Machine learning expert Alan Edelman expressed his keenness to train Bangladeshi young programmers in developing new technologies through Artificial Intelligence.

Alan Stuart Edelman, the father of the programming language Julia, is a Professor of Applied Mathematics at the Massachusetts Institute of Technology.

Edelman made a keynote presentation at a session styled ‘AI and Machine Learning’ at BASIS SoftExpo at Bangabandhu International Conference Centre (BICC) in Dhaka.

Prof Edelman said, “The dependency on Google is not good for the young developers. They should focus on developing service and products from own innovations. Julia will support the developers to implement their innovation in programming.”

Prof Edelman focused on comparative feature between Googles’ TensorFlow and Julia.

He said Bangladeshi youth are very talented. They would show excellence if they will be given proper mentorship and training program. MIT and Julia Computing will support local organizations in this regard.”

Prof. Alan Edelman described how machine learning and artificial intelligence will evolve in the next few years and how they will create the impact on the lives of people. 

Post Telecom and Information Technology Minister Mustafa Jabbar was the chief guest on the occasion moderated by BASIS former President Habibullah N Karim.

University of Asia Pacific Vice-Chancellor Prof Jamilur Reza Chowdhury, Mascagni senior expert Prof Samdani spoke at the panel discussion while BASIS President Syed Almas Kabir made an address of welcome.

Mustafa Jabbar said the Dhaka trip of the Father of Machine Learning Prof Alen is a milestone for the technology sector in the country. 

“Bangladesh experienced a tremendous growth in the ICT industry in the participation of people from all walks of lives. Youths lead the innovations here. They have interest in new technologies like Machine Learning,” Mustafa Jabbar said.

Prof Jamilur Reza Chowdhury said the Machine Learning is not a new concept in the world though there is started some initiatives through artificial intelligence in Bangladesh recently. We should focus on developing programming language in Bangla so that the machine learning would easier,”

Mascagni official Dr Samdani said Machine learning is the frontier of future technologies.

BASIS President Syed Almas Kabir informed the session that BASIS has engaged Prof Eledman as an advisor for the development of the technology sector in Bangladesh.

However, Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning. Machine learning can also be unsupervised and be used to learn and establish baseline behavioural profiles for various entities and then used to find meaningful anomalies.

Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data.

While talking about Machine Learning we can’t ignore Machine Intelligence (MI) also known as Artificial Intelligence (AI) which is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals.

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip "AI is whatever hasn't been done yet. 

For instance, optical character recognition is frequently excluded from "artificial intelligence", has become a routine technology. Capabilities generally classified as AI as of 2017 include successfully understanding human speech, competing at a high level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data, including images and videos.

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