All Groups Crete Digital Nomads Bali Sacramento Think Vermont Tulsa Remote Developers Work From Home Cryptocurrency Canada Argentina Brazil Australia Show All
RemoteYo Emmanuel Emeka Onwuzulike BRYTER Instinct Science Hrishikesh Pardeshi Ebury Eduflow Carlowahlstedt Clipboard Health Alter Lindazmassie C2 Digital Limelight Platforms (U.S.) Inc David Clark-Sally
|
Threads
View context
RemoteYo 4 years ago
This talk mostly reiterates his basic talking points so it feels a lot like rambling. And the title is not justified by the argument.
There is, however, a case to be made that the computer tech age has reached an end. Tech companies turning to investing in banking and real estate is not a good sign.
like(0)
There is, however, a case to be made that the computer tech age has reached an end. Tech companies turning to investing in banking and real estate is not a good sign.
View context
RemoteYo 4 years ago
"Brain floating point" is a cool name. i guess brain's synaptic precision could go way lower, as low as 26 distinct synapse weights: https://elifesciences.org/articles/10778
> A particularly interesting research direction puts these three trends together, with a system running on large-scale ML accelerator hardware, with a goal of being able to train a model that can perform thousands or millions of tasks in a single model. Such a model might be made up of many different components of different structures,
yup, he is building a brain
like(0)
> A particularly interesting research direction puts these three trends together, with a system running on large-scale ML accelerator hardware, with a goal of being able to train a model that can perform thousands or millions of tasks in a single model. Such a model might be made up of many different components of different structures,
yup, he is building a brain
View context
RemoteYo 4 years ago
These articles (and a lot of what g. marcus writes) are attacking strawmen. I ve never heard no one claiming that NNs will invent new theories and i dont think that 2008 article is widely read. But, for things that are hard both computationally and theoretically, like protein folding, NNs may really be revolutionizing the field even if we don't know how they do it. Scientists do not buy-in foolishly into every AI hype. The problems lie with VCs and funding bodies, which are indeed swayed by adding "AI" to every kind of proposal. That's a separate problem, though
like(0)
