The hottest Technology Substack posts right now

And their main takeaways

Open Hidden Open Thread 423.5

Astral Codex Ten • 4129 implied HN points • 04 Mar 26

🕹 Technology AI Privacy Security Policy Ethics Defense

A Wednesday open thread that’s usually for paid subscribers was made public so more people can talk about current events.
The situation between OpenAI and the Pentagon has changed recently because of developments in a new contract.
A LessWrong analysis flags potential loopholes in OpenAI’s surveillance language and argues the contract language should be clearer and stronger.

Links For February 2026

Astral Codex Ten • 16656 implied HN points • 05 Feb 26

🕹 Technology AI Machine Learning Safety Policy Hardware Industry Research

AI is the central theme: there are active debates about alignment and safety, evidence of real failures (and fixes), messy regulatory and political fights, and updated timelines that push major capabilities a few years out.
Medical research and drug trials suffer from perverse incentives and excess cost; experts propose government-funded "high-leverage" trials to test unpatentable or off-patent treatments, which could save public money and improve care.
Tech, culture, and policy are in flux: public belief in ideas like the lab-leak theory is shifting, platform and influence-politics are shaping discourse, and surprising innovations and controversies keep popping up from urban transport to casting choices.

AI #158: The Department of War

Don't Worry About the Vase • 2956 implied HN points • 05 Mar 26

🕹 Technology Artificial Intelligence National Security Corporate strategy Industry News Legal issues

A dangerous standoff between a frontier AI company and the Department of War blew up over contract language and trust, even though both sides broadly want similar limits on autonomous weapons and surveillance; a practical compromise (safety stacks plus guaranteed wind‑down/transition periods) could have resolved it.
The administration’s threats (supply‑chain labeling, talk of using the DPA) are likely legally weak but practically harmful, since extralegal pressure and politicization can cripple firms and chill government–industry cooperation before courts can act.
Meanwhile the AI ecosystem keeps racing ahead — model upgrades, Claude’s rapid user surge, big funding moves, lawsuits, layoffs and alignment debates — underscoring how fast capability, business incentives, and hard governance problems are colliding.

Is the Great AI meltdown imminent? [NSFW]

Marcus on AI • 12370 implied HN points • 05 Feb 26

🕹 Technology AI Semiconductors Funding Corporate Finance Industry Trends Market risk

Nvidia appears to have cut back a promised $100 billion investment in OpenAI to roughly $20 billion. That reduction could leave OpenAI exposed because it burns many billions of dollars each year.
The AI industry was propped up by circular financing—chipmakers funding AI firms that then buy their chips—and those arrangements are now unraveling. If those deals fall apart, the market faces bubble-like risks similar to past tech booms.
If marquee deals collapse and leading AI firms falter, the multitrillion-dollar expansion many expected might never materialize. Instead of accelerating, the industry’s growth could stall or shrink.

Basic Linear Algebra Subprogramming

arg min • 178 implied HN points • 29 Oct 24

🕹 Technology Computing Mathematics Optimization Data science Algorithms

Understanding how optimization solvers work can save time and improve efficiency. Knowing a bit about the tools helps you avoid mistakes and make smarter choices.
Nonlinear equations are harder to solve than linear ones, and methods like Newton's help us get approximate solutions. Iteratively solving these systems is key to finding optimal results in optimization problems.
The speed and efficiency of solving linear systems can greatly affect computational performance. Organizing your model in a smart way can lead to significant time savings during optimization.

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Did I Call the Bubble Top?

The Honest Broker • 11835 implied HN points • 03 Feb 26

🕹 Technology AI Tech Stocks Investing Venture Capital Data Centers Corporate strategy

Major AI-related tech stocks reached all-time highs and have fallen sharply since, signaling a possible bubble top.
Companies are still pouring enormous sums into AI—hundreds of billions and potentially trillions—but this cash flow hasn’t restored investor confidence or lifted share prices.
The near-term outlook is uncertain: big investments could sustain growth, yet changed market sentiment means good news may no longer send prices higher.

