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1. Deep Learning, Big Data and Artificial Intelligence

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Deep learning is a subset of machine learning, which in turn is a technology for the development of artificial intelligence (AI or AI). Since about 2006, deep learning has been considered by AI researchers to be the most promising approach of AI. All of the breakthroughs in the field of artificial intelligence, such as the victory over a human Go master by Google’s Deepmind team, have been achieved through deep learning.

KI: What will the future bring?
The development of AI special chips is still in its infancy. The reason why deep learning has become a useful method in the field of artificial intelligence is the fact that the hardware has become fast enough for many layers of artificial neural networks. Unlike the traditional PC, AI calculations require a variety of special chips that can handle large amounts of data in parallel.

With the AI booming for many areas from voice assistants to autonomous driving, software and AI hardware technology is likely to make further big leaps in the coming years. In the first half of 2017 alone, CB’s major venture capitalists invested $ 1.8 billion in AI technology, according to CB Insights. That’s already more than in 2016 as a whole, which was already a record.

Deep learning is a subset of machine learning, which in turn is a technology for the development of artificial intelligence (AI or AI). All of the breakthroughs in the field of artificial intelligence, such as the victory over a human Go master by Google’s Deepmind team, have been achieved through deep learning.

In the case of unsupervised learning, the algorithm is usually fed with huge amounts of data that have not been previously detected by humans and thus pre-sorted. This form of machine learning is particularly interesting in the big data age.

The dynamics of platform economies – the fact that in the digital economy a few large players such as Amazon or Google determine the rules for everyone through their platforms – could be compounded by AI. Because data is the raw material to train and improve the artificial neural networks. “AI is an industry

With voice assistants such as Apple’s Siri, Amazon Alexa, or Google Now, Pascal Finette, vice president of Singularity University, is repeating what has already been said for other technologies: The beginnings are disappointing – but soon the assistants will make huge strides. “Skeptics will reply that artificial intelligence is not only a question of computing power but also a question of quality of the algorithms.

Deep Learning relies on a multitude of artificial neurons, which are arranged in numerous layers and filter out relevant information more and more. Instead of focusing on the neurons of biological brains, as in the classic computer on a central, very powerful processor unit, there are numerous, relatively weak computing units, but they are strongly networked with each other. This form of machine learning works especially well in combination with AI-optimized special chips and large amounts of data.

Not everywhere where AI or Machine Learning is written, however, is currently artificial intelligence in the strict sense in it. Especially with chatbots, but also in many social media tools and some tasks for which IBM Watson is used, are still simple scripts are used, which do not improve over time.

Frequently, semi-supervised or supervised learning is often the starting point: here, a human already knows the correct result – for example, the difference between cat videos and non-cat videos. The algorithm now tries to make a hypothesis from the existing data, in this case, to distinguish cat videos from other videos.

It is clear: The boom of the AI is no fluke, the technology is now widely used and the more we use it, the better the AI software is by training data. Google has been calling itself an “AI first” company for some time.

Deep Learning relies on a multitude of artificial neurons, which are arranged in numerous layers and filter out relevant information more and more. Not everywhere where AI or Machine Learning is written, however, is currently artificial intelligence in the strict sense in it. The reason why deep learning has become a useful method in the field of artificial intelligence is the fact that the hardware has become fast enough for many layers of artificial neural networks.

Machine learning, often deep learning, is currently used primarily in speech recognition, image recognition and speech assistants such as Alexa, Siri or Google Now but also in software solutions for autonomous driving.

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Innovation

Rise of An African-Induced Innovation – Solar Powered Car in Kenya

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Kenyan student, Samuel Karumbo, has graced Kenya and Africa with an amazing solar-powered car.

Before, the history of science and technology in Africa received little or no attention compared to other regions in the world. It had become a common thing to read mostly negative things about Africa. Today, however, that conception is fast changing as African countries like Kenya, Nigeria, Ghana, South Africa are fast making their way in the technology industry.

There have been an increased number of great technological developments in Africa from startups to inventions. Though most of these innovations are emerging from the thriving of tech hubs popping up across Africa, most of the technology transforming the continent comes from elsewhere.

However, Africans can still boost of progress in the Technology industry. It is in Africa that we will hear of inventions like; Ugandan Engineers Mamaope jacket that can detect pneumonia, Cameroon’s Arthur Zang’s tablet that monitors your heartSteamaco electricity grid in Kenya that can provide electricity for a whole village.

Also, we are talking of the latest developer of a solar powered car that is making rounds in Kenya. The solar powered car was developed by a 30 year old Kenyan student Samuel Karumbo. His childhood desire to own a less expensive car motivated him to come out with this innovation – transforming dream to reality

Benefits of a Solar Powered Car

The invention of a solar powered car is practical in a continent characterized by very hot climatic conditions. The car uses energy from the conversion of the sun’s energy into electricity through the exchange of photons and electrons inside the solar cell. Thus, the availability of sun at all time during the day, gives everyone the opportunity to have this car without cost for maintenance.

A solar powered car has many benefits that make it fit for the African environment. Some of them are;

  •      It produces no harmful emission in the air when it is running
  •      Its motor is much more efficient and quiet than the gasoline engine.
  •      The motor does not produce vibrations and it is generally smaller and  maintenance free.
  •      The car is much lighter.
  •      The car does not require refueling and oil changes since it uses the sun to get its energy
  •      He said the vehicle depends heavily on gravity when on descend.
  •      The motor acts as a generator for producing energy for later use.
  •      The car can cover about 50 km in a day.
  •      This hybrid car can also be used to charge phones or provide home lighting.

In other to achieve a complete dream, Karumbo is appealing for financial support for his project.

There is always this problem of funding that always pops up. And this has been a major barrier for young inventors, creators and entrepreneurs in Africa. Unfortunately or fortunately, most funds for African technology do not come from philanthropists. They come from foreign investors who always expect returns.

Challenges faced by Young African Inventors and Creators

Access to capital

Young inventors and startups in Africa face a severe lack of capital that would allow them to grow their businesses beyond local, informal markets.

Physical infrastructure

According to Ndubuisi Ekekwe, founder of the African Institute of Technology, while rapid advances in internet penetration are improving the innovation atmosphere, basic components of infrastructure like power, roads, post offices are still severely lacking. Investments in these basic building blocks will allow businesses to expand more rapidly and make their operations more efficient.

He added that many potential foreign investors are scared away by corrupt public institutions and the seeming inability or unwillingness of African legal systems to enforce property rights and IP protection.

Most African inventions are geared towards solving the problems faced by Africans. For example, Dougbeh Chris Nyan born in Liberia  worked with Scientists both in Liberia and America to invent a battery-powered device that provides a quick and cheap test for seven different infections at a time. It is generally common to find a person in Africa diagnosed of different diseases, thus making the invention Africa-induced.

African governments should encourage young creators and inventors to bring inventions that will come to solve an African problem. This will lead to Africa’s rise in Technology in the nearest future.

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