Voice and language recognition software is getting better and better. Once upon a time, it was something that was extremely clunky and unreliable and even the best systems required you to spend far too much time training them while speaking extremely slowly and enunciating like…well…like a computer. However, at last the systems have improved to the point where it’s possible to at least accurately convey meaning through talk to text features without having to clarify every other word. In fact, I know a trucker who does most of his communication using talk to text on his phone. It makes a few mistakes here and there but its accuracy is still pretty impressive considering he’s speaking normally while in a large moving vehicle.
Then there are the voice assistants on our phones. Whether you talk to Siri, Alexa, or Cortana (all four of you, you know who you are) that voice recognition starts out needing a little training but nothing like it used to. And the more you use it to look up local restaurants, find a factoid to settle an argument or to book a hotel room, the more accurate it gets. Now, they are even in the homes of many, listening constantly for you to need their assistance with something – everything from dimming the lights to spinning up your favorite playlist on Spotify.
The improvements in this software hold a lot of potential. It has already been used for years in business to accommodate certain employees who may not be able to speak clearly or who lose the use of their arms. It is also a much more efficient way to record information than the increasingly dated keyboard. Typing is inherently inefficient, creating the possibility for misspellings that need to be corrected lest they convey an unintended meaning. It also requires a keyboard, which adds space, weight and money to your computer. As voice recognition software improves, the keyboard can be replaced with a simple microphone, probably the one on your phone. Imagine being able to compose reliable messages for business, a book, notes on a law case and have them all transcribed without having to take the time to proofread them. The time savings would be impressive. Or perhaps a more mundane situation in which you’re sitting at home and have a craving for pizza, but you can’t quite remember the name of the place you got it from last month. You throw the question out into the air and your device reminds you of the name, the price and asks you if you’d like it to order a pizza for you. If you think about it, Alexa and other smart devices are only a step or two away from that level of functionality.
Another use would be in hospitals. Embedded microphones would record conversations with your doctor, highlighting the important points and recording all of the important information. This would save time and increase efficiency in a number of ways. No more would nurses and admins have to spend hours on data entry, with all the potential transcription errors that entail. Incidentally, that would also save you having to answer the same questions three times every time you go in for a checkup. It also means no one, or at least very few people have to come in contact with the Petri dishes known as keyboards in an environment that should be kept as sterile as possible.
Lectures and presentations could be recorded and transcribed instantly, making information readily available in real time. The possibilities are enormous.
Yet, there are potential problems that arise, namely, who owns all that data getting generated and recorded? Is it the place where the recording happens? The place where they are stored? Some other party? At TARTLE, we believe all the data you generate is yours. So if it’s your information and your data that is being recorded, then you deserve to be the primary beneficiary of sharing it, or of deciding whether you want to share that data or not. These are questions that will be addressed sooner or later in the legislative realm which is why we are encouraging people to sign up at tartle.co to join the TARTLE movement. Together we can help steer that eventual legislation in a direction that will benefit not just a few, but each person who works to generate that data in the first place.
What’s your data worth? Sign up and join the TARTLE Marketplace with this link here.
Quantum computing sounds pretty futuristic doesn’t it? It sounds like the pinnacle of technology, the most advanced stuff, somewhere on the bleeding edge of the tech world. What if I told you that was only partially true?
Yes, it is advanced and represents the next big step in computing. No doubt about that. Yet, it’s been getting actively worked on for well over twenty years. In fact, way back in 1996 Bell Labs was working on quantum-based methods for searching databases. Not only that, in 1998 a quantum computer that could implement the algorithm was successfully built. We’ve had functional, although not yet useful forms of this technology for quite a while. While it’s still near the edge, it’s hardly on the bleeding part of it anymore.
What does it matter though? Why have people been trying to build a functional quantum computer for so long? It has a lot to do with the nature of quantum mechanics. Don’t worry, we aren’t going deep into it here, partly because it would take too long and partly because I don’t know enough to go that deep. Suffice to say that particles on the quantum level operate in numerous different states at once. If that could be exploited, if we could take advantage of a quark’s ability to do two seemingly different and even contradictory things at once, it could dramatically increase the speed and storage capacity of our computers. That search algorithm from Bell Labs is just the tip of the iceberg. Currently, when a computer has to search through a database it starts at item one and moves on through in a linear fashion down to the last item. That takes time and energy. So perfecting an algorithm that can enable multiple search modes and paths to be done at the same time would be a game-changer.
Naturally, nothing goes smoothly. As the quest to build better and better quantum computers has continued, there have been certain roadblocks. Researchers needed to find new ways to put that algorithm into action. To help solve the problem, they turned to electrons.
Electrons are negatively charged particles that orbit the nucleus of an atom, and are the part that has the most to do with atoms bonding together. Roughly speaking, what they do is bounce around looking for defects in a material and fill the defect, or hole when they find it. This process initially looks very, very random. But, as with anything having to do with the quantum realm, looks can be pretty deceiving. Researchers studied the process more and realized that it looks a lot like the electrons are following Bell Labs search algorithm, just putting it into practice in a better way.
That’s the real irony here, not only has quantum computing been in existence since the 1990s, the solution to take it to the next level may actually lie in nature. It also looks like the same quantum search patterns are at work in DNA assembly and crystal growth. It’s possible that this algorithm that researchers stumbled onto over twenty years ago is in nature everywhere, much like the Fibonacci Sequence. By duplicating this natural process that is able to see the whole picture and deal with a massive amount of variables all at once it should be possible to take quantum computing out of the research lab and into the living room.
TARTLE is doing something similar with data. In connecting organizations with source data, we’re helping them to see the whole picture, the whole context behind the data they are collecting. It’s never just one or two things that lead to quantifiable choices but rather a whole system of variables that go into making one decision over another. It’s only by recognizing and trying to understand that can we really make the best and most productive uses of our data.
What’s your data worth?