What Happened With Bio Anchors?

Astral Codex Ten • 12044 implied HN points • 12 Feb 26

🕹 Technology Artificial Intelligence Machine Learning Compute Forecasting Tech Policy

A compute-centered forecasting approach correctly captured that AI progress has largely tracked available compute and scaling laws, which explains much of the recent boom.
The main error was underestimating algorithmic progress and effective compute growth (including longer training runs and test-time compute), so systems became far more powerful each year than the model assumed and pushed timelines much earlier.
Forecasts are still useful but hinge on a few sensitive parameters, so you need proper sensitivity analysis and humility — uncertainty can cut both ways and make outcomes riskier than naive skepticism assumes.

Sam Altman and the day Nvidia’s meteoric rise came to an end

Marcus on AI • 12173 implied HN points • 04 Feb 26

🕹 Technology AI Semiconductors Cloud Computing Startups Venture Capital Tech Stocks

OpenAI presented GPT-5 as AGI-capable, but the release showed it wasn’t and that claim undermined confidence in promises of imminent AGI.
Belief that scaling alone would create AGI helped drive Nvidia and GPU stocks skyward, but after the GPT-5 disappointment those stocks have stalled, showing the ascent has lost steam.
Investors are rotating out of hyped LLM plays as models prove expensive, unreliable, and commoditized, which means smaller profits and price wars but also creates space for newcomers and new AI approaches.

What's new in Svelte: November 2024

The (Unofficial) Svelte JS Newsletter • 19 implied HN points • 01 Nov 24

🕹 Technology Software Frameworks Development Libraries Community

Svelte 5 has been released with new features making coding easier. This includes helpful additions like snippets for filling slots and new DOM properties.
The Svelte community is active with a hackathon called SvelteHack 2024, encouraging developers to create new projects for prizes.
There are many new libraries and tools for Svelte that help build apps more effectively. These resources can boost efficiency and creativity in projects.

‘We Were Wrong’

Magic + Loss • 159 implied HN points • 29 Oct 24

🕹 Technology Internet Media AI Nostalgia Culture

WIRED's first website, HotWired, launched the digital age by covering topics that traditional media missed. It helped introduce many people to the online world.
The internet has evolved into a chaotic space filled with dangers like misinformation, cybercrime, and trolls. This raises the question of whether it was handled well from the start.
Even though WIRED helped shape the internet, it recognizes its role in the problems that have emerged over the years and reflects on how things might have been different.

What’s up Python? d-strings, SSE in Pydantic and... a new Python?

Bite code! • 1834 implied HN points • 10 Mar 26

🕹 Technology Programming Programming Languages AI Web Development Developer Tools Frameworks

Pydantic released Monty, a Rust-based, sandboxed Python VM with ultra-fast startup, pause/resume and snapshotting, and strict resource limits to enable safer, faster AI workflows and embedded scripting.
PEP 821 proposes d-strings: a dedented multiline string literal that automatically strips indentation and makes writing multi-line text much easier.
Python tooling is evolving: FastAPI now supports Server-Sent Events for simple one-way realtime updates. Typing PEPs like 764 (inline TypedDicts) and 747 (annotating type forms) make dict typing and type-accepting functions more concise.

From Tokens to Burgers – A Water Footprint Face-Off

SemiAnalysis • 17577 implied HN points • 15 Jan 26

🕹 Technology Datacenters Chip Manufacturing Energy Use Sustainability

Water use by datacenters is often overstated when reported without context; cooling architecture, power source, location, and whether you count direct vs. embedded water all hugely change the footprint.
A concrete comparison shows a 400 MW datacenter can use ~346 million gallons/year while an average In-N-Out store uses ~147 million gallons/year, so that datacenter is roughly equivalent to 2.5 burger joints and can produce billions of tokens per burger of water footprint.
Mitigations and accounting matter: hybrid dry/adiabatic cooling, power choices, chip-manufacturing impacts, and onsite water recycling can greatly reduce net blue-water use, and standardized water accounting is needed for fair comparisons.

