HDM Artificial Intelligence

From platform to sensors

HDM Group Artificial Intelligence

Artificial Intelligence is the branch of computer science that studies the development of hardware and software systems with typical human capabilities and capable of autonomously pursuing a defined purpose by making decisions that, until then, were usually entrusted to human beings.
The typical skills of the human being relate specifically to understanding and processing of natural language (NLP – Natural Language Processing) and images (Image Processing),
learning, reasoning and planning skills and interaction with people, machines and the environment.
Unlike traditional software, an AI system is not based on programming (i.e. on the work of developers who write the operating code of the system) but on learning techniques: that is, algorithms are defined that process a huge amount of data from which it is the system itself that must derive its understanding and reasoning abilities.

AI & fashion

Algorithms reshape the shopping experience and intercept less predictable trends!

Machine Learning

In the fashion sector, data processing capacity is essential in sales forecasting, production planning, merchandising and stock management.
Thanks to machine learning techniques, companies can identify patterns in data and build models capable of predicting future results.
This helps to create a more flexible and faster supply chain and manage inventory in an automated and intelligent way.

ChatBot

AI chatbots, also called “intelligent assistants”, represent a perfect case study of the use of artificial intelligence in the fashion sector. Chatbots, designed to mimic the behavior of customer care workers, can support the customer in many ways.
For example, they can accompany product research, verification of size and availability, access to information on shipping and returns.

Immage processing and face recognition

The AI ​​is capable of analyzing and identifying a coherent and complete set of attributes of different images, in order to provide recommendations on the product most relevant to the customer. This significantly reduces the time spent in product categorization, while creating upsale opportunities.
    
   
    

AI & Industry

Big data and AI offer Industry 4.0 a huge boost to market growth and development!

Predictive Analytics

The basic idea is to exploit the data generated before, during and after the production process to obtain information on product quality or forecasts of future failures.
They use predictive analysis to identify defective transmissions, predict problems and detect anomalies in the event of engine failure. All these cases concern models based on machine learning and in each of them, the models are able to provide highly precise results even with minimal training data.
             
          
        

Predictive maintenance

 The premise of predictive maintenance is to use the production line data to predict when production equipment is likely to fail and then take action to repair or replace equipment before this happens. Although not a perfect analogy, one could think of the relationship between predictive maintenance and predictive analysis similar to that between quality assurance and quality control: the first focuses on the process, the second on the product.
However, as with predictive analysis, predictive maintenance depends on the ability to synthesize information from huge datasets, often with minimal training data.

Industrial Robotics

Collaborative robots, or cobots, are designed specifically to work with humans.
Adding AI to cobots allows them to be deployed faster, monitor their workspaces to change conditions and adapt to them. As for industrial robots more generally, artificial intelligence can improve the accuracy and reliability of robots, as well as allow more advanced forms of mobility. Perhaps above all, artificial intelligence can play a key role in reducing the programming and engineering efforts needed to create and implement industrial automation.

Computer Vision

Artificial intelligence has two obvious advantages over humans when it comes to visual inspection: speed and precision. An artificial vision system that uses AI-enhanced and more sensitive cameras than the naked eye can identify microscopic defects that human inspectors could lose at a rate they cannot hope to match.
   

   
    

Inventory Management

There are a myriad of ways in which AI can reduce inventory management costs, from optimizing what’s kept on hand to anticipating gaps before they occur.
Again, it’s the ability to gather staggering amounts of data and find the hidden patterns inside that make AI so natural for this application.

AI & Social Monitoring & Social Security

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Social Creation and Management

Traditional marketing automation tools help simplify social media planning and monitoring. But artificial intelligence tools push it further.
There are tools to automatically generate social media content through channels, to automatically include hashtags and shortened links. There are also tools to automatically schedule these shares in bulk. Overall, AI is now able to handle some types of social media creation and management in minutes.

Social Insight

Artificial intelligence is used to analyze social media posts on a large scale, understand what is said in them, then extract insights based on that information.
Properly applied, this data allows AI social media tools to help you track your global brand equity, find emerging consumer trends, find new audiences to target, keep your brand reputation under control, and identify new avenues. promising for the promotion of social media.

Social Media Advertising

Artificial intelligence tools exist today that will actually write Facebook and Instagram ads for you. The ads are optimized per click and, thanks to the ability of the AI, to predict on a large scale which language will improve the results.

Social Security

By virtue of safety rules AI is increasingly used to study the movement, the behavior of crowds of people and the creation of human gatherings   
   
    

AI & Healthcare

Its diffusion finds logic and support in all the algorithms studied for genetics, the study of tumors, the study of the evolution of degenerative diseases.


Wearable devices for studying biometric data


Wearable devices for studying posture

Wearable devices for remote monitoring
of the patient

AI & Bank, Finance and Insurance

Managin Finance

Looking to the future we can see AI helping us manage our finances. PFM (personal financial management) is one of the recent developments in portfolio management based on artificial intelligence. Artificial intelligence can be used to create algorithms to help consumers make smart decisions about their money when they are about to spend. The idea behind the portfolio is very simple: accumulate all the data from your web figure and create your spending chart. From a small-scale investment to a large-scale investment, AI is committed to being a valuable adviser and personal defender for managing finances.
    

Fraud Detection and Management

Each company aims to reduce the risk conditions surrounding it. Banks and financial institutions take fraud very seriously. You can use past spending behavior on different transaction tools to highlight strange behavior, such as using a card from another country only a few hours after it has been used elsewhere or an attempt to withdraw an unusual amount of money for the account in question. Another excellent feature of AI detection is that the system has no qualms about learning. If he raises a red flag for a regular transaction and a human being corrects it, the system can learn from experience and make even more sophisticated decisions about what can be considered fraud and what cannot.

Financial Advisory System

When the pressure increases on financial institutions to reduce their commission rates on individual investments, machines can do what humans don’t work for a single checking account. Another evolving field is bionic consulting, which combines machine calculations and human intuition to provide options that are much more efficient than those provided by their individual components. Collaboration between man and machine is the key to success. An excellent balance and the ability to consider AI as a component of decision making as important as the human point of view is the future of financial decision making.

Risk Assessment

AI and ML are taking the place of a human analyst very quickly since the inaccuracies that are involved in human selection can cost millions. Artificial intelligence is based on machine learning that learns over time, less chance of error and analysis of large volumes of data. Artificial intelligence has established automation in areas that require intelligent analytics and a clear view.
    
   
     
   

Trading

Trading and investments depend on the ability to accurately predict the future. The machines are fantastic in that they can process a large amount of data in a short time. Machines can also be taught to observe patterns in past data and predict how these patterns might repeat themselves in the future. Although anomalies such as the financial crisis of 2008 exist in the data, it is possible to teach a machine to study the data to find “triggers” for these anomalies and plan interventions also in future forecasts. In addition, depending on the individual’s risk appetite, artificial intelligence can suggest portfolio solutions to meet each person’s demand. So a person with a high risk appetite can rely on artificial intelligence to decide when to buy, hold and sell shares. Those with a lower risk appetite can receive alerts when the market should fall and can therefore decide whether to stay on the investment position or exit.