artificial-intelligence

Have you come across the term “wearable technology”? 

 

While it may sound futuristic, it has become an integral part of our daily lives, whether in health, leisure, or work. 

Smartwatches were the gateway to a broader ecosystem of wearable devices designed to act as constant companions to our bodies. These include health-monitoring bracelets, smart rings, and fitness trackers, all aimed at tracking vital signs in real time. Users can monitor their cardiovascular health during workouts and daily activities with ease. 

Many wearables also analyse sleep patterns, offering insights into sleep quality by measuring duration, sleep stages (light, deep, and REM), and disturbances. This data helps users make informed adjustments to improve rest. Additionally, blood pressure monitoring features support the management of hypertension and overall heart health. 

Equipped with accelerometers and gyroscopes, these devices accurately track physical activity—counting steps, estimating calories burned, and monitoring various types of exercise. Built-in GPS functionality allows users to map routes and track distances during outdoor activities such as running, cycling, or hiking. 

Modern wearables also include stress management tools, such as guided breathing exercises and mindfulness reminders. Hydration and movement alerts further encourage healthy daily habits. 

 

Core Functions of Wearable Technology 

 

• Fitness and Wellness: Ideal for fitness enthusiasts, wearables offer features like GPS tracking, step counting, calorie monitoring, and personalised training programmes. 

• Entertainment and Personalisation: Devices such as VR headsets deliver immersive experiences, while smartwatches allow users to customise watch faces and settings. 

• Safety and Emergency Support: Some wearables detect falls or unusual activity and can alert emergency contacts, offering reassurance to users and their families. 

• Accessibility and Convenience: Smartwatches enable users to check messages, emails, and make calls without reaching for their phones—streamlining daily tasks. 

• Productivity Enhancement: With instant access to notifications and key information, users can stay focused without frequent smartphone interruptions. 

 

Examples of Wearable Technology 

 

• Smart Jewellery: Includes smart rings, glasses, wristbands, and watches. These compact devices connect to smartphone apps for easy interaction and data tracking. 

• Fitness Trackers: Typically worn on the wrist, head, or chest, these devices monitor physical activity and vital signs, syncing with apps for data analysis and goal tracking. 

• Augmented Reality (AR) Headsets: Overlay digital content onto the real world, enabling users to interact with both physical and virtual environments. 

• Smart Clothing: Embedded with sensors, smart garments can monitor health metrics, interact with devices, and adapt to environmental or user-specific conditions. 

• Wearable Virtual Assistants: Devices like Bee and Omi attach to clothing and respond to voice or gesture commands. They offer features such as translation, fitness tracking, and task automation. 

• AI Hearing Aids: These intelligent devices filter background noise and adjust automatically to the user’s environment. Many also support audio streaming, translation, and fitness tracking. 

 

The Future of Wearable Technology 

 

As public awareness of health and wellness grows, wearable technology has evolved into a vital tool for personal health management. These devices empower users to set and achieve fitness goals, gain real-time health insights, and adopt healthier lifestyles. 

With ongoing advancements, wearable technology will continue to shape the future, becoming more secure, efficient, and accessible for all. 

 

Key Takeaways 

 

• Wearable technology includes devices such as smartwatches, fitness bands, and smart rings that support users in managing their health and daily routines. 

• These devices enable real-time monitoring of health metrics like heart rate, sleep patterns, and blood pressure, aiding cardiovascular health and sleep quality. 

• Wearables offer a wide range of features, including fitness tracking, safety alerts, and stress management tools, supporting both physical and mental wellbeing. 

• Examples include smart jewellery, fitness trackers, augmented reality headsets, smart clothing, wearable virtual assistants, and AI-powered hearing aids. 

• Once a novelty, wearable technology has become an essential tool for achieving fitness goals and maintaining a balanced lifestyle. 

In recent years, the intersection of technology, medicine, and healthcare has created an environment ripe for innovations that transform how we manage our health and interact with medical services. Over time, the healthcare sector has increasingly absorbed technological advances and applied them within the field – and this relationship has opened the way for a powerful strategy known as cross-industry collaboration, where different sectors come together to share knowledge, experience, and technology, resulting in two distinct strands: HealthTech and MedTech.

 

What is meant by cross-industry?

In many cases, an innovative solution developed in one industry can serve as an effective remedy for challenges faced in another sector. This is the essence of the cross-industry approach: a strategic method that encourages the exploration of hybrid solutions by fostering collaboration between companies from diverse fields.

By leveraging unique insights and technologies from various industries, this approach aims to catalyse innovation, accelerate growth, and uncover a wide range of tailored solutions. These collaborations can create mutually beneficial opportunities, driving value for all parties involved while pushing the boundaries of what’s possible in their respective domains.