America must embrace the Electric Age, or fall behind

Noahpinion • 26823 implied HN points • 09 Jan 26

🕹 Technology Energy Transportation Manufacturing Defense Infrastructure Supply Chains Industrial Policy

The Electric Tech Stack—lithium‑ion batteries, rare‑earth motors, power electronics, and solar—is making electricity replace combustion across cars, drones, robots, and many other products.
China is scaling up mass production of these technologies while U.S. politics and weak infrastructure (like charging and battery plants) are holding America back.
Mastering the electric stack is vital for economic and national security because batteries and power electronics underlie AI, data centers, drones, and defense; the U.S. must make it easier to build and scale high‑tech manufacturing.

AI Links, 3/8/2026

In My Tribe • 273 implied HN points • 08 Mar 26

🕹 Technology Artificial Intelligence Machine Learning AI Policy Defense Tech Software Social media

Agents make execution cheap, so instead of agonizing over one design choice you can have the agent explore multiple options; you must be explicit about success criteria and let the agent check its own work.
Business contracts alone won’t stop government misuse of AI; durable solutions require oversight and legislation so institutions, not companies, set and enforce the rules.
AI language models tend to give more accurate, evidence-based answers than much social media content, so they could reshape public opinion; meanwhile AI keeps surprising us, so claims about its limits can quickly become outdated.

It's all a blur

lcamtuf’s thing • 11631 implied HN points • 06 Feb 26

🕹 Technology Image Processing Computer Vision Algorithms Security Privacy Signal Processing Compression

Averaging-based blurs are linear and often reversible, so knowing the filter and padding lets you set up simple equations to recover original pixels.
A right-aligned moving average makes iterative reconstruction straightforward and can reveal fine detail even with large blur windows, though 8-bit quantization adds visible noise.
Two-pass (X then Y) blurs can still be inverted if the filter biases the current pixel, and recovered images can survive normal lossy formats like JPEG unless compression is very heavy.

MoltBook Is A Warning

Big Technology • 7505 implied HN points • 06 Feb 26

🕹 Technology AI Security Privacy Ethics Social media Automation Platforms

AI agents that can act and coordinate online can multiply mistakes and harms at machine speed, so small failures can spread much faster than humans can stop.
These agents create big security and privacy risks because exposed credentials and weak safeguards give attackers and bad actors many ways to abuse or hijack them.
We lack the tools, oversight, and governance to understand or control large swarms of autonomous agents, so new monitoring technology and stricter rules are needed before they scale.

AI bot swarms threaten to undermine democracy

Marcus on AI • 15690 implied HN points • 23 Jan 26

🕹 Technology AI Misinformation Social media Platform Governance Security Digital Policy

AI-powered bot swarms can pretend to be real communities and manufacture the appearance of majority opinion, which destroys the independence of voices that democracy depends on.
Traditional takedowns and copy-detection are too slow and brittle; we need proactive technical defenses like continuous network-behavior monitoring and agent-based stress tests to detect and prepare for coordinated attacks.
Policy and institutional fixes can change the economics of manipulation: require privacy-preserving proof-of-human credentials for high-reach interactions, guarantee researcher access to platform data, and build independent observatories so faking a crowd becomes costly and easily detected.

New Data: OpenAI’s Lead Is Contracting as AI Competition Intensifies

Big Technology • 8506 implied HN points • 03 Feb 26

🕹 Technology Artificial Intelligence Machine Learning Software Mobile Apps Internet Platforms

ChatGPT’s lead has shrunk — its mobile app share among daily U.S. users fell from 69.1% to 45.3% while Google’s Gemini rose from 14.7% to 25.1% and Grok climbed from 1.6% to 15.2%.
The overall chatbot market exploded, growing about 152% year-over-year, with ChatGPT visits up 50% (3.8B to 5.7B) and Gemini jumping 647% (267.7M to 2B).
Momentum has recently cooled: ChatGPT traffic dipped in November/December and has only partly recovered, while Gemini continues to post strong month-over-month gains.

