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Beyond such academic issues and beyond neuroscience itself, the models of this chapter point to the possibility of new types of computers to serve humankind In this book, arti cial intelligence goes beyond the concept of computers that act human when queried with a keyboard In this book the test for arti cial intelligence is: Can it learn Can it learn the equivalent of fetching a ball, for example Intelligence like this applies nicely to self-contained robots, but it might also apply to immobile systems that follow complex procedures Prior to attempting to build a system with arti cial intelligence, however, it might be reasonable rst to analyze biological memory systems and intelligence Below we review the underlying psychological knowledge that leads to memory system models and, ultimately, to rudimentary models of cognition..

An organization can quickly onboard its new business operations onto a cloud deployment, managed by a cloud service provider, which can be quickly ramped up based on actual business demand from the new business, or ramped down if the business experiment does not succeed This application of cloud computing will encourage more risk-taking with new business models, and should spur a burst of new business innovation as a result of a much lower risk pro le for new business experimentation enabled by cloud computing Cloud-Enabled Call Centers In many ways this is a natural t with the recent evolution of associated call-center technologies, such as Voice over Internet Protocol (VoIP), which is intrinsically cloud resonant A truly cloud-enabled call center could be fully distributed and incremental, able to expand or contract as demand warrants, in increments as small as one agent at a time.

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4.1 TRAFFIC ENGINEERING Table 4.2 Comparison of aggregate measurement methods Method Passive measurements Active measurements Piggybacking Delay (1) X X Delay variation (2) X (4) Packet loss (2) X X

Figure 10-11: When you open a curves dialog, it always displays a straight line graph, indicating that the tonal values of the image (the input greyscale) you have opened is identical to that which the image will output. When you click and drag on the line, to curve it, you are remapping the greyscale pixels, as we explained in the histogram section previously, so that the output values are different from those of the original image. (Curves dialogs from Photoshop CS, courtesy of Adobe Systems)

In this manner this could enable call centers to become even more responsive and ef cient, in that infrastructure costs can more precisely scale proportionate with labor costs We have offered a few examples of cloud-enabled business models here This is a small list, but your imagination is the only barrier to imagining the ways in which an existing enterprise can leverage cloud computing models to enable portions of a current business.

command line. Looking at the command line whenever you execute a command is important, because that command appears on the command line, and a prompt or list of options may appear as well. If you have Dynamic Input on, the tooltip also displays the prompt. (Click the Dynamic Input button on the status bar to turn it on and off.) See the section, Responding to commands, later in this chapter for more information on what to do next.

Figure 3.12 Representation of f (x) from Fig. 3.9 onto the averages and differences of the Haar scaling function and wavelets to order 23.

You won t win every project from existing clients, nor will you be qualified to submit proposals on all work. It may seem obvious, but many consultants don t strive to build the relationships with clients that keep them informed about: What s going on in the client s organization. The people involved. What you can do to help, even if that means steering the client to a competing firm to handle the work. If you find yourself out of the loop, your client relationship balance sheet needs fixing.

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