13 Aug
2018

What are the Top AI Trends of 2018?

Hardware manufacturing company Lanner put together a list of the most exciting topics in AI in 2018. Think: Decision-making in real-time, quality, predictive ordering and smart opportunity assessment.

Artificial Intelligence
Industry 4.0
Smart Factory
IIoT
Quelles sont les principales tendances en matière d'IA en 2018 ?

Artificial Intelligence (AI) is a complicated and popular topic across multiple industries as innovations throughout the field make leaps and strides. The team at hardware manufacturing company Lanner put together a list of what the most exciting topics in AI are in 2018. See the list below and read more about some key benefits of AI to manufacturers.

Lanner's Top 10 AI Trends in 2018:


1. Machine learning: Machine learning (ML) is the branch of artificial intelligence that focuses on equipping machines with the ability to learn without human intervention or programming.

2. Deep neural networks & deep learning theory: Deep neural networks (DNNs) are artificial neural networks that contain multiple hidden layers between their input and output layers, occasionally referred to as “stacked” neural networks. Deep learning is the branch of machine learning that deals with learning data representations instead of task specific algorithms.

3. Machine vision: With artificial intelligence, machine vision systems will be equipped with the ability to learn from their experiences. 

4. Edge AI: One of the most interesting differences between human brains and artificial intelligence tools is the location the “processing” takes place. With AI, the majority of processing and analysis is done in cloud servers rather than on edge devices due to the large data and computing power they require.

5. Customer interaction: According to Gartner, over 80% of all customer interactions will be handles by an AI by the year 2020.

 

 

 

 

6. Big data & analytics: AI’s ability to manage and interpret vast volumes of data much quicker and much more accurately than human beings is what sets it aside as a potentially revolutionary technology. 

7. Natural language recognition: One of the biggest challenges for artificial intelligence technologies has been interpreting intent from the natural language human beings use.

8. The Internet of Intelligent Things: The widespread adoption of AI technologies alongside the continuing expansion of the Internet of Things will begin to build upon the technological foundations laid by previous associated technologies. 

9. AI as a workplace norm: With a growing product base and many more innovations lingering on the horizon, 2018 could also be the year artificial intelligence becomes an everyday technology for a large number of businesses and organizations. 

10. Ethics & responsibility: As the computational power and responsibilities given to AI grow, more attention will need to be given to the ethical considerations of artificial intelligence.

 

Click to enlarge

AI Trends for 2018

 

Infographic: lanner-america.com

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
5
Juin 2018

Visualize the uses of AI and analytics with this interactive tool

English
4
Avril 2018

McKinsey - An executive’s guide to AI

English
9
Mai 2018

Manufacturing Brands That Make Use of Artificial Intelligence

English

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Juin 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French
27
Juin 2023

Going Beyond the Numbers: Maximizing ROI with Data Analytics in Manufacturing

Technology has given rise to data – reams of it. In fact, in today’s digital environment there is more data available to manufacturers than in all of history combined. Yet for many manufacturers big data is a big problem.

English