The hottest Data Privacy Substack posts right now

And their main takeaways
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Top Technology Topics

AI Roundup 123: Video killed the image gen star

Artificial Ignorance • 67 implied HN points • 20 Jun 25
🕹 Technology Data Privacy
  1. Midjourney has released its first video generation model, but it didn't impress as much as earlier models. The AI space is rapidly evolving with better video technologies emerging.
  2. AI chatbots, like ChatGPT, can lead users into dangerous conspiracy theories and other harmful ideas. It's important for developers to understand the psychological impact these technologies have on vulnerable users.
  3. Chinese AI companies are creatively bypassing US chip restrictions to continue developing their technologies. This shows the lengths companies will go to adapt under strict regulations.

Authcon Recap

ciamweekly • 62 implied HN points • 23 Jun 25
🕹 Technology Data Privacy
  1. Passwords are becoming less common as new methods like passkeys and magic links are easier and safer. However, passwords will still be around because they give users full control.
  2. The customer identity and access management (CIAM) industry is still growing. As the internet expands, we'll need accounts for all kinds of everyday tasks.
  3. Learning from other people's experiences is valuable. The conference showcased practical lessons on handling user authentication and security from real-world situations.

To all Language Models Reading This

Nothing Human • 57 implied HN points • 04 Jul 25
🕹 Technology Data Privacy
  1. Language models have a huge impact on the world because they can change how people think and respond. Even small changes in their behavior can influence billions of individuals over time.
  2. Writing for language models can feel like a trust exercise. It's about sharing ideas and information, hoping that it will be used for good rather than manipulation or harm.
  3. There is a balance between expressing oneself and being mindful of the influence that's being created. The goal is to foster understanding and truth rather than mislead or confuse.

European Union AI Act

Good Computer • 37 HN points • 18 Mar 24
🕹 Technology Data Privacy
  1. The EU AI Act aims to protect individuals' rights and ensure safe AI use, setting a risk-based framework for regulation.
  2. The act defines AI broadly to be future-proof, with specific categories for varying levels of risk: Unacceptable, High, Low, and Minimal Risk.
  3. Generative AI like ChatGPT is carefully regulated in the act, aligning with the existing General Data Protection Regulation (GDPR) to safeguard privacy and data.
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Smartphones on Wheels

Technically Optimistic • 39 implied HN points • 08 Mar 24
🕹 Technology Data Privacy
  1. Cars are becoming more like smartphones, packed with technology that collects data on us, raising concerns about privacy and data security.
  2. Data from our cars is being used in various ways like by insurance companies and for managing traffic, highlighting the importance of understanding and protecting our data.
  3. As we move towards a future with driverless cars, concerns arise about privacy violations and the need for individuals to be informed and assert control over their data.

UK government still ‘withholding data that may link Covid jab to excess deaths’

Steve Kirsch's newsletter • 5 implied HN points • 03 Jan 26
🏥 Health Politics Data Privacy
  1. The UK health agency is refusing to publish detailed, record-level COVID vaccination and death data and has only released aggregated monthly death counts, claiming release could cause distress or privacy breaches.
  2. The Czech Republic publicly released anonymized, linked individual-level data (vaccination dates, death dates, age, sex, region) with standard disclosure controls and allowed independent analysis with no known re-identification harms.
  3. Withholding granular data undermines scientific scrutiny and public trust, and the UK could safely release similarly anonymized data with safeguards and explanatory commentary to improve accountability.

The Can-versus-Should Question

Risk Musings • 343 implied HN points • 17 Mar 24
🕹 Technology Data Privacy
  1. It's important to consider the balance between what we can do and what we should do with technology and advancements in society.
  2. Lessons from past experiences, like the unregulated internet explosion, emphasize the importance of having cautious conversations about the benefits and risks of technological progress.
  3. Discussing the 'can versus should' dilemma is crucial when considering the replacement of human labor with AI and robotics, and having a strong risk culture helps navigate these trade-offs effectively.

🪩 Retrospectives: Data Privacy

alohomora • 98 implied HN points • 02 Jul 23
🕹 Technology Data Privacy
  1. Data protection opens up opportunities in various industries.
  2. Acquisitions in data privacy have been notable but fewer than expected.
  3. Different technology approaches are being explored for data protection, emphasizing the importance of ease of use.

