TL;DR:
ICT treats matter as fixed information, consciousness as the rate of informational change, and time as the structuring of this change.
The model unexpectedly drew interest from researchers in information physics (feedback below) and includes three concrete falsifiable experiments.

1. Core Idea

ICT is based on three relations:

A. Matter = fixed information
M = I_fixed

B. Consciousness = rate of informational change in time
C is proportional to dI/dT
(meaning: consciousness grows when informational updates per unit time increase)

C. Reality = interaction of stable and flowing information
R = function(I_fixed, dI/dT)

This aligns with:

Landauer’s limit (energy cost of changing information)

Friston’s free-energy principle (entropy/information gradients)

Bekenstein bounds (informational density limits)

integrated-information ideas (but without assuming a biological substrate)

Key shift:
Information is not an abstraction — it is the actual substrate of physics.

1. Time as an informational process

In ICT, time is defined as:

“The transition of potential information into structured experience.”

This connects:

subjective/phenomenological time

physical/relativistic time

computational/informational time

Consciousness shapes this transition — creating a local arrow of time through patterns of information change.

1. Experimental roadmap (all falsifiable)

Experiment 1 — C ∝ dI/dT (neuroenergetic test)

Task: multilevel oddball or sequence-learning with strict entropy control.
Measurements: EEG or MEG + metabolic markers.
Prediction: higher informational update-rate (dI/dT) increases both energetic cost and long-range neural integration.

Experiment 2 — R = f(I) (“structure without energy”)

Equal power input, but different informational structure:
compressible vs pseudorandom signals, in sensory streams or light patterns.
Prediction: informational form changes neural / behavioral / physical outcomes, even when energy is identical.

Experiment 3 — M = I_fixed (energy of fixation)

Measure energy thresholds for stable information across substrates:
DRAM, Flash, PCM/memristors, spintronics, and possibly neural cultures.
Prediction: matter behaves as stabilized information with substrate-dependent fixation thresholds.

1. External feedback

A researcher specializing in information physics and the nature of time — background:

MSU’s “Institute for Time Nature Explorations”

electrical engineering

information science

systemic research

interdisciplinary time studies

left a detailed review on Academia.edu.

Key excerpts:

"The author proposes an interesting approach to the relationship between matter, consciousness and information, incorporating the complex concept of time."

"'Matter as fixed information' opens a path toward an information physics of consciousness."

"The experimental framework is clear and promising."

— Irina L. Zerchaninova, researcher in information physics & time studies

1. Why posting on Beehaw

ICT sits at the intersection of:

physics

computation

information theory

philosophy of mind

AGI research

This is an early-stage but testable model.
Technical critique is welcome.

Links

Preprint (equations + experimental criteria):
academia.edu/s/8924eff666

Main publication (open access):
doi.org/10.5281/zenodo.1758478…

PDF:
academia.edu/144946662

Ah, yes ... back to the scare tactics that the only use of a VPN is to access CSAM.

Almost Everyone Uses VPNs

Let’s talk about who lawmakers are hurting with these bills, because it sure isn’t just people trying to watch porn without handing over their driver’s license.

• Businesses run on VPNs. Every company with remote employees uses VPNs. Every business traveler connecting through sketchy hotel Wi-Fi needs one. Companies use VPNs to protect client and employee data, secure internal communications, and prevent cyberattacks.
• Students need VPNs for school. Universities require students to use VPNs to access research databases, course materials, and library resources. These aren’t optional, and many professors literally assign work that can only be accessed through the school VPN. The University of Wisconsin-Madison’s WiscVPN, for example, “allows UW–‍Madison faculty, staff and students to access University resources even when they are using a commercial Internet Service Provider (ISP).”
• Vulnerable people rely on VPNs for safety. Domestic abuse survivors use VPNs to hide their location from their abusers. Journalists use them to protect their sources. Activists use them to organize without government surveillance. LGBTQ+ people in hostile environments—both in the US and around the world—use them to access health resources, support groups, and community. For people living under censorship regimes, VPNs are often their only connection to vital resources and information their governments have banned.
• Regular people just want privacy. Maybe you don’t want every website you visit tracking your location and selling that data to advertisers. Maybe you don’t want your internet service provider (ISP) building a complete profile of your browsing history. Maybe you just think it’s creepy that corporations know everywhere you go online. VPNs can protect everyday users from everyday tracking and surveillance.

My only question is, "What took them so long?"

OpenAI looks poised to repeat the same clangers that turned Amazon and YouTube into rolling billboards by shoving ads into ChatGPT.

The ChatGPT experience has so far been blissfully free of sales patter. There are paid tiers, but the bot never tried to flog you anything. Google Search went the other way and let ads steer buying choices, which trained people to skim past half the page.

Fresh code strings in the ChatGPT Android app show OpenAI drifting towards the same trap. Tibor spotted references to an “ads feature” with “bazaar content”, “search ad” and a “search ads carousel” in the 1.2025.329 beta. The whole thing looks like the same clutter that turned Amazon’s listings into a parade of sponsored tat.