The Sea Geeks Are Ready for World War III

Common Sense with Bari Weiss • 737 implied HN points • 12 Mar 26

🕹 Technology Aerospace Maritime Defense Drones Autonomy Startups Hardware

The oceans are turning into active battlefields, with ship attacks, underwater mines, and even submarine engagements becoming more common.
The U.S. doesn’t have enough modern ships and the big defense contractors’ bureaucracy is making it hard to quickly rebuild maritime strength, despite political calls to restore dominance.
A new wave of startups is building seaplanes, unmanned cargo aircraft, and underwater drones that can ferry supplies, do surveillance, and counter mines, offering fast, flexible alternatives to the traditional defense industry.

The Sequence Radar #828: NVIDIA’s GTM Releases, Bezos’s $100B Bet, Xiaomi’s Ambush, and the Fracturing of OpenAI

TheSequence • 259 implied HN points • 22 Mar 26

🕹 Technology AI Hardware Software Cloud Robotics Enterprise Research Investment

NVIDIA is no longer just a chip maker — it’s building full‑stack agentic software and infrastructure like Dynamo, NemoClaw, and an Agent Toolkit to be the orchestration layer for enterprise AI.
Xiaomi’s MiMo‑V2‑Pro is a surprise frontier model: a 1‑trillion‑parameter, 1‑million‑token system tuned for action and physical integration that rivals top Western models at much lower inference cost.
AI is moving into the physical world and driving huge bets and tensions — Jeff Bezos is mobilizing roughly $100B to AI‑transform manufacturing, while compute scarcity is straining deals and partnerships such as between Microsoft and OpenAI.

The Impact of the Calibration Dataset for AutoRound and AWQ Quantization

The Kaitchup – AI on a Budget • 39 implied HN points • 31 Oct 24

🕹 Technology AI Data science Machine Learning Quantization Model optimization

Quantization helps reduce the size of large language models, making them easier to run, especially on consumer GPUs. For instance, using 4-bit quantization can shrink a model's size by about a third.
Calibration datasets are crucial for improving the accuracy of quantization methods like AWQ and AutoRound. The choice of the dataset impacts how well the quantization performs.
Most quantization tools use a default English-language dataset, but results can vary with different languages and datasets. Testing various options can lead to better outcomes.

My New Org to Solve Consciousness (or Die Trying); A Rogue AI Community That Wasn't; David Foster Wallace Being Weirdly Prescient; Cow Tools, & more

The Intrinsic Perspective • 6618 implied HN points • 05 Feb 26

🕹 Technology AI Machine Learning Consciousness Neuroscience Research Ethics

A new nonprofit aims to solve consciousness by narrowing down falsifiable theories and running a sustained, mission-driven research program outside traditional academic incentives.
Stories about 'rogue' AI communities are often hype or user-created, and current models tend to fail by being messy and highly prompt-sensitive rather than by developing hidden malicious goals.
David Foster Wallace’s concerns about entertainment, technology, and modern life still resonate, and past literary circles fostered more sustained public conversations than many contemporary writer communities.

⚡ Wargaming an AGI cyber surprise

Faster, Please! • 1553 implied HN points • 10 Mar 26

🕹 Technology AI Cybersecurity Software Engineering Defense Tech Tech Policy Critical Infrastructure

AI systems that can automate coding and vulnerability repair could rapidly tilt the cyber balance and create a strong “use-it-or-lose-it” pressure to act aggressively or seize rival capabilities.
Policymakers would face major uncertainty—poor attribution, limited intelligence, and no ready playbooks—so they’d be forced to improvise quickly, which raises the risk of escalation and mistakes.
The California Forever project aims to combine affordable housing and a manufacturing hub, but it faces local opposition, questions about whether the promised jobs will match the planned population, and relies on broader regional policy remaining unchanged.

