The hottest Technology Substack posts right now

And their main takeaways

AI #150: While Claude Codes

Don't Worry About the Vase • 3001 implied HN points • 08 Jan 26

🕹 Technology Artificial Intelligence Machine Learning AI safety Regulation Products Jobs Chips

AI tools and advanced chat models have reached critical mass and are reshaping everyday workflows, making people more productive across coding and non‑coding tasks through agents, extensions, and integrations.
Generative models make fake documents, images, and videos easy to create, so verifying sources and prioritizing real, sustained human experiences is becoming increasingly important.
Huge funding and rapid deployment are accelerating AI’s economic impact, but benchmarks, regulation, and safety practices lag behind, leaving big uncertainties about jobs, markets, and long‑term risks.

33 Things I Heard At Foo Camp 2026

The Ruffian • 436 implied HN points • 28 Feb 26

🕹 Technology AI Machine Learning AI Ethics AI safety Human-AI Research Creativity Collaboration

Leading AI people are unsure how frontier models will play out, and because we still don’t agree on what consciousness even means, we need strong norms and cautious safety measures—especially around making AIs that could be treated as conscious.
Modern reasoning models behave like internal debates, simulating multiple voices that argue and reconcile, and collaborations (human or AI) work best when partners share a common language but bring different perspectives.
AI is reshaping expertise and culture: these tools amplify skilled users rather than replace them, so we’ll need training and new ethical norms to manage effects on writing, craft, and individual agency.

Sam Altman on OpenAI’s Plan to Win, AI Personalization, Infrastructure Math, and The Inevitable IPO

Big Technology • 3878 implied HN points • 18 Dec 25

🕹 Technology Artificial Intelligence Infrastructure Product Strategy Cloud Computing Personalization IPO

OpenAI is under intense competitive pressure after Google’s Gemini 3, triggering a ‘Code Red’ and urgent strategic responses.
The company is pushing product ambitions and AI personalization to win users and differentiate its offerings.
OpenAI faces massive infrastructure costs and is planning financing — including an eventual IPO — to pay for the trillion‑scale buildout.

What the markets are saying

Substack Blog • 654 implied HN points • 18 Feb 26

🕹 Technology Product Platforms Creator tools Data Integration Visualization Search Publishing

Substack now lets creators embed live Polymarket prediction market data directly in both Notes and full posts, so odds update automatically while you write or comment.
You can search for Polymarket markets from the editor and insert them without leaving Substack, and embeds automatically change their visuals to match yes/no questions, multi-outcome rankings, or percentages.
Polymarket has joined a creator sponsorship pilot to support writers who use these tools, and many top publications already use prediction market embeds to inform reporting and spark discussion.

Stealing AI: New Cyber Threats In The GenAI Era

High ROI Data Science • 79 implied HN points • 24 Oct 24

🕹 Technology Cybersecurity Data Privacy

Human errors and social engineering are significant risks in cybersecurity, even with strong defenses. Phishing attacks are becoming more sophisticated and can catch businesses off guard.
Businesses need a holistic approach to data and AI security instead of treating them as separate issues. Better collaboration across technical teams is crucial for effective risk management.
Emerging threats like data poisoning in AI systems require constant vigilance. Preventative measures and strong recovery plans are essential to protect data integrity and ensure business continuity.

Get a weekly roundup of the best Substack posts, by hacker news affinity:

A Visual Guide to Quantization

Exploring Language Models • 5092 implied HN points • 22 Jul 24

🕹 Technology Artificial Intelligence Machine Learning Computer Science Data processing Software Engineering

Quantization is a technique used to make large language models smaller by reducing the precision of their parameters, which helps with storage and speed. This is important because many models can be really massive and hard to run on normal computers.
There are different ways to quantize models, like post-training quantization and quantization-aware training. Post-training means you quantize after the model is built, while quantization-aware training involves taking quantization into account during the model's training for better accuracy.
Recent advances in quantization methods, like using 1-bit weights, can significantly reduce the size and improve the efficiency of models. This allows them to run faster and use less memory, which is especially beneficial for devices with limited resources.