 

MedTech & HealthTech

According to the World Health Organisation (WHO), healthcare can be defined as «the application of organised knowledge and skills in the form of devices, medicines, vaccines, procedures, and systems developed to address health problems and enhance the quality of lives.”

Even with the terms HealthTech and MedTech often used synonymously, they serve distinct purposes in the healthcare ecosystem. HealthTech solutions are more concerned with leveraging technology to augment the overall healthcare experience for patients,  including innovations that enhance telehealth platforms, mobile health applications, and data analysis tools that allow patients to monitor their health in real time, thereby empowering them to take an active role in their health journey.

MedTech solutions, on the other hand, are focused on advancements in medical treatment and diagnostic processes. This encompasses improvements in diagnostic efficiency and accuracy, as well as the design and development of state-of-the-art medical devices, surgical tools, and patient monitoring systems. MedTech innovations particularly cater to healthcare professionals by providing them with the tools necessary for effective patient diagnosis and treatment.

A simplified distinction can thus be established: MedTech focuses on the development and application of technologies aimed at managing healthcare and enhancing diagnostic capabilities, while HealthTech prioritises the creation of tools and systems that enhance the patient experience and support consumer engagement in their own health management.

 

Examples of technologies in the health sector and their uses

With these differences established, we can now cite some examples illustrating the impact of various technologies in the health sector that have affected – and revolutionised – medical practices and the general day-to-day lives of patients around the world:

1. Neurotechnology

Neurotechnology has existed in the medical realm for some time, yet continues to progress in astonishing ways. It includes both implantable and external devices, covering all elements designed to comprehend brain functions. With the aid of these technologies, we can visualise the workings of the human brain and control, repair, or enhance its operations.

Neurotechnology components can include computers, electrodes, and other devices that interpret electrical impulses. At this moment in time, neurotechnology is utilised for various processes such as:

• Brain imaging: capturing magnetic fields generated by the brain’s electrical activities
• Neurostimulation: activating the brain and nervous system to influence brain functions
• Neuro-devices: devices employed to monitor and regulate brain activities, using implants

2. Telemedicine and telehealth

Telemedicine has grown rapidly in recent years, and many health systems now use it. It benefits both patients and healthcare workers: for patients, telemedicine offers convenience, making it easier to access care, save money, avoid travel expenses – and the risk of missing work for in-person visits. For healthcare professionals, it lowers costs and limits their exposure to illness, while also allowing them to see more patients with greater flexibility.

3. Wearable technology

Wearable technology, commonly referred to as wearable tech, encompasses a range of devices designed to track various health metrics, such as monitoring the heart rate in real-time, analysing sleep patterns to assess sleep quality, measuring blood pressure, and even tracking physical activity levels such as the number of steps taken and calories burned. On top of that, many models incorporate features like GPS tracking for outdoor activities, stress management tools, and reminders for hydration and movement. As health awareness grows, these devices have morphed from mere novelties into essential tools for many, aiding users in achieving their fitness goals and maintaining a healthy lifestyle.

4. Robotics in surgery

These advanced technologies support surgeons in performing minimally invasive procedures with remarkable precision and agility. They not only simplify straightforward surgical procedures, but also enable the performance of more intricate operations, thus enhancing the overall effectiveness and outcomes of medical interventions. By providing a steady hand and clear visual field, they permit surgeons to navigate complex anatomical structures with confidence and skill.

As these technologies continue to evolve, collaboration across industries will become ever more crucial. This synergy will not only drive innovation but also create a more efficient, personalised, and patient-centric healthcare ecosystem. The success of this collaborative approach can lead to a future where healthcare is more accessible, effective, and tailored to individual needs, promoting lasting well-being for all.

 

Key Takeaways

 

• Cross-industry collaboration is a strategy that fosters the exchange of knowledge and technologies, enabling the exploration of hybrid solutions that can solve challenges across industries.
• Examples of technologies that have revolutionised healthcare include neurotechnology, telemedicine, wearable technology, and surgical robotics, each contributing in distinct ways to the care provided and its management.
• Cross-sector collaboration can create a more accessible and efficient healthcare system, enabling patients to take an active role in their health and providing professionals with the necessary tools for effective diagnosis and treatment.
• The synergy between technology and healthcare promises a future where care is more personalised and tailored to individual needs, promoting lasting well-being for all.

In a dynamic and competitive world, access to information is crucial for business success. Companies that want to stand out need to go beyond simply collecting data by turning them into actionable insights that drive the growth and profitability of their business. It is in this context that business intelligence (BI) becomes an essential tool. 

