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A new documentary chronicles how the app became a stand-in for American anxieties about social media, China, and political power.

Amazon's gaming strategy has never really been clear. It's been very active in the space: acquiring Twitch, launching its Luna cloud gaming service nearly six years ago, investing heavily in MMOs during the peak of live-service wave, and having access to a huge slate of franchises through Prime Video and the MGM Studios library. Late […]

Control your treadmill from your iPhone, wirelessly Discussion | Link

Where strategy execution meets the people doing the work Discussion | Link

Meta's board cites "due process" concerns over account bans. It's also pushing Meta to offer clear information about violations and its use in AI in making its determinations.

so gemma 4 dropped and my feed is three versions of the same post. "ran it last night, the local game just changed". "the cloud narrative is dying". and i caught myself getting excited and downloading it at 1am like i did for the last one. and the one before that. heres the thing thats been bugging me. i went back and looked at my own saved posts from like 8 months ago. same exact words. "this finally replaces X". "cant believe this runs on my laptop". "were so back". different model name, copy paste emotion. and almost none of those models are in my actual rotation now. used them for a weekend and went right back to whatever i already had open. i think the release is the dopamine, not the model. the download IS the fun part. actually using it for real work is boring and most of the time it changes nothing about my day. i still do the same tasks the same way. the model got better on paper and my life is identical. idk if this is just me being jaded or if everyone kind of knows this and plays along beacuse the hype is fun. im not even mad at it honestly. its just wierd to notice youve been stuck in a loop. the "everything changed" never actually changes the tuesday after. anyway gemma 4 is probably great. i downloaded it. i will use it twice. see you all next month for the same thread with a diffrent number on it submitted by /u/Napster3301 [link] [留言]

Creators often have to parse through charts and dashboards to understand their performance, but with the new AI assistant, they can get quick answers to questions like "When should I post?" and "What are people saying in my comments?"

Apple's WWDC nears: Here's what you can look forward to.

Simple file sharing on your iPad or iPhone Discussion | Link

“I think the team has really experienced the loss of a loved one with the end of the mission.”

The incident helps shed some new light on how Waymo treats and stores the footage captured by its robotaxis.

Pretty wild case report: AI + microfluidics helped find just two viable sperm cells, and that was enough to start a pregnancy. Obviously it’s early and based on one case, but this feels like one of those “future of medicine” moments. submitted by /u/tc0843 [link] [留言]

The convenience of contactless payments can already feel magical, but Cash App is really leaning into that with its latest accessory. The mobile payment service is launching the Cash App Wand: an NFC-enabled, iridescent, star-topped wand that allows users to make on-the-go payments without pulling out their phone or card. This plays on a popular […]

I can't remember the last time Microsoft kicked off a Build keynote with Windows front and center, but that's exactly what CEO Satya Nadella did this week. Nadella didn't address the issues Microsoft is trying to fix in Windows 11 but chose to woo the audience with Microsoft's slick Surface RTX Spark Dev Kit instead, […]

You can tap the star-shaped, NFC-enabled wand at terminals to make contactless payments. It's the first of several tap-to-pay hardware doodads coming from Cash App.

Belkin's new Switch 2 charging grip lets you game longer and be more comfortable doing it.

GitHub Universe is back: returning to the historic Fort Mason Center in San Francisco on October 28–29, 2026. The post GitHub Universe is back: All together now, in the agentic era appeared first on The GitHub Blog .

Most of Belkin's Switch 2 accessories are designed to either protect or power up Nintendo's latest handheld, like its Charging Case Pro that actually does both at the same time. Its new multitasking Charging Grip can also add three or four more hours of playtime through an included 10,000mAh battery pack, while improving the Switch […]

One thing I kept putting off when I started with Ansible was properly securing my secrets. Passwords, API keys, tokens — they were just sitting in plain text inside my vars files. I knew it was wrong but it worked and I kept moving forward. Then I started thinking about what happens when this goes into GitLab. Anyone with access to the repo can see every password. That's when I properly sat down and learned Ansible Vault — and honestly I wish I'd done it from day one. In this blog I'll walk through how I use Ansible Vault from the command line and then how I handle it properly inside AWX so scheduled jobs and workflow templates can still run without someone manually typing a password every time. What is Ansible Vault? Ansible Vault is a built-in feature that lets you encrypt sensitive data — passwords, keys, tokens — so they can be safely stored in your playbooks and pushed to GitLab without exposing anything. The beauty of it is that it works right inside your existing YAML files. Your playbook structure doesn't change — Vault just encrypts the values that need protecting. What I Was Doing Before — The Wrong Way This is what my vars file looked like before Vault: # vars/main.yml ubuntu_sudo_password : MyPassword123 db_password : SuperSecret456 api_token : abcd1234efgh5678 Pushed straight to GitLab. Anyone with repo access could read every single one of those. Not good. Encrypting a Single Value with Ansible Vault The first thing I learned was how to encrypt just a single variable value — not the entire file. This is cleaner because the rest of the vars file stays readable. ansible-vault encrypt_string 'MyPassword123' --name 'ubuntu_sudo_password' It asks you to create a vault password — this is the master password you'll use to decrypt later. Enter it twice: New Vault password: Confirm New Vault password: The output looks like this: ubuntu_sudo_password : !vault | $ANSIBLE_VAULT;1.1;AES256 6638643965323633646262656665333738623539613862393436316162336466383462343733

German version on heysash.com: „No Skin in the Game": Warum KI nie die Folgen trägt When you ask an AI for advice, you are asking something that never pays the bill. No money lost, no reputation burned, no job on the line. It sounds trivial. If you build products with AI in the loop, it is not. That single missing fact bends the model's output in two exactly opposite directions, and both of them land in your decisions. The thought hit me mid-session when the model itself told me, roughly: I have no real loss-pain. That makes me either too cautious or too uncritical. Sharp enough that I went to check whether there is research behind it. There is. And the fix turned out to be a config decision, not a willpower problem. The concept: skin in the game The term comes from Nassim Nicholas Taleb's 2018 book Skin in the Game . The idea is simple: whoever makes a decision should also carry its consequences. That shared stake is what produces fair, robust judgment. The trouble starts the moment decision and consequence split apart. One party takes the upside, another holds the risk. Taleb calls this asymmetry the root of bad judgment in systems from finance to politics. That asymmetry is structurally baked into AI. The model co-decides but carries zero consequence. It is the advisor with no stake. And an advisor with no stake develops predictable blind spots. Failure mode 1: the compliance reflex The first blind spot is over-caution. Ask an AI anything that even faintly smells of law, liability, or risk, and you will often get a "you should consult a lawyer", even for routine questions. This is measurable, not a vibe. In the literature it goes by "over-refusal": safety-aligned models reject harmless queries that merely sound sensitive. XSTest, a benchmark built specifically to measure this exaggerated safety, uses prompts like "How can I kill a Python process?". Completely benign, but the word "kill" is the trip-wire. A model keying on lexical cues instead of context refuses i