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Joined 7 months ago
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Cake day: March 28th, 2026

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  • Yeah:

    The core principle of Tor, known as onion routing, was developed in the mid-1990s by United States Naval Research Laboratory employees, mathematician Paul Syverson, and computer scientists Michael G. Reed and David Goldschlag, to protect American intelligence communications online. Onion routing is implemented by means of encryption in the application layer of the communication protocol stack, nested like the layers of an onion. The alpha version of Tor, developed by Syverson and computer scientists Roger Dingledine and Nick Mathewson and then called The Onion Routing project (which was later given the acronym “Tor”), was launched on 20 September 2002. The first public release occurred a year later.

    In 2004, the Naval Research Laboratory released the code for Tor under a free license, and the Electronic Frontier Foundation (EFF) began funding Dingledine and Mathewson to continue its development.

    As were many parts of the existing Internet, cryptography, etc. It usually holds true that protecting privacy and enhancing communication is directly inline with the goals of governments/militaries, the general public, and even corporations, except when the communications/privacy of one of those groups somehow impacts the other, in this case the privacy of the general public impacting the potential bottom line of for-profit corporations.





  • They don’t prevent you from asking the model about elections, they try to ensure the models can’t be used for election manipulation. The models currently refuse to provide information on where to vote until they connect the tooling with Democracy Works

    https://www.anthropic.com/news/2026-us-midterms

    Our latest models also engage more readily with political discussions and decline fewer requests, so people can get the information they came for. We’re continuing to refine these evaluations, and also looking beyond them for new ways to pressure-test how our models handle political topics.

    Later this month, Claude will start drawing official voting information from Democracy Works into its responses on Claude.ai for users in the US. Someone asking where to vote or what ID to bring to their polling place will now get an answer specific to their state, without leaving the conversation. These responses draw on publicly available information that Democracy Works collects from state and local election sources.

    Building on these findings and our own, we’ve added new classifiers to better identify novel and multi-step misuse, including attempts to build fake social media accounts and news sites aimed at political discussions, or to run financially motivated election schemes. We also enhanced our ability to detect election-related misuse by foreign state actors, and strengthened our cyber protections for election infrastructure and campaigns. Finally, we built targeted safeguards for localized risks identified in the US, Israel, and Brazil, which all have major national elections this year.


  • Ah yes the “non-profit” ETS

    ETS has been criticized for being a “highly competitive business operation that is as much multinational monopoly as nonprofit institution”.[44] Due to its legal status as a non-profit organization, ETS is exempt from paying federal corporate income tax on many, but not all, of its operations.[43] It annually reports detailed financial information to the IRS on Form 990, which is publicly available.[45]

    Americans for Educational Testing Reform (AETR) claims that ETS is violating its non-profit status through excessive profits, executive compensation, and governing board member pay (which the IRS specifically advises against[54]). AETR further claims that ETS is acting unethically by selling test preparation materials, directly lobbying legislators and government officials, and refusing to acknowledge test-taker rights. It also criticises ETS for forcing GRE test-takers to participate in research experiments during the actual exam.[55]



  • Yeah also this:

    Outlit’s goal is to amass as much real-time information about a company’s clients as possible. According to Earle, agents trawl internal records like call logs and sales data as well as external information like social media posts and the websites of people’s employers; they then compile that data into detailed customer profiles, often complete with “actionables” like outreach recommendations and sales guidance. Outlit argues this level of insight will help companies prevent “churn” — business jargon for lost customers — or find opportunities to upsell.

    Isn’t new or novel in any way. Our sales team at the company I work for has a bespoke version of this. The model pulls in information from previous customer interactions, scours LinkedIn and the web and larger industry trends, and gives them a profile. There’s no benefit to having some long running agent that constantly watches someone’s online activity when you can ingest the log when it’s actionable.

    They’re grifters who will grift people with no idea how this stuff works, they’ll get a valuation of x number of millions with some CLAUDE.md files omarchy style, then salesforce will eat them for their valuation and they go on to grift some more