Can't guarantee for the splash of color but I've had my eye on Fossil Hybrid smartwatch gen 6 for everything else you mentioned. It's maybe worth a look?
I can understand AMD not actively working on this solution since it gains them little while costing a hefty amount of developer time. Especially considering the fact that nVidia will be able to arbitrarily break this implementation with every update. What I don't understand is why they would take it down completely, is there some safety concern or are we in the 11 competing standards xkcd again?
The reasons for closing haven't really been elaborated on, just commented on as sad and devastating; I haven't managed to glean anything more from the rest of the article.
However, it's incredible to me to keep an organization like this going for 17 years. The landscape is constantly shifting and looking back at the world and technology from 2007, and even 2014, they've survived a lot. Going down now just shows how bad the market is in reality.
>However, it's incredible to me to keep an organization like this going for 17 years.
Exactly. Say what you want about the state-of-affairs today, imagine what the women in tech landscape looked like almost 20 years ago! I'm sure they accomplished a lot, and that's awesome.
Exactly! I consider this a mission accomplished scenario. And the lack of funding is the graceful curtain call it deserves. (imagine another curtain call filled with scandal!)
the next generation of female diversification initiatives will be more specialized aka more diversified for age, race, geography, and industry. This is good all around. Edit: And could be carried as a side hustle by existing institutions.
How is them going down related to the market? They are a non-profit.
This is pure speculation but I would imagine that they reasons for closing are likely resource related (most likely financial) as organisers and managers can be replaced
Isn't rspack[0] trying to handle full feature parity? I've just come across it earlier today so I'm not an expert but I'm looking forward to the full 1.0 release
This after not fixing the save corrupting bug in Sunbreak expansion basically since it launched doesn't look good... I love the series to bits, but I'll think twice about getting the sequel
Maybe you'd be better served by something like Toggl? You can create projects and really finely track time in it. Also the web ui gives you option to export a nice report on any given period for your tracked time.
Its amazing to me that it has become such a default, similarly to Slack before it. At least some Slack communities tried and worked on getting the channels indexed so that it shows up during web searches, now with discord I need an account just to view the content...
A hard pass from me, especially when an answer to a simple question requires me to drink from their firehose of a search...
I always go with discord in newer projects. Why? I feel like most people have discord nowadays and it just works (TM). I rarely have a case where a person said that they can’t join because they don’t have discord or don’t want to create an account because other reasons.
Beside that, money is also a big factor. Slack for example is getting more expensive for communities.
It does not "just work," and you're not going to hear from me because I'm not joining yet another Discord server just to wade through searching through chat. Do a free forum. They've worked for 30 years and I might actually find my answer by Googling and won't need to even making a forum account.
I actually entirely agree with you. Nobody needs to take on accommodations they don't want to. And that was kind of my point; you should be aware that choosing Discord limits your participants and also limits your participants ability to engage with your project.
This isn't necessarily a bad thing; may even be a positive aspect. In a quickly changing project, maybe it's good if your documentation isn't too "sticky" and the solution to a problem isn't low-touch "read the docs" but high-touch "ask me so that I can experience the pain points"
Slack doesn't require phone number validation, Discord does. Try to login first time with FF on Linux and with uBlock Origin defaults and then pooof, insta ban! Guess what, your phone number is banned for validation too forever,
Love the self-consciousness of it all, even having a "Should this exist" with an XKCD that jumped right to my mind as soon as I read the title.
Honestly, as someone who has to periodically jump into Python to do some scraping and data wrangling I dearly hope we land on something that is sane and maintainable in the near future. I'm just so tired of (ana)conda, poetry, pyenv, and even pip itself.
This strongly resonates with my memory of Marshall McLuhan and his book Understanding Media: Extensions of man; Where he defines media as any extension of ourselves or our senses. Arguing that a car (but in essence) its wheels, are extensions of our legs, and by giving us the ability to traverse further faster shaped our perception and the evolution of society.
However it's a large book and I'll have to give it a reread since this is based on a vague recollection. But it's been in my mind more and more lately, especially with all the AI hype in the news.
The efficiency of Apple silicon is a matter of fact now, however isn't nVidia with its cuda still king in this segment? Please correct me if I'm wrong but doing ml/dl on CPU instead of GPU seems to be the least efficient way to go about it?
Note that I was talking about the CPU specifically. GPU on Apple is also more efficient (approx 0.25TFLOPs/watt for M1 series), but Apple GPUs lack support for ML-optimized FP representation (primary reason why Nvidia is so good in this domain). Apple does have a matrix coprocessor which offers excellent performance/watt for inference, but these units are relatively small and only offer limited aggregated performance.
I think it’s just a question of time until Apple offers hardware support for BFLOAT and other formats on the GPU and AMX (they already have BFLOAT16 in the CPU), at which point their ML performance will improve dramatically.
Yes, Nvidia still obliterates M1/M2 in Deep Learning. M1 is close to GTX1650 in real-world DL workloads though in theory based on TFlops it should be around GTX1070.
