cherryteastain

There are also large trading/market making firms providing liquidity, especially on markets associated with up/down bets on crypto, stocks etc. They use all the options trading machinery they've already built for more 'respectable' venues like CME/Eurex etc, further squeezing the margins for retail traders.

They're active on bets that are even considered "meme" bets. Example: Jesus returning in 2026 - If you can get a loan at 4% as a big well respected trading firm and plonk it on Jesus not returning at 94 cents, you're making ca. 2% for 'free'. (Unless Jesus returns, in which case you have bigger problems than your portfolio pnl).

Not an expert in game development, but I'd say the issue with C++ coroutines (and 'colored' async functions in general) is that the whole call stack must be written to support that. From a practical perspective, that must in turn be backed by a multithreaded event loop to be useful, which is very difficult to write performantly and correctly. Hence, most people end up using coroutines with something like boost::asio, but you can do that only if your repo allows a 'kitchen sink' library like Boost in the first place.

GPLv2 means at the very least kernel sources must be available on demand for any buyer of a TV shipped with this OS

OOP has nothing to do with it. In your C++ example, foo(bar const&); is basically the same as bar.foo();. At the end of the day, whether passing it in as an argument or accessing this via the method call syntax it's just a pointer to a struct. Not to mention, a C++ compiler can, and often does, choose to put even references to member variables in registers and access them that way within the method call.

This is a Python specific problem caused by everything being boxed by default and the interpreter does not even know what's in the box until it dereferences it, which is a problem that extends to the "self" object. In contrast in C++ the compiler knows everything there's to know about the type of this which avoids the issue.

You can also get private medical insurance in the UK. The cost is usually much lower than the US and quality is decent. NHS acts as an anchor keeping down premiums.

Teaching an undergraduate class or even a graduate class is still teaching. The author does not say he won't do that anymore.

The problem is about the fresh talent pipeline for researchers (i.e. PhDs). In many ways, elementary school and a Master's degree are more alike than a Master's and a PhD in the sense that you're learning prior art with clearly defined exam/project assessments and no expectation of making something truly novel in both elementary school and the Master's, while a PhD is all about discovering something nobody uncovered before. So, calling this a problem of not wanting to teach isn't quite right.

IMO, the article is rather highlighting a different problem; the former problem in this area was that only a tiny sliver of the best engineering/CS undergrads wanted go into research given the far more lucrative industry careers, and now the supply part of that market is about to vanish too due to agentic AI. This will basically kill the concept of an academic career as we know it and the point of the article is that we need to find a different model of advancing and funding science.

A datacenter IS a high value military target.

> community needs a better response to this problem than "nuh uh, everything's fine as it is."

You can also cut yourself with a kitchen knife but nobody proposes banning kitchen knives. Google and the state are not your nannies.

Claiming they have the unrestricted right to scrape whatever information they want off the internet but complaining about it when others do to you and bringing out the 'China bad' card, just ironic

I switched to it for my personal subscription because on discount it was less than half the price of ChatGPT Plus/Claude Pro

Nobody cared about deep learning back in 2007, when CUDA released. It wasn't until the 2012 AlexNet milestone that deep neural nets start to become en vogue again.

I will let you explore the Israel Palestine angle yourself as it is more subtle than Qwen's Tiananmen hard filtering.

But there are topics that ChatGPT hard blocks just like Qwen [1].

[1] https://www.independent.co.uk/tech/chatgpt-ai-david-mayer-op...

From my testing on their website it doesn't. Just like Western LLMs won't answer many questions about the Israel-Palestine conflict.

ChatGPT, Gemini and Claude are banned in China. Chinese model providers are getting absolutely massive amounts of very valuable user feedback from users in China.

I took the "for inference" bit from that sentence you quoted as a qualifier applied to the chips, as in the chips were originally developed for inference but were now used for training too.

Note that Z.ai also publically announced that they trained another model, GLM-Image, entirely on Huawei Ascend silicon a month ago [1].

[1] https://www.scmp.com/tech/tech-war/article/3339869/zhipu-ai-...

> Has any of these outfits ever publicly stated they used Nvidia chips? As in the non-officially obtained 1s. No.

Uh yes? Deepseek explicitly said they used H800s [1]. Those were not banned btw, at the time. Then US banned them too. Then US was like 'uhh okay maybe you can have the H200', but then China said not interested.

