Artificial Intelligence-Challenges Ahead

Artificial intelligence (AI) has revolutionized information technology. The new economy of information technology has shaped the way we are living. Google led the way, showing the power of data-driven artificial intelligence delivered over the cloud, not only in search but also in tasks like language translation and computer vision. Artificial intelligence run through the cloud is now the dominant approach used by researchers at technology companies, universities and government labs.

We’re seeing a rebirth of artificial intelligence driven by the cloud, huge amounts of data and the learning algorithms of software. Some predict that we are headed much further.

Artificial intelligences are now ubiquitous, from GPS navigation systems and Google algorithms to automated customer service and Apple’s Siri, to say nothing of Deep Blue and Watson — but no machine has met Turing’s standard. The quest to do so, however, and the lines of research inspired by the general challenge of modeling human thought, have profoundly influenced both computer and cognitive science.

The ethics of artificial intelligence is already an area of huge concern when it comes to the military’s use of unmanned vehicles. In November 2012, the Department of Defense tried to establish guidelines around minimizing failures and mistakes for robots deployed to kill targets. The United Nations is expected to address the topic this year. Military robots can save soldiers’ lives, and proponents say they aren’t susceptible to mistakes caused by passion, revenge, pressure and fatigue.

It is important to remember that the benefits to Facebook and Google aren’t hard to imagine. Rather than depending on users following brands, they could simply scan people’s pictures and know whether they prefer Coke or Pepsi. Or, going a step further, the machine could determine your location, recognize you haven’t posted a picture of yourself smiling in some time, and recommend you buy tickets to the funny movie playing around the corner.

The following  highlight application areas where AI technology is having a strong impact on industry and everyday life.

AI Application Areas

Aerospace
Petroleum
Business Intelligence
Process Support and Workflow
Logistics and Supply Chains
Financial Advisory Systems
Documentation and Layout
Emergency Response
Homeland Security
Bio-Informatics

AI Technology Areas

Knowledge-Based Systems: data mining, expert systems, knowledge management, KBS methodology, ontologies

Planning and Workflow Systems: modelling, task setting, planning, execution, monitoring and coordination of activities

Adaptive Systems: case-based reasoning: a technique for utilising past experiences and existing corporate resources such as databases to guide diagnosis and fault finding

Intelligent User Interfaces: intelligent agents, document presentation and argumentation, dynamic creation of content

Intelligent Virtual Worlds: collaborative workspaces, virtual operations centres, meeting assistants

For more than 50 years, we’ve been hearing about the promise of artificial intelligence and intelligent machines, but most of the big success stories to date – the IBM Watsons of the world – have been the result of massive efforts by universities and corporate R&D labs rather than by emerging start-ups. That could change soon, as artificial intelligence shows signs of becoming the next big trend for tech start-ups in Silicon Valley.

Improving customer satisfaction by bringing down response times, fewer redundancies, a reduced time to market for new products and a more personalized approach. Artificial Intelligence helps organizations improve customer interactions resulting in more loyal customers. IBM’s Watson for example has developed a financial services assistant that can provide better advice on financial products based on market conditions, life events, client’s past decisions and available offerings.

However there are some shortfalls. One is the realization that the creation of a comprehensive AI solution such as IBM Watson – as amazing as it has been – may simply be too expensive to be economically viable over the long haul. Even IBM has been forced to admit that it needs to rethink how it does AI. The company wants Watson to eventually become a $10 billion a year business, but thus far, Watson has only been able to generate $100 million in new business. As a result, IBM is now talking about partnering with the entrepreneurial ecosystem to develop AI apps for Watson, the same way that developers partner with companies such as Apple to develop iOS apps.

The second factor is a realization by companies such as Google and Facebook that they can use AI to solve smaller, real-world problems. AI doesn’t have to be able to beat a human at chess or win Jeopardy! – if it can produce better search queries or analyze your social graph, then that may be good enough. Facebook, with its DeepFace project, promises to solve the problem of facial recognition so that it can help with Facebook photos. New “deep learning” initiatives at Facebook can be used to make sense of your social graph.

Third, Google  is without question one of the most innovative companies on the planet.  It’s a company that is known mostly for its amazingly successful search and advertising businesses, and will probably be known for this for the foreseeable future. But lately it’s also quickly becoming known for its rather unorthodox array of secondary business efforts. These efforts include things like driverless cars, wearable technology (Google Glass), human-like robotics, high-altitude Internet broadcasting balloons, contact lenses that monitor glucose in tears, and even an effort to potentially solve death (Difficult to believe though).

“It sounds not as dangerous as computers that take over the world, but it’s something that helps with complexity and uncertainty,” Peter Norvig, 53, ( Director Research, Google) says in an interview. The results of his work may be no less far-reaching than the exploration of Mars. It touches on how billions of people already use search, browse the Web, circulate e-mail, and translate documents and speech on personal computers and mobile devices. In years to come, artificial intelligence (AI) systems might remind us of our appointments, drive our cars, and connect us with friends. “Imagine a very near future when you don’t forget anything because the computer remembers,” Google Chief Executive Officer Eric Schmidt said at a recent  conference in Berlin. “You are never lost. You are never lonely.” AI in action: Google Instant

Moreover there is just so much data available these days and as humans we need assistance in gathering, analyzing and understanding it. A recent IDC Digital Universe Study predicted that the amount of data that currently exists is going to double every two years from 2012 to 2020. We need to realize that without the help of AI, it is incredibly difficult for any business to sort through all the data and then make informed decisions and take advantage of opportunities.

Artificial Intelligence has already made promises for decades and only recently we are seeing some, significant, results. There are many challenges involved in creating truly intelligent software and machines. Venture capital firms investing in these companies thus need to have a very long investment horizon. Although of course the acquisition of DeepMind by Google suggests otherwise.

We’ve seen huge changes in the way that humans interact with machines. Previously, human minds were responsible for coming up with creative and smart solutions to solve problems and machines would help by completing manual tasks. Now, we allow machines to do the thinking for us and simplify our involvement.   Take for example, the SatNav, a product used globally every day.  We, as the driver, decide where we want to go, and our trusty SatNav tells us the best, quickest or cheapest way to get there.

“Although robots are important to society, they cannot yet do most tasks carried out by humans,” says Granada scientist Eduardo Ros Vidal, “We have been talking about humanoids for years, but we still don’t see them on the streets.”

The following predicts a futuristic view of how our machines will progress in the decades ahead:

2015-2020 – $10,000 robots that read human emotions, perform household chores, and provide security are slowly being accepted as family members.

2020-2030 – $20,000 bots are efficient at most human jobs; some enjoy limited human rights.

2030-2040 – SuperBots outthink humans, making human-machine data transfers commonplace.

Imagine a super-computer-like hard drive linked wirelessly to your mind. An encyclopedia of information pops into your head and photographic memory becomes the norm. With computer-like abilities, you’re now a whiz at processing data. In fact, when faced with making a decision, in just seconds, you can run dozens or even hundreds of “what if” simulations through your mind. You then make the correct decision – always.

Most people welcome mind improvements like this that promise a happier, and certainly far more intelligent life; but some conservatives may find this “magical future” somewhat unsettling. However, while the contours of when this bold science will arrive may be a bit foggy, the map for how we get there is crystal clear. It’s only a question of when, not if.

Best Regards,
Raj Kosaraju

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