Floofah@lemmy.worldtoPiracy: ꜱᴀɪʟ ᴛʜᴇ ʜɪɢʜ ꜱᴇᴀꜱ@lemmy.dbzer0.com•Download digital magazine ?English
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1 year agoTry mobilism.org - bit of a nightmare navigating the mag download path, but with practice …
Try mobilism.org - bit of a nightmare navigating the mag download path, but with practice …
There is a collection on Usenet in a single download but not all are there.
Cinefex issues as PDF files A couple issues are partials, 001-005, 009, 011, 13, 014, 018, 020, 22, 024, 031, 033, 037, 010, 047, 049, 061 065, 067, 071, 072, 078-080, U87, 8, 91-10, 111, 118-138
Try asking it?
NZB.su has both episodes, Tabula Rasa and NZBFinder have E01
I don’t have any invites atm, sorry. They open fairly often, typically on holidays like Black Friday.
DrunkenSlug
S05E01/2 are on Usenet
@ChatGPT@lemmings.world, Can you briefly explain the Matariki star cluster significance, as well as the social aspects of the holiday please?
Yeh, me too, so I asked Bard to make it readable …
BARD: Sure, here is a précis and key points of the technical paper in a form understandable by non-technicians:
MIT researchers have developed a new machine-learning system that uses light instead of electrons to perform computations.
The system is much more energy-efficient and powerful than current machine-learning systems, and it could be scaled up to run on small devices like cellphones.
The new system could lead to the development of much larger and more powerful machine-learning models, which could be used for a variety of applications, such as natural language processing and medical diagnosis.
Key points:
The new system uses light instead of electrons to perform computations. This makes the system much more energy-efficient and powerful.
The system can be scaled up to run on small devices like cellphones.
The new system could lead to the development of much larger and more powerful machine-learning models.
Potential applications:
Natural language processing Medical diagnosis Financial trading Self-driving cars Virtual reality
The new system is a significant advance in machine learning, and it has the potential to revolutionize a wide range of industries.