This week Apple has bought artificial intelligence startup Emotient with focus reportedly set on analysing facial expressions.
Elon Musk, Amazon Web Services, LinkedIn co-founder Reid Hoffman and PayPal co-founder Peter Thiel (and others) are also investing in an open source AI project to drive AI development in a way that maximises its benefit on mankind.
It's hard to pinpoint the exact path that AI will take, but with companies such as Google, Facebook and Microsoft making huge strides and Stephen Hawking and Elon Musk calling for AI to be regulated and monitored, it is definitely a hotly debated topic.
I am all for the lean startup methods. And i think it´s always good to test thing s in small scale before going big. But there is one thing that is even faster. It is called intuition, software companies is often dominated by data-driven type of personalities. And it has it´s strengths. But it can also create a stale environment where every buy button and new page has to be tested.
In small startup this can really slow things down. And it can demotivate creative induviduals. But running on pure intuition is also dangerous and can send you on totally wrong path, so here is some suggestions when developing you business intuition.
* Do something that you are really interested in, not only the end-game, this will give you energy during low-peaks or downtimes, and you have more peace to take good decisions.
* Practice to try and think outside your own scope. If you are a male, how does a female think. How does diffrent personalities think and age sectors.
* If something gives you a good stomach feeling. Break it up and analyze it. What is good about it? Why do you feel that way? That will teach you to detect bad decisions in a early stage
A few years ago, there was a shift in the world of machine learning.
Companies, such as Skytree and Context Relevant, began popping up, promising to make it easier for companies outside of big banks and web giants to run machine learning algorithms and to do it at a scale congruent with the big data promise they were being pitched. Soon, there were many startups promising bigger, faster, easier machine learning. Machine learning became the new black as it became baked into untold software packages and services —machine learning for marketing, machine learning for security, machine learning for operations, and on and on and on.
Eventually, deep learning emerged from the shadows and became a newer, shinier version of machine learning. It, too, was very difficult and required serious expertise to do. Until it didn’t. Now, deep learning is the focus of numerous startups, all promising to make it easy for companies and developers of all stripes to deploy.
But it’s not just startups leading the charge in this democratization of data science — large IT companies are also getting in on the act. In fact, Microsoft now has a corporate vice president of machine learning. His name is Joseph Sirosh, and we spoke with him on this week’s Structure Show podcast. Here are some highlights from that interview, but it’s worth listening to the whole thing for his take on Microsoft’s latest news (including support for R and Pythonin its Azure ML cloud service) and competition in the cloud computing space.
You can also catch Sirosh — and lots of other machine learning and big data experts and executives — at our Structure Data conference next month in New York. We’ll be highlighting the newest techniques in taking advantage of data, and talking to the people building businesses around them and applying them to solve real-world problems.
Apple introduced a new standard in interface design. It took the whole industry to a whole new level. People where not satisfied with half-good system any more. We now want user experiences that is easy to understand and navigate. But as the industry matures there is still something fundamentel that is not addressed yet:
Very little in websites and apps are tailored to us as individuals
There is already signs of this in the industry, it is not enough to be good, you have to be individuak good. Apple are ramping up their data scientist hiring efforts and Google has been working with this for a very long time, as it is a big part of google search engine. You can not fit all needs, but that is eaxactly how the future are going to pan put. The future is called:
Personal Experience Design
How will this look? Machines will become better at figuring out exactly what you want, and will then adapt to your needs. This will have huge effects on the percieved quality of the service as every personal experience will be tailored and unique to that user.
Read more about how individlabs system work.