AI 资讯

Read this release today. Some crazy numbers. The tau2-bench number is 98% across all difficulty levels. That is the one that got me because usually these releases post a strong easy score and then quietly die at hard difficulty. This one... claims it holds. For multi-step agent work that actually matters more than most benchmarks. A model that drifts on step 4 of a 6 step chain is a debugging nightmare regardless of what its SWE score looks like. Raw capability is mid, Toolathlon at 49.5, GDPval at 45.8. So this is clearly a reliability play, not a frontier capability play. Depending on your use case that is either fine or a dealbreaker. 198B sparse MoE 11B activ 400 TPS 256K context Apache 2.0 runs locally on M4 Max and DGX Spark. Has anyone actually put this through agent evals or am I just reading the release card. submitted by /u/Skid_gates_99 [link] [留言]

IDK I might be wrong but.....I don't think it's happening anytime soon. ChatGPT, Claude, Gemini.....they are good....but they are too lazy. Gave them a task to create a Masterdata for all smartphone models being sold by a particular brand. Gave explicit instructions for all models. Explicitly asked for a list 1st and then asked it to create MasterData. Lazy ahh model just put in like 21 popular ones out of the hundreds of the available models and variants. Is this how it will overtake us and replace all the labor intensive work? submitted by /u/naamnhiptahai [link] [留言]

For nearly 80 years, Ferrari occupied a unique cultural space where its cars were aspirational, even for people who resented those who could afford them. The price, the exclusivity, and the opacity of the buying process allowed Ferrari to sail above ordinary criticism. You might not be able to afford one, but you still wanted […]

This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. At this time last week, I was getting ready to ask people what drugs they were on. I was waiting […]

Sennheiser's latest flagship headphones close the gap to Bose and Sony thanks to improved sound and more effective ANC.

Hey all! This is my first time writing a blog. It is about the migration from mongoDB database to a postgreSQL one. How we changed the architecture completely using AI. Any criticism is welcome submitted by /u/SID_069 [link] [留言]

As GenAI starts flooding every platform, I’m beginning to wonder if live sports are one of the last truly AI-resistant industries. You still can’t prompt a model to recreate the real tension of a 14–14 tie-break in a volleyball final and maybe you never will. I read an interesting piece from NJF Holdings about this. Frankly speaking, I barely know who Nicole Junkermann is but she seems to be focused on AI infrastructure and sports rights in AI era. I agree with her, that the more polished and “perfect” AI-generated content becomes, the more valuable becomes true human unpredictability and even mistakes. The basic idea is that sports become more valuable precisely because they can’t be generated. Does that idea hold up, or do you think AI entertainment eventually becomes “good enough” to compete with the real thing? submitted by /u/AssistantStraight983 [link] [留言]

Hi, I’m Kenny, I’ve been building aislop. I starting working on this after using Claude Code, codex and opencode several times and noticing some slops. They aren’t syntax and passes most tests, they are patterns like empty catch blocks, useless comments, duplicated helpers, dead code and many more. So I built a tool to scan and check for these patterns and wired it into hooks so after each tool call, the agent checks for the slops. You can try it out with npx aislop scan. It’s all local and no c

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

Found this during a routine review. Analysts discovered that pasting alert context into an AI tool cut triage time significantly and started doing it because it worked, which is a reasonable thing to do when you are under pressure to move faster. The problem is that alert context includes internal hostnames, IP ranges, user identities and sometimes partial log data, none of which was supposed to leave the environment. No policy covered it because the productivity gain was not something that had been thought through when the AI use policy was written. Now trying to figure out how to give them a sanctioned version of the same capability without the data handling risk, which is harder than it sounds because the whole point is that the external tool is faster than what we have internally. submitted by /u/Only_Helicopter_8127 [link] [留言]

Though YouTube has always been a place where up-and-coming artists could be discovered and make it big, in recent years the platform has become a launching pad for some of Hollywood's most exciting new horror directors. The filmmakers behind films like Talk to Me, Iron Lung, and Obsession all started off as content creators posting […]

Acer is aiming to take on the MacBook Neo more directly with a new Swift Air 14, a new 14-inch laptop that starts at $699. The laptop will use Intel's lower-cost Core Series 3 "Wildcat Lake" chips - either Core 5 or Core 7 models, both of which are six-core processors. It comes in green, […]

If you're looking for a fun way to connect with nature while collecting bird species on an app like Pokémon, give this smart feeder a try.

There's also a new 360-degree convertible model, the Swift Spin 14 AI.

Acer's upcoming Nitro Blaze Link is a companion handheld for gaming

If you're using Amazon SES and emails to @privaterelay.appleid.com are silently failing, the cause is almost certainly SES's account-level suppression list treating Apple relay DSN errors as hard bounces. Fix: Emails Not Delivered to Apple Private Relay Addresses (Amazon SES) If your app supports Sign in with Apple , some of your users will have a Hide My Email address — a relay address like abc123@privaterelay.appleid.com that forwards to their real inbox. These addresses are easy to break silently. Here's the symptom we ran into and exactly how we fixed it. The Symptom Transactional emails (alerts, welcome emails) worked fine for regular email addresses but never arrived for users who signed in with Apple. We were also receiving bounce notifications like this: Subject : Delivery Status Notification (Failure) An error occurred while trying to deliver the mail to the following recipients: prw8xms8tv@privaterelay.appleid.com Confusingly, some of these emails were being delivered — Apple's relay occasionally returns a DSN error even on successful delivery. But over time, delivery stopped entirely for affected addresses. Root Cause: SES Suppression List Amazon SES has an account-level suppression list . When a send results in a bounce (even a soft or misleading one), SES adds that address to the suppression list and silently drops all future sends to it — no error, no log entry from your code's perspective. Apple's private relay sometimes returns a non-standard response that SES interprets as a hard bounce. Once that happens: Send to Apple relay → Apple returns DSN error → SES logs as hard bounce → Address added to suppression list → Every future send silently dropped We found 9 Apple relay addresses on our suppression list, the oldest suppressed since September 2025 — meaning those users had missed months of emails. The Fix Step 1 — Remove suppressed Apple relay addresses In the AWS Console : Go to Amazon SES (make sure you're in the correct region) Left sidebar → Con