Jrcb4 The Impact of Artificial Intelligence on Learning final

Key skills 
 
 
Ability to 
understand 
spoken messages 
Initiate, sustain 
and conclude 
conversations 
Read, understand 
and drafts texts 
Real time 
translation 
Semantic search 
Speech-to-text 
Grammar and 
spelling 
Rhetoric impact 
Online dictionaries 
Culture-aware 
machine 
translation 
Sentiment 
analysis 
Personalised 
messaging 

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mergers and acquisitions were about 21.8 billion USD worldwide, and start-ups without 
revenue fetched prices that amount to $5-10 million per AI expert.
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As highly-qualified 
experts can now earn very high annual salaries, universities will have great difficulties in 
finding competent teachers for this specialty. Some practical implementation work can be 
done by relative novices using openly available development tools and learning materials, 
but the development of mission-critical applications requires quite advanced skills.
60
One rather immediate result of this situation is that high-level AI talent and compute 
capability will probably be provided as a service. This would perhaps mean that there is 
not going to be massive needs for high-level AI competences. Due to the high wage 
differentials, many current students of statistics, mathematics, mathematical physics, 
computer and chip design, and perhaps neurophysiology may, however, reconsider their 
career paths and find new identities as experts in AI. Moreover, in the current informal 
learning environment, easy access to state-of-the-art technologies and research could 
also mean that high-level AI competences may emerge from unexpected places, for 
example, through open software and open hardware communities. 
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Data from PitchBook, quoted in (Bass 2018). 
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One key bottleneck for neural AI is its energy consumption. As a result, many chip designers are now 
trying to develop semiconductor chips that can be used for specific AI applications, see e.g. (Salvo 2018). 

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