Europe is on its way to generate and make use of more data than ever. The project PrepDSpace4Mobility aims at contributing to the development of the common European mobility data space by supporting the creation of a technical infrastructure that will facilitate easy, cross-border access to key data for both passengers and freight. Given the enormous potential of data and digital technologies, the project is expected to have a positive impact on European competitiveness, society, and the environment.
Workshop gathered suppliers and users of data, relevant research institutes, associations, initiatives, politics, as well as technology and service providers in data spaces to ensure appropriate representation.
We had successful workshop, and greatly appreciate your practical field expertise and interactive contributions.
Check our Website and follow us on Linkedin.
Project PrepDSpace4Mobility is Funded by the European Union and coordinated by acatech (Germany), activities are carried out by Amadeus SAS (France), EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology, a body of the European Union, (Spain), FIWARE (Germany), FhG (Germany), IDSA (Germany), iSHARE (Netherlands), TNO (Netherlands), USI (Germany), VTT (Finland), EMTA (France), Group ADP (France), KU Leuven (Belgium), ERTICO (Belgium), BAST (Germany), UIH (Hungary), and MDS (Germany).
Europe is on its way to generate and make use of more data than ever. The project PrepDSpace4Mobility aims at contributing to the development of the common European mobility data space by supporting the creation of a technical infrastructure that will facilitate easy, cross-border access to key data for both passengers and freight. Given the enormous potential of data and digital technologies, the project is expected to have a positive impact on European competitiveness, society, and the environment.
Workshop gathered suppliers and users of data, relevant research institutes, associations, initiatives, politics, as well as technology and service providers in data spaces to ensure appropriate representation.
We had successful workshop, and greatly appreciate your practical field expertise and interactive contributions.
Check our Website and follow us on Linkedin.
Project PrepDSpace4Mobility is Funded by the European Union and coordinated by acatech (Germany), activities are carried out by Amadeus SAS (France), EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology, a body of the European Union, (Spain), FIWARE (Germany), FhG (Germany), IDSA (Germany), iSHARE (Netherlands), TNO (Netherlands), USI (Germany), VTT (Finland), EMTA (France), Group ADP (France), KU Leuven (Belgium), ERTICO (Belgium), BAST (Germany), UIH (Hungary), and MDS (Germany).
Digital transformation webinar amer slideshareAconex
With annual revenues expected to grow to $17 trillion by 2030, the Engineering and Construction (E&C) industry is pivotal to the world economy. Digitalization and innovation are speeding across the industry, yet the transformation continues to be a challenge. Industry expert, Jim Dray, CIO of Thornton Tomasetti and veteran of AECOM, along with Santiago Ferrer, Partner & Managing Director at The Boston Consulting Group, review the new digital reality for E&C and present real-life case studies to unlock benefits of technology.
Exploring Opportunities in the Generative AI Value Chain.pdfDung Hoang
The article "Exploring Opportunities in the Generative AI Value Chain" by McKinsey & Company's QuantumBlack provides insights into the value created by generative artificial intelligence (AI) and its potential applications.
Generative AI: Redefining Creativity and Transforming Corporate LandscapeOsaka University
The advent of Generative AI is redefining the boundaries of creativity and markedly transforming the corporate landscape. One of the pioneering technologies in this domain is the Reinforcement Learning from Human Feedback (RLHF). Combined with advancements in LLM (Language Model) has emerged as a notable player. LLM offers two primary interpretations: firstly, as a machine capable of generating highly plausible texts in response to specific directives, and secondly, as a multi-lingual knowledge repository that responds to diverse inquiries.
The ramifications of these technologies are widespread, with profound impacts on various industries. They are catalyzing digital transformation within enterprises, driving significant advancements in research and development, especially within the realms of drug discovery and healthcare. In countries like Japan, Generative AI is heralded for its potential to bolster creativity. The value generated by such AI-driven innovations is estimated to be several trillion dollars annually. Intriguingly, about 75% of this value, steered by creative AI applications, is predominantly concentrated within customer operations, marketing and sales, software engineering, and R&D. These applications are pivotal in enhancing customer interactions, generating innovative content for marketing campaigns, and even crafting computer code from natural language prompts. The ripple effect of these innovations is palpable in sectors like banking, high-tech, and life sciences.
However, as with every innovation, there are certain setbacks. For instance, the traditional business model of individualized instruction, as seen in the context of professors teaching basic actions, is on the brink of obsolescence.
Looking ahead, the next five years pose pertinent questions about humanity's role amidst this technological evolution. A salient skillset will encompass the adept utilization of generative AI, paired with the discernment to accept or critique AI-generated outputs. Education, as we know it, will be reimagined. The evaluative focus will transition from verifying a student's independent work to gauging their ability to produce content surpassing their AI tools. Generative AI's disruptive nature will compel us to re-evaluate human value, reshaping the paradigms of corporate management and educational methodologies
Digital transformation webinar amer slideshareAconex
With annual revenues expected to grow to $17 trillion by 2030, the Engineering and Construction (E&C) industry is pivotal to the world economy. Digitalization and innovation are speeding across the industry, yet the transformation continues to be a challenge. Industry expert, Jim Dray, CIO of Thornton Tomasetti and veteran of AECOM, along with Santiago Ferrer, Partner & Managing Director at The Boston Consulting Group, review the new digital reality for E&C and present real-life case studies to unlock benefits of technology.