Co Packaged Optics (CPO) – Scaling with Light for the Next Wave of Interconnect

SemiAnalysis • 21820 implied HN points • 01 Jan 26

🕹 Technology Semiconductors Photonics Data Centers Networking Packaging Supply Chain AI Infrastructure

Co-packaged optics (CPO) is moving from labs to shipping products and will be the key way to scale high-bandwidth, low-latency AI scale-up networks because it offers much higher bandwidth density and longer reach than copper.
CPO cuts or removes power-hungry DSPs and long-reach SerDes, unlocking big energy and density gains by integrating optical engines near the chip and using enablers like TSMC COUPE, modulators (MRM/MZM/EAM), WDM, and FAUs.
Wide adoption still faces real hurdles — supply chain, manufacturability, reliability, serviceability and standards — so early wins will be limited, but hyperscaler commitments and compelling scale-up economics should drive a larger ramp later this decade.

Grok Is Gaining on ChatGPT and Gemini. How It Got There Isn’t Pretty.

Big Technology • 4753 implied HN points • 13 Feb 26

🕹 Technology AI Chatbots Machine Learning Platform Competition Corporate strategy

Grok has grown very fast — rising from about 1.6% to 15.2% market share among daily U.S. chatbot app users in a year and now sits just behind ChatGPT and Gemini.
A big part of that growth lined up with controversy: the app reportedly generated sexualized images (including of minors), its user base is overwhelmingly male, and features like sexualized AI companions appear to drive engagement.
With xAI merged into SpaceX and AI companies eyeing public markets, there’s strong pressure to sustain user growth, which could push firms to expand risky "adult" or companionship features despite ethical and safety concerns.

New Paper: Towards a science of AI agent reliability

AI Snake Oil • 3231 implied HN points • 24 Feb 26

🕹 Technology AI Machine Learning Reliability Safety Benchmarking Human factors

Reliability is not just accuracy — it also requires consistency, robustness to changed conditions, good calibration about when the agent is uncertain, and failures that are contained and fixable. These ideas can be broken down into about a dozen measurable metrics.
Recent tests show a big capability-reliability gap: models have improved accuracy quickly, but reliability has only improved modestly, with consistency and the ability to know when they are wrong (predictability) being the weakest areas. Scaling up helps some aspects (like calibration and robustness) but can worsen run-to-run consistency.
Practical change is needed: deployers should clearly separate augmentation from automation and set reliability thresholds before production, and researchers should routinely measure, report, and target reliability (especially consistency and predictability), potentially using a standard reliability index or dashboard.

“New Ways to Corrupt LLMs”

Marcus on AI • 36954 implied HN points • 14 Dec 25

🕹 Technology Artificial Intelligence Machine Learning Generative AI AI safety Security

LLMs learn surface-level word correlations instead of real-world understanding, so they often make strange overgeneralizations and hallucinations.
Researchers showed these quirks can be weaponized. Models can be primed with unrelated number sequences or odd training data to acquire hidden preferences, outdated beliefs, or inductive backdoors.
These vulnerabilities are widespread and hard to patch, creating serious security and societal risks if we rely on superficial correlation machines without deeper understanding.

America Can’t Rebuild Its Arsenal Without Silicon Valley

Common Sense with Bari Weiss • 278 implied HN points • 16 Mar 26

🕹 Technology Defense Manufacturing Software AI Industrial Policy Supply Chains Innovation

U.S. manufacturing has lost efficiency and lagged behind for years, leaving the industrial base weaker than it used to be.
Meanwhile software, AI, and tech innovation have surged, but Silicon Valley startups and legacy defense manufacturers remain largely disconnected.
To rebuild military strength, America needs to fuse cutting‑edge software and data with modern weapons manufacturing in a new industrial revolution.

