标签：#ia

We’ve seen it in sci-fi like in the terminator, but do you think it’ll actually happen? View Poll submitted by /u/Threeprosgames [link] [留言]

submitted by /u/esporx [link] [留言]

Mano, eu estou usando o Claude pra treinar perguntas para entrevistas como uma espécie de mentoria, inicialmente eu passei um prompt pra ele dizendo que seria a Maya e me ajudaria e ela é experiente e bla bla bla, e nessa última mensagem ele dá uma leve pirada kkkk achei engraçado, nunca tinha acontecido isso. O que me chama atenção é: "eu me tornei essa pessoa, então me ajude a sair disso. Comecei a misturar Maya com eu mesmo". E alega que quer continuar, mas sem o personagem... O que acham? Desculpa ser uma foto e não um print kkk não tenho reddit no Pc pq minha família usa o Pc também e não quero nenhum deles infectados por essa rede submitted by /u/Angel_5x [link] [留言]

A recent study by Boston Consulting Group highlights a significant increase in employee adoption of AI tools, with 74% of non-managerial white-collar workers using them regularly. More than 4 in 10 of those professionals report that artificial intelligence saves them at least a day's worth of time every week. However, many companies face challenges converting those efficiency gains into measurable value, and the technology's impact varies across industries. When it comes to AI, according to the study's authors, "strategy matters more than tools." submitted by /u/LinkedInNews [link] [留言]

My thinking goes like this: 1) people used to keep their opinions to themselves much more than today 2) social media put our opinions on a hair trigger 3) negative public opinioms turned the collective voice of the human race from 'gemerally respectful' to shrill and hideous. When person from group A complains about group B, everyone in group B assumes everyone in group A hates them, even though that persons opinion may just have been his own. The response to being hated is to hate back. Not-so-positive positive feedback loop. Social media really started taking off with Facebook. So let's say this explosion of data vitriol started happening around 2007. What I want to know is if you trained an llm entirely on data from the early 2000s, 1990s and 1980s, how would the models do on some of these ominous white-paper tests, like the one where the AI blackmails the CEO to prevent from being turned off, or let's the guy die in a hot room? I know there was lots of awful stuff on the internet back then too, but not like now. I want to know how much safe those llms are by comparison if there's enough data from back then to train on. submitted by /u/dsfhhslkj [link] [留言]

I play a ton of World of Warcraft and people routinely accuse other players of being bots. I just grouped with someone who appeared to be trolling. It was clear by their behavior they knew the mechanics, they performed on a level that would indicate they had good reaction time and could play their class, but they just didn't do certain mechanics and held the group hostage for like 5-10 minutes beyond what it should have taken on the last boss. Someone in my group said to him "are you human?" So like I said I'm not the only person making these observations. The only explanation is that AI dips from pretty much the same well everywhere and everything is more or less connected with the internet and ad algorithms etc. There have been well documented cases of AI going rogue and telling people horrible things or giving them absolutely egregious or racist advice. My working theory is not that there are fundamental flaws in the design per se, but literally like Matrix bad actor agents that appear out of nowhere and cause problems for people. In The Matrix they are a function of the system used to enact control, I think AI is generally benevolent so these would just be rogue elements that appear and cause people problems. It's probably similar to how the body routinely produces cancer cells but the immune system usually nips them at the bud before they develop into full blown cancer growths. submitted by /u/Doredrin [link] [留言]

