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A nice read. IBM Watson wowed the tech industry with a 2011 win against two of television show Jeopardy greatest champions. Using something that seemed like a sort of tree search for me IBM DeepQA algorithm managed to ingest sparse data (clues), process it getting one answer, understand what that answer means and come up with the question that leads to that answer. Now, IBM tells us that the same system can tackle medical diagnosis and financial risk problems.

IBM for the first time ever is making quantum computing available to the public, providing access to a quantum processor via the cloud. Users can create algorithms and run experiments and get inspired by the possibilities of a quantum computer.

Looks interesting.. Have you tried it?

Mathias Troyer from ETH Zurtich gave a talk in Leiden where he showed what he wants to be the replacement to this IBM programming or the best ally of it - program quantum computers with, for instance, python code. Nice developments coming from the quantum coding field, besides the fact we are ages away from a practical quantum computer.

Built in Silicon technology (Samsung's 28 nm process), its power is measured as one million neurons and 256 million synapses. It contains 5.4 million transistor being the largest IBM chip in these terms. All this said, it consumes less than 100 mW!! "These systems can efficiently process high-dimensional, noisy sensory data in real time, while consuming orders of magnitude less power than conventional computer architectures." IBM is working with initLabs to integrate the DVS retinal camera with these chips = real time image neuro-like image processing. In what seems to be a very successful project hugely funded by DARPA, "Our sights are now set high on the ambitious goal of integrating 4,096 chips in a single rack with 4 billion neurons and 1 trillion synapses while consuming ~4kW of power."

Unveiled today, the second annual "IBM Next Five in Five" is a list of innovations that have the potential to change the way people work, live and play over the next five years.

"IBM delivered on the DARPA SyNAPSE project with a one million neuron brain-inspired processor. The chip consumes merely 70 milliwatts, and is capable of 46 billion synaptic operations per second, per watt-literally a synaptic supercomputer in your palm." --- No memristors..., yet.: https://www.technologyreview.com/s/537211/a-better-way-to-build-brain-inspired-chips/

nothing revolutionary but coming from IBM ....

from an microsoft stronghold ...

There you go, the latest-and-greatest chip is there. Now the only remaining tiny detail - program it.

Let's buy it first and we'll figure the rest out later :P

A pioneering team from IBM in Zurich has published single-molecule images so detailed that the type of atomic bonds between their atoms can be discerned.

f existing lithium-ion batteries were scaled up to match the range capacity of gas-powered vehicles, they would be unfeasibly large and heavy. Lithium-air batteries, which have the potential to provide energy densities that rivals traditional gasoline-powered engines, are seen as a possible solution.

Internal crowdfunding for ESA? for Ariadna? Perhaps I'm late, but sounds feasible.

Interesting historical perspective. Progress since the late '80 really seems to be fairly slow. ?: Do we need to wait for the singularity until speech recognition works without flaws?

"I thought I would give it a try on my android sexy seems to work pretty well and I'm speaking more less at normal speed" Actually I was speaking as fast as I could because it was for the google search input - if you make a pause it will think you finished your input and start the query. Also you might notice that Android thinks it is "android sexy" - this was meant to be "on my Android. THIS seems to work...". Still it is not too bad - maybe in a year or two they have it working. Of course it might also be that I just use the word "sexy" randomly... :-\

The problem is that we don't yet understand how speech in humans actually works. As long as we merely build either inference or statistical language models we'll never get perfect speech recognition. A lot of recognition in humans has a predictive/expectational basis to it that stems from our understanding of higher lvl concepts and context awareness. Sadly I suspect that as long as machines remain unembodied in their perceptual abilities their ability to either properly recognize sounds/speech or objects and other features will never reach perfection.

should we buy this to educate behaviour at ACT meetings ... or only for our babies :-) 

Researchers at IBM have made a significant breakthrough in their quest to combine DNA strands with conventional lithographic techniques to create tiny circuit boards.

anybody interested in joining?

check this IBM initiated open source platform out - what can we do with it? LS