 

 

What is Business Intelligence? 

Business intelligence is a set of processes, technologies and tools that transform raw data into strategic information to help companies make assertive decisions. 

By collecting, organising, analysing and visualising data from various sources, BI provides managers with a complete and comprehensive view of their organisation’s performance, allowing them to identify opportunities, optimise processes, reduce costs, increase efficiency and make smarter decisions to achieve strategic objectives. This article provides an introduction to BI, but it can only cover the tip of the iceberg. 

Traditional business intelligence emerged in the 1960s as a system for sharing information within organisations. In the 1980s it developed alongside computer models to aid decision-making and transform data into information. Modern BI solutions prioritise governed data on reliable platforms, the autonomy of business users, and fast access to information. 

 

What are the Advantages of Business Intelligence for Business? 

More and more people generate and/or create data every day, making the latter ever more diverse and unstructured. 

In this sense, and once we know what business intelligence is, a careful use of the BI approach can help any organisation gain a competitive advantage by reducing the time and effort needed to acquire, integrate, distribute, analyse and respond to new data. 

The better a company’s data processing is, the more it will benefit from BI. In fact, the leaders in data processing exert enormous pressure on all competitors who fail to recognise the potential of their data in good time. Late adopters are forced to accelerate their analytical ambitions to keep up with competitors and new market entrants. 

BI is thus right at the core of all data-driven companies, making it the epicentre of their transformation. The implementation of new BI tools is aimed at boosting an organisation’s impact and rendering it more efficient. But with the right BI technology, you can also gain a number of additional benefits.

These include: 

• Higher efficiency of operational processes 

• Insights into customer behaviour and buying patterns 

• Precise control of sales, marketing and the financial performance 

• Clear reference points based on historical and current data 

• Instant alerts on data anomalies and customer problems 

• Analyses that can be shared in real time between various departments 

In the past, business intelligence tools were mainly used by data analysts and IT users. But nowadays, BI platforms make business intelligence available to everyone, from executives to operations teams. 

To this end, FI Group has launched a new digital space that integrates several applications in a single platform. This way our clients can benefit from greater transparency about the services they develop with us. 

For the future, it is vital that the people and companies around us adapt and use new digital resources to reach their full potential, converging on innovative and exciting ideas. 

 

FI Connect 

FI Connect is a HUB of digital applications created by the FI Group to transform, automate and optimise our customer relationships.

This suite of applications enables FI Group to offer a more structured consultancy support, making our clients’ lives easier and letting them focus on their R&D projects by ensuring better communication and greater efficiency in our delivery of their R&D claims.

 

Business Intelligence Applications 

The versatility of Business Intelligence allows it to be applied across various sectors and areas of activity within a company. Some examples of how BI can be used to generate value in different sectors include: 

 

Sales and Marketing 

• Analysis of marketing campaigns to identify the most effective ones and optimise marketing investments 

• Analysis of customer behaviour to understand their preferences, needs, and buying journey 

• Market segmentation to target campaigns and offers more precisely and effectively 

• Defining competitive prices based on market data and competitor analysis 

 

Finance 

• Cost and profitability analysis to identify areas for optimisation and improving profit margins 

• Cash flow monitoring to ensure the company’s financial health and make more informed investment decisions 

• Investment analysis to assess returns on investment and make more strategic decisions 

• Forecasting of financial trends to prepare for future events and mitigate risks 

 

Operations 

• Production monitoring to identify potential adversities and improve operational efficiency 

• Quality control to ensure that products meet the required quality standards 

• Stock management to optimise stock levels and reduce costs 

• Logistics optimisation to reduce transport and delivery costs 

 

Human Resources 

• Analysis of performance indicators to assess employee performance and identify areas for training and development 

• Talent retention to identify key turnover indicators and implement retention programs 

• People development to identify the skills and knowledge needed for the company’s success, and invest in employee development 

 

Customer Service 

• Analysis of customer feedback to identify areas for improvement and enhance the customer experience 

• Resolving problems quickly and effectively to shorten resolution times and increase customer satisfaction 

• Optimisation of service channels to direct customers to the most appropriate channel and reduce costs 

 

The provision of reliable information for making strategic decisions, to optimise processes, reduce costs and increase competitiveness makes BI a crucial differentiator for companies wishing to stand out in an increasingly competitive and dynamic market. 

Investing in a business intelligence solution is an investment in your company’s future. 

Share this article on business intelligence with your network of contacts. Explore FI Group’s article archive to find more related and relevant content. 

