In-depth: Artificial Intelligence 2019

Statista Digital Market Outlook - Trend Report

Künstliche Intelligenz ist lange keine Zukunftsmusik mehr, sie kommt bereits in vielen Bereichen zum Einsatz, zum Beispiel im produzierenden Gewerbe, im Finanzwesen, in der Unterhaltungsindustrie und im Bildungswesen. Die Automatisierung mit Hilfe von KI hilft nicht nur, Kosten zu reduzieren, auch ein deutliches Produktivitätswachstum wird dadurch erwartet.




Was ist enthalten?
  • Künstliche Intelligenz: Definition und Entstehungsgeschichte
  • Umsatzpotenzial
  • Technologie
  • Trends und Treiber
  • Anwendung von KI in verschiedenen Branchen
  • Start-ups: Finanzierungen und M&A
  • Wettbewerbslandschaft: Amazon, Apple, Baidu, ebay, Facebook, Google, IBM, Microsoft, Salesforce, UBER

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Artificial Intelligence (AI) essentially refers to computing technologies that are inspired by the ways people use their brains and nervous systems to reason and make decisions, but typically operate quite differently. As a concept AI has been the source of inspiration for many science fiction writers and futurologists for over a century. Today, advancements in computing and big data have made it a reality with machines now being deployed at a large scale across industries. The application of AI technologies is driving growth at individual, business and economic levels. In fact AI has started to outperform human beings in a range of work activities, including ones requiring cognitive abilities.

The current AI ecosystem consists of machine learning, robotics and artificial neural networks (ANNs). In Machine Learning, programs learn from existing data and apply this knowledge to new data or use it to predict data. The field of robotics is concerned with developing and training robots. Usually, the ability for a robot to interact with people and the world follows general and predictable ways. However, current efforts also revolve around using deep learning to train robots to manipulate situations and act with a certain degree of self awareness. ANNs are built to mimic the working of a human brain. Connected units (artificial neurons) are organized in layers to process information.

Over the last few decades the evolution of AI has mostly revolved around the advancement of linguistic, mathematical, and logical reasoning abilities. However, the next wave of AI advancements is towards developing emotional intelligence. At the same time, another technique by Google’s deep mind called sequential learning is enabling AIs to learn multiple skills. Deep learning, over the last few years, has made vast improvements in enabling machines to comprehend the physical world to a certain level and is used across industries for various tasks. Among the leading economies, China is investing lots of research and money into AI in recent years.

One of the major factors driving the current wave of AI growth is the rapid increase in corporate venture capital (CVC) investment in AI start-ups. On the technology front, rapid advancements in computing power drives the industry to the next level. Similarly, open source platforms promote and enable collaborative learning which is conducive for the growth of AI. The current wave of growth in the AI industry is as much about the abundant availability of big data as it is about the software and hardware. The amount of big data being generated by today’s increasingly digitized economy is growing at a rate of 40% each year and is expected to reach 44 zettabytes by 2020. This growth in big data drives the improvement of AI algorithms.

AI solutions are increasingly being customized to serve the needs across multiple industries such as automotive, healthcare, education, finance, entertainment, and others. In the automotive sector, AI is primarily used to power autonomous cars, with these systems expected to become standard in new vehicles over the medium to long term. In healthcare industry, developments in the field of AI and machine learning have not only accelerated the pace of innovation in the industry but are also changing entire operating models. In addition, AI is being tested at providing customized learning programs for each student in education industry, whereas in finance industry, AI wealth management solutions offer higher personalization.

With the rise of AI, more and more start-ups venture into the space. Most worked in the field of Machine Learning algorithms, followed by natural language processing. The annual global funding of AI start-ups experienced a high growth of almost 70% average growth rates from US$0.6 billion in 2012 to US$4.9 billion in 2016. The corresponding number of deals grew by 47% in the same timeframe from 151 in 2012 to 703 in 2016. In terms of M&A, the number of deals jumped up by 38% in 2017. Looking at the most recent M&A deals, big tech companies like Google, Apple, Amazon, Microsoft, IBM or Facebook appear often as the acquirer. But also Chinese tech giants like Baidu or rising stars in the start-up world, like Twitter, Uber or Spotify acquire AI companies.

Companies from various industries are currently developing AI and related applications. Google, IBM and Microsoft are leading AI innovations in the IT industry, whereas Amazon and eBay are investing in AI to improve their ecommerce platform and ridesharing company UBER is using AI on autonomous driving, food deliveries and mapping research. Collaborative development is on the rise and leading companies such as Amazon, Apple, Facebook, Google/DeepMind, IBM, and Microsoft are currently working in partnership towards developing AI applications. Acquisition of small scale AI companies by tech giants like Apple, IBM and Microsoft in relevant field is in the rise towards decreasing the learning curve. Other leading companies include Baidu, Facebook and Salesforce.

  • Sprache: Englisch
  • Veröffentlicht: Februar 2019
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