Applied Technology Knowledge at the service of our clients

NLP Challenges

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Artificial Intelligence has experienced an accelerated growth, and one of the areas that has shown great potential is NLP (Natural Language Processing). Do you know what challenges we face?

NLP is the ability of systems to understand and communicate in human language. Although there have been significant advances in this field, its evolution faces a number of challenges.

One of the main difficulties of NLP is dealing with the ambiguity of human language. Words and phrases can have multiple interpretations depending on the context in which they are used. Resolving them requires a deep knowledge of the context and the ability to correctly interpret the intention of the sender. For this, it is necessary to develop algorithms that can capture and analyze the context properly.

NLP Challenges


Another challenge is linguistic variability. Languages vary in terms of grammar, vocabulary, structure and idiomatic expressions. Moreover, within a single language, there may be dialectal and regional variations. This makes it difficult to develop NLP models that are efficient and accurate in different linguistic contexts. Adaptability and machine learning capabilities are crucial to overcome this challenge and make NLP systems truly global.

For systems to understand human language effectively, they need to possess deep, contextualized knowledge. Understanding involves not only recognizing words and phrases, but also grasping the meaning behind them, inferring relationships, analyzing emotions, and detecting linguistic subtleties. Building NLP models that are capable of obtaining this level of knowledge and understanding is a key challenge in the evolution of NLP. This involves the development of more advanced machine learning algorithms and techniques, as well as the integration of structured and unstructured data from a variety of sources.

Although NLP systems have proven to be successful in specific tasks, such as speech recognition or machine translation, generalization and adaptation to new domains and contexts remains a major challenge. NLP models often have difficulty applying knowledge acquired in one domain to completely new situations. This is because human language is highly variable and constantly evolving. The ability to adapt to new contexts and learn continuously is essential.

The evolution of NLP also raises important ethical and bias issues. NLP systems can be influenced by inherent biases in training data, which can result in discriminatory or unfair responses. The use of NLP technology raises concerns about data privacy and security, as well as social and economic impact in different sectors.

The evolution of NLP offers great potential for improving human-machine communication. However, there are still significant challenges to overcome. As researchers and practitioners continue to work on these problems, we can expect significant advances, leading to more sophisticated and beneficial applications of AI in various fields and industry sectors.

At LAUDE we understand that applied intelligence is a fundamental element for the success of our clients’ business processes. Our solutions are designed to help them face current market challenges and achieve their goals more efficiently and effectively. We offer the ability to extract valuable information from your data, gain actionable insights and improve data-driven decision making. We are committed to providing you with the tools you need to drive your growth, increase your competitiveness and achieve success in an ever-changing business world.

The Two Tracks of IoT

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The benefits of integrating Telecommunications in production models have been anticipated for quite some time. Now, no one doubts the potential of connected machines and their positive impact in all social and economic spheres.

As a result, the IoT phenomenon is undergoing a spectacular development, and everything suggests that this will continue.

Some studies show that the number of IoT connections will grow to 24.6 billion in 2025. For these growth estimates to become reality the key factor is the speed with which different use cases related to this area are designed and implemented. Use cases that, depending on each situation, can be oriented towards a large social mass or to a single enterprise or business sector with specific needs.

The experience tells us that if the impact of the use case on the user you are targeting is relevant, the implementation of the use case is carried out quickly. On the contrary, if the use case has a certain technological complexity or the number of potential beneficiaries is reduced, the adoption of the same slows down.

Commonly, use cases developed for the mass market are associated with a simplification of technology, which facilitates the development and adoption of the project. However, when talking about new production models with higher efficiency standards by incorporating telecommunications, the technological complexity is likely to increase. There is no doubt that the arrival of 5G is breaking down certain barriers, offer higher performance and facilitate the adoption of new use cases related to connected things. But it will be in exchange for greater complexity in the configuration and operations, both regarding the operators’ networks and the necessary infrastructure for the new production models.

These two aspects of IoT – massive IoT in the consumer markets versus critical IoT in the area of production – are going to be led by two different actors.

On the one hand, operators will be the sponsors of massive IoT, more interested in making the most of their investments by operating a single network for a high volume of subscribers with similar approaches and requirements. That is, they will promote massive connectivity of things without differentiating elements and with limited value added to the end customer, although perhaps appropriate for those cases where innovation is not a determining factor.

