OPPOSITION No B 3 053 383

ExplosionAI UG (haftungsbeschränkt), Alexanderstr. 7, 10178, Berlin, Germany (opponent), represented by Sasse, Bachelin & Lichtenhahn Rechtsanwälte Partnerschaft mbB, Alexanderstr. 9, 10178, Berlin, Germany (professional representative)

a g a i n s t

Prescott Consolidated Limited, Trident Chambers, Wickhams Cay 1, Road Town

Null, Tortola, Virgin Islands (british) (applicant), represented by J. Lahidalga, Calle Arturo Soria 243 Dpl. Esc. 4-1º Izd., 28033 Madrid, Spain (professional representative).

On 29/08/2019, the Opposition Division takes the following

DECISION:

1. Opposition No B 3 053 383 is upheld for all the contested goods and services, namely:

Class 9: Software; application software; databases; artificial intelligence apparatus; hardware; accounting machines; calculators.

Class 42: Software development services; development and testing of computing methods, algorithms and software.

2. European Union trade mark application No 17 319 823 is rejected for all the contested goods and services. It may proceed for the remaining services.

3. The applicant bears the costs, fixed at EUR 620.

REASONS

The opponent filed an opposition against some of the goods and services of European Union trade mark application No 17 319 823 for the word mark ‘Prodigy A.I.’, namely against all the goods in Class 9 and the services in Class 42. The opposition is based on European Union trade mark registration No 17 308 552 for the word mark ‘Prodigy’. The opponent invoked Article 8(1)(a) and (b) EUTMR.

LIKELIHOOD OF CONFUSION — ARTICLE 8(1)(b) EUTMR

A likelihood of confusion exists if there is a risk that the public might believe that the goods or services in question, under the assumption that they bear the marks in question, come from the same undertaking or, as the case may be, from economically linked undertakings. Whether a likelihood of confusion exists depends on the appreciation in a global assessment of several factors, which are interdependent. These factors include the similarity of the signs, the similarity of the goods and services, the distinctiveness of the earlier mark, the distinctive and dominant elements of the conflicting signs, and the relevant public.

1. The goods and services

The goods and services on which the opposition is based are the following:

Class 9: Computer software and hardware for data analysis, machine learning, artificial intelligence, robotics, and robots; Computer software for computer system and application development, deployment and management; Software for determining and predicting patterns in data; Software for training data models using machine learning and deep learning processes; Software for machine learning and deep learning algorithms and processes; Software for data analysis, evaluation, calculation, and processing; Downloadable mobile applications for determining and predicting patterns in data; Downloadable mobile applications for machine learning and deep learning algorithms and processes; Downloadable mobile applications for training data models using machine learning and deep learning processes; Downloadable mobile applications for data analysis, evaluation, calculation, and processing.

Class 42: Computer systems analysis; Research and development of technology in the field of determining and predicting patterns in data; Research and development of technology in the field of training data models using machine learning and deep learning processes; Research and development of technology in the field of data analysis, evaluation, calculation, and processing; Research and development of technology in the field of machine learning and deep learning algorithms and processes; Software development and product development in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Software development consulting in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Software development in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Software as a service (SAAS) services featuring software for determining and predicting patterns in data; Software as a service (SAAS) services featuring software for machine learning and deep learning algorithms and processes; Software as a service (SAAS) services featuring software for training data models using machine learning and deep learning processes; Software as a service (SAAS) services, namely, hosting software for use by others for use in determining and predicting patterns in data; Software as a service (SAAS) services, namely, hosting software for use by others for use in training data models using machine learning and deep learning processes; Software as a service (SAAS) services, namely, hosting software for use by others for use in machine learning and deep learning algorithms and processes; Software as a service (SAAS) services, namely, hosting software for use by others for use in data analysis, evaluation, calculation, and processing; Technology consultation and research in the field of artificial intelligence, robotics, and robots; Technology consultation and research in the field of machine learning and deep learning algorithms and processes; Technology consultation and research in the field of training data models using machine learning and deep learning processes; Advanced product research in the field of artificial intelligence; Computer software development in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Design and development of software and hardware for data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Design and development of software in the field of mobile applications; Design and development of computer software; Design and development of on-line computer software systems; Development and creation of computer programmes for data processing; Providing information in the fields of technology and software development via an on-line website; Scientific and technological services, namely, research and design in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Scientific and technological services, namely, scientific research and development of software and hardware in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots; Writing of data processing programs.