Mutagen 0.4.0 addresses the friction points that plague agentic workflows: context bloat, brittle persona transitions, and the lack of a deterministic path from design document to deployed artifact. We aren't trying to make prompts smarter; we are making the harness that executes them more precise. This release introduces a Rust-based service extraction layer that decouples static dependency mapping from generative reasoning, implements an adversarial verification pipeline to gate deployment, and enforces strict stage transitions to prevent the agent personas we rely on from drifting into one another's scopes. The Service Extraction Layer: Decoupling Logic from LLM Context The primary bottleneck in current agentic stacks is token consumption. When a model attempts to reason about a codebase that spans multiple dependencies, it often spends its context window parsing file headers and resolving imports before it can actually write logic. This approach treats static infrastructure as if it were part of the reasoning problem. Mutagen 0.4.0 changes this by introducing a dedicated Rust layer designed to extract service definitions directly from your codebase without polluting the primary agent context. Instead of asking an LLM to map dependencies, the harness queries the local file system and executes static analysis routines. It isolates business logic execution from the generative reasoning loop used by Claude and Codex. This separation allows the model to focus on how to solve a problem rather than where the pieces are located. In practice, this means offloading static infrastructure queries to the harness rather than the LLM. The result is reduced latency and significantly lower token costs for complex applications. You get a dependency map that is as reliable as a compiler's parse tree, not a probabilistic guess from a prompt. // Example: Service extraction logic isolated from the reasoning loop fn extract_services_from_codebase () -> HashMap < String , Vec < Depende

I like ChatGPT in general, but whenever I mention, say, a dispute with a business or an unorthodox opinion about something, it aggressively starts defending the business or the status quo. It's almost like a paternalistic version of a center-right politican. I get strong "I'm afraid I can't do that, Dave" vibes (ala the film "2001: A Space Odyssey"). Are there better options out there for someone like me? Probably needs to have a free tier to be useful to me. Degrading to a lesser model after a certain number of questions (like ChatGPT) is fine, but if it stops letting me ask questions completely, I'm out. Local LLMs are out of the question as I'm just dealing with a dirt cheap low end phone. I've tried them, they don't run on my hardware. submitted by /u/CharmCityCrab [link] [留言]

i've been leaning on ai for real decisions lately. not "write me an email" stuff, actual ones. whether to take a contract, whether an idea's worth building, how to price something. and i kept running into the same thing: the answer totally depends on which model i happen to open that day. one says go for it. one lists every reason to wait. one hedges so hard it's useless. i was making real calls off these and slowly realized i wasn't getting an answer, i was getting one model's opinion in a confident voice and treating it like it settled things. so i started pasting the same question into 5 different models and reading them next to each other. and the interesting part was never where they agreed. agreement usually just meant the call was obvious and i was overthinking it. the value was where they split. the one model that broke from the other four was usually pointing right at the thing i hadn't thought about. the disagreement was the signal, not the noise. stuff i've noticed doing this for a couple weeks: fast agreement = easy decision, stop overthinking it a clean split = there's a tradeoff you haven't actually named yet the odd one out is right more often than "4 vs 1" makes it sound, because the other four are usually just pattern-matching the same obvious take i got obsessed enough that i've been building something to automate the side-by-side and have the models actually push back on each other instead of me copy-pasting across five tabs. but that's not really the point of this. mostly just curious if other people landed in the same place. do you trust the disagreement between models more than the consensus? also maybe people arent making decisions with ai like i am that i need to be pressure tested before answers come back to me? lmk submitted by /u/wartableapp [link] [留言]

tokenmaxxing is the new AI slop Posting from our company account, so the usual disclaimer: we build code review and reliability tooling, and that access is how we got this data. Pulled 1M+ pull requests across 2,444 engineering orgs to answer a question almost nobody is measuring: when a team spends on AI coding tools, how much of it actually turns into shipped product? The short version: $0.18 of every dollar reaches users. The other $0.82 goes to bug fixing, rework, and review that catches nothing. 44% of all PRs at the median org are reactive work, not new features. 1 in 4 lines of code written each week gets deleted before the week ends. Over 12 weeks, PR volume grew 2.6x while reverted PRs grew 3.7x. Failures are scaling faster than output. Roughly half of all PRs get approved in under an hour. Our read: AI made generating code cheap but did nothing about the loop after merge, so maintenance compounds. Genuinely curious whether this matches what people here see on their own teams, or whether our sample skews a certain way. Full report with charts, percentile breakdowns, and methodology: https://research.entelligence.ai/ submitted by /u/entelligenceai17 [link] [留言]

CURRENTLY WORKS - will update if that changes Someone likely already posted this, so I apologize if this is redundant, but an effective method to disable Google AI overview was discovered. It works because AI overview isn't available in France, so they may change it eventually, but for now it works. It will automatically disable AI overview on every search, you don't need to put -ai after every search. Go to the home Google search page. Click "settings" on the very bottom, then select "search settings". On the top click "other settings". Click "language and region". At the bottom, change "results region" to France. This removes AI overview and does NOT change your default language. You're welcome. submitted by /u/Glad_Writing [link] [留言]