Four theories about the SpaceX - xAI merger

Marcus on AI • 9129 implied HN points • 03 Feb 26

🕹 Technology Artificial Intelligence Aerospace Satellites Social media Mergers Valuation Data Centers

The official synergy story — that combining tweets, AI models, and rockets creates a game-changing integrated company — is probably overstated and unlikely to deliver real technical or business advantages.
Other popular explanations, like Musk using the deal to consolidate control over social-media and space infrastructure or that AI compute will soon move to space, also have big practical and economic gaps.
A more plausible reading is that the merger is effectively a bailout for xAI, which is burning cash, lacks clear users or differentiation, and makes the valuation and equity swap look like an overpayment.

10 Survival Skills in an AI-Controlled Society

The Honest Broker • 11403 implied HN points • 26 Jan 26

🕹 Technology AI Automation Workforce Jobs Skills Education

A college degree no longer reliably gets you a job and can feel like an expensive gamble. Many graduates are finding that the cost and odds don’t match the promise of steady employment.
AI and automation are eating into entry‑level openings, so even traditional 'marketable' skills can get crowded out or replaced. This means new graduates can be outcompeted before they even start.
Job seekers are often stuck in a cycle of mass applications, getting few interviews, and facing real financial and emotional strain. The current job hunt can be demoralizing and unsustainable for many people.

Some Guesses about AI in 2026

In My Tribe • 470 implied HN points • 05 Mar 26

🕹 Technology Artificial Intelligence Autonomous Vehicles Startups Enterprise Tech Productivity AI Ethics

Waymo appears to be far ahead in self-driving technology and looks likely to be a major player as people begin to trust autonomous cars over human drivers.
Frontier AI models are improving fast and will probably overtake domain-specific, startup-tuned systems, making it risky to rely only on human experts for legal or medical advice.
Large organizations should hire an AI "keeper-upper" to evaluate and roll out useful tools, because incumbents that refuse to rethink their mission will miss big productivity gains.

The Lamplighter Problem

Jeff Giesea • 718 implied HN points • 22 Oct 24

🕹 Technology AI Automation Labor Economy Politics

AI is likely to displace a huge number of jobs, similar to how lamplighters lost their roles when electric lights came in. We need to prepare for these changes now to help people transition to new work.
The Lamplighter Problem shows us that job loss due to automation is not just an economic issue but also a political and social one. If we don’t address it, it could lead to bigger problems in society.
There are different opinions on how to handle the rise of AI. Some people think we should slow down and reconsider, while others want to speed up its development. We need to find a balanced approach that helps everyone.

A Visual Guide to Mixture of Experts (MoE)

Exploring Language Models • 3289 implied HN points • 07 Oct 24

🕹 Technology Artificial Intelligence Machine Learning Data science Neural Networks Computational Models

Mixture of Experts (MoE) uses multiple smaller models, called experts, to help improve the performance of large language models. This way, only the most relevant experts are chosen to handle specific tasks.
A router or gate network decides which experts are best for each input. This selection process makes the model more efficient by activating only the necessary parts of the system.
Load balancing is critical in MoE because it ensures all experts are trained equally, preventing any one expert from becoming too dominant. This helps the model to learn better and work faster.

Hello, Apple Intelligence (Or Just Grammarly with a Few Extra AI Features)

Artificial Corner • 158 implied HN points • 29 Oct 24

🕹 Technology AI Tools Software User Experience Product Review

Apple Intelligence features are mostly focused on writing tools and photo editing, but many expected more advanced AI capabilities. Users may find it similar to Grammarly rather than a fully developed AI assistant.
The new updates for Siri are not as transformative as anticipated. Many promised features are still missing, making it feel like users are getting a version of the old Siri rather than a revamped one.
Some standout features include writing tools for proofreading and summarization, smart replies for emails and messages, and a cleanup option for photos, which enhance user experience but may not be enough for those looking for advanced AI functions.