FI Group weighs the benefits and challenges of business automation

Automation driven by technological advances such as artificial intelligence, robotics and machine learning is rapidly changing the landscape of work. Repetitive and manual tasks previously performed by humans are being automated, freeing up time and resources for more creative, strategic, and complex activities.

Automation is guaranteed to boost the  productivity, efficiency and safety, along with reducing  costs and human error. It is essential to recognise, however, that this new reality also entails some adversities including rising unemployment, social inequality, and a need to retrain the workforce. To reflect on this need to adapt and develop new skills is essential if a business is to thrive in an increasingly automated world.

 

What is Business Automation?

Business automation is the current use of computerised systems, software applications, devices and other technological tools to perform processes automatically or semi-automatically, entirely without or with minimal human intervention. It can de facto be applied to various levels and areas of the company, from operational to managerial processes.

As the technological advances and automation tools themselves are increasingly becoming accessible to people unable to program them, business automation is found ever more frequently in all company routines. Especially so in the routines of companies aiming for continued competitiveness by banking on innovation.

 

Benefits and Challenges of Business Automation: The Benefits

By the strategic implementation of innovative technologies, business automation can offer a range of benefits that optimise the performance and open up a range of growth potentials.

 

Greater Productivity, Efficiency and Quality

Automation saves time, reduces effort, and the incidence of manual errors. Automated processes guarantee consistent results and a high quality, with tasks carried out identically and without human error. And if there should be errors nonetheless, they can all be corrected by changing the underlying process.

 

Reducing Costs and Optimising Resources

By eliminating redundant tasks, automation can optimise the use of resources, significantly reducing the company’s operating costs, along with the waste of materials, time and energy.

 

More Employee and Customer Satisfaction

Wherever manual tasks are «tedious» or very demanding, automation enables staff to turn to more pleasurable and creative activities, boosting their satisfaction. And by dedicating themselves to activities that please them more, they end up having more time to focus on better customer service.

 

Greater Competitiveness and Strategic Advantages

In an increasingly competitive market, automation puts a company at the forefront of innovation, providing a crucial strategic advantage for success. By automating specific processes, you will be able to respond to market changes and customer needs with the flexibility that entails. Freeing up resources will meanwhile also help you make the most of new market opportunities.

 

Key Business Automation Processes

When weighing up the benefits and challenges of business automation, it is imperative that business automation not be viewed in an exclusive manner, as there are various automation technologies that organisations can apply.

Business process automation (BPA) is a strategy pursued to optimise a company’s processes by implementing software and technologies. As a rule, BPA involves creating automatically sequenced activities that respond to process flows and not just individual tasks. Various software programs are available to automate the management and provision of financial reports, HR processes, marketing activities, the commercial management, and even workflows, to name but a few.

Robotic process automation (RPA) uses software «bots» to imitate human responses at the user interface, automating recurring and rule-based tasks. This in turn permits problems to be solved without interrupting human workflows or the need for human monitoring and supervision, unlike other automation methods.

RPA supports companies in activities such as processing requests, sending notifications, updating profiles, making complex calculations, monitoring already automated tasks, and many others. Call centres, data migration, help desks and credit applications are only four examples where RPA can be useful.

Finally, intelligent process automation (IPA) is a technology resulting from the convergence of robotic process automation (RPA) and various AI technologies in the automation of business processes. IPA aims to take automation to a higher level of complexity, increasing agility across the board. Some examples of IPA include new, intelligent CRM systems that eliminate manual tasks, inventory control with the ability to automate an organisation’s entire value chain, or quality management.

 

Benefits and Challenges of Business Automation: The Challenges

According to a report by the McKinsey Global Institute, automation could eliminate 15 % of all global working hours by 2030, leaving around 400 million people unemployed.

Among the countries this report takes a closer look at, it is estimated that workers in Japan will be the most affected by this development. But the story is similar in the United States, where 23 % of all working hours could be lost to services and automation processes, taking millions of jobs along with them. [Jobs threatened by automation | source: Statista]

Medium-term automation could lead to the loss of 39 million jobs in the US by 2030, while rapid automation could make 73 million people lose theirs. But to offset the potential job losses, around 20 million of these newly unemployed could transfer to similar jobs where they perform slightly different tasks.

Even so, a significant proportion would need to be fully retrained in the US and many other developed countries. According to McKinsey, a third of the US workforce may have to be retrained by 2030, as well as almost half the Japanese workforce.

Rapid automation could also cost China and India 236 and 120 million jobs, respectively. The worst-case scenario in Japan would lose 30 million jobs. Mexico could have 18 million workers made redundant by then, and Germany 17 million.