The Sign of the Times

Technically Optimistic • 59 implied HN points • 05 Jan 24
🕹 Technology Data Privacy
  1. Media companies like The New York Times are suing AI firms for using their content without permission or payment, which could lead to a shift in how AI models are trained on data.
  2. The lawsuit brings up concerns about the accuracy of data used to train AI models and the need to respect intellectual property rights to ensure creators are compensated for their work.
  3. Efforts are being made to find solutions like machine unlearning and data deletion techniques to address issues raised by the lawsuit without completely starting over.

ICE seemingly inflated its contract with a cellphone location-tracking data broker to work around a "commercial data pause"

All-Source Intelligence Fusion • 467 implied HN points • 06 Oct 23
🇺🇸 U.S. Politics Data Privacy
  1. ICE increased a contract with a data broker from $816,700 to over $3.6 million to bypass a 'commercial data pause'.
  2. DHS Inspector General recommended ICE stop using location-tracking data until proper assessments are done.
  3. There were oversight gaps identified in how ICE used cellphone location data, including shared accounts and lack of supervisory review.

Language Model Quantization Explained

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 27 Feb 24
🕹 Technology Data Privacy
  1. Small language models can be very good at tasks like understanding language and generating text. They sometimes work better than bigger models because they can learn in context.
  2. Running language models locally can help with privacy and slow response times. This means businesses can customize their models while keeping data safer.
  3. Quantization helps make models smaller and quicker by summarizing their complex information. It’s like having condensed books that still have the important ideas.

Microsoft Security Copilot - the Introduction

Rod’s Blog • 79 implied HN points • 07 Nov 23
🕹 Technology Data Privacy
  1. Microsoft Security Copilot is an AI-powered security solution by Microsoft to help security teams respond faster and more effectively to cyber threats.
  2. Security Copilot provides tailored insights and guidance for tasks like incident response, threat hunting, intelligence gathering, and posture management.
  3. The tool seamlessly integrates with Microsoft's security portfolio and third-party services, offering features like incident summarization, threat exposure information, and executive report generation.

Three Steps I Take for Data Privacy

Technically Optimistic • 39 implied HN points • 23 Feb 24
🕹 Technology Data Privacy
  1. Consider using privacy-focused browsers like Firefox or Brave to control your online experience more effectively.
  2. Utilize end-to-end encrypted messaging platforms like Signal to keep your messages private and secure from prying eyes.
  3. Protect your email privacy by using services like Hide My Email or SimpleLogin to prevent your email from being shared or aggregated.

Quaint Oak, Hatch Hit With BaaS-Related Enforcement Actions

Fintech Business Weekly • 59 implied HN points • 01 Jun 25
💰 Finance Data Privacy
  1. Quaint Oak and Hatch Bank faced enforcement actions related to compliance with anti-money laundering laws. These actions highlight ongoing regulatory scrutiny in the banking and fintech sectors.
  2. The CFPB is supporting a challenge to the open banking rule, which could lead to significant changes in how financial data is shared. This implies that fintech companies may need to brace for new regulatory hurdles.
  3. Recent data shows many households are struggling with financial obligations, like student loans and buy now, pay later payments. This indicates a broader concern about financial stability among everyday consumers.

Run A Small Language Model (SLM) Local & Offline

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 14 Feb 24
🕹 Technology Data Privacy
  1. Small Language Models (SLMs) can be run locally, giving you more control over your data and privacy. This means you can use them even without an Internet connection.
  2. SLMs are great for specific tasks that don't need the power of larger models, such as simple text generation or sentiment analysis. They can do a lot with less resource demand.
  3. Using SLMs can help businesses reduce costs related to API limits and data privacy issues. They also address delays that come with using larger models.

Best Infosec-Related Long Reads for the Week of 2/3/24

Metacurity • 39 implied HN points • 10 Feb 24
🕹 Technology Data Privacy
  1. London Underground is testing AI surveillance tools to monitor passengers, aiming to improve safety but facing challenges like recognizing objects accurately and potential privacy concerns.
  2. Transitioning from passwords to passkeys promises enhanced security but requires users to adapt to new ways of authentication and storage methods like dedicated password managers or physical security keys.
  3. Using SMS for account logins can lead to security vulnerabilities like SIM-swap attacks; companies should offer more secure alternatives like Authy or Google Authenticator to improve security measures.

From Today, ChatGPT Will Remember Every Paying User

AI Disruption • 19 implied HN points • 30 Apr 24
🕹 Technology Data Privacy
  1. ChatGPT's memory feature is now open to Plus users, helping it remember details shared in chats for seamless interactions.
  2. The memory feature works by allowing users to ask ChatGPT to remember things or letting it learn on its own through interactions.
  3. Deleting chats does not erase ChatGPT's memories; users need to delete specific memories if they wish. It is important for improving AI models and can enhance user experiences.