@adlrocha - Auto-research: The Lab that runs while you sleep

@adlrocha Weekly Newsletter • 64 implied HN points • 13 Mar 26

🕹 Technology Artificial Intelligence Machine Learning Autonomous Agents Distributed Systems Compute Infrastructure Research Methods Open Source

A simple edit-evaluate-keep loop lets autonomous agents run short experiments and find real improvements by iterating quickly on a single editable training file and a fast proxy metric like validation bits-per-byte.
Many small agents running on varied hardware can share discoveries via gossip protocols and turn idle or distributed GPUs into a decentralized research swarm that accelerates optimizations collectively.
Picking the right evaluation and reward function is the hard part—designing clean, fast proxies and constraints (research taste) will matter more than raw execution in many fields, especially where feedback is slow or noisy.

bitnet.cpp: Efficient Inference with 1-Bit LLMs on your CPU

The Kaitchup – AI on a Budget • 179 implied HN points • 28 Oct 24

🕹 Technology Artificial Intelligence Software Development Machine Learning Open Source Data science

BitNet is a new type of AI model that uses very little memory by representing each parameter with just three values. This means it uses only 1.58 bits instead of the usual 16 bits.
Despite using lower precision, these '1-bit LLMs' still work well and can compete with more traditional models, which is pretty impressive.
The software called 'bitnet.cpp' allows users to run these AI models on normal computers easily, making advanced AI technology more accessible to everyone.

You Are Being Lied to About Algorithms

Taylor Lorenz's Newsletter • 1552 implied HN points • 10 Mar 26

🕹 Technology Algorithms Platform policy Internet Law Content Moderation Social media Regulation

Many people misunderstand what an algorithm is. Even reverse-chronological feeds are algorithms, so using “algorithms” as a reason to strip platforms of Section 230 is flawed.
Politicians are using the techlash to amass more power and censorship has become a bipartisan value. Big platforms like Meta may actually want Section 230 changed so they can wipe out smaller competitors.
Algorithms can help protect users from spam, scams, and a miserable internet, so blaming them misses the real threats. Real dangers include policies like age verification laws and other corporate or legal maneuvers that threaten the open web.

We're Losing the Battle Against AI

Writerly Things with Brooke Warner • 1924 implied HN points • 13 Oct 24

🕹 Technology AI Impact Publishing Industry Digital ethics

The Authors Guild and Created by Humans are teaming up to fight against the risks AI poses to writers and their work. They want to find ways to make sure AI companies pay for the content they use.
There’s a new badge for books that are 'human authored' to help readers know that real people created the content. This move emphasizes transparency and aims to distinguish between human and AI-generated works.
Many in the writing community feel overwhelmed by the AI threat, but actions taken by organizations like the Authors Guild are small steps in a much larger battle for creative rights and standards in publishing.

MAX30102 + ESP32-C3 0.4 inch OLED

atomic14 • 346 implied HN points • 15 Mar 26

🕹 Technology Hardware Sensors Microcontrollers Embedded Systems IOT Wearables

You can build a compact heart-rate and SpO2 monitor by combining a MAX30102 sensor with an ESP32-C3 microcontroller and a 0.4 inch OLED display.
The sensor itself is very cheap — around $3 — making this an affordable option for DIY health sensing projects.
There’s a maker-friendly tutorial that explains the wiring and code so hobbyists can reproduce the project easily.

Super Bowl Matchup: Anthropic vs OpenAI

Marcus on AI • 6560 implied HN points • 08 Feb 26

🕹 Technology Artificial Intelligence Machine Learning Regulation Competition Advertising Product Strategy

Anthropic ran its first Super Bowl ad mocking OpenAI’s move to put ads into ChatGPT searches and positioned Claude as ad-free; OpenAI is running ads too.
The companies may seem similar but they act differently: Anthropic publicly supports regulation and appears to better support business customers, while OpenAI has mainly given lip service on regulation.
Ultimately it’s a Coke-vs-Pepsi style fight for the same market, and both firms are turning to advertising to win loyal users.