Exploring Opportunities in the Generative AI Value Chain.pdfDung Hoang
The article "Exploring Opportunities in the Generative AI Value Chain" by McKinsey & Company's QuantumBlack provides insights into the value created by generative artificial intelligence (AI) and its potential applications.
Generative AI: Redefining Creativity and Transforming Corporate LandscapeOsaka University
The advent of Generative AI is redefining the boundaries of creativity and markedly transforming the corporate landscape. One of the pioneering technologies in this domain is the Reinforcement Learning from Human Feedback (RLHF). Combined with advancements in LLM (Language Model) has emerged as a notable player. LLM offers two primary interpretations: firstly, as a machine capable of generating highly plausible texts in response to specific directives, and secondly, as a multi-lingual knowledge repository that responds to diverse inquiries.
The ramifications of these technologies are widespread, with profound impacts on various industries. They are catalyzing digital transformation within enterprises, driving significant advancements in research and development, especially within the realms of drug discovery and healthcare. In countries like Japan, Generative AI is heralded for its potential to bolster creativity. The value generated by such AI-driven innovations is estimated to be several trillion dollars annually. Intriguingly, about 75% of this value, steered by creative AI applications, is predominantly concentrated within customer operations, marketing and sales, software engineering, and R&D. These applications are pivotal in enhancing customer interactions, generating innovative content for marketing campaigns, and even crafting computer code from natural language prompts. The ripple effect of these innovations is palpable in sectors like banking, high-tech, and life sciences.
However, as with every innovation, there are certain setbacks. For instance, the traditional business model of individualized instruction, as seen in the context of professors teaching basic actions, is on the brink of obsolescence.
Looking ahead, the next five years pose pertinent questions about humanity's role amidst this technological evolution. A salient skillset will encompass the adept utilization of generative AI, paired with the discernment to accept or critique AI-generated outputs. Education, as we know it, will be reimagined. The evaluative focus will transition from verifying a student's independent work to gauging their ability to produce content surpassing their AI tools. Generative AI's disruptive nature will compel us to re-evaluate human value, reshaping the paradigms of corporate management and educational methodologies
JPC2018[C3]Secrets of fulfilling the last-mile delivery of Microsoft Azure AI...MPN Japan
(This session will be provided English Only)
Empower digital transformation with conversational AI through Microsoft Azure. This session will discuss the solution of how conversational AI can bring transformation in products, empower employees, optimize operations, and engage customers with greater interactivity in this digitalized era. For more information, please visit our website http://jp.intumit.com/
(英語のみのセッションです)
デジタル・トランスフォーメーション時代により優れた対話系 AI を Microsoft Azure AI と共に顧客サービスの強化する事に成功。金融業界、政府や研究機関、電子や光学に多くのチャットボット ソリューションを提供している Intumit からのご紹介です。詳しくは http://jp.intumit.com/ までよろしくお願いいたします。
45. 株式会社エデュテックパートナーズ
Business
IT
Relationships that business uses IT
Ex: ERP supports accounting
and production management
Business
AI etc
Fusion of business and technology
Ex: Business model by IoT and AI
Previous technologies utilization Current technologies utilization
Fusion of business and technology
With the progress of technology, the relationship between
business and IT has changed to fusion of business and
technology
47. 株式会社エデュテックパートナーズ
Fusion of business and technology
In particular, the impact of AI on profitability is
indispensable for all industries
Reference: Prediction of increase in profit dividends by AI in 2035 2017.7 by Accenture
Prediction of increase in profit dividends by AI in 2035
AI impact ration Other impact
water, electricity, Gas
Information and communication
Professional Services
Art and Entertainment
Public service
Financial Services
Other services
Manufacturing industry
Transportation and Warehousing
Welfare services
Forestry and fisheries industry
Healthcare
Wholesale and Retail
Construction
Accommodation and beverages
Education
48. 株式会社エデュテックパートナーズ
Failures of AI developments
The trend of totally depending AI and IoT businesses on
consultants or vendors is increasing
The increase of vague requests, such as
“We want to use AI/deep learning for our business"
↓
The company is not considering what to do with AI
49. 株式会社エデュテックパートナーズ
Typical failure patterns in AI developments
1. Considering the introducing AI for business without a purpose.
2. Insufficient data required / poor quality of data
3. AI can achieve purpose, but cannot achieve cost effectiveness
4. A company can't get employee cooperation for AI projects
Failures of AI developments
As the Company’s AI adoption will become a goal not
means, Failure projects are increasing
50. 株式会社エデュテックパートナーズ
AI Development process
AI development requires both business side and
analytics and engineering side capabilities
POC Result
evaluation
Decision
Making
AI
Development
AI
operation
Business Skills
Analytics
Engineering
Proof
Of
concept
Finding
Business
challenges
AI Services
Model
planning
Decision
Making
51. 株式会社エデュテックパートナーズ
Ruptures of the AI development process
The gap in understanding between order companies
and AI vendors tends to be a problem and creates GAPs.
POC Result
evaluation
Decision
Making
AI
Development
AI
operation
Business Skills
Analytics
Engineering
Ambiguous business
challenges and
objectives,
Business side cannot
make decisions based
on the POC results
Proof
Of
concept
Finding
Business
challenges
AI Services
Model
planning
Decision
Making
52. 株式会社エデュテックパートナーズ
Data science / AI Skills
AI skills require “a skill to find challenges", “Skill to built
AI models" and “A skill to promote AI projects"
A Skill to Find
challenges
A skill to build
AI models
A skill to promote
AI projects