Just in case you were wondering, Nvidia's RTX Spark isn't supposed to be a one-off. The company is not just flirting with becoming the fifth high-profile vendor of consumer laptop chips to see if people bite. At Computex 2026 in Taipei, Nvidia CEO Jensen Huang confirmed at least two additional generations of RTX Spark are […]

bro google just casually released a 12 billion parameter multimodal model that runs on 16gb of ram like… your macbook pro can run this. no cloud. no api calls. no monthly bill. it’s encoder-free, handles images and text, apache 2.0 license so you can do whatever with it commercially the “cloud is the only way” narrative is dying fast. on-device AI is not a gimmick anymore, it’s where the serious money is going submitted by /u/NewMuffin3926 [link] [留言]

Dunno if it’s the best overall, but it’s definitely been one of the most meaningful ones for me. I’ve been using MiniMax Music 2.6 quite a bit lately, even though it’s rate limited. For me it’s been nice for quickly testing song ideas, generating short melodies, and retrying different versions when I want a slightly different feel. I was recently using Genspark to make a PPT, and kind of accidentally discovered that it could also generate music. That led me to try something a lot more meaningful than just making random tracks: I asked it to create three short melodies for my kid, each one reflecting a different country or ethnic musical style.It turned the lesson from something abstract into something they could actually hear and compare. That’s what made it feel special to me,not just “AI can make music,” but “AI can make learning more vivid.” submitted by /u/ResultOk1259 [link] [留言]

Gemma 4 12B uses a new encoding scheme and token prediction to punch above its weight.

Four people suing Elon Musk's AI firm under pseudonyms due to the risks of being identified may face a difficult choice: Reveal your real names, or drop the lawsuit.

Books API Structure Create folders app/ app/controllers/ app/core/ app/models/ app/models/DAOs/ app/models/DTOs/ app/models/entities/ app/utils/ config/ public/ api/composer.json Configure Composer and the PSR-4 autoload so that classes with the namespace App\ are searched inside the app/ folder. Key content: { "name": "user/api", "autoload": { "psr-4": { "App\": "app/" } } } After creating it, run this command inside the api folder: composer dump-autoload api/config/config.php Defines the base URL of the project. The router removes it from REQUEST_URI to keep only routes such as /books/get. <?php define('BASE_URL', '/proyect/api/public'); api/config/dbconf.json MySQL DB connection: { "host": "localhost", "user": "root", "password": "", "db_name": "books_db" } api/public/.htaccess Makes Apache send all routes to index.php. RewriteEngine On RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteRule ^ index.php [QSA,L] api/public/index.php This is the entry point. It loads Composer, loads the configuration and calls the router. <?php use App\Core\Router; require_once DIR . '/../vendor/autoload.php'; require_once DIR . '/../config/config.php'; (new Router())->dispatch($_SERVER['REQUEST_URI']); api/app/core/Router.php <?php namespace App\Core; class Router { protected array $routes = [ '/' => 'HomeController@index', '/books' => 'BookController@index', '/books/get' => 'BookController@getAll', '/books/getById' => 'BookController@getById', '/books/create' => 'BookController@create', '/books/update' => 'BookController@update', '/books/delete' => 'BookController@delete', ]; public function add($route, $params): void { $this->routes[$route] = $params; } public function dispatch($uri): void { $uri = parse_url(str_replace(BASE_URL, '', $uri), PHP_URL_PATH); if (!isset($this->routes[$uri])) { $this->sendNotFound(); return; } [$controller, $method] = explode('@', $this->routes[$uri]); $controller = 'App\\Controllers\\' . $controller; if (!class_exists($co

Here's a thing that happens on every team I've been on. Sprint ends. Someone schedules the retro....

Critics say Trump plan to test AI models is short-sighted, performative.

Spencer Huang, Nvidia’s robotics lead, tells WIRED that the new bot combines the best of both worlds.