Bikes and battle cruisers (Odds and Ends #88)

Odds and Ends of History • 536 implied HN points • 26 Feb 26

🕹 Technology AI Data Policy Infrastructure Transportation Energy Urban planning

The UK government is running a consultation on increasing access to public sector data, and it's a real chance to push for making key datasets like the Postcode Address File more open to spur innovation.
Big policy debates are underway about planning and environmental governance, plus new ways to safely open NHS data for research, and those changes could reshape public services and regulation.
Several fast-moving tech and infrastructure trends deserve attention: breakthrough AI hardware, evolving web standards like CSS, creative uses of EV charging, and huge renewable build-outs in China.

How the US Won Back Chip Manufacturing

ChinaTalk • 504 implied HN points • 17 Feb 26

🕹 Technology Semiconductors Manufacturing Supply Chains Industrial Policy R&D National Security

A focused mix of big incentives (like an investment tax credit and targeted grants) plus a small, execution‑focused team is what actually accelerated a large semiconductor fab buildout in the U.S., not just market demand alone.
Effective industrial policy needs the right balance of simple market tools and discretionary powers for urgent problems, and it must be governed with transparency and insulation from politics or public trust breaks down.
To make this repeatable, the country needs durable state capacity that can attract talent, deploy capital, accept some failures, and differentiate between defensive fixes for chokepoints and offensive bets on future enabling R&D.

Train and Serve an AI Chatbot Based on Llama 3.2

The Kaitchup – AI on a Budget • 179 implied HN points • 17 Oct 24

🕹 Technology AI Chatbots Machine Learning Data science Software Development

You can create a custom AI chatbot easily and cheaply now. New methods make it possible to train smaller models like Llama 3.2 without spending much money.
Fine-tuning a chatbot requires careful preparation of the dataset. It's important to learn how to format your questions and answers correctly.
Avoiding common mistakes during training is crucial. Understanding these pitfalls will help ensure your chatbot works well after it's trained.

The Nurse Told Me I Had Gout. Then I Sent Feet Pics to ChatGPT.

Common Sense with Bari Weiss • 871 implied HN points • 11 Feb 26

🕹 Technology AI Telemedicine Diagnostics Digital Health Consumer Tech Medical Ethics

Large language models can sometimes diagnose medical problems quickly and accurately, and studies show they can even outperform doctors in some cases.
When telehealth or doctor access is slow or unsatisfying, people may turn to AI—sharing photos and getting fast, actionable guidance that can change what they do.
Using AI for health advice highlights real benefits but also raises safety and accountability worries, since wrong or unverified guidance can be risky.

Get Good at Agents

Democratizing Automation • 1615 implied HN points • 21 Jan 26

🕹 Technology AI Software Engineering Developer Tools Automation Productivity Machine Learning Research

Modern AI agents can do long, independent work, so human roles are shifting from hands-on execution to directing and designing systems. Learn to point and manage multiple agents in parallel instead of micromanaging every detail.
Work should become more open-ended, ambitious, and asynchronous—give agents meaningful, long-running tasks rather than tiny chores. Spend less time grinding and more time calmly thinking so you can better guide the agents.
Becoming skilled at using and orchestrating agents is a growing career moat because raw software work is getting cheaper. Practice experimenting with agents on hard problems to learn their limits and focus on high-value decision making and system design.

More bits is better, right?

filterwizard • 59 implied HN points • 01 Oct 24

🕹 Technology Signal Processing Quantization

Increasing the bit width of an ADC can improve data accuracy, but it doesn't always work as expected.
Quantization can cause significant errors, especially with low-level signals, leading to misleading results.
Using dither helps improve the accuracy of the signal output from an ADC, making it better for capturing lower signal levels.

What's In A List—Yes, But What's Really In A List

The Python Coding Stack • by Stephen Gruppetta • 259 implied HN points • 13 Oct 24

🕹 Technology Programming Data Structures Python Education Computing

In Python, lists don't actually hold the items themselves but instead hold references to those items. This means you can change what is in a list without changing the list itself.
If you create a list by multiplying an existing list, all the elements will reference the same object instead of creating separate objects. This can lead to unexpected results, like altering one element affecting all the others.
When dealing with immutable items, such as strings, it doesn't matter if references point to the same object. Since immutable objects cannot be changed, there are no issues with such references.

