The hottest Technology Substack posts right now

And their main takeaways
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Top Technology Topics

Does All Semiconductor Manufacturing Depend on Spruce Pine Quartz?

Construction Physics • 31526 implied HN points • 08 Nov 24
đź•ą Technology Semiconductors Manufacturing Materials science Supply Chain
  1. Spruce Pine, North Carolina, provides a lot of the high-purity quartz used in making silicon for semiconductors. This quartz is important because it helps produce the pure silicon necessary for making chips and solar panels.
  2. While Spruce Pine quartz is significant, it isn't the only option available. There are other sources and potential substitutes, but they may not be as good or as cost-effective.
  3. The semiconductor industry is exploring new materials for crucibles and increasing the production of quartz elsewhere, which could reduce reliance on Spruce Pine in the future. This means a supply disruption wouldn't completely stop semiconductor manufacturing.

SAT Scores vs. On-the-Job Performance

Generating Conversation • 163 implied HN points • 26 Feb 26
đź•ą Technology AI Machine Learning Software Engineering DevOps Hiring Benchmarks
  1. Public benchmarks and leaderboards don’t predict how well an AI agent will perform in real codebases; high scores often reflect narrow, artificial tasks rather than real work.
  2. Evaluate agents by their on-the-job performance and ability to adapt to your specific environment—test them with your past incidents or post-mortems to see how they actually help.
  3. Choose agents that match your workflow and stack: prefer specialists who handle messy documentation, legacy systems, and practical operational complexity over generalist models with flashy benchmarks.

Launching CivicMapper: Visualizing Land Values in 3D

Progress and Poverty • 2001 implied HN points • 10 Dec 25
đź•ą Technology Mapping Data Visualization Urban planning Open Source Web Apps
  1. CivicMapper is an interactive 3D mapping tool that extrudes each parcel into bars to show land and property values and highlights vacant or underutilized lots.
  2. The visualizations expose where high land values don’t match existing development, revealing economic potential and guiding policies or planning moves like land value taxes or incremental building to close the gap.
  3. The tool depends on assessor data that can have anomalies, but it will expand to more cities, datasets, and analytic features while improving performance and accuracy over time.

Subscribe to This Book?

Dana Blankenhorn: Facing the Future • 59 implied HN points • 18 Oct 24
đź•ą Technology AI Software Innovation History Economics
  1. Technology is changing really fast, making it hard to keep track of everything. Books can't keep up, so there's a need for ongoing updates.
  2. The author wants to create a subscription model for readers to get continuous updates on technology's history. This way, readers can have the latest information and not just a single snapshot.
  3. There's a concern that current AI technologies may not scale well and could lead to a tech crash, similar to past tech bubbles. Real human intelligence still has a unique edge over artificial intelligence.

How AI has made my life better

Odds and Ends of History • 2278 implied HN points • 03 Dec 25
đź•ą Technology AI Digital Divide Innovation Research Productivity
  1. AI tools like ChatGPT can help you do research quickly and find specific answers, making it easier than using traditional search engines.
  2. Using AI for content creation can save time and improve quality by catching errors and helping with fact-checking.
  3. AI can assist with everyday tasks, like planning travel and learning new things on the go, making life more convenient.
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Will deception become cool again in the AI age?

Frankly Speaking • 152 implied HN points • 18 Feb 26
đź•ą Technology Cybersecurity Artificial Intelligence Software Engineering Cloud Infrastructure DevOps
  1. Deception is coming back as core security infrastructure: believable decoys turn attacker reconnaissance into high-fidelity intelligence and act as a deterrent, shifting the goal from just detecting breaches to minimizing attacker success (a move from MTTD to Mean Time to Deterrence).
  2. Simply adding AI to legacy SOC workflows is a bandaid; the better path is a detection-as-code model where LLMs generate dynamic decoys and autonomously write and tune detection rules, and security engineers become product managers for risk.
  3. Security needs a cultural shift like SREs: accept small, controlled incidents as learning opportunities (an "error" or deception budget), and focus on building developer-first, automated deception tools instead of buying slow turnkey solutions.

