Real Words or Buzzwords: Exponential Technology. What are exponential technologies, and how will they shape the future? Our guest in this episode is Niki Skene. Niki  is a former TEDxAmbassador and Faculty Coach at Singularity University. Since 2015 he has been working intensively on the forces involved in the exponential development of technologies and, as a result, the disruption of sectors such as retail, automotive, finance, health, food and energy through so-called "exponential organizations".

Episode 9 of the Asigmo Data Science Podcast is out now and we are thrilled to welcome our guest Clemens Wasner! Clemens is one of the leading minds in the DACH region in the field of Applied Artificial Intelligence and also the founder of AI Austria, an independent think tank with the goal of establishing Austria as a pioneer in the field of Artificial Intelligence. Last but not least, he is the Vice President of the newly founded association Adra. Adra, as of May 2021, aims to invest 2.6 billion euros together with the EU Commission, in organizations working in the field of AI.

Virtual reality - the reality that exists in the form of bits and bytes activated by electromagnetic energy and made powerful by IT and the Internet - has changed the way we relate to o­ne another. It has also revolutionized economics and business. In today’s episode, our guest is Sergi Sergiev. He has 10+ years of experience in data science, machine learning, and data mining, especially in IoT, Finance, Retail and the eCommerce sector; where he works in the areas of deep-learning, robotics and time series. Now he focuses on projects which apply Data Science for retailers to be more effective and customer-centric.

Aleksandar Linc-Djordjevic is the managing director at #Data Science Conference, one of the most successful conferences on data science in the world spanning six continents. He is also the president of the Institute of Contemporary Science. The institute is a non-government institution, operating in Serbia consisting of experienced and motivated individuals, aiming to grow a community of like-minded people. 

In German there is a saying that goes: ''Geteilte Freude ist doppelte Freude, geteilter Schmerz ist halber Schmerz.'' This translates to: ''shared joy is double joy, shared sorrow is halved sorrow''. Susanne encompasses this saying with her willingness to help women in their careers and has dedicated parts of her career to doing so. She is there for them, through their highs and lows, and sees a future where there is room for all to succeed. Susanna is an Azure Infrastructure Specialist, at Microsoft. She is also the author of Women of colour in tech. She has run marathons and is an avid game nerd.

Our guest today is Yudan Lin the founder of Unexpected Data. By creating unexpected and inspirational content, Unexpected Data supports you in understanding what it takes to live in the world of Data Science, Machine Learning and Artificial Intelligence. Taboos are especially investigated: from sex, justice, and the digital fight for our attention. By sharing career journeys, challenges had, lessons learnt, Unexpected Data highlights people and initiatives who support the common good. 

“It was a bright cold day in April, and the clocks were striking thirteen.” Today’s episode will not be a deep dive into Orwell's classic novel 1984, rather an insight into what perhaps might sound too much like a dystopian future. With the launch of the documentary Coded Bias, the conversation of all-powerful artificial intelligence systems, and the entities that deploy them is becoming more difficult to navigate. On today’s episode, Dr. Rania Wazir joins us for a discussion on the incremental steps that are being taken to regulate the field.

In today’s episode, our guest Ramin Hasani is here to talk about data quilty and touch on the world of Robotics. He is a machine learning scientist at the Computer Science and Artificial Intelligence Lab, at MIT. He has completed his PhD studies (with distinction) in Computer Science, at TU Wien, Austria. His research focuses on developing interpretable deep learning and decision-making algorithms.