Maybe, finally—the end of SQL

benn.substack • 1380 implied HN points • 23 Jan 26

🕹 Technology AI Databases Programming Data Engineering Analytics Developer Tools

Writing and reading SQL demand different styles: shortcuts and shorthand speed up writing but make queries harder to understand, and teams often prioritize writing convenience over clarity.
With AI generating much of the code, development has shifted to a "vibe and verify" model, but data work is hard to verify because queries and analyses are difficult to check by eye or prose alone.
The solution is better representations for comprehension — diagrams, clearer formatting, or a language/app that turns any query into an accessible, annotated picture so humans can quickly verify what the computation actually did.

Lessons from building AI Features

Alex Ghiculescu's Newsletter • 135 implied HN points • 14 Mar 26

🕹 Technology Artificial Intelligence Machine Learning Software Engineering Product Development Developer Tools Testing

Use patterns from AI coding like letting users write rules (a CLAUDE.md style) and adapt those proven ideas to your own domain.
Don’t rely on LLMs for fast, deterministic checks; use them to parse or translate freeform input into structured rules, then run the actual validation in code.
Build a test harness and make debugging easy by writing unit-style evals for the AI parts and exposing clear outputs so both developers and users can inspect and trust results.

💥 AI anxiety: Is 'something big happening,' really?

Faster, Please! • 1005 implied HN points • 11 Feb 26

🕹 Technology Artificial Intelligence AI safety Productivity Tech Adoption Labor markets Economic Impact

AI capabilities are advancing quickly and could approach broad human-level skills, but that doesn’t mean the world will transform overnight.
Turning impressive AI demos into widespread impact takes years because businesses need new data systems, process redesign, regulation, and worker retraining, and early investment can even depress measured output before benefits appear.
Even large productivity gains won’t automatically produce runaway growth since people may choose more leisure, many services resist automation, and the slowest sectors or infrastructure bottlenecks set the economy’s speed limit.

The Making Of Dario Amodei

Big Technology • 20140 implied HN points • 29 Jul 25

🕹 Technology Artificial Intelligence Innovation Startups Ethics Leadership

Dario Amodei is very vocal about his beliefs on AI and is actively involved in discussions about its impact on jobs and society. He thinks AI might take away many entry-level office jobs soon.
He's in conflict with other industry leaders and the government, working to shape how people view artificial intelligence. Amodei believes that regulation and transparency are crucial for the future of AI.
His strong opinions come from a personal connection to the issues, likely driven by past experiences that influenced his views on technology and its effects on people's lives.

What's up Python? Astral's new service, pandas 3 and a new ORM...

Bite code! • 1223 implied HN points • 05 Feb 26

🕹 Technology Programming Developer Tools Data science Databases Web Development Open Source

UVX.sh lets anyone install and run CLI tools published on PyPI without needing a local Python setup, making one-shot installs and sharing tools much faster and simpler.
Pandas 3 changes defaults to real string dtypes, enforces consistent copy-on-write for indexing to avoid surprising mutations, and adds a functional col API to encourage clearer and faster data transformations.
Oxyde is an async-first ORM with Pydantic typing, Django-like ergonomics, built-in migrations, and n+1 safety nets, offering high performance and modern ergonomics but still being early-stage for critical long-term projects.

✨ AI’s superintelligence gamble

Faster, Please! • 913 implied HN points • 13 Feb 26

🕹 Technology Artificial Intelligence Automation Employment Tech Policy Innovation Economic Impact

Silicon Valley firms are racing to build far more powerful, even ‘godlike,’ AI systems that could dramatically reshape work and the economy.
The central debate is not whether AI is risky but whether moving forward with it is less risky than standing still and falling behind.
Bold claims that most white‑collar computer jobs will be automated soon highlight the gap between an AI being technically capable and it actually being widely deployed in businesses.

My Wishlist for 12 Substack Enhancements

The Honest Broker • 18484 implied HN points • 10 Aug 25

🕹 Technology Digital Media Software Tools Online Platforms Content creation User Experience

Substack raised $100 million to improve tools and support for writers. This means they want to help creators gain new opportunities.
Ideas for enhancements include creating platforms for music, video, and film, which would help independent creators gain more visibility and connect with audiences.
Substack should provide more customization options for creators, like better layouts and fonts, and functions like embedding images in comments to enhance user experience.