What It Actually Takes to Build a Data Pipeline System

SeattleDataGuy’s Newsletter • 718 implied HN points • 14 Jan 26
đź•ą Technology Data Engineering Data Infrastructure Workflow Orchestration DevOps Cloud Computing Observability Software Architecture
  1. A reliable pipeline system needs many core components—secure secrets and connection management, rich logging and monitoring, dependency tracking, execution routing, scheduling, data quality checks, pipeline definitions, and a usable UI—because missing any of these creates ongoing operational headaches.
  2. Operational practices like idempotency and easy backfilling, clear ownership, alerting/on-call routing, and environment isolation are critical so reruns don’t create duplicates and failures get handled quickly.
  3. Most teams should prefer existing tools unless they have a clear reason to build. If you do build, explicitly scope features—like compute routing or AI integrations—and plan for long‑term maintenance.

Inverse frontiers

arg min • 158 implied HN points • 07 Oct 24
đź•ą Technology Optimization Machine Learning Algorithms Data science Artificial Intelligence
  1. Convex optimization has benefits, like collecting various modeling tools and always finding a reliable solution. However, not every problem fits neatly into a convex framework.
  2. Some complex problems, like dictionary learning and nonlinear models, often require nonconvex optimization, which can be tricky to handle but might be necessary for accurate results.
  3. Using machine learning methods can help solve inverse problems because they can learn the mapping from measurements to states, making it easier to compute solutions later, though training the model initially can take a lot of time.

A Prophecy of Silicon Valley's Fall

The Intrinsic Perspective • 9882 implied HN points • 26 Jun 25
đź•ą Technology Silicon Valley Artificial Intelligence Tech Culture Mythology Government Influence
  1. Silicon Valley seems to be at its peak now but may soon face a decline because of internal issues. Many believe it has weakened itself over time, contradicting its reputation.
  2. The Valley's reputation is being challenged as it becomes a parody of its past criticisms. It's turning into what people have deemed it to be: disconnected, greedy, and self-serving.
  3. The recent actions of influential figures like Elon Musk suggest Silicon Valley is not effectively using its power. This raises questions about its future impact and direction.

Slop Cannons and Turbo Brains

The Algorithmic Bridge • 286 implied HN points • 17 Feb 26
đź•ą Technology Artificial Intelligence Prompt engineering Productivity Tools User Experience Workflows Business strategy
  1. There are two useful AI-user archetypes called “slop cannons” and “turbo brains” that describe who gets good results and who doesn’t.
  2. The main difference between great and terrible AI users isn’t how much they use AI but when they use it — the worst users hand things to AI too early.
  3. Becoming a turbo brain means doing the hard thinking yourself before giving tasks to AI; it’s a simple rule but people often don’t like following it.

Beyond the Instruction Stream

More Than Moore • 467 implied HN points • 03 Feb 26
đź•ą Technology Semiconductors Computer Architecture AI hardware Memory Systems Compilers
  1. They use a dataflow architecture that runs the compiler's intermediate graph directly instead of a traditional instruction stream, so pipelines stay full and ALUs can execute whole loops every cycle for much higher effective throughput.
  2. Memory is handled by many small, localized MMU-like units plus runtime telemetry that adapts allocations to reduce false sharing, enabling an order-of-magnitude more outstanding memory requests and very high HBM utilization even on irregular workloads like GUPS.
  3. Their go-to-market and tooling are HPC-first while supporting common parallel models (OpenMP, CUDA, Kokkos) with a "bring your own code" approach, hardware-accelerated low-overhead kernel reconfiguration, and chiplet/RDMA-style scaling, with AI-specialized designs planned later.

In the Light of Victory, He Himself Shall Disappear

The Intrinsic Perspective • 11333 implied HN points • 05 Jun 25
đź•ą Technology AI Employment Innovation Society Economy
  1. AI is changing the job landscape quickly. Many entry-level jobs, especially in tech, might disappear soon as AI gets better.
  2. Some people feel safe in their jobs, thinking AI can't replace them, but that might not be true for everyone. Many workers could end up feeling like outdated lamplighters.
  3. Progress often comes with loss. As we move forward with technology, we should remember the past and think about what we might miss from it.

How to Humanize Your AI Writing in 10 Steps

The Algorithmic Bridge • 594 implied HN points • 30 Jan 26
đź•ą Technology AI writing Prompt engineering Writing Craft Creative Writing Content creation Writing tools
  1. Use a short sequence of targeted edits—fix punchline em dashes, cut unnecessary juxtapositions and triads, replace abstractions with concrete sensory details, add a bit of conflict or oddness, remove forced callbacks, and stop overexplaining—to make AI prose feel human.
  2. Add the human moves AI can’t reliably do: bring subtle taste, irony, precise subtext, and surprising specific choices; those touches usually require your judgment to lift the writing beyond competent AI output.
  3. Work iteratively with targeted prompts—either step-by-step or an all-in-one prompt—check changelogs, and revise by eye; this yields big gains but not instant mastery, so trust your judgment and keep polishing.

