I recently came across an HP labs video on the excitement of one of the researchers on next wave developing to compute and gather information.

It shows some of the efforts to be more efficient and yet more powerful. Innovation’s role is in resolving conflicts like this, and that’s exciting.

The whole industry is at a tipping point where new generations of capability will be arriving simultaneously for computing, storage, networking and sensing… which should allow for a novel, innovative dimension of applications and services to take advantage of the new abilities and generate new levels of business value.

With the abundance of infromation resources available, we can all use some help to sift through for the nuggets we can use.

I mentioned that I was giving a presentation this week at the New Horizons Forum at the AIAA conference. Since it may provide some useful insight about the research underway at HP labs in a larger context, here is the content of one slide from that presentation:

1 datum is a point

2 data are a line

3 data are a trend

100 data are a picture

Having sensors to generate the data that fuels a more proactive business is important, but there is more to sensing than the sensors and the data collected. A holistic ecosystem view is needed. Unfortunately, this means that the tools of today may not be up to the tasks required.

You may have heard about HP’s efforts to place a million node sensor network in the ground for Shell, gathering seismic information. Traditionally, this kind of information was just a flash of perspective taken in the dark from a few locations. Instead, this sensing effort with Shell generated a much more fine-grained view, taken from a myriad of angles, to understand in-depth what was underground. 

In order to do implement the system, HP not only had to invent the sensors (relatively cheap and yet very sensitive MEMS devices), but we also create the networking and management techniques to make it useful. Building upon what we’ve learned, we’ve been researching whole new approaches to information storage and computation that will be required to generate value from massive amounts of information.

HP has many of the foundational patents on memristor devices and sensing techniques and we should soon see the shift in storage and computing that the implementation of these techniques should enable. The whole concept of computing will likely need to bow to the onslaught of information from sensing and the related metadata, changing how information is transferred within the computing environment -- shifting from computing on bits to analyzing information in graphs on highly parallelizes computing platforms: Cog Ex Machina

In addition, research is underway to understand how information can be analyzed, automated and displayed. New techniques can be applied to focus attention on the areas needing the creativity that people can provide.

In the marketplace, last year was the year of Big Data as a buzzword with its primary focus on generating insight from the massive amounts of information being collected. Frankly, that will not be enough for the future envisioned – we need to shift the focus to time-to-action, not insight and that is what many of our research efforts underway will enable.

Next week, I am going to be part of a panel at the New Horizons Forum that is part of the American Institute of Aeronautics and Astronautics (AIAA) conference. The panel is going to be focused on: Information Technology – Spin-On Technology for Aeronautics and Space. Essentially leveraging efforts into Aeronautics and space.

I’ll have a few minutes to present where I’ll focus on the shift in how we will use people and computing in the future and talk through some examples. In many organizations have so much data coming in that there is no way that any organization can effectively consume it, using today’s techniques.

I’ll use a simple model to show how things are changing and where HP labs is focusing research. The model is that one datum is a point, 2 data are a line and three are a trend. 100 data points are a picture or pattern. When you can move beyond calculations at the bit level and actions in isolation, whole new levels of capability open up.

Today, we think about working with data primarily in isolation. We need to start thinking about storing massive amounts of data (using devices like memristors), computing on the patterns using different techniques (like Cog Ex Machina) and using whole new approaches to focus the attention of those who need to act upon the context described by the data (like automation and gamification).

A holistic shift in how we approach sensing will be needed:

When I think about the work done with HP and Shell to gather detailed seismic information for oil detection and production, it makes me wonder about possibilities of families of sensors gathering data for planetary exploration. It also makes me wonder about using crowd sourcing techniques to tease out meaning from the unique items that pattern matching on all that data can identify.

It should be an interesting panel, for the audience and the panelists.

HP Labs researchers may have figured out a way to create a chip that generates neuron-like behavior, using a combination of memristors and capacitors to create a signal pattern similar to a neuron.

“To get the sort of spiking behavior seen in a neuron, the authors turned to a simplified model of neurons that allow them to transmit signals. When a neuron fires, sodium channels open, allowing ions to rush into a nerve cell, and changing the relative charges inside and outside its membrane. In response to these changes, potassium channels then open, allowing different ions out, and restoring the charge balance. That shuts the whole thing down, and allows various pumps to start restoring the initial ion balance.”

Each unit consists of a capacitor (to allow it to build up charge) in parallel to a memristor (which allows the charge to be released suddenly. The combination produces spikes of activity as soon as a given voltage threshold is exceeded. The researchers called this circuit a “neuristor.”

The illustration is courtesy of UC Berkeley.