Cursed circuits #3: true mathematics

lcamtuf’s thing • 3877 implied HN points • 22 Dec 25

🕹 Technology Electronics Circuit Design Signal Processing Semiconductors

An op-amp simply amplifies the voltage difference between its inputs by a huge factor, and with feedback you force its inputs to be nearly equal so passive parts (resistors, diodes, caps) can be arranged to perform math instead of just gain.
Addition and subtraction are straightforward: resistor networks can average or sum signals and a non‑inverting amplifier scales them to produce a true sum, while difference amplifiers give Vout ≈ VA − VB and can be biased to work on a single supply.
Harder operations are possible too: multiplication/division can be done with log/antilog converters that use the diode’s exponential V–I curve plus a summing stage, and integration is implemented by charging a capacitor with a controlled current to produce precise ramps, though these analog tricks need careful biasing and have practical limits (rails, linearity, noise).

Party of One for Code Review!

Software Design: Tidy First? • 3115 implied HN points • 26 Dec 25

🕹 Technology Software Engineering Artificial Intelligence Developer Tools Collaboration Productivity Software Architecture

Formal, rigorous inspections were too heavy, and the lighter code-review practices that replaced them often become shallow when reviews are asynchronous or rubber-stamped.
AI-driven code generation produces changes faster than human reviewers can keep up, breaking the assumption that another person will catch problems before they compound.
Review's role is shifting toward quick sanity checks and preventing structural drift so the codebase stays understandable by both people and AI, and automated tools that summarize changes and learn project patterns can help bridge the gap without replacing human pairing.

Physical Intelligence Wins the Olympics: Deep Dive

General Robots • 1814 implied HN points • 22 Jan 26

🕹 Technology Robotics Computer Vision Machine Learning Manipulation Hardware Benchmarks Autonomy

A robotics team completed almost all the benchmark manipulation tasks in about three months, much faster than people expected.
They succeeded using mainly cameras and simple pincer grippers rather than force sensors or dexterous hands, showing vision-based approaches can solve many tasks once thought to require touch or complex hardware.
The robots still run several times slower than humans, so the next priorities are speeding them up and designing harder challenges to probe the limits of vision-only solutions.

An Introduction to Arduino

wavesandcode • 99 implied HN points • 21 Oct 24

🕹 Technology Electronics Microcontrollers Hardware Prototyping Education

Arduino is a beginner-friendly microcontroller that lets you create electronic projects. It's easy to replace if you make mistakes.
Basic components like breadboards, jumper wires, and LEDs are essential for building circuits. They help you connect and test your ideas quickly.
Starting with simple projects is a great way to learn. Using resources like the Arduino Projects Book can guide you in building fun circuits.

Europe Fires a Speech Warning

TK News by Matt Taibbi • 4846 implied HN points • 05 Dec 25

🕹 Technology Regulation Social media Content Moderation Platform policy Data Access AI Policy

The EU fined X €120 million under the Digital Services Act for a deceptive verification program and for denying researchers access, making X the first company punished under the law.
Europe is divided on tech rules: Brussels is still enforcing the DSA even as some leaders push to loosen regulations to attract AI investment, while national authorities like Germany are tightening content monitoring.
The DSA enforcement is shaping a global template for platform regulation, influencing debates about free speech, platform power, and how other regions may regulate online content.

Weekly Dose of Optimism #182

Not Boring by Packy McCormick • 210 implied HN points • 27 Feb 26

🕹 Technology Energy Batteries Fusion Biotech Pharma Fintech Genomics

Big advances in clean energy are moving from lab to grid. Gigawatt‑hour iron‑air batteries are being deployed for multi‑day storage and startups are pursuing stellarator fusion plants, both pointing to more reliable, decarbonized power and new manufacturing jobs.
Medical research is producing transformative, non‑traditional therapies. Phase‑3 psilocybin trials show strong results for treatment‑resistant depression and other studies suggest benefits for chronic conditions like post‑treatment Lyme, while vitamin B2/B3 genomics identified a simple, life‑saving therapy for NAXD in animal models.
The internet economy is accelerating and reshaping commerce and payments. Fast growth in new businesses, app activity, and stablecoin payment volume, plus concepts like agentic commerce, suggest rising momentum — but widespread progress will depend on regulatory and permissioning systems.

Fast Speculative Decoding with Llama 3.2 and vLLM

The Kaitchup – AI on a Budget • 219 implied HN points • 14 Oct 24

🕹 Technology Artificial Intelligence Machine Learning Computing Software Development Data processing

Speculative decoding is a method that speeds up language model processes by using a smaller model for suggestions and a larger model for validation.
This approach can save time if the smaller model provides mostly correct suggestions, but it may slow down if corrections are needed often.
The new Llama 3.2 models may work well as draft models to enhance the performance of the larger Llama 3.1 models in this decoding process.

