It has become common to talk about data being the new oil. But a recent piece from WIRED magazine points out problems with this analogy. Primarily, you must extract oil for it to be valuable and that is the hard part. Framing data as oil is not illuminating for executives trying to value their data assets. Oil is valuable, marketable, and tradable. Without significant effort, data is not. Data has more in common with land that may contain oil deposits than it does with oil.
Framing data as a real asset may help executives understand its value. Read More
Daily Archives: August 1, 2019
Calibrated Quantum Mesh – Better Than Deep Learning for Natural Language
There’s a brand new algorithm for natural language search (NLS) and natural language understanding (NLU) that not only outperforms traditional RNN/LSTM or even CNN algos, but is self-training and doesn’t require labeled training data. Sounds almost too good to be true but the original results are quite impressive.
Calibrated Quantum Mesh (CQM) is the handiwork of Praful Krishna and his team at Coseer in the bay area. While the company is still small they have been working with several Fortune 500 companies and have started making the rounds of the technical conferences. Read More
This autonomous bicycle shows China’s rising expertise in AI chips
It might not look like much, but this wobbly self-driving bicycle is a symbol of growing Chinese expertise in advanced chip design
One chip to rule them all: It natively runs all types of AI software
We tend to think of AI as a monolithic entity, but it has actually developed along multiple branches. One of the main branches involves performing traditional calculations but feeding the results into another layer that takes input from multiple calculations and weighs them before performing its calculations and forwarding those on. Another branch involves mimicking the behavior of traditional neurons: many small units communicating in bursts of activity called spikes, and keeping track of the history of past activity.
Each of these, in turn, has different branches based on the structure of its layers and communications networks, types of calculations performed, and so on. Rather than being able to act in a manner we would recognize as intelligent, many of these are very good at specialized problems, like pattern recognition or playing poker. And processors that are meant to accelerate the performance of the software can typically only improve a subset of them.
That last division may have come to an end with the development of Tianjic by a large team of researchers primarily based in China. Read More
It’s Sentient — Meet the classified artificial brain being developed by US intelligence programs
At the final session of the 2019 Space Symposium in Colorado Springs, attendees straggled into a giant ballroom to listen to an Air Force official and a National Geospatial-Intelligence Agency (NGA) executive discuss, as the panel title put it, “Enterprise Disruption.” The presentation stayed as vague as the title until a direct question from the audience seemed to make the panelists squirm.
Just how good, the person wondered, had the military and intelligence communities’ algorithms gotten at interpreting data and taking action based on that analysis? They pointed out that the commercial satellite industry has software that can tally shipping containers on cargo ships and cars in parking lots soon after their pictures are snapped in space. “When will the Department of Defense have real-time, automated, global order of battle?” they asked.
“That’s a great question,” said Chirag Parikh, director of the NGA’s Office of Sciences and Methodologies. “And there’s a lot of really good classified answers.” Read More
Rick's Cafe AI 