Fred_Liuuuu

MEOW

[Fred_Liuuuu @FredLiuuuu]

@ashutosh_270497 @OpenAI Same here @thsottiaux

[Fred_Liuuuu @FredLiuuuu]

Project context, decisions, files, and open tasks should carry across sessions, and those threads should sync seamlessly across devices so I can continue the same work from desktop, mobile, or Codex without losing context.

[Fred_Liuuuu @FredLiuuuu]

@suoxuan12138 @jav_code_find

[Fred_Liuuuu @FredLiuuuu]

@oscarf00 @sahilwise True

[Fred_Liuuuu @FredLiuuuu]

@spatiallyme @SSOUIC You can actually put it off and just keep it charging, it will still update itself

[Fred_Liuuuu @FredLiuuuu]

@eHETEROPHOBIA @Futur3Sn0w yep

[Fred_Liuuuu @FredLiuuuu]

@blackyneko “查不到”就很搞笑

[Twitch @Twitch]

🚀 TRANSMISSION INCOMING...we’ve joined forces with @NASA for the first-ever Twitch stream from space. 🌌 Tune in Feb. 12 @ 11:45 AM EST to chat with astronauts, Don Pettit LIVE from the International Space Station and Matt Dominick, freshly back from orbit!
Don't miss liftoff https://t.co/cGKwEpvhcX

[东北御厨💙💛 @DongBeiYuZaiLXF]

我觉得邓紫棋和杨笠的那段对话，反映出的是墙内墙外女性的区别。

我邓紫棋作为一个一直生活在墙外从小到大没有体验过墙内女生那种来自原生家庭，或者来自男性太多压迫的人，她发表那些言论其实蛮正常的。

其实女性越独立，女性地位越高的社会，她们对待男性的态度反而不会那么苛刻，也不会那么敏感。因为习惯乐得到周边男性给予她们的尊重，内心受的伤也比较少。男人在他们心中的形象显然没有那么糟糕。

相对而言，墙内的女性，在社会生活中，其实是无时无刻都要面临性别歧视的。所以才会在她们有优势和话语权的地方显得特别强势，比如在结婚的时候谈彩礼，比如在自己的家庭内部，会对老公表现得非常强势。

所以，女权越好的社会，男人的日子反而是很好过。最起码不会面对彩礼的问题，不需要面对结婚必须要买房子的问题，由于女性在社会上面对的压力相对较小，相对的在家庭里面表现得也会更加温柔。

就好像被很多人爱着的人更容易去爱别人。被很多人伤害过的人也更容易去伤害别人。

前者的爱是一种回报，后者的伤害是一种防御性的应激。

在墙内这样的环境下，做男人做女人其实都非常不容易。没有必要彼此之间互相憎恨，互相挤兑一切不好的现状，其实根源上说，都不是对面的异性造成的。

[Fred_Liuuuu @FredLiuuuu]

@egg_1046 @GPTDAOCN intp确实很e

[⁣凍檸茶走冰走檸走茶走甜唔該 @CitronaTeo]

国行 Mac 破解使用 Apple Intelligence 教程 https://t.co/lQnleGo2u1

[Benjamin De Kraker @BenjaminDEKR]

ChatGPT, Claude, and Perplexity -- three totally different AI services -- are all down right now.

What the actual F is going on?

[Alex George Pickering @AlexGPickering]

Indeed.

[Fred_Liuuuu @FredLiuuuu]

@theapplehub Only if it is in a size of iPhone 13 mini lol

[Ziming Liu @ZimingLiu11]

MLPs are so foundational, but are there alternatives? MLPs place activation functions on neurons, but can we instead place (learnable) activation functions on weights? Yes, we KAN! We propose Kolmogorov-Arnold Networks (KAN), which are more accurate and interpretable than MLPs.🧵

[大变活人 @seanwei001]

声致发光——如果用声波使水下气泡破裂，就会产生光，目前无法解释这是为什么。

[Bojan Tunguz @tunguz]

It’s important to be very specific when talking to the IT guys.

[Fred_Liuuuu @FredLiuuuu]

@MajinBuOfficial @upintheozone Showing F1-F4 and changing the rest into Touch Bar would be great.