Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.
Einband grossInnovation unleashed: AITEK 6
ISBN/GTIN

Innovation unleashed: AITEK 6

E-BookEPUBePub WasserzeichenE-Book
264 Seiten
Englisch
Books on Demanderschienen am15.09.20231. Auflage
Exploring the cutting-edge concepts of the manual AITEK 6 platform: auto-ML, custom vector base, autonomous process management and predictive dashboards with innovative knowledge cartridges.

Bruno Ciroussel, born in Lyon in 1964, is a french and swiss businessman. He is an engineer and author of the "Aitek methodology" dedicated to Auto-ML, now in its 6th edition, and has implemented his methodology in an universal Auto-ML platform: the "Aitek Engine", applicable in multiple functional domains such as banking, insurance, healthcare, logistics and telecom. He has also adapted his Aitek platform for deployment in the territorial surveillance, Homeland, and customs security sectors and delivered. Bruno Ciroussel is also author, lecturer and speaker on various issues encompassing Artificial Intelligence, Machine Learning as well as the impact of these and other technologies on business, security, government, and the democratic system.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR81,20
E-BookEPUBePub WasserzeichenE-Book
EUR19,99

Produkt

KlappentextExploring the cutting-edge concepts of the manual AITEK 6 platform: auto-ML, custom vector base, autonomous process management and predictive dashboards with innovative knowledge cartridges.

Bruno Ciroussel, born in Lyon in 1964, is a french and swiss businessman. He is an engineer and author of the "Aitek methodology" dedicated to Auto-ML, now in its 6th edition, and has implemented his methodology in an universal Auto-ML platform: the "Aitek Engine", applicable in multiple functional domains such as banking, insurance, healthcare, logistics and telecom. He has also adapted his Aitek platform for deployment in the territorial surveillance, Homeland, and customs security sectors and delivered. Bruno Ciroussel is also author, lecturer and speaker on various issues encompassing Artificial Intelligence, Machine Learning as well as the impact of these and other technologies on business, security, government, and the democratic system.
Details
Weitere ISBN/GTIN9782322510177
ProduktartE-Book
EinbandartE-Book
FormatEPUB
Format HinweisePub Wasserzeichen
Erscheinungsjahr2023
Erscheinungsdatum15.09.2023
Auflage1. Auflage
Seiten264 Seiten
SpracheEnglisch
Artikel-Nr.12433488
Rubriken
Genre9200

Inhalt/Kritik

Leseprobe

5. The Genesis of AITEK

Before reaching this level of progress, AITEK went through several development phases:


Figure 2 AITEK Timeline


Every change name includes addition and thus an
improvement in the technology used by the solution.


Figure 2 AITEK Technologies Evolution


AITEK's journey towards its current level of progress has encompassed several key developmental phases. Each phase has played a crucial role in shaping AITEK into the innovative solution it is today.

The initial phase involved extensive research and analysis, where the founders of AITEK recognized the existing gaps and frustrations in traditional management systems. They conducted in-depth studies to understand the limitations and challenges faced by organizations in effectively managing their operations and making informed decisions.

Building upon this knowledge, the next phase focused on the conceptualization and design of AITEK. The team worked tirelessly to develop a comprehensive methodology that would address the identified issues and provide a fresh perspective on how organizations could manage their performance. This involved incorporating cutting-edge technologies like machine learning and Big Data into the solution framework.

Once the conceptualization was complete, the development phase commenced. A dedicated team of skilled engineers, data scientists, and domain experts collaborated to bring AITEK to life. They leveraged their expertise to create a powerful software platform that could seamlessly integrate with existing information systems and databases. This phase also involved rigorous testing and refinement to ensure the functionality, reliability, and accuracy of AITEK.

Throughout the development process, AITEK actively engaged with industry professionals and business experts. These partnerships allowed for valuable insights and feedback, enabling AITEK to align its solution with real-world business needs and industry standards. The knowledge models, containing business norms, standards, vocabulary, rules, and regulatory constraints, were carefully crafted in collaboration with these experts, further enhancing the effectiveness and relevance of AITEK.

Upon reaching a stable and refined version of the solution, the deployment phase followed. AITEK worked closely with a select group of forward-thinking organizations to conduct proof-of-concept workshops. These workshops served as testing grounds where AITEK demonstrated its capabilities, addressed specific business challenges faced by the participating organizations, and refined the solution further based on their feedback.

The deployment phase also involved seamless integration with the organizations' existing information systems, ensuring a smooth transition and compatibility. AITEK's implementation team provided dedicated support and training to empower users and maximize the value derived from the solution.

