AI & Machine Learning

We can see a lot of hype about AI and Machine Learning, and its potential to transform businesses. More and more companies are adopting machine learning solutions, setting up accelerators, opening R&D centers, and investing into startups. Also, there is a large number of reports with AI market estimates and forecasts. However, it’s challenging to get the right information on machine learning development that will actually work for your business. Here are our five expert tips to make machine learning development work for you.

With growing amounts of computational power, machine learning and deep learning are increasingly making their way into numerous sectors. They are widely used for recognizing objects, translating speech in real-time, determining potential outcomes, understanding consumer habits, making personalized recommendations, and a lot more. Still, some questions remain uncertain. What do these two entail? And should companies invest in machine learning development to benefit their businesses? We provide the answers to these questions in our article.

Policy approaches to education, skills training, employment, and income distribution should all now assume a post-AI perspective. This will require us to question some of our most deeply held convictions. A world where autonomous AI systems can predict and manipulate our choices will force us to rethink the meaning of freedom. Similarly, we will also have to rethink the meaning and purpose of education, skills, jobs, and wages.

What do artificial intelligence (AI), invention, and social good have in common? While on the surface they serve very different purposes, at their core, they all require you to do one thing in order to be successful at them: think differently. When it comes to AI, invention, and social good, the possibilities are endless. Technology will only continue to become more advanced, creating new opportunities to fix societal problems related to health, sustainability, conservation, accessibility, and much more. If you’re thinking of jumping into AI for good, just remember the most important rule: think differently.

Artificial Intelligence has been buzzing around more frequently with higher and ever-increasing intensity every passing day. Reason is as clear as a crystal: Its power and possibilities it can create. It doesn’t really matter who thinks of AI highly or lowly but one thing is certain: Its time has come. Before you buy time in realizing and delay in deciding of its adoption, it may come and stare straight in your face! You may not even have the bargaining power that you still enjoy today. 

While some things are easy to measure, intelligence is not one of them. Intelligence is a very abstract and complex thing to measure. How do we, people, perceive artificial intelligence and what are our expectations from it? It seems when people judge AI’s ability, we are harsh. We want AI to be perfect. We do not show the flexibility we provide to human mistakes proportionally to AIs. We want AI to be “like a human”. Whatever the reason is, it is a common pattern. We expect artificial intelligence to be comparable to human intelligence.

Only a fraction of the population of this planet has a skill set considered essential to business and technology today. Solving tough A.I. problems is not like building the flavor-of-the-month smartphone app. In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research. The path to success is to first start with a problem that would be a good candidate for machine learning, and then be prepared to experiment with training sets comprised of your own data.

When it comes to emerging technologies, many talk about the importance of incorporating them in day to day processes – especially when it comes to businesses. But there only a few that have hands on experience with them. So we decided to interview some experts who have spent years working on different technologies, experimenting with their use cases and guiding others who wanted to grow in that field.

Every day, there are news stories about exciting applications for analytics in robotics or on the edge of IoT. Analytics is helping to improve the quality of life for people. It is reducing costs or helping control consumption of energy or managing devices in the home, as well as reducing industrial costs, improving energy efficiency, and making goods cheaper as a result. Looking to the future, the IoT systems and artificial intelligence platforms that we create today will become the baseline for the way future generations think about and engage with technology. They will form the foundations for future ecosystems.

More practical applications of AI are on the horizon. Those applications will include helping the transportation industry to solve some of our biggest challenges in getting from place to place. AI is getting smarter thanks to innovative programmers—but it’s also making our transportation system better by building on the building blocks these programmers provided. AI can assist with urban design and traffic control in several ways, including adjusting variable speed zones based on traffic, traffic light timing, and smart pricing for vehicle tolls. Here are 4 important ways AI will help improve our transportation system.

It’s a pivotal time for those involved in Artificial Intelligence, as many within the community are looking at how it can improve the state of the world we live in. A new approach to AI research by MIT IQ is the latest initiative to want to tackle some of these concerns. Whilst there are many initiatives actively researching Artificial Intelligence applications for the good of society, MIT aims to take a different approach to the very foundations of the field. Through this, they hope to answer some of the most burning questions that will help to drive the development of AI.