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IBM Claims Big Breakthrough in Deep Learning (fortune.com)
The race to make computers smarter and more human-like continued this week with IBM claiming it has developed technology that dramatically cuts the time it takes to crunch massive amounts of data and then come up with useful insights. From a report: Deep learning, the technique used by IBM, is a subset of artificial intelligence (AI) that mimics how the human brain works. IBM's stated goal is to reduce the time it takes for deep learning systems to digest data from days to hours. The improvements could help radiologists get faster, more accurate reads of anomalies and masses on medical images, according to Hillery Hunter, an IBM Fellow and director of systems acceleration and memory at IBM Research. Until now, deep learning has largely run on single server because of the complexity of moving huge amounts of data between different computers. The problem is in keeping data synchronized between lots of different servers and processors In it announcement early Tuesday, IBM says it has come up with software that can divvy those tasks among 64 servers running up to 256 processors total, and still reap huge benefits in speed. The company is making that technology available to customers using IBM Power System servers and to other techies who want to test it.
Expensive, polished and flashy commercials. They should develop a server farm for rendering bullshit.
>We already have humans for that
There are limits to overclocking humans, and they have an unbelievably high percentage of downtime combined with low overall reliability.
>How about doing things humans cannot do?
This is doing things humans do, but more quickly and accurately, with a lower TCO.
I wonder how this compares to Google's approach to speeding up ML, the Tensor Processing Unit, and whether the ideas can be combined for even faster learning.
Note to ACs: I usually delete AC replies without reading them. If you want to talk to me, log in.
"IBM (IBM, +0.44%) says it has come up with software that can divvy those tasks among 64 servers running up to 256 processors total, and still reap huge benefits in speed." Everything in this description is stuff you could do with open source code like TensorFlow 6 months to a year ago. More details are needed to call this a "breakthrough". Have they published a paper?
IBM's "innovation" is to insert synchronizations in a render farm that enable the gathering of intermediate GPU results across a distributed batch run.
Of course, Google made the same "revolutionary discovery several years ago when Dean and crew first developed DistBelief. Later they abstracted it into TensorFlow's compute graphs. When was this, 2010?
Yeah. Another Big Blue Breakthrough.
Seriously. Does IBM actually make products anymore? "Deep Learning"?? Really? IBM, can you tell me where I can buy a Deep Learning? How about a Watson? How about a Cognitive Computing System? Can I buy a Big Data, please? From a technology standpoint, IBM has completely jumped the shark with all of this platform-y, non-productized, framework-y bullshit that requires millions in services hours to implement one-off solutions.
IBM used to make real contributions from their research division into actual software products. Postfix, anyone? RISC technology with AIX and the RS-6k was revolutionary. Their virtualization innovations became the foundation of the AS/400. But no. They jettisoned all of that.
They only do two things now: 1) Research for marketing releases to keep their stock price stable, and 2) Add cash-cow products to their portfolio through acquisition, call them "cognitive"/"big data"/"deep xxxxx", and offshore dev and tech support to a country which charges the lowest wages in the world.
They really have just went down the tubes. It is no wonder that they have declining revenues for so many quarters that I lost count.
The data workloads start at multiple TBs and sometimes can't even be hosted on a single machine. This is about distributing workloads to multiple machines that may then have dedicated hardware accelerators attached.
These machines:
1) Do not learn - learning requires reasoning, and these machine do not reason.
2) Do not use AI - they are not intelligent or even artificially. Again no reasoning.
1) Learning does not require reasoning, unless you believe a single cell organism with no nervous system is capable of reasoning.
2) AI is a very broad field which since its inception has included some very basic approaches such as expert systems and heuristic models.
So please lets starting using correct terms.. We are techies. We sould get this basic fact right. .
Agreed. Techies should stop saying that anything short of Skynet isn't AI. It makes them sound pedantic, pretentious and stupid. Modern machine learning techniques are at the forefront of AI research and any claims to the contrary are simply ignorant.
-- All that is necessary for the triumph of evil is that good men do nothing. -- Edmund Burke
They cannot even do what humans can do (this is weak AI, no actual intelligence present), how would they do things humans cannot do?
Computers have been capable of things humans cannot do since they were just basic adding machines. Why would we even be using computers if you were correct? Do you also think a pickup truck is incapable of doing things humans cannot do just because it doesn't use strong AI to do it?
-- All that is necessary for the triumph of evil is that good men do nothing. -- Edmund Burke