The contested goods and services are the following:

Class 9: Software; application software; databases; artificial intelligence apparatus; hardware; accounting machines; calculators.

Class 42: Software development services; development and testing of computing methods, algorithms and software.

The relevant factors relating to the comparison of the goods or services include, inter alia, the nature and purpose of the goods or services, the distribution channels, the sales outlets, the producers, the method of use and whether they are in competition with each other or complementary to each other.

Contested goods in Class 9

The contested software; application software; hardware include, as broader categories, or overlap with, the opponent’s computer software and hardware for data analysis, machine learning, artificial intelligence, robotics, and robots. Since the Opposition Division cannot dissect ex officio the broad categories of the contested goods, they are considered identical to the opponent’s goods.

The contested databases are similar to the opponent’s design and development of computer software in Class 42. Apart from being complementary, these goods and services target the same public and they have the same commercial origin.

The contested calculators; accounting machines overlap with the opponent’s computer hardware for data analysis as computers are calculating machines. Therefore, they are identical.

The contested artificial intelligence apparatus is included in the broad category of the opponent’s computer software and hardware for artificial intelligence. Therefore, they are identical.

Contested services in Class 42

The contested software development services; development and testing of computing methods, algorithms and software are at least similar to the opponent’s software development and product development in the field of data analysis and processing, machine learning, artificial intelligence, robotics, and robots as they coincide at least in the same targeted public, distribution channels and commercial origin.

2. Relevant public — degree of attention

The average consumer of the category of products concerned is deemed to be reasonably well informed and reasonably observant and circumspect. It should also be borne in mind that the average consumer’s degree of attention is likely to vary according to the category of goods or services in question.

In the present case, the goods and services found to be identical or similar are directed at the public at large and at business customers with specific professional knowledge or expertise.

The public’s degree of attentiveness may vary from average to high, depending on the price, specialised nature, or terms and conditions of the goods and services purchased.

3. The signs

Prodigy	Prodigy A.I.
Earlier trade mark	Contested sign

The relevant territory is the European Union.

The global appreciation of the visual, aural or conceptual similarity of the marks in question must be based on the overall impression given by the marks, bearing in mind, in particular, their distinctive and dominant components (11/11/1997, C‑251/95, Sabèl, EU:C:1997:528, § 23).

The element ‘PRODIGY’ present in both signs will be understood as referring to a very talented child by the English-speaking part of the public. The same meaning will be perceived by, for example, the French-speaking public due to the close equivalent ‘prodige’. This word will be meaningless for the remaining part of the public. In any event, it will be distinctive as it has no meaning in relation to the goods and services in question.

The element ‘A.I.’ of the contested sign will be associated with artificial intelligence by at least part of the public (such as the English-speaking public and professionals who are likely to be familiar with this abbreviation). Bearing in mind that the relevant goods and services are IT-related, this element is non-distinctive for these goods and services. For part of the public, such as non-English-speaking part of the general public, that would not associate any meaning with this element, it is considered distinctive.

Visually, the signs coincide in the distinctive element ‘Prodigy’ which constitutes the whole earlier mark and plays an independent and distinctive role in the contested sign. However, they differ in the element ‘A.I.’ of the contested sign which is non-distinctive and is placed at the end of the contested sign, where consumers pay less attention.

Therefore, the signs are highly similar.