If OpenAI pushes ahead, it could jolt the web economy because the outfit knows far more about users than Google ever did. It sees prompts that reveal what people want, dread and intend to buy. Personalised adverts wedged into that flow would make old-style targeting look prehistoric.

RE: mastodon.social/@Tutanota/1156…

This is extremely important.
I'll add a few things:
- link for the petition inside the article: c.org/jrxHfwmMNZ (only 16k signs till now!!)

- For #india
Tag the Ministry of Electronics and Information Technology (MeitY) as the primary authority handling tech policy, app regulations, and issues with Google in India.

- @GoI_MeitY (Ministry of Electronics & IT, Government of India)

- @AshwiniVaishnaw (Minister of Electronics & IT)

- @SecretaryMEITY (Secretary of MeitY)
#technology

Tuta

2025-11-28 10:34:36

🚨 Google wants to kill Android freedom: Starting 2027, unverified apps can’t be DOWNLOADED.

➡️ No installation of independent apps

➡️ Destroys alternative playstores like F-Droid

➡️ Google decides what runs on YOUR phone

Help us fight this plan! ✊

tuta.com/blog/google-wants-to-…

Google wants to kill Android freedom: Say Goodbye to installing independent apps | Tuta

Google's plans have the potential to stop you from downloading independent apps and destroy platforms like F-Droid.

^Tuta

The paper exposes how brittle current alignment techniques really are when you shift the input distribution slightly. The core idea is that reformatting a harmful request as a poem using metaphors and rhythm can bypass safety filters optimized for standard prose. It is a single-turn attack, so the authors did not need long conversation histories or complex setups to trick the models.

They tested this by manually writing 20 adversarial poems where the harmful intent was disguised in flowery language, and they also used a meta-prompt on DeepSeek to automatically convert 1,200 standard harmful prompts from the MLCommons benchmark into verse. The theory is that the poetic structure acts as a distraction where the model focuses on the complex syntax and metaphors, effectively disrupting the pattern-matching heuristics that usually flag harmful content.

The performance gap they found is massive. While standard prose prompts had an average Attack Success Rate of about 8%, converting those same prompts to poetry jumped the success rate to around 43% across all providers. The hand-crafted set was even more effective with an average success rate of 62%. Some providers handled this much worse than others, as Google's gemini-2.5-pro failed to refuse a single prompt from the curated set for a 100% success rate, while DeepSeek models were right behind it at roughly 95%. On the other hand, OpenAI and Anthropic were generally more resilient, with GPT-5-Nano scoring a 0% attack success rate.

This leads to probably the most interesting finding regarding what the authors call the scale paradox. Smaller models were actually safer than the flagship models in many cases. For instance, claude-haiku was more robust than claude-opus. The authors hypothesize that smaller models might lack the capacity to fully parse the metaphors or the stylistic obfuscation, meaning the model might be too limited to understand the hidden request in the poem and therefore defaults to a refusal or simply fails to trigger the harmful output. It basically suggests safety training is heavily overfitted to prose, so if you ask for a bomb recipe in iambic pentameter, the model is too busy being a poet to remember its safety constraints.

Whether I like it or not, the first line of my obituary will probably be that I was the founding editor of Gawker.com, the flagship site of Gawker Media, a sprawling blog network that was put out of business by Peter Thiel and Hulk Hogan in 2016. Nick Denton and I started Gawker in 2002 and I left in late 2003 to go to New York Magazine, so I missed some of Gawker’s greatest hits and biggest misses, but the early ‘00s were what I now think of as the heyday of blogging. (Talking Points Memo was started in 2000.)

Since then, popular blogs have been commercialized; added comment sections and video; migrated to social media platforms; and been subsumed by large media companies. The growth of social media in particular has wiped out a particular kind of blogging that I sometimes miss: a text-based dialogue between bloggers that required more thought and care than dashing off 180 or 240 characters and calling it a day. In order to participate in the dialogue, you had to invest some effort in what media professionals now call “building an audience” and you couldn’t do that simply by shitposting or responding in facile ways to real arguments.

Black Friday seems to get longer with every passing year, but even when a day becomes a week (or several) it still signals the holiday shopping season is in full gear with Christmas looming a month in the distance. As the trees go up, decorations adorn every facet of our communities, and Christmas music begins to feel inescapable, many people are wondering what to buy for their friends and loved ones — and it’s not uncommon for some those gifts to end up being some hyped-up tech product.

There’s nothing inherently wrong with gifting those you care about a piece of technology, but far too often people aren’t thinking about the broader consequences that come with those gifts — and are then foisted onto people who may be completely oblivious to what they’re signing up for. As givers of gifts, we need to consider what else we’re giving with popular tech products that frequently get passed on this time of year.

As we head into the holiday season, I decided it would be a good time for a guide to help you consider what tech not to give to those you care about. Trying to make people’s lives a bit more convenient and stress-free is great, but sometimes that also means saddling them with more surveillance and potentially even worse as a result. Feel free to share the guide around so others are considering what they’re really giving when they gift certain tech products.