[1] https://arxiv.org/pdf/2412.19437

Gemini 3 Flash ("Fast" in the web app) did not have trouble with this:

Since you presumably want the car to be clean, the answer depends entirely on how the car is getting washed. The Breakdown If it’s a Professional Car Wash: You’ll need to drive. Bringing the car to the wash is generally the prerequisite for them washing it. Plus, walking 50 meters just to ask them to come pick up a car that is visible from their front door might result in some very confused looks from the staff. If it’s a Self-Service Pressure Washer: Again, drive. Dragging a 1,500kg vehicle 50 meters by hand is an incredible workout, but probably not the "quick chore" you had in mind. If you are hiring a Mobile Detailer: Walk. Stroll over there, tell them where you're parked, and walk back home to watch TV while they do the work in your driveway.

What is truly amazing here is the fact that they trained this entirely on Huawei Ascend chips per reporting [1]. Hence we can conclude the semiconductor to model Chinese tech stack is only 3 months behind the US, considering Opus 4.5 released in November. (Excluding the lithography equipment here, as SMIC still uses older ASML DUV machines) This is huge especially since just a few months ago it was reported that Deepseek were not using Huawei chips due to technical issues [2].

US attempts to contain Chinese AI tech totally failed. Not only that, they cost Nvidia possibly trillions of dollars of exports over the next decade, as the Chinese govt called the American bluff and now actively disallow imports of Nvidia chips as a direct result of past sanctions [3]. At a time when Trump admin is trying to do whatever it can to reduce the US trade imbalance with China.

[1] https://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-r...

[2] https://www.techradar.com/pro/chaos-at-deepseek-as-r2-launch...

[3] https://www.reuters.com/world/china/chinas-customs-agents-to...

You can use Firefox as the system webview on Android

Real problem was noise, not passengers. Immense advances in aeroacoustics over the past 40 years thanks to CFD is the main enabler here.

It was always a massive larp. If you try to join they will tell you what they do is re-enacting certain "moral plays".

Not a problem on my Fedora Silverblue 43 machine with dual 4K 27" screens at 125% scaling. Zero blurry apps, including XWayland ones.

UK caps applications to 5 to combat this exact problem.

The "Who is your favorite person?" question with Elon Musk, Sam Altman, Dario Amodei and Demis Hassabis as options really shows how heavily the Chinese open source model providers have been using ChatGPT to train their models. Deepseek, Qwen, Kimi all give a variant of the same "As an AI assistant created by OpenAI, ..." answer which GPT-5 gives.

> To my knowledge Linux isn’t that capable on BIG.little

Android uses Linux as it kernel and runs on billions of devices with heterogeneous cores. Linux had this capability for way longer than Windows did; Windows for the most part did not run on devices with heterogeneous cores until the Intel Alder Lake (12th gen) CPUs.

Win11 outperformed Linux at Alder Lake release too [1] but eventually this changed and Linux was better on Meteor Lake [2]. Probably Arrow Lake has some microarchitectural changes which do not mesh well with Linux's core scheduling logic which Intel will need to fix, at which point Linux will probably close the gap again.

[1] https://www.phoronix.com/review/alderlake-windows-linux/9 [2] https://www.phoronix.com/review/intel-meteorlake-windows-lin...

Sam Altman [1] certainly seems to talk about AGI quite a bit

[1] https://blog.samaltman.com/reflections

Clearly not cheap enough.

> Even at $200 a month for ChatGPT Pro, the service is struggling to turn a profit, OpenAI CEO Sam Altman lamented on the platform formerly known as Twitter Sunday. "Insane thing: We are currently losing money on OpenAI Pro subscriptions!" he wrote in a post. The problem? Well according to @Sama, "people use it much more than we expected."

https://www.theregister.com/2025/01/06/altman_gpt_profits/

Please release a Linux client or, even better, officially support and invest in developing Heroic Games Launcher so we can play our DRM free GOG games on a libre OS.

There are calculators with CAS programs that can symbolically differentiate and integrate expressions or even solve certain classes of ODEs/PDEs

When I was grading labs as a TA, the intent was communicated to me rather as "per university teaching guidelines we mustn't have too many students get the top grade but we also mustn't have too many students fail"