Google’s Quest For AI Domination

The only way for everyone is to go up. The same thing applies to technology. The digital innovations we are now using will only keep on getting faster, better and more state-of-the-art as the years go by. Only those who have the foresight to dream big can likewise achieve greatness. There are many of those companies who have kept on dreaming big for quite some time now. Since the tech explosion and now the consequential widespread use of smart technology, there are businesses that have been staples on the market and as such grew exponentially to where they are now. Fine examples are Amazon, Google, eBay, Facebook, and many others who have dominated the world in just about every aspect of it.

With that being said, let’s talk about Google’s unending devotion to developing artificial intelligence. Google is the popular web browser. You all know it and you are probably using one in your day-to-day too. Yet Google has other divisions that tap other market and one of them involves continuing scientific research and advances directed to the AI technology. Right now, we have databases after databases of data, files, and ideas that are stored somewhere safe and secure and they virtually make the world go round without all of us knowing. But if Google becomes successful in their quest for AI domination, we may be able to let go of some of the bulkiest and hardest to maintain computer databases by taking advantage of whatever this mind-blowing technology can offer to all of us. Surely, we can expect a total overhaul of the current computer systems in place in favor of the latest and the best and it may be a struggle for many to keep up but we may very well have to cross that bridge sooner or later.

An exponential increase in the availability of digital data, the force of computing power and the brilliance of algorithms has fuelled excitement about this formerly obscure corner of computer science. The West’s largest tech firms, including Alphabet (Google’s parent), Amazon, Apple, Facebook, IBM and Microsoft are investing huge sums to develop their AI capabilities, as are their counterparts in China. Although it is difficult to separate tech firms’ investments in AI from other kinds, so far in 2017 (see chart 1) companies globally have completed around $21.3bn in mergers and acquisitions related to AI, according to PitchBook, a data provider, or around 26 times more than in 2015.

Machine learning is the branch of AI that is most relevant to these firms. Computers sift through data to recognise patterns and make predictions without being explicitly programmed to do so. The technique is now used in all manner of applications in the tech industry, including online ad targeting, product recommendations, augmented reality and self-driving cars. Zoubin Ghahramani, who leads AI research at Uber, believes that AI will be as transformative as the rise of computers.

(Via: https://www.economist.com/news/business/21732125-tech-giants-are-investing-billions-transformative-technology-google-leads-race)

Databases were handy in the inventory management and its role in bringing to life the first ever software we got our hands on but all of that is set to change once artificial intelligence finally becomes our reality. It may be surprising for some but some aspects of AI are already in use right now in many parts of the web and even by Google itself or even on the phone you are using. Certain Gmail features and Siri on iPhone are some examples of AI already in use and there are many more. It is essentially important for businesses especially tech companies have AI foundations in their systems if they want to be able to keep up with all the changes that will take place in the years to come but Google is arguably one of the top Western companies that have really taken this AI dream quite seriously. Google already makes use of machine learning in various ways such as in categorizing Youtube contents, in Google Photos, a core feature of the Android operating system, among others. When it comes to research, Google Brain is not only ambitious but one of the best in generating money from machine-learning innovations.

Six years ago he co-founded the Google Brain project, which for years has been at the cutting edge of developments in artificial intelligence.

Fast forward to 2017, and his AI work is centrestage. These days AI is part of everything Google does with chief executive Sundar ­Pichai having declared Google an “AI-first company”.

Dean was the key attraction at the company’s AI conference held in Tokyo last week. He says AI and machine learning, where computers “learn” without being explicitly programmed, are being used to improve seven of Google’s products, each with more than a billion users.

Studies in artificial intelligence have been part of computer science for decades, but mostly beyond the reach of technology to implement effectively. The recent ability to collect huge amounts of data with sensors, collate that data by moving it across fast-fibre networks, process it with fast computers and store it in massive databases has changed that.

(Via: http://www.theaustralian.com.au/business/technology/googles-jeff-dean-were-using-ai-to-build-machine-learning-systems/news-story/c0120711ad2368cc8d9938f7575a78ba)

It was not long ago when Google began its pursuit of artificial intelligence and so much has happened already. The company even coined up the term “AI-first Company” as a part of Google’s identity. As of now, seven Google products exclusively use machine learning in their operation and they may be the key to Google’s eventual success with it in time. They may eventually wipe out the need in using extensive databases in collecting a substantial amount of data and making sense out of all those information collected as the machines itself will eventually be capable of decoding the message and then decide what to do about it. It is not a perfect technology, though, and the flaws identified so far can be costly, which is probably why we are still not seeing the fullest potential of machine learning and we have just barely scratched its surface.

For now, let’s continue on worrying about mundane problems like when your computer starts to malfunction and you can no longer access your data because of a broken hard drive. Issues like this, although costly and bothersome, are something we know we can manage, unlike the mystery that is machine learning. For now, let the rest of computer experts worry and tinker about our real-life issues that most likely involved these https://www.harddriverecovery.org/ms-exchange-data-recovery.html and https://www.harddriverecovery.org/SQL_database_recovery.html. Quite troublesome as they are but surely pales in comparison to the problems posed by artificial intelligence.

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