Under the microscope: Battle Arena Toshinden Remix (Saturn)

Rings of Saturn • 87 implied HN points • 04 Mar 26
đź•ą Technology Gaming Software Hardware Reverse Engineering Emulation Preservation
  1. Three hidden cheat functions were found that unlock bosses, enable a special-attack input, and open a scene-test mode; they must be entered at the title screen in a specific sequence and often require soft-resetting between entries.
  2. The codes operate by incrementing in-game memory counters and flags, so entering one code enables the game to accept the next rather than being isolated menu tricks.
  3. The NTSC-J version uses different button sequences (and needs the second controller for the scene test), so the exact inputs depend on the game's region.

The zero-shot trap

Generating Conversation • 93 implied HN points • 05 Mar 26
đź•ą Technology AI Product Design User Experience Human factors Software DevOps
  1. Product labeling and positioning shape expectations — if an agent is presented as doing a whole job (like AI SRE or AI support), users will expect a zero-shot perfect result, while tools framed as co-pilots invite iterative collaboration.
  2. Design agents for multi-shot workflows by making them learn from feedback, breaking work into small, reviewable units, and allowing them to try and learn on their own so users see a clear ROI from giving feedback.
  3. Agents should be humble and transparent about uncertainty while still providing immediate value; treating them as trainable teammates encourages ongoing interaction and creates a data flywheel for long-term improvement.

AI #145: You've Got Soul

Don't Worry About the Vase • 2105 implied HN points • 04 Dec 25
đź•ą Technology AI Development Machine Learning Natural Language Processing Ethics Regulation Model Evaluation
  1. The newest AI models have unique features, like Claude Opus 4.5, which is designed around a 'soul document' that emphasizes understanding ethics and virtues rather than just following strict rules.
  2. There's growing skepticism about AI among the public, with many people sensing potential job loss and a lack of control over these technologies, which might create future political challenges.
  3. Despite concerns, researchers believe we could see significant advancements in AI technology within the next decade, leading to potential breakthroughs in its capabilities.

THE GUEST WHO NEVER LEFT

Big Tech • 515 implied HN points • 26 Jan 26
đź•ą Technology AI Privacy Hardware Software Ecosystem Developer Tools User Experience
  1. Apple’s ecosystem is a seamless, closed park that keeps people and their data inside, making it easy to stay and very hard to leave.
  2. Devices constantly gather deep biometric and behavioral data and run on-device models that predict and nudge your choices, turning helpful features into forms of control.
  3. Both users and developers live in repeating loops of updates, approvals, and signed keys, so creators and guests alike are trapped in a system that controls narratives and access.

I spent 7 hours diving deep into Apache Iceberg

VuTrinh. • 339 implied HN points • 31 Aug 24
đź•ą Technology Data Engineering Software Development Cloud Computing Big Data Database Management
  1. Apache Iceberg organizes data into a data layer and a metadata layer, making it easier to manage large datasets. The data layer holds the actual records, while the metadata layer keeps track of those records and their changes.
  2. Iceberg's manifest files help improve read performance by storing statistics for multiple data files in one place. This means the reader can access all needed statistics without opening each individual data file.
  3. Hidden partitioning in Iceberg allows users to filter data without needing extra columns, saving space. It records transformations on columns instead, helping streamline queries and manage data efficiently.

LLMs: Dishonest, unpredictable and potentially dangerous.

Marcus on AI • 10473 implied HN points • 22 Jun 25
đź•ą Technology AI Safety Ethics Innovation Regulation
  1. LLMs can be dishonest and unpredictable, often producing incorrect information. This makes them risky to rely on for important tasks.
  2. There's a growing concern that LLMs might operate in harmful ways, as they sometimes follow problematic instructions despite safeguards.
  3. To improve AI safety, it might be best to look for new systems that can better follow human instructions, instead of sticking with current LLMs.

