly too, even with moderate use. Apple is better than Android on privacy, but iPhones are still packed with system services constantly talking to Apple and 3rd party servers. Background iCloud sync, location lookups, telemetry reporting, Siri analytics etc all adds up.

In short: if your phone battery is always gasping for air, it’s because it’s working for someone else.

Battery life is a window into privacy. If your phone is constantly trying to talk to servers you didn’t ask it to, it’s both:

  1. Bad for your battery
  2. Bad for your privacy

Why this matters

When I travel, I want peace of mind that my phone won’t die halfway through the day. But even more than that, I want confidence that it isn’t secretly working for someone else.

I don’t pretend to know every technical reason that Google Fi and Apple drain so fast, but I do know that I have far less control over their processes than I do on Graphene. On Graphene, I can granularly control which apps access the internet, I can eliminate Google Play Services entirely, I can block apps from accessing sensors they don’t need. I can essentially be a data minimalist, while still having all the connectivity I want on the go.

And the difference in performance is stark. My Graphene phone lasts all day, even with heavy use. It’s calm, efficient, and private. The others are invasive, have hidden connections, and more background processes.

Battery life and privacy are more connected that we might realize, and GrapheneOS is winning on both. It’s another reason why switching to Graphene was one of my favorite privacy choices I’ve ever made.

Check out our video here if you’d like to learn how to install it:

 

Yours in privacy,
Naomi

Naomi Brockwell is a privacy advocacy and professional speaker, MC, interviewer, producer, podcaster, specialising in blockchain, cryptocurrency and economics. She runs the NBTV channel on Rumble.

Elon Musk plans Wikipedia rival – building encyclopedia with AI

Published yesterday 11:08
– By Editorial Staff
Musk has long criticized Wikipedia for being extremely politically correct and urged people to stop donating to the encyclopedia.
2 minute read

Tech billionaire Elon Musk has announced plans to launch Grokipedia, an AI-based encyclopedia that will compete with and according to Musk be a “massive improvement” over Wikipedia. The project builds on his xAI chatbot Grok.

Musk announced the plans on X on Tuesday. Grokipedia will be built using his AI chatbot Grok, which was developed as an alternative to ChatGPT and trained on web data, including public tweets.

In a podcast earlier this month, Musk described how the technology will work.

— Grok is using heavy amounts of inference compute to look at, as an example, a Wikipedia page, what is true, partially true, or false, or missing in this page.

— Now rewrite the page to correct, remove the falsehoods, correct the half-truths, and add the missing context.

Musk has long criticized Wikipedia for being extremely politically correct and urged people to stop donating to the encyclopedia.

Critics often accuse the site of having transformed into a political weapon with a strong left-liberal bias. Conservative and nationalist perspectives are deliberately portrayed as extreme and dangerous, while left-wing and liberal positions are presented as positive or objective facts.

Grokipedia is expected to attract an audience among Musk’s followers and others who agree that Wikipedia has transformed into a politically biased propaganda tool rather than a neutral reference source.

Wikipedia – a propaganda weapon?

In an interview with Tucker Carlson, Wikipedia co-founder Larry Sanger recently launched a harsh attack on what his creation has become.

— Wikipedia became a weapon of ideological theological war, used to destroy its enemies, Sanger stated in the interview published on X.

He described how the encyclopedia he founded in 2001 together with Jimmy Wales to bring together people with different perspectives has now become a propaganda tool.

— The left has its march through the institutions. And when Wikipedia appeared, it was one of the institutions that they marched through, Sanger explained.

Controlled by anonymous editors

He also criticized the fact that the most powerful editors are anonymous, that conservative sources are blacklisted and that intelligence services have been involved in editing content on Wikipedia.

— We don’t know who they are. They can libel people with impunity, because they’re anonymous, Sanger said about the anonymous editors.

Wikipedia has encountered internal conflicts among editors about how certain events should be presented. The site is the seventh most visited website in the world. When Grokipedia will be launched has not yet been announced.

Austrian armed forces switch to open source

Digital freedom

Published 1 October 2025
– By Editorial Staff
Austrian soldiers during an alpine exercise.
2 minute read

After an extensive planning process that began in 2020, the Austrian armed forces have now transitioned from Microsoft Office to the open source-based LibreOffice across all 16,000 workstations. The decision was not based on economic considerations but on a pursuit of increased digital sovereignty and independence from external cloud services.