Aurally, irrespective of the different pronunciation rules in different parts of the relevant territory, the pronunciation of the signs coincides in the sound of the distinctive word ‛Prodigy’, present identically in both signs. The pronunciation differs in the sound of the letters ‛A.I.’ of the contested mark, which have no counterpart in the earlier sign.

Therefore, the signs are highly similar.

Conceptually, reference is made to the previous assertions concerning the semantic content conveyed by the marks. As the signs will be associated with a similar meaning by, for example, the English- and French-speaking-part of the public, the signs are conceptually highly similar.

For the part of the public, that will perceive the meaning of the element of the contested sign, namely ‘A.I.’ as explained above and will not associate any meaning with the word ‘PRODIGY’, one of the signs will not be associated with any meaning, so that the signs will not be conceptually similar. However, this conceptual difference has very little, if any, impact on the comparison of the signs as it is confined to a non-distinctive element.

For the remaining part of the public, for which neither of the signs has a meaning. since a conceptual comparison is not possible, the conceptual aspect does not influence the assessment of the similarity of the signs.

As the signs have been found similar in at least one aspect of the comparison, the examination of likelihood of confusion will proceed.

4. Distinctiveness of the earlier mark

The distinctiveness of the earlier mark is one of the factors to be taken into account in the global assessment of likelihood of confusion.

The opponent did not explicitly claim that its mark is particularly distinctive by virtue of intensive use or reputation.

Consequently, the assessment of the distinctiveness of the earlier mark will rest on its distinctiveness per se. In the present case, the earlier trade mark as a whole has no meaning for any of the goods and services in question from the perspective of the public in the relevant territory. Therefore, the distinctiveness of the earlier mark must be seen as normal.

5. Global assessment, other arguments and conclusion

The goods and services are identical and similar and they target general public and professionals. The level of attention may vary from average to high.

The signs are visually and aurally highly similar. Conceptually they are also highly similar at least for part of the public and for the remaining part of the public they are either not similar or the conceptual comparison is neutral.

Likelihood of confusion covers situations where the consumer directly confuses the trade marks themselves, or where the consumer makes a connection between the conflicting signs and assumes that the goods/services covered are from the same or economically linked undertakings. Indeed, it is highly conceivable that the relevant consumer will perceive the contested mark as a sub-brand, a variation of the earlier mark, configured in a different way according to the type of goods or services that it designates (23/10/2002, T‑104/01, Fifties, EU:T:2002:262, § 49).

Considering all the above, there is a likelihood of confusion on the part of the public.

Therefore, the opposition is well founded on the basis of the opponent’s European Union trade mark registration No 17 308 552. It follows that the contested trade mark must be rejected for all the contested goods and services.

Since the opposition is fully successful on the basis of the ground of Article 8(1)(b) EUTMR, there is no need to further examine the other ground of the opposition, namely Article 8(1)(a) EUTMR.

COSTS

According to Article 109(1) EUTMR, the losing party in opposition proceedings must bear the fees and costs incurred by the other party.

Since the applicant is the losing party, it must bear the opposition fee as well as the costs incurred by the opponent in the course of these proceedings.

According to Article 109(1) and (7) EUTMR and Article 18(1)(c)(i) EUTMIR (former Rule 94(3) and (6) and Rule 94(7)(d)(i) EUTMIR, in force before 01/10/2017), the costs to be paid to the opponent are the opposition fee and the costs of representation, which are to be fixed on the basis of the maximum rate set therein.

The Opposition Division

Angela DI BLASIO

Katarzyna ZANIECKA

Kieran HENEGHAN

According to Article 67 EUTMR, any party adversely affected by this decision has a right to appeal against this decision. According to Article 68 EUTMR, notice of appeal must be filed in writing at the Office within two months of the date of notification of this decision. It must be filed in the language of the proceedings in which the decision subject to appeal was taken. Furthermore, a written statement of the grounds for appeal must be filed within four months of the same date. The notice of appeal will be deemed to have been filed only when the appeal fee of EUR 720 has been paid.