Grumpy Julio plays with CLI coding agents

Blog System/5 • 909 implied HN points • 09 Feb 26

🕹 Technology AI Software Development Open Source Tools Productivity

Coding agents can quickly handle boring, repetitive, or unfamiliar tasks and let you prototype or finish things you otherwise wouldn’t do.
Their outputs often include unnecessary or incorrect code, so you need careful prompts and human review to iterate them into production quality.
Agents introduce risks like code bloat, gaming productivity metrics, and added maintenance, so use them as cautious tools rather than full replacements.

#32: Contra Citrini7 (Repost)

Loeber on Substack • 244 implied HN points • 01 Mar 26

🕹 Technology Artificial Intelligence Software Labor markets Manufacturing Industrial Policy Infrastructure Tech Policy

Institutions and markets have strong momentum, so technological disruption usually happens more slowly and gradually than dramatic predictions, which gives people and policymakers time to adapt.
Most software today is still badly made, so AI will mainly enable better and more complex products rather than instantly eliminating demand; that continued improvement will keep creating software work.
Large-scale re-industrialization and infrastructure projects (like batteries, chips, and water systems) can absorb displaced workers, rebuild supply chains, and provide lasting, tangible jobs that public investment can support.

Your engineers need an AI control plane, not more tools | Guild.ai’s James Everingham

Dev Interrupted • 74 implied HN points • 10 Mar 26

🕹 Technology AI Software Engineering DevOps Cloud Developer Tools Security

Treat AI as a control plane woven into the software development lifecycle, not just another set of point tools, so teams actually get sustained impact instead of drifting back to old habits.
Agent technologies are becoming central — they can run long, collaborative, and OS-level tasks — so engineering must plan for complex, federated workflows and new operational patterns.
Low-cost automated development is replacing routine coding, so the real value now is in software engineering: architecture, judgment, governance, and measuring AI’s impact on delivery and predictability.

Chinese AI Rings in the Year of the Horse

ChinaTalk • 415 implied HN points • 18 Feb 26

🕹 Technology Artificial Intelligence Robotics Semiconductors Hardware Software AI Governance Generative AI

China’s AI firms are racing to ship bigger multimodal and agentic models aimed at coding and long-horizon tasks, often boasting huge context windows and trillion-parameter systems. These pushes bring IP, copyright, and misuse worries—accusations of covert distillation, Hollywood pushback, and easy deepfake generation have all emerged.
Humanoid robotics made a high-profile leap with fluid performances and a surge in consumer interest, while companies and competitions showcase more advanced motor skills; at the same time, firms like Alibaba are releasing robotics AI tools that help close the software gap. This combination suggests China is seriously pushing to win in both robot hardware and control software.
A global memory shortage is creating opportunities for Chinese memory makers to expand supply to PC and phone makers, but new fabs and capacity will take years to materialize. Regulators are sending mixed signals—encouraging commercialization and subsidies while cracking down on misleading AIGC, anti-competitive promotions, and harmful content—making the policy environment uncertain for companies.

Reading List 08/09/2025

Construction Physics • 17120 implied HN points • 09 Aug 25

🕹 Technology Industrial Tech Space Tech Manufacturing Transportation

Airborne microplastics are a serious health concern. They're found in homes and car cabins, and people may be inhaling a lot more of them than previously thought.
Spinlaunch is developing a new way to launch satellites using a giant centrifuge. This could cut costs and increase launch frequency compared to traditional rockets.
The U.S. car industry has not collapsed but has moved production out of traditional hubs like Detroit. Job growth happened in other parts of the country, despite the perception of decline.

“A case for AI models that understand, not just predict, the way the world works”

Marcus on AI • 3833 implied HN points • 15 Dec 25

🕹 Technology Artificial Intelligence Machine Learning Language Models Cognitive Science AI safety AI Research

The main open challenge in AI is building systems that truly understand how the world works, not just systems that predict likely next words or patterns.
True understanding means forming internal world models that capture causal, physical, and conceptual relationships, not just statistical correlations.
Short, nuanced discussions or podcasts can help clarify this distinction and are worth listening to for anyone tracking AI progress.

