Study Machine Learning / Deep Learning

Expert: Simon Decker

Length: 60 pages

Format: PDF, Download

The current IDG study Machine Learning / Deep Learning 2018 by IDG Research Services examines the importance of AI for companies.

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The pressure to innovate is on the departments

The "BILD-Zeitung" trembles with reference to Tesla boss Elon Musk about "the greatest risk for civilisation", the news magazine "Spiegel" warns that God does not need a teacher - artificial intelligence (AI) is making headlines in the press. In contrast, the experts from various IT providers who met in the COMPUTERWOCHE editorial office in mid-December took a more objective view. The following conclusions emerged from their lively discussion:

  1. The acceptance of AI / ML does not depend on the size of the company
  2. Many companies do not know where to start with AI / ML
  3. Companies discover process mining
  4. Even algorithms have limits
  5. AI leads to the battle of the decision-makers
  6. AI and ML only work according to an interdisciplinary team approach
  7. Germany has a good starting position, but needs a cultural change

In order to exploit the potential of artificial intelligence and machine learning, Germany needs a cultural change. Not easy in a country where many decision-makers still have reservations about new ideas.

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Table of contents

Management summary

The key findings at a glance
The Key Findings

  1. Artificial intelligence and machine learning are high on the agenda
  2. Larger companies in particular are already using AI applications
  3. Technology is available - there is a need to catch up in terms of know-how
  4. Speech recognition, assistance systems and planning tools are most used AI methods
  5. Machine learning should primarily optimise internal processes
  6. Companies classify cyber attacks using AI systems as a risk
  7. Benefits of Artificial Intelligence and Machine Learning: The winner is - the IT department!
  8. Artificial intelligence and machine learning are disruptive technologies
  9. Machine Learning stays in-house
  10. Price, trust and good cooperation determine the choice of service provider for machine learning

Further study results

    1. Machine learning is primarily considered for use in logistics and manufacturing
    2. Majority of companies can envisage storing AI data in the cloud
    3. Selective use of AI and ML dominates
    4. Majority of IT platforms support artificial intelligence and machine learning
    5. Open source dominates machine learning modules
    6. Companies source machine learning solutions from different sources
    7. Scalability, operating costs and price are the most important criteria of a machine learning solution
    8. CIOs and IT managers "wear the hat" when it comes to machine learning
    9. Transaction and address data are used most frequently
    10. High demand for experience and best practices

A look into the future - Machine learning and AI are top issues for all companies

Simon Decker - New Business Development

Your expert

Simon Decker | New Business Development | Alexander Thamm GmbH

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