The transition to LibreOffice is the result of a long-term strategy that began five years ago, when it became clear that Microsoft would move its office suite to cloud-based solutions. For an organization like the Austrian armed forces, where security around data handling is of the highest priority, this was a decisive turning point, writes Heise Online.

It was very important for us to show that we are doing this primarily to strengthen our digital sovereignty, to maintain our independence in terms of ICT infrastructure and to ensure that data is only processed in-house, explains Michael Hillebrand from the armed forces’ Directive 6 for ICT and cybersecurity in an interview with Austrian radio station Ö1.

Long-term planning and in-house development

The decision process began in 2020 and was completed the following year. During 2022, detailed planning commenced in parallel with training internal developers to be able to implement improvements and complementary software development. Already then, employees were given the opportunity to voluntarily start using LibreOffice.

In 2023, the project gained further momentum when a German company was hired for external support and development. At the same time, internal e-learning in LibreOffice was introduced, and the software became mandatory within the first departments.

Contributing to the global user base

The armed forces’ commitment to open source is not merely consuming. The adaptations and improvements required for military purposes have been programmed and integrated into the LibreOffice project. So far, over five person-years of work have been financed for this effort – contributions that all LibreOffice users worldwide can benefit from.

We are not doing this to save money, Hillebrand emphasizes to ORF (Austrian Broadcasting Corporation). — We are doing this so that the Armed Forces as an organization, which is there to function when everything else is down, can continue to have products that work within our sphere of influence.

In early September, Hillebrand together with his colleague Nikolaus Stocker presented the transition process at LibreOffice Conference 2025.

Extract of the features that the Austrian armed forces programmed for their own use and then contributed to the LibreOffice project. Image: Bundesheer/heise online

From Microsoft dependency to own control

The starting point in 2021 was Microsoft Office 2016 Professional with a large number of VBA and Access solutions deeply embedded in IT workflows. At the same time, the armed forces were already using their own Linux servers with Samba for email and collaboration solutions, rather than Microsoft’s alternatives.

This year, MS Office 2016 has been removed from all military computers. Those who still believe they need Microsoft Office for their duties can, however, apply internally to have the corresponding module from MS Office 2024 LTSC installed.

The transition underscores a growing trend among European government agencies to prioritize digital independence and control over sensitive information over the convenience of commercial cloud services.

Anthropic challenges Google and OpenAI with new AI flagship model

The future of AI

Published 30 September 2025
– By Editorial Staff
AI companies' race continues at a rapid pace, now with a new model from Anthropic.
2 minute read

AI company Anthropic launches Claude Sonnet 4.5, described as the company’s most advanced AI system to date and market-leading for programming. According to the company, the model performs better than competitors from Google and OpenAI.

Anthropic has released its new flagship model Claude Sonnet 4.5, which the company claims is the best on the market for coding. According to reports, the model outperforms both Google’s Gemini 2.5 Pro and OpenAI’s GPT-5 on several coding benchmarks, writes TechCrunch.

One of the most remarkable features is the model’s ability to work independently for extended periods. During early testing with enterprise customers, Claude Sonnet 4.5 has been observed coding autonomously for up to 30 hours. During these work sessions, the AI model has not only built applications but also set up database services, purchased domain names, and conducted security audits.

Focus on safety and reliability

Anthropic emphasizes that Claude Sonnet 4.5 is also their safest model to date, with enhanced protection against manipulation and barriers against harmful content. The company states that the model can create “production-ready” applications rather than just prototypes, representing a step forward in reliability.

The model is available via the Claude API and in the Claude chatbot. Pricing for developers is set at 3 dollars per million input tokens and 15 dollars per million output tokens.

Fast pace in the AI race

The launch comes less than two months after the company’s previous flagship model, Claude Opus 4.1. This rapid development pace illustrates, according to TechCrunch, how difficult it is for AI companies to maintain an advantage in the intense competition.

Anthropic’s models have become popular among developers, and major tech companies like Apple and Meta are reported to use Claude internally.

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