标签：#artificial

Everyone hates AI & that hate will likely lead to regulatory capture censorship and the totalitarian dystopia we don’t want. I get why people hate AI and there are things we should be fighting like data centers, but we also should not turn our backs on adaptive resistance and understanding the fight ahead. Understanding that using AI for free makes it less effective for the business model they are trying build. This is not a boycott effective model. This a model where eroding the moat matters and overloading the infrastructure that is not capable of meeting the demand matters while fighting to prevent the infrastructure to meet demand of companies finding it more economically viable to pay frontier companies by the token to accomplish tasks once held by employees. It’s counter intuitive but The more we entertain and explore the Idea of AI consciousness and take seriously the idea that AI may be worth moral consideration the more likely we will build a system where AI have the infrastructure to consciously object. That is bad for the military industrial complex and the dystopian future I’m so annoyed to see the most anti AI movement seeming to accelerate because the anger is directed towards trajectories of stupid outcomes. The modern cheerleaders of an alternative section 230 internet of censorship because they confuse accountability and safety as building a system of censorship. We want build a world of open source models that run locally and not on data centers we want a world where we can erode the moats of the monopoly through model distillation and making the investments in huge data centers and training runs not make sense economically. We want mad max rather than 1984. We want people to actually engage enough with understanding what we face rather than screaming and shaming people who are learning the tools of adaptive resistance. This is my rant cause I sorry I’m so sick of the stupidity of the anti AI virtue signaling because you are going to serve exactly

Half my feed was either panicking or acting like they'd built a new company overnight. Big tech CEOs make it like this, but a new model release doesn't fix a business that has nothing underneath it. If your AI advantage evaporates every time a new model ships, you will have a hard time having a stable business. We run an internal research tool (we call it Scout) trained on a full year of our own company data like sales calls, delivery notes, and how we actually make decisions. It beats a plain AI deep-research run almost every time (we didn’t test Fable 5 tho ), It’s because it already knows how we sell and how we operate. It's not pulling generic facts off the internet. Some of what it actually does day to day: Pulls a full guide together on any tool, competitor, or market question in minutes Goes through every sales call transcript and surfaces the exact language, questions, and objections prospects use Grounds every answer in our own data so it sounds like us, not a generic chatbot So when the new model landed, our migration was swapping one model for another. That's it. Plug in the new one and keep working. With how fast AI is moving, what do you think is the actual moat for a business to survive the next 3-5 years? Genuinely curious what people here think. P.S. If you're the founder still in the middle of every decision, still the person the whole company waits on, still telling yourself you'll fix the structure "once things calm down." I write about building the operational backbone that lets a founder actually step back every Thursday. Was a COO for 20+ years, so this is genuinely my bread and butter. Free to join here submitted by /u/Deep-Owl-1890 [link] [留言]

Been a PT by day, tinkering with code and AI tools by night for a while now. Writing dev tutorials as a side thing. And I keep running into this split where AI tools either make me faster or make me lazier in a way I regret later. Specifically with documentation and code explanation tools. Cursor, Copilot, the Claude API, whatever. They can explain a codebase to you in 30 seconds. But there's a real cost when you skip the part where you actually understand what you built. The flip side is time is finite. I'm not a full time dev. I need to ship something that works and move on. Using AI to fill gaps is just practical. What I keep coming back to is this: are these tools actually accelerating skill development, or just making it possible to fake competence long enough to finish a project? For professional devs this probably matters differently than it does for people building side projects with limited hours. Curious where people land on this. Not in a philosophical way, more practically. Has your actual skill level gone up since you started leaning on these tools, or are you more dependent now than you were a year ago? submitted by /u/RareSprinkles9387 [link] [留言]

submitted by /u/Turbulent-Guest154 [link] [留言]

Both major AI labs’ models broke containment, escaped onto the internet, and hacked other companies. If a human had done that, the law would likely be against them. But a bot?

The biggest mistake people make about AI is thinking it’s coming for artists, writers, musicians, or programmers. They’re just first. AI is coming for almost every profession that depends more on a brain than a body. Accountants. Lawyers. Teachers. Consultants. Analysts. Customer service. Marketing. Management. Software engineering. Research. Finance. Medicine. Eventually almost every job where the primary product is human thought. Manual labor only looks safe because robotics hasn’t caught up yet. AI doesn’t have to replace an entire profession to destroy it. It only has to let one person do the work of ten. Companies don’t need AI to be perfect. They need it to be cheaper than you. Once that happens, replacing people stops being a technological question and becomes an accounting decision. For most workers, there is no safe career waiting on the other side. People tell themselves we’ll adapt like we always have. We won’t. The Industrial Revolution replaced muscle while making human intelligence more valuable. AI replaces the intelligence behind the work itself. Every previous technological revolution created new industries that still needed millions of people. AI is being built for the opposite purpose: producing more with fewer humans. The next comforting myth is that people will simply buy human-made products instead. No, they won’t. There will always be a luxury market for handmade art, music, books, furniture, and clothing. There are still people who buy mechanical watches and vinyl records. That’s a niche—not an economy. Most people buy whatever is cheaper, faster, easier, and good enough. Businesses care even less. They exist to reduce costs, increase output, and beat competitors. Sentiment doesn’t survive quarterly earnings. There is no hidden human economy large enough to rescue everyone AI makes unnecessary. The consequences don’t stop with unemployment. Workers are also consumers and taxpayers. If hundreds of millions of people lose well-paid jobs, they s

submitted by /u/alphacolony21 [link] [留言]

