Those are amazing accomplishments but I am more interested in research developments in things like In-Memory (Analog) or other different approaches.
Companies like EnCharge, Mythic, etc.
And much more efficient devices like RRAM, MRAM, and FETs. Like FE-FETs with AlScN.
The stuff just coming out of research or still in research is more exciting in terms of the potential for truly huge efficiency and performance boosts.
Taalas is interesting also because of it's efficiency and speed. Guess it was just purchased by AMD.
pure_magic 50 minutes ago [-]
This text is most likely AI-generated. Borderline unreadable.
paaloeye 37 minutes ago [-]
def. AI-assisted, both content and style style/nav.
Content-wise, it looks legit, but with that amount of stuff, it's nearly impossible to say for sure.
Not slope tho!
postalrat 46 minutes ago [-]
Most like AI generated? If you can't tell then what's the problem?
catlifeonmars 12 minutes ago [-]
It’s shorthand for “it’s unreadable, but in the way an AI would write it”. I’m not OP, but that’s the issue. If it was well written (even if AI written), there would be no problem.
As it turns out, you still need to be a good writer in order to prompt an AI to write well.
hadlock 1 hours ago [-]
Maybe it's just me, but between the extremely thin font and layout design, I find this extremely difficult to parse. Overuse and improper use of italics is confusing as well.
paaloeye 43 minutes ago [-]
Not too shabby, but it shouldn't have been like 3 posts
brcmthrowaway 37 minutes ago [-]
I have a feeling the hardware architecture for LLMs are completely wrong. There's no way hundreds of kilowatts is required for intelligence.. just in terms of the physics. Is there someone out there in the analog/neuromorphic computing world that could make these power-hungry monsters completely redundant?
jagged-chisel 32 minutes ago [-]
I have a gut feeling the particular stochastic processes we’re currently using are the wrong ones to go beyond LLMs into actual intelligence.
logicallee 18 minutes ago [-]
human brain uses 20 watts.
jhide 47 minutes ago [-]
[dead]
Rendered at 01:39:23 GMT+0000 (Coordinated Universal Time) with Vercel.
Companies like EnCharge, Mythic, etc.
And much more efficient devices like RRAM, MRAM, and FETs. Like FE-FETs with AlScN.
The stuff just coming out of research or still in research is more exciting in terms of the potential for truly huge efficiency and performance boosts.
Taalas is interesting also because of it's efficiency and speed. Guess it was just purchased by AMD.
Not slope tho!
As it turns out, you still need to be a good writer in order to prompt an AI to write well.