The jobs most at risk from automation tend to be physical and predictable, such as fast food workers or machine operators. The safest jobs are generally the less predictable ones, including managers, engineers, scientists, teachers, and plumbers. [Automation could eliminate 73 million jobs in the US by 2030 | source: Statista]

The concept of digital twins has emerged as a powerful tool across various industries in recent years, revolutionizing the way organizations design, operate, and manage complex systems.

From astronomy to smart cities, digital twins are reshaping the landscape of innovation, and driving efficiency, productivity, and sustainability.

 

Data-driven learning systems

Definition

A digital twin is a virtual replica or simulation of a physical asset, process, or system that enables its real-time monitoring, analysis, and optimization.  

The object under study is equipped with various sensors linked to vital areas of its functionality. These sensors generate data on several aspects of the physical object’s performance. The data are then sent to a processing system and applied to the digital copy.

Once populated with the data, the digital copy can be used to run simulations, investigate performance issues and develop possible improvements, all with the aim of generating valuable information.

 

The 4 types of digital twin

Digital twins are divided into 4 levels, bottom-up, depending on the integration level of data and parameters:

• Level 1: Component Twin
• This represent the smallest elements of a system such as a specific part of the equipment or product.
• Level 2: Digital Product Twin
• Virtual representations of physical products or assets.
• Level 3: System Twin
• These represent entire systems or ecosystems, embracing multiple interconnected components, processes, and stakeholders.
• Level 4:  Digital Process Twin
• Replicates the behaviour and dynamics of complex processes or systems, such as manufacturing processes, supply chains, or industrial operations.

 

Application: industrial uses of digital twins

 

Automotive/transportation: driving innovation with digital vehicle twins

Digital vehicle twins allow engineers to analyse how different factors such as aerodynamics, fuel efficiency, and safety features impact the overall performance. By simulating various driving conditions and scenarios, engineers can identify potential issues, refine designs, and improve the reliability and safety of vehicles.

The twins also enable predictive maintenance and condition monitoring of vehicles, enabling fleet operators to anticipate maintenance needs, minimize downtime, and optimize asset utilization.

 

Telecommunications: efficient networks and better customer experience

Telecommunication companies use digital network twins to create virtual replicas of their infrastructures, including towers, antennas, switches, and cables. These digital twins simulate network behaviour, traffic patterns, and performance metrics, enabling operators to identify bottlenecks, predict capacity requirements, and optimize resource allocation.

By integrating real-time data from network elements, sensors, and customer interactions,  digital network twins provide operators with actionable insights into network health, enabling proactive maintenance, fault prediction, and service restoration.

 

Construction: building the future with BIM

In the construction industry, digital twins are known as Building Information Models (BIM). BIMs are a digital representation of a building or infrastructure project that mirror the geometry, spatial relationships, and other relevant data.

Digital twins of construction projects enable architects, engineers, and contractors to collaborate more effectively, visualize designs in 3D, and identify potential conflicts or errors before the start of construction. By simulating construction processes and sequencing activities, BIMs help to optimize project schedules, reduce costs, and improve project efficiency overall.

 

Medicine: personalized proactive patient care with digital health twins

Digital health twins are virtual representations of individual patients. They enable clinicians to tailor treatment plans and interventions to the patient’s unique medical history, genetic makeup, and lifestyle factors.

By analysing data from wearable devices, electronic health records (EHRs), and medical imaging, clinicians can identify trends, detect early warning signs, and intervene proactively to prevent adverse health outcomes.

Pharmaceutical companies can leverage digital twins to simulate drug interactions, predict drug efficacy, and identify patient subpopulations for targeted therapies, leading to more efficient drug discovery and development processes.

 

Smart cities: optimizing urban systems with citywide twins

In smart cities, digital twins are known as citywide twins. By modelling transportation networks, energy grids, water systems, and other critical infrastructure, citywide twins help to identify inefficiencies, anticipate future needs, and develop strategies for sustainable growth. They also support resilience to and preparedness for disasters by modelling the impact of natural catastrophes, pandemics, and other crises. In addition to which they also facilitate citizen engagement and participatory planning by providing interactive platforms for residents to explore urban data, provide feedback, and contribute to the development of their communities. By fostering transparency and collaboration, citywide twins empower citizens to play an active role in shaping the future of their cities.

 

Astronomy: exploring the cosmos with virtual observatories

Digital twins of telescopes allow astronomers to test different configurations, calibrate instruments, and optimize their performance before conducting actual observations. In addition, virtual observatories can integrate data from multiple telescopes and sensors, enabling astronomers to correlate observations and detect hidden patterns in the vastness of space.

