标签：#artificial

This question gets surprisingly complicated. Using AI to fix grammar? Most people seem fine with that. Using it to brainstorm ideas? Probably fine Using it to write the first draft? Depends who you ask. Using it to do the entire assignment while you barely understand the topic? That's where most people would probably draw the line But the line keeps moving Calculators, spellcheck, Google and autocomplete were all seen as shortcuts at some point. Now they're just normal tools. Do you think AI will follow the same pattern? Or is there something fundamentally different about outsourcing actual thinking? submitted by /u/cactussignal [link] [留言]

submitted by /u/KeanuRave100 [link] [留言]

A log? A trace? The model output? A record showing that the tool call happened? All of those can tell you what happened. They don't necessarily tell you whether the agent was actually allowed to do it. That distinction gets more important as agents move from generating text to acting on real systems: sending payments, changing infrastructure, updating customer records, approving workflows, calling internal APIs. A lot of agent stacks still reduce this to identity and access. The agent has an API key. The API accepts the request. The action runs. But having credentials isn't the same as having permission for a specific action. The harder question is: Was this agent authorized to perform this action, against this target, under this policy, at that point in time? And the answer shouldn't depend on asking the agent after the fact. The authorization needs to exist before execution. It needs to be tied to what is actually being executed. And later, you should be able to verify what authorized the action. That means being able to answer fairly basic questions: who issued the authorization? Which policy was applied? What action was it tied to? Who could use it? When was it valid? Had it already been used? Was authority delegated? This is where the execution boundary becomes interesting. It's one thing for a system somewhere upstream to decide that an action is allowed. It's another to make sure that decision still applies when the action actually reaches the system that will execute it. As agents get access to production systems, "the model decided to do it" isn't going to be much of an audit answer. The question is simpler: Can you prove the agent had the authority to do it? submitted by /u/docybo [link] [留言]

The idea of whether machines will dominate us is generally treated as a new one in current discussions on AI risk, since in 1863 Samuel Butler published a letter titled 'Darwin Among the Machines' which made an argument closely resembling the one in today's debate. He stated that the real danger was not that machines would gain control of power, but that people would find machines so useful that it would become practically impossible to get rid of them, so that by that stage the question of who was actually in charge would have already been answered — no matter who seemed to be in control. He said that a society which, in principle, could not destroy its machines had already "created a race of beings towards whom it is beyond our power to destroy" and had thus become "acquiescent in our bondage." This is a quite different claim from the one that says 'superintelligence takes over'; it's similar to the sorts of arguments currently being made regarding algorithmic dependence, attention economy lock-in, and infrastructure that is too deeply embedded to be undone — arguments that can be applied to any technology that is sufficiently indispensable, not just to intelligent machines. The full letter, together with the historical background (it is also the immediate source of the "Butlerian Jihad" in Dune, a fact that most people are unaware of) can be found here: https://romaricjannel.substack.com/p/the-rise-of-mechanical-life I'm wondering if people here consider "acquiescence through indispensability" to be a real and separate risk category or whether it's just a rewording of dependence anxiety that appears each time a major technology is introduced. submitted by /u/Smart_Fly_5783 [link] [留言]

submitted by /u/Shot-Height-7194 [link] [留言]

Spent the $200 within 8 hours on Astra. At first I was blown away, but checked things more thoroughly the next day, and a lot of the stuff it build wasn’t working. Actually 3 of the 4 things I asked Astra to do didn’t work. Quite disappointed. The demos focus mostly on 3D, Blender and games, but for coding and agentic use it was not an improvement at all for me. Maybe I could have prompted better, but when it spends 2+ hours on each task, you can’t really iterate and steer it. But still I feel like this is something AGI should have handled? Now I’m back to my usual setup with KIMI K.3 and DeepSeek flash trough standardcompute. Also keeping my max plan at both OpenAI and Claude, but $400+/month is starting to hurt. What are your thoughts? Closing in on AGI or was this all a part of a coordinated marketing stunt? submitted by /u/Firm-Club-8334 [link] [留言]

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

submitted by /u/ThereWas [link] [留言]

The era of AI inference has arrived. Imagine a healthcare system analyzing millions of data points in real time to accelerate life-saving medical research, or an intelligent assistant instantly resolving thousands of complex customer needs at once. These real-world breakthroughs rely on advanced infrastructure acting as the engine of continuous intelligence, powering real-time services while…

Job seekers are trying to game the application process using AI. It’s not working, and not for the reasons you might think.

Battlefields in Ukraine are littered with the remnants of drones, which are now firmly established as a critical weapon of modern warfare. But behind all that wreckage, there’s a new gold mine for the defense sector. The data drones generate will far outlast the wars in which they are used to fight, increasingly becoming part…

ChatGPT, Claude, and Grok all suffered outages at nearly the exact same time for reasons that remain murky.

OpenAI leaders think the company’s next generation model, which excels at computer use and coding, may mark a major milestone in AI development.

OpenAI recently estimated its Cursor partnership would make more than $1 billion in revenue a year, WIRED has learned. It still walked away after Elon Musk’s SpaceX acquired the AI coding startup.

The long-rumored deal will give the chip giant access to—and help it promote—a huge repository of open-source AI models and data sets.

Restaurant menus with AI-generated food images are going viral for their off-putting aesthetic. But AI’s impact on modern menus runs even deeper.

The company is reducing pressure on workers to use artificial intelligence tools while encouraging them to experiment with Hatch, its most advanced AI project yet.

The US government wrote a letter in support of OpenAI’s argument that training AI on others' intellectual property is fair use.

A startup called Mostik has a wild new approach to combining the capabilities of AI models.

Google's Pro model updates are seemingly paused, but there's yet another Gemini Flash today.