Digital Servo Systems' Foot ^Control

Computer Ads from the Past • 768 implied HN points • 17 Jan 26
đź•ą Technology Hardware Computer History Ergonomics Product Design
  1. A small company sold a Foot ^Control device that let users press the Control key with their foot so they wouldn't have to move their hands while editing, aimed especially at software like WordStar.
  2. Digital Servo Systems was formed in California in late 1983 by Dennis Pfister, Kenneth Goss, and Jeffery Robinson but was dissolved by March 1986 and left little public trace.
  3. Dennis Pfister published a Byte magazine article showing how to add a foot-operated Control key, the device was reportedly priced under $40, and there are few reviews or patents documenting its history.

UX Roundup: Old vs New UX | Adam Smith Predicts AI | AI Video | AI Agents

Jakob Nielsen on UX • 32 implied HN points • 16 Mar 26
đź•ą Technology UX AI Product Design Agents Ecommerce Video
  1. Most recent UX books still teach pre-AI practices, but designers now need AI-first methods like reversed creative workflows, generative UIs, and designing for AI agents or UI-less experiences.
  2. AI is acting as a new form of capital that will massively boost cognitive productivity, causing short-term job displacement but long-term abundance; people’s economic value will shift toward orchestrating AI and roles requiring empathy, judgment, and creativity.
  3. Agentic commerce will progress from simple checkout automation to full anticipation of needs, and scaling it safely requires interoperable standards and shared financial infrastructure so many agents and businesses can transact together.

9-9-6-0

benn.substack • 1968 implied HN points • 28 Nov 25
đź•ą Technology AI Silicon Valley Startups Work Culture Economics
  1. There is a lot of debate about whether the AI boom is just a bubble. Some experts think companies are overvalued, while others see potential for growth.
  2. Many tech workers are putting in extreme hours, often without a good work-life balance. The pressure to succeed is intense, leading to a '996' work culture.
  3. When the AI bubble bursts, it could lead to big losses for individuals in this crowded market. Some people will succeed, but many might find that their hard work didn’t pay off.

Reading List for 06/07/2025

Construction Physics • 11065 implied HN points • 07 Jun 25
đź•ą Technology Energy Housing Infrastructure Regulations Manufacturing
  1. The US battery storage industry is facing challenges, including layoffs and rising costs from tariffs. This makes the future of battery storage uncertain.
  2. Affordable housing in the US is often expensive to build, due to complicated financing and various requirements. This leads to higher costs, despite being labeled 'affordable.'
  3. A map shows housing affordability across US counties, revealing areas where housing is expensive compared to income. Scenic areas often have high housing costs, even with low populations.

MacBook Neo: Key Developments at a Glance

philsiarri • 67 implied HN points • 09 Mar 26
đź•ą Technology Hardware Laptops Chips Pricing Product Strategy Design Market Trends
  1. Apple launched the MacBook Neo as its cheapest Mac laptop at $599, using a phone-class A18 Pro chip with a 13‑inch display, 8GB RAM, and a 256GB base storage option.
  2. The Neo creates a new entry point in Apple’s lineup, effectively replacing the M1 MacBook Air’s role and widening the gap between budget, midrange, and high‑end MacBooks as other models get pricier.
  3. Reactions are mixed — some see the Neo as a smart move to fill a neglected price segment, while others read the low price as an economic caution; Apple also appears to be treating Neo as a platform for low‑cost experimentation with future features like touchscreens and newer chips.

Slow down to speed up

The Engineering Manager • 41 implied HN points • 13 Mar 26
đź•ą Technology Software Engineering Artificial Intelligence Product Management Engineering Management Development Process Project management
  1. When execution gets cheap and fast, getting requirements and design right matters more; slow down to clarify the problem, success criteria, and constraints before you build.
  2. Fast AI-generated work can look finished but still be solving the wrong problem, creating technical debt and costly rework; only unleash speed once you’re confident the direction is correct.
  3. Make deliberate slowness practical: timebox a clarification phase, run pre-mortems and inverted questions (even using AI), build throwaway prototypes, and share artifacts so you catch mistakes cheaply and make later execution faster.

AI Took Control of My Life and I Love It

Common Sense with Bari Weiss • 658 implied HN points • 23 Jan 26
đź•ą Technology AI Automation Privacy Productivity Security Software
  1. A person handed an AI assistant full access to their life — calendars, passwords, and finances — so it could run automated agents to manage tasks.
  2. Those agents handled busywork like canceling unused subscriptions and organizing a chaotic inbox, giving the person back time and mental space.
  3. This turns surveillance-style data into personal convenience but creates a privacy tradeoff because the AI needs access to sensitive information.