The development of new technologies has changed our perceptions and how we grow businesses of late, bringing a range of new concepts and routines to our daily lives. Web 3.0 and metaverses, for example, are two emerging technologies that are expected to revolutionize the way we do business in the years to come, and continually scrutinized and evaluated at this point in time.

 

Web 3.0

Web 3.0, which may also be known as the semantic web, is a concept developed for the next generation of the world wide web, using artificial intelligence (IA) and learning algorithms as well as blockchain technologies to understand data in their sharing, and facilitate the search for information and its storage in a decentralized computer network, based on the context.

Blockchain is a method of storing information – i.e. a database – that is shared among a network of computers and duplicates and distributes transactions and information, making it difficult or impossible for the system to be manipulated and hacked.

Compared to the current internet network – referred to as Web 2.0 – a decentralized web would offer greater security and privacy, along with more data ownership, as it allows users to manage and control their personal information, rather than relying on the architecture of a central server and its relationship with the client, as is the case today.

 

Metaverse

“Metaverse” is a term referring to virtual worlds that allow online social interaction using digital avatars, embracing virtual reality (VR) or augmented reality (AR) technologies to create an immersive experience. Within the space created, aspects of the physical world are simulated and reinforced through resources such as social media and digital currencies, as well as avatars, events, online activity centres, etc., elements that vary from one platform to the next.

In the last two decades, the emergence and proliferation of games promoting popular metaverses, such as Minecraft and Second Life, have engendered attempts to create ever more platforms aiming to integrate virtual and physical spaces in metaverse interactions.

 

Technology and business

According to Citi, metaverse businesses are expected to contribute between $ 8 and $13 trillion to the global economy by 2030, with an estimated five billion users. But what is more important to start with is to consider the users likely to go for these new technologies, and what they are looking for.

In the most popular metaverses such as Roblox and Minecraft, people in general and generation Z (born between 1997 and 2010) in particular are increasingly spending their money on virtual items and accessories, many of them exclusive to the respective metaverse. Which indicates that, apart from creating virtual versions of existing physical products, there are also development potentials for unique virtual products and experiences.

Marketing can play a key role in this, too. In 2022, major brands like Disney and Nike announced strategies or projects that embraced metaverses as a new means of engaging with customers, of broadening the understanding and study of online consumer behaviour, and enabling even more personalized and precisely focused experiences tailored to the interests and needs of each target audience.

Web 3.0 could likewise enhance customer relationships. Trust-building between businesses and their customers is eased given the transparency ensured by the «immutability» of data stored in blockchain technologies, infusing the latter with greater confidence in the information’s authenticity. Better legal compliance is another benefit, with immutable transaction records that are transparent to all parties helping businesses meet governance requirements.

As Web 3.0 is designed to be decentralized, applications are unlikely to require expensive servers and data centres, and can be run on computer networks provided by end users, eliminating the need for third-party service providers. Another cost-saving benefit is the potentially easier supply chain monitoring, enabling possible issues to be identified with greater agility and better time management.

 

What is the upshot for us?

Web 3.0 and metaverses are highly networked in their focus on sharing content and experiences online, and both based on advanced technologies such as the AI employed in their development and blockchains, a concept undergoing constant evaluation as an integral element of Web 3.0, set to power metaverse services.

Although adjustments may be necessary, the future potential of these two technologies is huge and highly promising, offering countless opportunities for innovation in a new digital wave able to change the way we do business in all kinds of ways. Potential challenges do exist – such as the incorporation of Web 3.0 in the metaverse, potentially leading to a virtual world that is fully integrated with the internet, or the availability of resources that support these new tools – but they can be overcome with time, promising a new era of access and change.

OpenAI, Chat GPT, and generative language models

2023 will go down as the breakthrough year for ChatGPT due to the intuitive capabilities and wide scope of applications of the tool.

But where did it all start?

Created in 2015, OpenAI has notable founders such as Elon Musk and Sam Altman with the aim of integrating artificial intelligence into society for the benefit of humanity. Looking back on the last seven months, you can definitely say their work has impacted society through their creation of ChatGPT.

In a nutshell, ChatGPT is an AI application that has been ‘trained’ to understand natural language and conversation. Pulling data from the internet and presenting its findings in easy to understand responses. Furthermore, it can be used as a translator, create content, summarise text and process / write code.

