Today I talked with a few brilliant engineers about their latest, to be released Chipsets, and was I blown away by the brilliance of these product engineers and managers.  Two chips I would like to briefly highlight today are the Qualcomm Snapdragon 800, and the Nvidia Tegra 4 Chipset advancements.

Qualcomm

The Qualcomm Snapdragon Chipset is so off the charts amazing from a consumer standpoint, they had a room with a tablet plugged into a large high definition headset, and the room encapsulated a complete set of surround sound speakers, as well as each chair was equipped with a common headset.  The tablet was plugged into the HD system through an HDMI cable, and that was it.  I won’t bore you about 2K verses 4K High Definition upgrade standards, but what I can tell you was the video sequence they played on this Android tablet was of such high caliber quality and no lag whatsoever, and the sound was so superb, it would in fact give ANY of the movie theaters I have been to ever, a run for their money.  I have been to quite a few movies in my lifetime.

The Nvidia team had us put on the headsets, which were your basic headsets, nothing special, but the same N channel surround sound that came out of each channel, e.g. center, front & side left, front & side right, and back channels was emulated through the headsets with the same superior sound quality, and power.  The demonstrators had us remove our headsets as they were blasting sound through each channel, and we couldn’t believe the sound was not coming through the speakers, but was coming through the headsets themselves.

Qualcomm is looking at the second half of this year for general release to be pushed to their partners, and/or the consumers.  That part was unclear, however, what was clear, was the amazing power you will have in your Android tablet coming soon.

Nvidia

I had the rare pleasure to speak with an amazing engineer at NVidia that took the time and patience to go through advancements of the Nvidia Tegra 4 Chipset.  Instead of giving you the granular tech jargonese that we went through, I will sum it up in two ways.  The Nvidia Tegra 3 Chipset already had an efficiency with a 5th core that primarily remained idle, and was used to gain battery life in mobile phones.  What it did, and continues to do in the Tegra 4, at an idle period of the phone, instead of using these four massive processors to burn up the battery life, this 5th ‘light weight’, low power consumption core would handle the idle times, and give the four massive boys a rest.  This extends the battery life significantly.  Well, now the boys and girls at Nvidia said, after Tegra 3, hey, we have this 5th core, let’s allow ourselves to push the envelope slightly, not only use this core for battery life efficiency on your phone, but let’s let the mobile applications have access to this core so now you have 4 mean, powerful cores hard at work, and one slightly advanced core being used for both efficiency and graphical applications, like games.  Brilliant.

Finally, Nvidia doesn’t stop there, it is now in the business development phase of bringing you cloud gaming, essentially Elastic Computing for Graphical Calculations in a cloud with an exponential set of these Chipsets, where you can subscribe to this gaming service, and all of the hard core tough calculations of rendering graphics at lighting speed is done in the cloud, and just the basic pixels get pushed to your phone, relatively a really light weight signature. Your phone or computer becomes a terminal emulator, which can focus on your inputs, instead of graphic rendering, and the cloud does all the hard work, again, brilliant, and the future of gaming.  The engineer and I just looked at each other, and we knew, this was the pie in the sky for the gaming industry.  Hold on to your hats, this is going to be a wild ride.  Now, they are still in the stage where they must solidify the details with a cloud company that hosts these servers, and provides the gaming service, e.g. business development, but the technology has arrived.  In addition, engineering and science packages like Mathematica may also use this type of Elastic Computing High Yield for massive calculations.