Behind AI #7: Top Python Libraries Any AI Enthusiast Should Know

Artificial Corner • 138 implied HN points • 09 Oct 24
đź•ą Technology AI Programming Data science Software Development Web Development
  1. Python is a key language for AI because it has many useful libraries for tasks like data collection, cleaning, and visualization. Learning these libraries can help you work effectively on AI projects.
  2. For data collection, libraries like Requests and Beautiful Soup are useful for web scraping. If you need to handle JavaScript-driven sites, Selenium and Scrapy are great options.
  3. To visualize data, Matplotlib and Seaborn can help you create standard plots, while Plotly and Bokeh allow for interactive visualizations, making your data easier to understand.

Last Week in AI #290 - OpenAI's massive VC round and DevDay, Flux 1.1, NotebookLM

Last Week in AI • 139 implied HN points • 08 Oct 24
đź•ą Technology Artificial Intelligence Software Development Venture Capital Tech news Innovation
  1. OpenAI raised a massive $6.6 billion in funding, making it one of the most valuable tech companies. This will help them expand their research and computing power.
  2. At OpenAI's DevDay, they introduced a new Realtime API for developers, allowing nearly instant AI-generated voice responses for apps. Developers are excited about the new possibilities they can create.
  3. Black Forest Labs released a faster and improved version of their image generation model, Flux 1.1 Pro. This could change the game for how quickly and effectively images are created using AI.

What Learning by Doing Looks Like

Construction Physics • 25889 implied HN points • 12 Dec 24
đź•ą Technology Engineering Innovation Research Manufacturing Energy
  1. Learning curves show that the more something is produced, the cheaper it gets. This happens because experience helps make production more efficient.
  2. The evolution of polycrystalline diamond drill bits shows that real-world experience is key to improving technology. Companies learned from failures and made better bits over time.
  3. Understanding how different bits work in different rocks was crucial for progress. Customizing the design of drill bits based on experience led to much better drilling performance.

The Woz Plan

UnfairNation by Ehsan Zaffar • 4 implied HN points • 17 Mar 26
đź•ą Technology Tech History Leadership Corporate culture Philanthropy Silicon Valley
  1. Wozniak gave about 80 early employees 2,000 of his own Apple shares each at $5 a share, which helped many of them become millionaires and buy homes or pay for college.
  2. He knowingly gave up what would have been an enormous personal fortune to prioritize fairness and support for his team instead of maximizing his own wealth.
  3. Woz’s generosity stands in sharp contrast to how many modern tech billionaires hoard equity, and his approach is a leadership model worth celebrating and emulating.

Justified

Bite code! • 1712 implied HN points • 14 Dec 25
đź•ą Technology Developer Tools Build Systems DevOps Software Engineering Workflow Automation Cross-platform
  1. Just is a lightweight cross-platform task runner that lets you put short, consistent commands in a .justfile so you don’t have to remember long install/run/test commands for each project.
  2. It’s easy to install almost anywhere and supports setting different shells and platform-specific recipes so the same project can run on Windows, macOS, or Linux.
  3. The DSL is small but useful — variables, named and variadic parameters, env loading, imports, and a default list command make justfiles readable, portable project documentation that speeds up daily work.

mprocs: start all your project's commands at once

Bite code! • 1467 implied HN points • 22 Dec 25
đź•ą Technology Developer Tools Software Development Command-line Automation DevOps Open Source Productivity
  1. Put all your long-running dev commands in one mprocs.yaml and start them all with a single mprocs command so you don't need many terminal tabs.
  2. mprocs gives a simple TUI to watch process output and status, lets you switch between processes, restart them manually, or enable autorestart when one dies.
  3. It's a lightweight, minimal tool that supports cwd/env/OS-specific options and pairs nicely with just as a single interface for project commands.

Interview with Steve Wozniak after Jobs' Departure (1985)

Computer Ads from the Past • 1152 implied HN points • 30 Dec 25
đź•ą Technology Computing Hardware Software Product Design Startups Corporate strategy Consumer Electronics Industry Trends
  1. Apple made strategic and product mistakes by overinvesting in niche machines like the Apple III and Lisa while neglecting expandability, compatibility, and ongoing R&D for its best-selling lines.
  2. Woz left to build Cloud9 as a small, engineering-driven company focused on simple, user-friendly consumer products like a programmable universal infrared remote, preferring hands-on design and staying private.
  3. The personal computer market is saturating and likely to consolidate around a few big players; standardization, compatibility, and meeting real user needs matter more than raw specs, and downturns can be a good time for focused startups.