 

The R&D

Ironically, you can find out about the R&D behind ChatGPT by simply asking it. The tool identifies five components that make up its development:

1. Training Data – Large amounts of text, sources that include books, articles, and websites – where it can capture grammar and context.
2. Pre-Training – Learning to predict the next word in sentences and understand the patterns and relationships it sees from its training data.
3. Fine-tuning – Final stages of learning translation, question answering, and conversation.
4. Architecture and Algorithms – Transformer models help natural language processing tasks, for example, capture contextual relationships effectively.
5. Iterative Development – The final stage of testing the previous four components, making fine adjustments to any imperfections.

However, it can be difficult to put all this development into perspective and understand the gravity of its intelligence. The English language is comprised of one million words. In comparison, ChatGPT is made up of ten billion words, including fifteen languages (incl. English, French, Russian, Chinese, Arabic and Urdu), and sixteen programming languages (incl. Python, Java, JavaScript, C++ and, HTML/CSS).

If you wanted to dive deeper into the development of the tool, tokenization is the breaking down of the sequence of text into smaller units, appropriately called tokens. These help ChatGPT’s natural language processing (NLP) for further development.

 

Applications

As previously mentioned, OpenAI reached their goal of impacting society through their work. The applications for ChatGPT are vast, content creation, consultancy, and customer support to name a few.

A popular term being used more and more within industries is, ‘ChatGPT won’t take people’s jobs, people that use it will’. Which to an extent is correct. If utilised correctly by competent professionals with in-depth knowledge of their profession, then ChatGPT can allow for streamlined workflows and increased productivity.

Despite having ten billion words, mistakes can still be made. Users who copy and paste its responses risk not only incorporating the errors the tool might have created but also limiting themselves by hindering personal development in their respective careers.

 

Introducing MarIA

FI Group has made the decision to move away from ChatGPT. At a glance this decision might undermine what was said previously about streamlining workflows, however, we have opted to use a different tool. We are launching MarIA which uses AzureGPT functions. Similar to ChatGPT, but can ensure that conversations and data shared with it remain in the Azure environment which provides an additional level of security.

On the topic of ChatGPT, FI Group France Scientific Director Charlie Grosman said:

‘while it generates useful and relevant information, in a short period of time, it is not a technology that employees should trust at an exact level».

What does MarIA mean for our clients?

FI Group requires a lot of sensitive information from our clients such as confidential R&D project details and employee salary, if this information is shared with ChatGPT it is then stored in OpenAI’s database and outside of our control. MarIA ensures that any private information is kept safe in our own database and cannot be accessed by anyone outside of FI Group.

Moreover, MarIA will also limit how much FI Group employees can use its functions. Ensuring that work is being done by real people and aided by the tool, when necessary, rather than the other way round. Meaning, clients can be assured they are getting genuine expert client opinions.

What is Articifial Intelligence (AI) ?

 

Articifial Intelligence is a technology that belongs to the field of computer science and aims to create systems and algorithms that run in a dynamic environment, based on the collection and processing of data. These computer programs must be able to simulate human intelligence. The main objective of AI is to create intelligent machines that can help solve complex problems in many fields.

There are several categories of Articifial Intelligence (AI), which can be classified according to their capability and level of sophistication. Here are some of the most common categories of Artificial Intelligence :

• Weak Articifial Intelligence : This category of AI can perform specific and limited tasks. It is often used for applications such as speech recognition or image classification. While it is very effective at specific tasks, it can’t replicate the versatility of human intelligence.
• Strong Articifial Intelligence : This category of AI is designed to replicate human intelligence in its entirety. It can think autonomously, solve complex problems, and perform a wide variety of tasks without being explicitly programmed for each one. However, strong AI does not yet exist in its entire form and scientists continue to work on ways to develop it.
• Super Articifial Intelligence : This category is a hypothetical version of AI that would be capable of surpassing human intellectual abilities in all areas. This form of AI does not yet exist, but some AI experts predict that it could be developed in the future.

To get as close as possible to human behaviour, Articifial Intelligence needs a lot of data, as well as a processing and learning capacity. To achieve this, three components are needed:

• Computer systems,
• Data with management systems (they can be collected from databases, files, etc.),
• Algorithms. Once the data has been processed, a machine learning model can be trained using algorithms. This model is then trained to learn to perform a specific task from the data autonomously.

To enable computers to learn from data, Articifial Intelligence relies on Machine Learning models (a method that aims to teach machines to learn from data and improve with experience). There are 3 learning methods used:

• Supervised: which uses defined data to learn to identify patterns and make predictions,
• Unsupervised: which learns from undefined data. It uses techniques such as clustering or dimension reduction to identify patterns and relationships in the data,
• Semi-supervised: uses both defined and undefined data.

It is important to note that AI is a constantly evolving field of research, and that definitions and distinctions between different types of Artificial Intelligence may change.

 

What is Articifial Intelligence used for?

