When I clicked, I thought that it was going to smash the turbine blades from the animation to suggest something like "all the performance without the thermals," but nope, they just became laptop fans. And seconds later, it started blowing heat/steam out of them!
That's the most uncanny marketing for an ARM laptop I've ever seen.
Yeah, but I still see apps that don't implement those features. Mostly React Native/Flutter apps that don't bother implementing native features. On Android it's even more depressing.
When they exist at all. Many apps that provide important notifications (like delivery tracking, drop-off time etc) put them under the same category as marketing stuff. You can't have just the transactional tracking, you have to opt-in for the marketing notifications as well.
Sure, but they didn't spend on training the model. If DeepSeek is providing the model for the same price as third parties, then it's probably still losing money when you account for the training.
We shouldn't take free open models for granted. They're a byproduct of the current AI craze, but the economics aren't on their side. It's not sustainable. Alibaba already stopped releasing the weights for their best models, for instance.
The Node world was built with asynchronicity in mind. First via callbacks, then Promises, then async/await (Promise-based), so it feels natural now.
But if you take Python (for example), it's a shitshow. You usually have two versions of the same API, split by function name, client, package, or namespace: `foo` and `afoo`, where the a-prefixed one is async and meant to be used inside async function call chains, and the other one is the blocking version for non-async chains (which are still very much in use). It's a pain to develop for, to maintain, to scale, everything.
Same thing happened to my wife as well. I helped her tailor her LinkedIn profile and resume with a lot of attention to detail: adding metrics, keywords, results, etc. Nevertheless, she never received any outreach recruiters and got very few application responses. It went like that for months, almost a year.
Then she asked ChatGPT 5.x for help. I was skeptical about the changes it recommended (and was skeptical at all about using AI for this given the homogeneification it tends to produce). But somehow it worked: few days later, a recruiter reached out, then another, then applications started moving forward, etc.
My guess is that, as LLMs are shoveled into every phase of the recruiting process, not having an LLM write your resume for you is now playing on hard mode. The LLMs reviewing resumes are downranking resumes and profiles that are not "speaking" the same language and activating the correct neurons, thus preventing you from moving forward. This contrasts with years ago when we had more humans in the loop and the pasteurised writing of GPT 3.5/4o would make you look less worthy. Again, just a theory, but...
When my mother gave birth to my younger brother, she started using cloth diapers on him, worried about the environmental impact of disposable diapers like the ones she used on me during my childhood. She went back to disposable in less than a month.
"Oil" is not a homogeneous thing. There are different grades of oil and refineries are built to process specific grades of oil. UAE produces the so-called "Dubai Crude" oil grade, which is very sought after.
The article has a benchmark and Opus has best score in two categories and the second-best in another (there are only three categories). Opus is probably the best choice when it comes to producing readable code right now. GPT (for example) lags way behind.
>perhaps we can come up with something like the "linux/postgres/git/http/etc" of the LLMs
I fear that this may not be feasible in the long term. The open-model free ride is not guaranteed to continue forever; some labs offer them for free for publicity after receiving millions in VC grants now, but that's not a sustainable business model. Models cost millions/billions in infrastructure to train. It's not like open-source software where people can just volunteer their time for free; here we are talking about spending real money upfront, for something that will get obsolete in months.
Current AI model "production" is more akin to an industrial endeavor than open-source arrangements we saw in the past. Until we see some breakthrough, I'm bearish on "open models will eventually save us from reliance on big companies".
What strikes me is that AI can also be the best teacher in the world: your Makefile is not working, you ask the LLM what's wrong, you learn something new about the syntax, you ask for more details, you learn more, you ask about other Makefile syntax gotchas, etc. This is the most efficient deliberate practice possible: you can learn in minutes what would take hours of Googling, tinkering and scouring docs. You have a dedicated teacher you can ask your silliest questions to and have the insight you need "click" way faster.
The problem is: (almost) nobody does that. You'll just ask Claude Code to fix the build, go grab a coffee and come back with everything working.