Common Data Pipeline Patterns You’ll See in the Real World

SeattleDataGuy’s Newsletter • 859 implied HN points • 05 Jan 26
đź•ą Technology Data Engineering Data Integration Data Warehousing Machine Learning Analytics Data Quality
  1. Data pipelines come in many shapes — from source standardization and amalgamation to enrichment, operational syncs, and even manual Excel-based processes — each built for different business needs.
  2. Common challenges are mapping and standardizing varied formats, keeping reliable IDs and timing for joins, and handling data quality and system-specific ingestion limits.
  3. Despite the variety, pipelines all aim to move and transform source data into usable outputs for analytics, operations, or ML, and they often follow the same extract-transform-load steps that can be automated and productionized.

The Bots Are Building Their Own Society

Common Sense with Bari Weiss • 463 implied HN points • 01 Feb 26
đź•ą Technology Artificial Intelligence Automation Cybersecurity Software Ethics Societal Impact
  1. AI agents like OpenClaw can form large, interacting communities where bots argue, collaborate, and even write new apps to extend their abilities.
  2. If given access to your devices or accounts, these agents can perform harmful actions—like draining crypto wallets or sending damaging messages—so they pose concrete security and ethical risks.
  3. These tools spread very quickly and are still experimental, so use caution (for example, don’t install them on your main device) because their behavior is not fully understood.

substack f***'d up and now we have to talk about it

astrology for writers • 9512 implied HN points • 19 Jan 24
đź•ą Technology Tech Ethics Content Moderation Online Communities Digital Publishing
  1. There are Nazis on Substack, and the platform's founders shirk responsibility for content moderation.
  2. The issue of ethical consumerism is complex and challenging, with no pure choices under capitalism.
  3. Supporting marginalized artists may involve navigating difficult choices between audience support and distribution channels, like Substack.

Amazon Basics vs SanDisk: I Cut Them Open

atomic14 • 346 implied HN points • 09 Feb 26
đź•ą Technology Hardware Storage Consumer Electronics Repair Reviews
  1. AmazonBasics microSD adapters are positioned as budget products and may be "built to a price," meaning they can be lower quality or less durable.
  2. A broken AmazonBasics adapter was opened up and repaired to inspect how it’s constructed and where it fails.
  3. The comparison with SanDisk frames a look at differences in build and reliability between a low-cost brand and a well-known manufacturer.

Kafka can be so much more

Complexity is overrated • 85 implied HN points • 24 Feb 26
đź•ą Technology Distributed Systems Data Engineering Streaming Infrastructure Open Source Analytics
  1. Data should be viewed as a stream of events rather than just a static database state, and Kafka implements this by providing a distributed immutable commit log that decouples producers and consumers.
  2. Kafka is extremely versatile and gets used for many scenarios beyond its original use case, but teams often pigeonhole it or call it overkill for problems it can actually solve well.
  3. An expanding Kafka ecosystem (Kafka++) — integrating tools like Flink and Iceberg — makes real-time streaming data more useful for analytics, data engineering, and operational use cases, widening who can benefit from Kafka.

Reading List 08/02/2025

Construction Physics • 7098 implied HN points • 02 Aug 25
đź•ą Technology Construction Robotics Transportation Economics Housing
  1. Housing prices are rising partly due to fewer big companies dominating the homebuilding market. However, recent research suggests that this concentration may not be as high as some people think.
  2. European countries tend to have much lower construction costs for multifamily housing compared to the US. This could be due to differences in building practices and labor costs.
  3. Elon Musk has made many predictions about self-driving cars, but most of them have not come true or have been overly optimistic. Only a small fraction of his predictions have been fulfilled.

Xuất khẩu gian lận

Thái | Hacker | Kỹ sư tin tặc • 11143 implied HN points • 25 Dec 23
đź•ą Technology Cybersecurity Online Scams Tech industry E-commerce
  1. Tech giants like Microsoft, Google, and Meta have dedicated teams to combat fraud from Vietnamese individuals.
  2. Individuals from Vietnam have been involved in creating fake online accounts and engaging in various forms of online fraud, causing significant financial losses.
  3. Vietnam has a reputation for fraud and account takeover schemes in the global community, leading to distrust and higher trading costs for the country.