On the other hand, innovative companies will emerge that will seek to adapt to and develop the opportunities offered by the latest technological trends to the very criticality of their businesses. It will therefore be an exclusive IoT, with the ability to include differentiating elements in production to facilitate responses to specific needs of a sector or a single company. In the event that the sponsors are operators, we would be facing a push approach, with massively provided connectivity. In the case of companies sponsoring, we are faced with a pull approach, which will aim at generating an additional technological leap focused on efficiencies.

The reality is that no single approach exists. We will rather be seeing a wide variety of propostiions and with different degrees of involvement from the operator side. The IoT project thus becomes a multi-faceted prism with several faces, which means that counting on the support of a telecommunications consultancy who is able to make the most of the capabilities offered by operators, as well as the new standards, is more than just convenient. The specialisation of the consultant in everything related to the opportunities that the technology offers, together with the customer’s knowledge about the workings and operations of its own industry, will produce a perfect symbiosis capable of drawing the company’s roadmap towards the digitisation of its business by incorporating new operating models that implies real innovation. IoT is therefore becoming the catalyst for digital transformation at both the consumption and production levels.

The two approaches are complementary and constitute two different aspects of the same unstoppable trend. The mass adoption of connectivity of things is necessary to advance the digital transformation of the society in the field of consumption. On the other hand, the adoption of critical IoT by companies contributes to the digital transformation of society in the field of production. The latter has its exponent in the phenomenon known as Industry 4.0. that seeks more modern and efficient production models, capable of getting us closer to the Sustainable Development Goals, so vital for the planet at this moment.

Agile Contracts

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Benefits of agreeing on the implementation of closed projects with Agile methodologies

The most complicated part of the life cycle of a project is to establish a contract between a customer who wants a product or a digital solution and the company that provides the service.

On countless occasions, compromises have to be made on deliveries, functionalities, performance levels or absence of bugs that will happen many months after the contract is signed. This is accentuated by the fact that project requirements evolve over time and require a high capacity for adaptation.

There are many cases in which the developed product does not match in all its details with what was agreed in the contract. This requires the team to make unintended over efforts, and in return the clients are often unsatisfied because their functional and temporal expectations are not met.

Complex Processes

The development of digital products and services is a purely human process, defined and implemented by people. It requires knowledge, with a high intellectual workload, which makes it a process where uncertainty is inevitable. Historically, this uncertainty has been covered through a protection of the main resources, which can even be oversized.

The adoption of an Agile philosophy to deal with this type of project as a whole drastically changes this perspective. Contracts do not disappear: they are transformed into Agile contracts that reduce their importance in exchange for greater commitment, transparency and collaboration with our clients.

The contract is created with requirements, a budget and a fixed duration. And, as far as possible, the development team weighs the functionalities and requirements that appear in the contract. In the same way as it will do with the backlog entries during the execution of the project. In the event that the development team is not available, or has not yet been decided at this point in the project, the joint review of this weighted list of requirements will be one of the first activities to be performed.

New Approach

At the beginning of the Agile development, the involvement of the customer allows these initial requirements not to be immutable. In fact, it is expected that they are not, and can be exchanged for other requirements of equivalent weight. Always in a transparent and collaborative manner.

We are inclined to incorporate a security layer to the scope initially specified in the contract. But with this new approach, this becomes a benefit. The client is guaranteed the product obtained at the end of the process will be the one with the highest possible business value. And in the event that this layer is not used, there will be no additional cost to the customer.

Agile Contract vs Time and Materials

Agile Contracts are not to be confused with a working environment based on Time and Materials. In our case, the commitments made to our customers are constant, before and after each iteration, and are much stronger because they are more realistic and involve all parties. It could be seen as the replacement of a long-term contract by multiple contracts reflected, on the one hand, in the BackLog and, on the other hand, in the Sprint meetings, both for planning and review.

In short, the Agile Contract paradigm is based on interchangeable initial requirements, a constant increase in value, a continuous evaluation of the product or service and an absolutely transparent collaboration framework.

These paradigm shifts lead us to achieve a different way of defining and approaching projects. Using agile contracts, putting collaboration before contracts and focusing on the value of the results.