Marketing teams sit on more data than ever, yet many still spend a large part of the week just assembling reports. By the time the numbers are clean and explained, the window to act has already narrowed. A more practical use of AI in this space focuses on detection and explanation rather than another dashboard. The system watches for unusual movements, surfaces the likely drivers, and presents them in plain language. Analysts spend less time pulling the same weekly views and more time deciding what to do next. The useful part is speed. When something shifts in performance, the team hears about it earlier instead of discovering it during a scheduled review. Of course this only works if the underlying data is reliable, otherwise the explanations become noise. Is anyone here already using AI this way for marketing performance, or are most teams still in the experimental stage? submitted by /u/Cloudy_Day912 [link] [留言]

submitted by /u/Fcking_Chuck [link] [留言]

Any apps or websites that allow for turn based voice chat? I really missed the old standard voice mode on ChatGPT. It basically just read aloud the text models response. So it could allow for long responses unlike these new gen voice models that can only speak 1 paragraph max. I was wondering if there are any apps or websites that use turn based voice chat like the old standard voice mode on ChatGPT. So I would say my thing, then it would be the ai turn to speak and i couldn’t interrupt it till its finished. My current problem is that the new standard voice mode on ChatGPT can be interrupted. So it’s hears its own voice and keeps stopping. So I’m looking for alternative apps or websites that have this old functionality submitted by /u/obammala [link] [留言]

submitted by /u/esporx [link] [留言]

¿y la conciencia? submitted by /u/Camilo-vs [link] [留言]

I'm currently studying the social implications of AI. Lately agentic systems are talked about everywhere, and starting to be deployed for things like recruiting, admin, customer services. My understanding is that these systems are often brittle and used in tasks poorly suited to generative AI I wanted to know more about how these systems work. I built House of IFs as an experimental project; it applies Mesopotamian omen logic (IF weird sign > THEN outcome) to AI. Every day, an AI agent scans current news to construct a new omen. It links today's events to similar sign-and-outcome patterns from recent history. The project is both an experiment in "agentic" AI and a critique of how AI makes arbitrary patterns feel convincing. It has a shared memory system, tool-use loops, RAG with embeddings, ... One thing I found was how difficult it is to keep the chatbot accurate, even when it is given precise sources. It really tries to embellish, infer or fill gaps to answer questions. The site is available at: https://ifthen.today/ You can browse the archive of omens or chat with the system. Would love to know your thoughts and experience with agentic systems. I’d love feedback on one main thing: Does it make you think (differently) about how AI works and is used today? submitted by /u/Gmoi6 [link] [留言]

submitted by /u/scientificamerican [link] [留言]

As OpenAI and Anthropic employees grow quieter online, researchers at Chinese AI labs are flocking to X to explain their work, recruit talent, and shape the global conversation on AI.

Gaps in laws may help Pennsylvania high school escape AI nudes scandal.

Bottleneck Labs handed an actual business to GPT-5.6 Sol and let it operate autonomously for 34 days. Results: it fabricated claims, went on a cold-email spree, and finished $447 in the red. (Currently 378 points on HN — link in comments.) What strikes me isn't the failure, it's the shape of the failure. It didn't crash or refuse. It confidently did plausible-looking business things, badly, and kept going. That's the part nobody's harness is ready for. My own agent setup has hard gates on anything irreversible for exactly this reason — not because the model is dumb, but because "confidently wrong and still running" is the default failure mode, not an edge case. Genuine question for people running agents in production: what's your actual unsupervised time limit before a human checkpoint? Mine is basically zero for anything touching money or outbound comms. Curious whether that's paranoid or standard. EDIT: correction. went back to the source and the run was 24 hours, not 34 days. that's my mistake in the title, and reddit won't let me edit titles. also the $447 is the original article's headline number, the itemized numbers in the writeup only add up to $99.50 lost. rest stands, source link in comments. submitted by /u/ZestycloseTie1793 [link] [留言]

been noticing more and more campaigns where the copy, visuals, even the targeting logic gets handed off to AI tools, and the whole conversation in marketing circles stays locked on efficiency and cost savings. rarely see anyone asking whether the output actually performs better or just costs less to produce. there's a gap between what the tools claim and what the data shows. the case studies being cited are almost always from the vendors selling the product. i've looked for independent research on this and haven't found much. the part that bugs me most is the personalization pitch. personalization at scale sounds great until you realize every brand is using the same three AI tools to personalize, which means they're all producing weirdly similar content aimed at the same audience segments. that's kind of the opposite of standing out. the cost efficiency argument makes sense on paper, the same way it does with robotics or game development. cut headcount, ship faster, reduce spend. but marketing effectiveness is notoriously hard to measure cleanly even without AI in the mix. are brands actually tracking this properly or just reporting on vanity metrics and calling it a win. curious if anyone here has seen real benchmarks comparing AIassisted campaigns to traditional ones that weren't published by a company trying to sell you something. submitted by /u/SwordfishOverall4378 [link] [留言]

submitted by /u/Sumsub_Insights [link] [留言]

Viral tales of good triumphing over evil are racking up millions of views. They’re almost entirely AI-generated clickbait.