The main goal of AI is to create intelligent machines that can help solve complex problems in many fields, such as medicine, engineering, finance, security, social sciences, gaming, etc. Articifial Intelligence is seen as a key technology for the future and has the potential to transform the way we live and work.

These examples are just a small portion of the application areas for AI, and new uses are regularly discovered as the technology continues to advance. AI can therefore be used to improve efficiency, accuracy, safety, and quality in many different areas.

The example of ChatGPT

One of the most popular supervised AI at the moment is Chat GPT (Chat Generative Pre-trained Transformer). This conversational tool aims to help its users solve problems, answer questions, and provide information in various domains. It therefore generates text from input data (questions, queries, etc.). It is based on Natural Language Processing technology (NLP) and uses unsupervised learning. It has been trained on a very large corpus of text to learn how to generate consistent and relevant answers based on user queries. This is possible because it has access to huge amounts of text, from various sources.

 

FI Group Scientific Department

As a pure player in the R&D ecosystem, FI Group France has created a Scientific Department back in 2019. They lead research in Artificial Intelligence and NLP mostly. This department is composed of seven Researchers (including two Industrial PhD CIFRE). One PhD student is conducting a thesis on data extraction and the construction of algorithms to evolve their grouping by theme and subject. The second PhD student is doing a thesis on unsupervised learning on data flows. She is developing methods capable of clustering data continuously.

The objective of this department is to allow the realization of a regular scientific and technological watch to propose new approaches, and thus to support R&D Financing Consultants in their daily missions. 

These projects are possible thanks to the development and experimentation of techniques in Machine Learning and Automatic Language Processing. These processes facilitate the search for information in a large volume of data. A third research topic concerns the acquisition of new knowledge and the involvement of collaborators, via Gamification processes and serious games.

 

The NASA project

One of the projects supported by FI Group is called NASA. This AI makes it possible to search for scientific articles based on various concepts.

For each query, the articles published between 2019 and 2021 (about 13 million) are used to represent this knowledge in the form of a graph of concepts. It is then possible to display 10 scientific articles published for each concept.

The first prototype of NASA «First STEP» (Scientific Taxonomy Exploration Prototype) was launched in March 2022. The second and the third were respectively put online in September 2022 and February 2023. This «Third STEP» proposes improvements in performance, quality and user experience.

 

Why does digital transformation matter? 

 

Case studies have argued that 50% of employees could be replaced by machines because of the big technological advancements in AI in the era of Digital Transformation, however, we see this as a complement instead as a negative human replacement. 

We see computer software’s and AI as an addition to our activities, working alongside people who are part of the chain of vision. People can improvise, be reactive and think critically, showcasing the advantage of people in unexpected situations. There is a clear link between the collaborative work that can be done by AI and people, rather than a separation.

Knowing how to be an efficient and productive team is always the main aim of any successful partnership. As discussed, both people and AI have different strengths and weaknesses. By delegating tasks based on these strengths and weaknesses the digital transformation and partnership between people and AI can become more efficient and impactful. 

What role does consultancy play in digital transformation? 

It is becoming harder and harder to talk about Consultancy without mentioning digitisation. The digitisation of consultant tasks can be eased by Robotic Process Automation (RPA) software’s. These systems are designed to emulate human’s actions when interacting with digital systems, such as recognising and extracting relevant data.

This automation undoubtedly contributes to the streamlining of the consulting process. It can gather information immediately, transfer documents instantly, create news queries in a few minutes, solve the incidences quickly and in the stages of verifying or making changes to procedures. 

So, the digital transformation allows for flexibility within automation systems, which develops ease and efficiently, making the consultants project writing time shorter. This is also a benefit for the client as it allows for quicker turn around time on R&D reports.

Focusing on the improvement of the value add of our services has always been one of our greatest priorities. Innovation and technology are core pillars of our business, we are always looking for ways to improve our internal procedures through digital advancements that are being made, to provide the best and most efficient results for our clients.

 

The FI Group solution 

• How can FI Group help our clients in this era of digital transformation?

We offer a free audit to highlight and show our clients areas in their R&D process that can be improved by our team and service.

To improve this process, we have created an application that have improved the line of communication between FI Group and clients, and allows 24h access to updated claim information, improving our traditional services through new digital tools.  

Introducing FI Connect. A new digital space that integrates several applications on a single platform. Benefiting our customers by providing greater transparency and showcasing the digital transformation that FI Group is currently undergoing and that will drive productivity for clients and consultants alike. 

 

Welcome to FI Connect

Find out if the service is available in your country to book a demo:

• Brazil
• France
• Portugal
• Spain
• UK