Core Insights - Tiiny AI has launched the Tiiny AI Pocket Lab, a personal AI computer designed for offline use, addressing concerns over data privacy and cloud dependency [1][2] - The device can run large language models with up to 120 billion parameters locally, achieving decoding speeds of over 20 tokens per second, making it suitable for practical daily use [3][4] - Tiiny AI aims to provide a more personal AI experience, allowing users to operate AI without ongoing fees or internet connectivity, contrasting with traditional cloud-based services [5][6] Product Features - The Pocket Lab is designed to work alongside existing computers, connecting via plug-and-play and enabling older devices to access advanced AI capabilities without hardware upgrades [5] - It includes TiinyOS, an on-device software platform that allows users to download and run open-source models and AI agents easily, as well as tools for developers to create local AI workflows [6] - The device is set to launch on Kickstarter in February at a price of $1,399, aimed at making local AI more accessible rather than positioning it as a premium product [7] Market Positioning - The Pocket Lab is positioned as capable of running large models locally, a feature that has been challenging for devices in its price range, thus placing it among a select group of emerging systems for high-capacity AI inference [8] - The growing interest in local AI solutions reflects broader industry discussions on data governance, enterprise security, and the economics of AI services [8] - Tiiny AI has received recognition from Guinness World Records for the Pocket Lab as "The smallest mini PC capable of running a 100B-parameter large language model locally," enhancing its market credibility [9]

The world is connected through fractured, censored, controllable siloed data and monetary networks.They work at the highest levels, but billions fall through the cracks, underserved and kept apart through fragmentation.We deserve neutral global networks.Infrastructure that lets us store, access, send, and do whatever we want with our own data and money.We believe this will change the world once implemented at scale.This is what Dash is for. ...

Core Insights - The article discusses the use of Automatic Content Recognition (ACR) technology in smart TVs, which tracks viewing habits and collects data for targeted advertising [3][12][17] - In 2022, advertisers spent approximately $18.6 billion on smart TV ads, with expectations for continued growth in this area [4] - ACR technology captures up to 7,200 images per hour, providing detailed insights into viewer preferences and personal information [6][17] Group 1: ACR Technology Overview - ACR operates in the background, identifying content displayed on screens by capturing screenshots and cross-referencing them with a media database [5][12] - The technology allows marketers to tailor content recommendations and track the effectiveness of advertisements [7][12] Group 2: Privacy Concerns - There are significant privacy risks associated with ACR, including potential exploitation of sensitive information, which could lead to identity theft [8][18] - Many users are unaware of ACR's presence and find it challenging to opt out due to complex settings [9][12] Group 3: Disabling ACR - The article provides detailed instructions on how to disable ACR on various smart TV brands, including Samsung, LG, Sony, Hisense, and TCL [10][11][20] - Disabling ACR may limit some smart features but enhances user privacy [16][18]

Core Insights - The SIIA has released a consumer survey that provides insights into attitudes regarding data privacy and comfort levels with various data uses under different conditions [1] Group 1: Consumer Attitudes - The survey reveals varying levels of comfort among consumers when it comes to data privacy, indicating a significant concern over how personal data is utilized [1] - Consumers express differing opinions on data sharing depending on the context, suggesting that transparency and purpose of data use are critical factors influencing their comfort levels [1] Group 2: Data Usage Conditions - The findings highlight that consumers are more willing to share data when they perceive a clear benefit, such as improved services or personalized experiences [1] - The survey results indicate that specific conditions under which data is used can significantly impact consumer trust and willingness to engage with companies [1]

Flaw in photo booth maker’s website exposes customers’ pictures https://t.co/BA2xbTe1zW ...

Legal & Regulatory - Kenyan court suspends US health aid deal [1] - Suspension due to data privacy concerns [1] - The deal is described as 'landmark' [1]

A Kenyan court temporarily froze the nation’s health deal with the US after a lobby group raised data-privacy concerns, even as President Donald Trump courts more African countries with similar pacts https://t.co/zMQ5Cf0tdZ ...

This video shows the moment a Colombian woman was arrested at a daycare center in Chicago on the 5th of November following what ICE called a targeted traffic stop. In a statement defending the arrest, the Department of Homeland Security said the woman's car was registered to a female illegal alien. But that made me wonder, how would they know that.They had to link vehicle registration data, which is held by the states, with citizenship data, which is held by the federal government. Documents show that ICE c ...

Consumer Credit - U.S. consumer credit increased by $9.18 billion in October 2025, significantly missing analyst expectations of $11.80 billion and falling from September's $13.09 billion, indicating a potential cooling in consumer borrowing [2][7] - Total U.S. consumer debt reached $18.09 trillion as of October 2025, marking a 2.9% increase year-over-year [3][7] - Outstanding bankcard balances climbed to $1.08 trillion, an increase of 3.7% year-over-year, while auto loans and leases saw a 1.3% rise to $1.685 trillion [3] Regulatory Scrutiny on Tech Giants - Republican Attorneys General launched a probe in May 2025 into Apple (AAPL) and Google (GOOGL) over their handling of Chinese-owned applications like TikTok and Deep Seek, citing data privacy concerns and potential violations of state consumer protection laws [4][7]

AI Regulation & Innovation - The industry emphasizes the need for a unified, light-handed approach to AI regulation at the federal level, cautioning against fragmented state laws [1] - Concerns exist that multiple, differing jurisdictional AI laws (potentially up to 55, plus territories) could hinder the United States' research and development pacing advantage [2] - The industry views the current patchwork of state AI laws as detrimental to maintaining the US's global innovation leadership [2][3] - The industry believes the innovation gap between the US and competitors like China is narrowing, and regulatory hurdles could exacerbate this [3] Preemption & Best Practices - There's ongoing debate regarding federal preemption of state AI laws, with attempts to include it in defense bills [4] - The industry acknowledges state-level concerns regarding consumer protection, fraud, online safety for children, and data privacy [5] - The industry suggests identifying best practices from state-level "laboratories of democracy" to inform a preemptive federal approach [6] - The industry highlights the potential for increased costs to consumers due to state-level compliance with varying AI regulations [7] Compliance Costs vs Innovation - The industry questions whether resources should be allocated to compliance with numerous state regulations or to fostering competition and innovation [7] - The industry draws a parallel to GDPR implementation in Europe, noting the initial scramble for compliance and the potential for similar challenges with fragmented AI laws in the US [6]