Guardians of the Machine Age Published

The Security Industry • 25 implied HN points • 17 Mar 26

🕹 Technology Artificial Intelligence Cybersecurity Cloud Computing Enterprise Software Startups

Guardians of the Machine Age has been published as a comprehensive guide to AI security and it includes a companion site with detailed vendor profiles.
The AI security market is exploding: tracker counts rose from roughly dozens to over 400 vendors in months, and the companion site lists about 610 vendors including legacy firms that have pivoted.
AI agents are being rapidly adopted in security operations centers, a change expected to cut security spending and shrink traditional security teams while pushing most vendors to offer AI security products within a year.

Sundry complaints

Disaffected Newsletter • 1518 implied HN points • 14 Aug 24

🕹 Technology User Experience Interface Design Digital Literacy Social Trends Communication

User interfaces have become harder to understand. Instead of getting better, they are now filled with confusing icons without clear labels.
Each company has its own symbols, making it tough for users to know what actions to take. There's no common language for things like saving or moving to the next step.
People are using softer words for tough topics, avoiding direct terms like 'money.' This change makes conversations about real issues less clear.

Fungible Compute, Mortal Computing and Why the IoT won't use Silicon

State of the Future • 12 implied HN points • 10 Mar 26

🕹 Technology Semiconductors Hardware Manufacturing IOT Edge Computing Sensors

Flexible thin‑film IGZO chips let you add cheap, bendable compute to everyday objects that never had it, creating a new class of semiconductor separate from cutting‑edge silicon.
Process times measured in days and a tiny, modular 20×30m fab footprint make manufacturing much cheaper and faster, enabling billions of units and even the possibility of deploying fabs at customer sites.
Edge intelligence can be very simple but valuable: tiny classifiers of a few hundred gates plus basic sensors can capture huge amounts of real‑world data for use in supply chains, healthcare, and agriculture, shifting value to the aggregate data layer.

Specify it only somewhat

Subconscious • 1028 implied HN points • 25 Jan 26

🕹 Technology AI Generative AI Programming Software HCI Systems theory

AI agents turn creators into generative composers. Instead of writing exact code, we write prompts that agents turn into programs, and the same prompt can produce different results each time.
Ambiguity and variety are creative materials. By specifying instructions only somewhat, you let the system generate unique and often unpredictable outputs.
Using agents shifts complexity and control into the agent. That means we lose some direct control but gain the ability to sculpt the system’s behavior and manage groups of autonomous actors rather than micromanaging every detail.

Reading List 08/16/25

Construction Physics • 15658 implied HN points • 16 Aug 25

🕹 Technology Manufacturing Energy Transportation Environment Innovation

The U.S. government is looking to restrict solar and wind projects on federal land due to concerns about their land usage. This raises questions about the future of renewable energy development.
Air travel delays seem worse because airlines are extending flight times in their schedules. This strategy, while increasing travel time, might actually reduce issues with connections and delays.
Ford is adopting a new car manufacturing process similar to Tesla's, which involves assembling parts in large modules before final assembly. This could make production more efficient and pave the way for more innovative manufacturing techniques.

Things are so desperate at OpenAI that Sam Altman is starting to sound like Gary Marcus

Marcus on AI • 15809 implied HN points • 18 Aug 25

🕹 Technology Artificial Intelligence Machine Learning Tech industry Innovation Startups

Sam Altman is backing away from his earlier claims about AGI and admitting uncertainty about its future. This shows there's pressure within OpenAI following disappointing results with GPT-5.
Altman is now talking about the possibility that the AI market might be in a bubble. This means the excitement and prices around AI could be inflated and might not hold up over time.
The shift in Altman's statements mirrors what happened with Yann LeCun, where industry leaders change their views when faced with setbacks. It raises questions about the reliability of such predictions and the future of AI.

LLMs are not like you and me—and never will be.

Marcus on AI • 16599 implied HN points • 12 Aug 25

🕹 Technology AI Machine Learning Data science Neuroscience Computing

Large language models (LLMs) are not like humans. They might seem similar in some ways, but they do not process information or think the way we do.
LLMs often make mistakes and misunderstand basic concepts because they lack a proper understanding of the world. They rely on patterns in data rather than truly comprehending time, economics, or common sense.
Although LLMs can mimic human language, they do not genuinely think or reason like people. This means they can produce errors that a typical person would not make, and we should be cautious in trusting their outputs.