As AITEK continues to evolve, it remains committed to ongoing research and development. The team closely monitors industry trends and emerging technologies to incorporate advancements that will further enhance the solution's capabilities. AITEK's development journey is a testament to its dedication to providing organizations with a cutting-edge management tool that drives efficiency, optimizes performance, and guides them towards future success.
5.1. The Founder s Biography

Bruno Ciroussel, born in Lyon in 1964, is a prominent figure in the field of applied mathematics and artificial intelligence. He is the main shareholder and president of Intertech Venture SA, a company based in Fribourg that operates in European, American, African and Asian markets. With a strong international outlook, Bruno Ciroussel has developed a diverse range of cultural backgrounds and experiences.

After completing his Baccalauréat E in Lyon and earning a DUT in Electrical Engineering and Industrial Computer Science, Bruno pursued further studies at the EPFL (Ecole Polytechnique Fédérale de Lausanne). It was during this time that he became deeply interested in applied mathematics and conceptualized a methodology based on Machine Learning. In his interviews, Bruno aims to demystify "machine learning" by highlighting its foundation in statistics and probability, presented in algorithmic form as a subset of artificial intelligence.

Bruno Ciroussel's passion for self-learning algorithms led him to develop the Aitek methodology, which focuses on classification, prediction, and knowledge acquisition through behavioral analysis of data. He emphasizes the importance of automatic and meticulous monitoring of data perception elements to collect and process information. This enables the prediction of market evolution and the identification of latent customer needs.

Apart from his business ventures, Bruno Ciroussel actively contributes to academia and teaching. He shares his expertise in security and human factors at ILCE and teaches strategic decision-making and state performance at ENA in Tunis. He is a founding member of the Laboratory of State Performance and collaborates with various universities in Switzerland, France, and the Maghreb region. Bruno supervises research projects, professional and research Masters, and PHD programs, collaborating with universities in Bordeaux, Lyon, Lausanne, Morocco, and Tunisia.

Bruno's passion for bridging the gap between research, teaching, and the business world led him to transform his research into a tangible commercial product through the establishment and management of his own start-up. The latest version of his platform, released in 2022, represents the culmination of over 21,000 man-days of research and development, spanning 15 years of continuous improvement and evolution. This cutting-edge software platform integrates over 25 years of Bruno's expertise in security and information processing.

In addition to his roles as president of companies that commercialize his research, Bruno Ciroussel is also a professor of computer science and data science. He serves as the dean of the computer science department at the Ishiqi Lab and Ishiqi Institute, further solidifying his commitment to advancing knowledge and nurturing future generations of experts in the field.

Bruno Ciroussel's remarkable journey showcases his dedication to pushing the boundaries of applied mathematics and artificial intelligence. His extensive contributions to research, teaching, and entrepreneurship have established him as a visionary leader in the field, propelling the development and application of cutting-edge technologies in various industries.
5.2. Concept Manual 1.0 and BI++

The data-driven semantic BPM (Business Process Management methodology is a comprehensive approach that revolves around the core elements of risk and performance, ultimately generating a robust data warehouse. This methodology leverages data to drive decision-making and optimize business processes.

One of the key features of this methodology is its automatic refresh capability, which updates the data warehouse based on the frequency of risks identified. This ensures that the information within the system remains up to date and relevant. Additionally, the methodology incorporates data cleaning techniques to enhance the quality and accuracy of the data, as well as qualifying the likelihood of risks associated with the collected data.

To facilitate effective analysis and reporting, the methodology includes a prospective reporting tool. This tool enables organizations to generate insightful reports that provide valuable insights into their business operations and potential risks. Furthermore, the methodology incorporates behavioural data mining techniques, allowing for the extraction of meaningful patterns and trends from the collected data.

The initial concept of this methodology, version 1.0, was implemented within the integrated BI++ solution between 2004 and 2010. This implementation received recognition in the form of the federal CTI Startup award in 2009. The award highlights the innovation and impact of the solution, acknowledging its contribution to the field of business intelligence and process management.

Overall, this data-driven semantic BPM methodology serves as a powerful framework for organizations seeking to enhance their decision-making processes, improve performance and mitigate risks. Its incorporation of automatic data refresh, data cleaning, likelihood qualification, prospective reporting, and behavioural data mining ensures a comprehensive and effective approach to managing and analyzing data for improved business outcomes.
5.3. Concept Manual 2.0 and GPS

The analysis of underlying data related to business activities provides valuable insights into the behaviour and patterns of these activities. By leveraging machine learning techniques within the methodology, the information can be effectively structured, leading to the creation of a comprehensive causal tree that represents the interdependencies among various business activities. This enables organizations to automate the optimization of performance and risk management, ultimately enhancing their operational efficiency and decision-making capabilities. Additionally, this approach empowers organizations with the ability to simulate different scenarios and assess their potential outcomes.

The concept of a knowledge cartridge emerged as a result of this approach. A knowledge cartridge is a specialized module or component that encapsulates domain-specific knowledge and expertise within the system. It serves as a repository of best practices, business rules, and regulatory constraints, enabling...
mehr