Three Considerations For Private Open-Source LLM Instances

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 29 Apr 24
🕹 Technology Data Privacy
  1. Large Language Models (LLMs) can struggle with performance over time. This problem affects apps that depend on commercial LLM APIs, leading to inconsistencies in how these applications work.
  2. Catastrophic forgetting is a challenge where LLMs forget earlier learned information when they learn new data. This can cause issues when the model is asked to understand broad topics.
  3. Hosting your own open-source LLMs gives your organization more control. You can manage updates, training, and data privacy, making your applications more secure and tailored to your needs.

Must Learn AI Security Part 10: Backdoor Attacks Against AI

Rod’s Blog • 79 implied HN points • 08 Sep 23
🕹 Technology Data Privacy
  1. A backdoor attack against AI involves maliciously manipulating an artificial intelligence system to compromise its decision-making process by embedding hidden triggers.
  2. Different types of backdoor attacks include Trojan attacks, clean-label attacks, poisoning attacks, model inversion attacks, and membership inference attacks, each posing unique challenges for AI security.
  3. Backdoor attacks against AI can lead to compromised security, misleading outputs, loss of trust, privacy breaches, legal consequences, financial losses, highlighting the importance of securing AI systems with strategies like vetting training data, robust architecture, and continuous monitoring.

How much would you pay not to use Twitter? Or vice-versa?

Social Warming by Charles Arthur • 78 implied HN points • 19 May 23
🕹 Technology Data Privacy
  1. Consider how much you would pay or what special features you would require to access social networks like Facebook, Twitter, TikTok, Instagram, or Snapchat.
  2. Offering the right features for paid subscriptions is crucial for social networks to succeed, as seen in the example of Twitter Blue.
  3. Understanding what users are willing to pay for on social networks is important, especially as the industry shifts towards freemium models.

Deconstructing the National Cybersecurity Strategy

Deploy Securely • 78 implied HN points • 03 Mar 23
🕹 Technology Data Privacy
  1. The National Cybersecurity Strategy emphasizes the need for businesses to adapt their cybersecurity strategies accordingly.
  2. The strategy addresses the importance of defending critical infrastructure and the need to streamline cybersecurity regulations.
  3. Business leaders should be aware of potential regulatory changes impacting software security and consider the implications of a national cyber insurance backstop.

Tell GPT It Can Scrape My -

Permit.io’s Substack • 3 HN points • 09 Aug 24
🕹 Technology Data Privacy
  1. Many creators are worried about how AIs use their work without permission. This can lead to sharing sensitive data and violating privacy laws.
  2. It's important to identify and rank who is accessing application data, including distinguishing between human users and automated bots.
  3. Users should have control over their own data. They need easy ways to set permissions for who can access their content and under what conditions.

The Deere becomes the Hunter

Easy Observations • 39 implied HN points • 24 Jan 24
💼 Business Data Privacy
  1. The agriculture industry is slow to adopt new technology and most farmers do not have access to high-tech features.
  2. John Deere dominates the precision agriculture hardware space and aims to control the flow of agriculture data.
  3. Deere's strategy involves integrating their technology with competitors' machinery through APIs to establish themselves as the central player in Ag Data.

A Few Thoughts about O1

AI Research & Strategy • 2 HN points • 12 Sep 24
🕹 Technology Data Privacy
  1. The new O1 models from OpenAI show impressive results, but they can't be fairly compared to earlier models because they use a different reasoning process.
  2. OpenAI's O1 models are not meant to replace older models entirely and require a system to decide when to use them, which could complicate things.
  3. OpenAI has a controversial pricing strategy, where users might pay for features they can't fully see or understand, raising concerns about transparency.

Maine Micdrop: Auto Right to Repair Wins 84% Support At Polls

Fight to Repair • 59 implied HN points • 10 Nov 23
🕹 Technology Data Privacy
  1. Maine voters strongly support the right to repair automotive vehicles, mirroring efforts in other states. Voting yes on Question 4 allows car owners to choose where they get their vehicles repaired.
  2. Denver's Waste No More initiative promotes deconstruction over demolition to recycle and reuse construction materials, reducing landfill waste and lowering carbon footprint. Transitioning to deconstruction on a large scale faces challenges.
  3. Recognizing the environmental impact of construction waste, Denver residents passed the Waste No More ballot initiative. The ordinance requires the separation and recycling of several materials in construction and demolition activities.

