Machine-learning algorithms are often used in recommendation

1. Machine-learning algorithms are often used in recommendation engines.

2. Q . What type of machine learning do you use for iprediq? A .We apply our own proprietary machine learning systems. The artificial intelligence we work on here automatically converts unstructured information into useful, actionable knowledge.

3. Q . What makes you believe iprediq’s domain / Machine learning  is the future? A . we get computers automatically learn from examples and predict the future accurately. The range of applications is huge from product recommendation to face recognition, to game playing,  to stock trading.

4. Q. Where can we expect to see machine learning in society in the near future? A. Machine learning has many very interesting future applications : §  Use in self-driving cars, such as in Google’s current driverless car project §  Applications for real time object recognition, as is necessary for many augmented reality applications §   language translation §  Learning to map brain imaging data to an indicator of what a person is thinking about §  Enhancing the automated identification and predictions to  serious ailments, such a cancer

5. Q. Any particular area you are excited about? A . The big leap we are making is not only to dig into things like structured databases but to analyze unstructured information — such as documents or images on the Internet — and be able to make use of them as well. That’s where the big gains are going to be in the next few years. I also think the only path to developing really powerful AI would be to use this unstructured information. It’s also called unsupervised learning— you just give it data and it learns by itself what to do with it, what the structure is, what the insights are. We are only interested in that kind of AI.

6. The INTERVIEW should be in 3rdparty. And don’t link this to facebook

7. Q . We read about Deep Learning and Machine learning a lot these days. It is said “ it works just like the brain” can you explain?

8. A . I do not agree to this. Though I am not a brain researcher, I feel  it’s very far from what the brain actually does. And describing it like the brain gives a bit of the aura of magic to it, which is dangerous. This leads to a lot of hype where people claim things that are not true. Artifical Intelligence has gone through a number of winters because people claimed things they couldn’t deliver.

9. Q. What would you say is our biggest benefit from machine learning and AI so far? A . I do not think that machine learning has some killer application that has radically changed our lives. I would rather say ,machine learning has become integrated into hundreds of different applications. Most of the time we aren’t even aware of it being  ther .

10. For instance, Netflix uses machine learning to improve its movie recommendations for us, Amazon applies it to recommending better products, Google uses it to translate languages, and digital cameras relies on it to identify faces in photographs. We're using the output of machine learning algorithms all the time, we just don't realize it.

11. Q. if I had to ask you to describe in as few words as you can, what would you say ? A . I need to think about this. Pls give me some time.  I think it would be “machines that learn .” Or put it another way it would be “end-to-end machine learning.” Well… let me think a bit more… It’s the idea that every component, every stage in a learning machine can be trained for better outcomes etc .

12. It will results in great new applications that are currently hard to imagine.