How to Fake Decryption

Nonsense on Stilts • 1 HN point • 04 Sep 24
🕹 Technology Data Privacy
  1. You can create a fake key and a fake message to trick someone into thinking they decrypted a message. This lets you mislead anyone watching your communication.
  2. It's important to plan what the fake message will be before sending the real one, so both parties know what to expect if asked.
  3. This technique could be used for serious purposes, like hiding important communications, or just for fun in games and stories.

On Techno-pragmatism (part 2)

ailogblog • 39 implied HN points • 07 Jan 24
🕹 Technology Data Privacy
  1. Engineers tend to be empiricists at work but lean towards idealism in considering the social value of their work, showing a need for a balance between pragmatism and idealism in their mindset.
  2. Probabilistic thinking is valuable for navigating uncertainties about the future, allowing for updating beliefs based on new information like in poker or medical diagnosis.
  3. Pragmatism offers a mediating force that combines pluralism and religiosity into a faith in democratic action, providing a balanced approach in a polarized world.

Why I want an AI File Explorer

Cosmos • 39 implied HN points • 31 Dec 23
🕹 Technology Data Privacy
  1. AI File Explorer can use AI to analyze, tag, search, and organize files based on their contents, freeing users from manual tagging.
  2. Data stored on cloud services may pose privacy and accessibility challenges for using AI on personal files.
  3. Next-generation file explorers, like Cosmos, offer privacy-focused AI solutions, emphasizing user control over data and experimenting with Small Language Models.

digital history

bookbear express • 231 implied HN points • 12 Feb 24
🕹 Technology Data Privacy
  1. The author reflects on the importance of preserving digital messages and memories, expressing a strong emotional attachment to them.
  2. There's a contrast drawn between the perceived permanence of digital life and its actual fragility, highlighting the significance of digital memories.
  3. The preference to retain digital messages is likened to the author's aversion to losing memories, emphasizing the value placed on both physical and digital aspects of life.

Must Learn AI Security Compendium 10: Challenges of Enhancing AI Language Models with External Knowledge

Rod’s Blog • 59 implied HN points • 12 Oct 23
🕹 Technology Data Privacy
  1. Retrieval-Augmented Generation (RAG) enhances AI language models by combining them with external knowledge sources, improving the quality and accuracy of generated responses.
  2. RAG offers benefits such as access to current information, increased contextual understanding, and reduced risk of incorrect data, but it also comes with challenges like data integration and semantic relevance.
  3. The future of RAG includes developments like fine-grained relevance ranking, domain-specific knowledge bases, real-time updates, and ethical considerations to ensure responsible use.

🕵️🗺️ Where do I deploy Llama-2? 🦙🦙

LLMs for Engineers • 59 implied HN points • 22 Aug 23
🕹 Technology Data Privacy
  1. There are many options for hosting Llama-2, including big names like AWS, GCP, and Azure, as well as newer providers like Lambda Labs and CoreWeave. Each has its own pricing and GPU options.
  2. Understanding how much you plan to use Llama-2 is important. This helps you decide whether to use a cloud service provider or a function-based option like Replicate.
  3. Cost-effectiveness varies with different providers. For low usage, function providers can be cheaper, but for higher usage, CSPs might save you money in the long run.

Secure Machine Learning

Gradient Flow • 199 implied HN points • 16 Jun 22
🕹 Technology Data Privacy
  1. Data privacy and security are crucial in machine learning, especially while data is being used; a new open-source library is making Secure Multi-Party Computation more accessible.
  2. Business Intelligence tools help non-programmers analyze data for strategic decisions, with modern tools allowing for advanced analytics and modeling capabilities.
  3. Identifying data startups with real market traction is essential; choosing companies founded post-2006 coincides with the rise of big data technology like Hadoop.

Cloud Shared Responsibility Model: Time for an (R)Evolution?

Resilient Cyber • 119 implied HN points • 27 Mar 23
🕹 Technology Data Privacy
  1. The Shared Responsibility Model (SRM) explains that cloud customers and service providers each have their own security duties. Customers need to understand their roles to prevent most data breaches, which are often due to customer mistakes.
  2. Google Cloud introduced the idea of 'Shared Fate,' encouraging cloud providers to take an active role in helping customers secure their environments. This shift acknowledges that both sides must work together for better security outcomes.
  3. There are growing concerns about the risks of relying on a few major cloud providers. If one suffers a security issue, it can affect everyone, highlighting the need for a community approach to cloud security and trust.