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3#19 - Unlocking Innovation: Digital Transformation, AI, and Tech Evolution (Nor)

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Manage episode 425272359 series 2940030
Conteúdo fornecido por Winfried Adalbert Etzel - DAMA Norway. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Winfried Adalbert Etzel - DAMA Norway ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

«Hva er mulig å gjøre med disse teknologiene når de blir 10 ganger så bra som de er idag? / What might be possible to do with these technologies when they become 10 times as good as they are today?»
Can moonshot innovation really be the key to solving challenges that traditional methods fail to address? Today, we're thrilled to welcome Yngvar Ugland from DNB's New Tech Lab, who will unravel the complexities of digital transformation and share his unique insights from both corporate and startup ecosystems. From breaking the mold of the classic "people, process, technology" framework to stressing the importance of customer-centric approaches, Yngvar’s perspective offers a refreshing and profound look into fostering genuine innovation within established enterprises.
Technological innovation isn't always smooth sailing, and Yngvar helps us understand the friction between traditional mindsets and innovative approaches. Balancing high-trust societies against the urgency-driven dynamics of capitalism, we discuss the complex landscape of AI hype and explore technologies like GPT-3 and GPT-4. With an optimistic outlook, Yngvar encourages us to embrace the transformative potential of generative AI, highlighting the unprecedented opportunities that lie ahead. Tune in to gain a deeper understanding of the ever-evolving world of technology and digital transformation.
Here are my key takeaways:

  • Yngvar has build and is leading the as he calls it «Moon-shoot unit at DNB».
  • What do we need to do to actually implement and adopt to new technology and ways of working?
  • How do we think tech for people in tech?
  • We can identify three needed dimensions for change:
    • a data / tech component,
    • a business component and
    • a change component.
  • There is a difference between necessary and sufficient - just because a change is necessary, doesn’t mean that the proposed solution is sufficient.
  • You need to find ways to navigate uncertainty, be active beyond concrete hypothesis testing, or tech-evaluation.
  • For organizations to be successful, you need to coordinate both maintenance, improvement and innovation - it’s not one of those, but all there in concert that can ensure success over time.

  • Innovation and digital transformation is not a streamlined process.
  • Uncertainty offers a space for opportunity.
  • We use the term agile without grasping its true meaning - an inspect-and-adapt mindset is key to agile.
  • The development from GPT-1 through GPT-2 to GPT-3 is an example for the exponential development of technology.
  • The digital infrastructure in Norway, that can utilize data and technology for value creation across public and private sectors is a reason for our success.
  • The difference to the US market is that there are large cooperations that take on societal challenges.
  • How our society is structure has an influence on how we perceive the need for innovation.
  • It is natural to meet resistance in change and innovation.
  • To iterate effectively you really need to live a mindset build around FAIL - First Attempt in Learning.
  • We overestimate the effect of technology in the short term and significantly underestimate the long term.

  continue reading

Capítulos

1. Innovation and Transformation in Technology (00:00:00)

2. Journey Into Consumer Technology Innovation (00:09:56)

3. The Innovation Spectrum in Technology (00:17:13)

4. Navigating Technology Innovation and Failure (00:34:14)

5. Managing AI Hype and Expectations (00:43:06)

6. Embracing AI Innovation Opportunities (00:46:48)

61 episódios

Artwork
iconCompartilhar
 
Manage episode 425272359 series 2940030
Conteúdo fornecido por Winfried Adalbert Etzel - DAMA Norway. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Winfried Adalbert Etzel - DAMA Norway ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

«Hva er mulig å gjøre med disse teknologiene når de blir 10 ganger så bra som de er idag? / What might be possible to do with these technologies when they become 10 times as good as they are today?»
Can moonshot innovation really be the key to solving challenges that traditional methods fail to address? Today, we're thrilled to welcome Yngvar Ugland from DNB's New Tech Lab, who will unravel the complexities of digital transformation and share his unique insights from both corporate and startup ecosystems. From breaking the mold of the classic "people, process, technology" framework to stressing the importance of customer-centric approaches, Yngvar’s perspective offers a refreshing and profound look into fostering genuine innovation within established enterprises.
Technological innovation isn't always smooth sailing, and Yngvar helps us understand the friction between traditional mindsets and innovative approaches. Balancing high-trust societies against the urgency-driven dynamics of capitalism, we discuss the complex landscape of AI hype and explore technologies like GPT-3 and GPT-4. With an optimistic outlook, Yngvar encourages us to embrace the transformative potential of generative AI, highlighting the unprecedented opportunities that lie ahead. Tune in to gain a deeper understanding of the ever-evolving world of technology and digital transformation.
Here are my key takeaways:

  • Yngvar has build and is leading the as he calls it «Moon-shoot unit at DNB».
  • What do we need to do to actually implement and adopt to new technology and ways of working?
  • How do we think tech for people in tech?
  • We can identify three needed dimensions for change:
    • a data / tech component,
    • a business component and
    • a change component.
  • There is a difference between necessary and sufficient - just because a change is necessary, doesn’t mean that the proposed solution is sufficient.
  • You need to find ways to navigate uncertainty, be active beyond concrete hypothesis testing, or tech-evaluation.
  • For organizations to be successful, you need to coordinate both maintenance, improvement and innovation - it’s not one of those, but all there in concert that can ensure success over time.

  • Innovation and digital transformation is not a streamlined process.
  • Uncertainty offers a space for opportunity.
  • We use the term agile without grasping its true meaning - an inspect-and-adapt mindset is key to agile.
  • The development from GPT-1 through GPT-2 to GPT-3 is an example for the exponential development of technology.
  • The digital infrastructure in Norway, that can utilize data and technology for value creation across public and private sectors is a reason for our success.
  • The difference to the US market is that there are large cooperations that take on societal challenges.
  • How our society is structure has an influence on how we perceive the need for innovation.
  • It is natural to meet resistance in change and innovation.
  • To iterate effectively you really need to live a mindset build around FAIL - First Attempt in Learning.
  • We overestimate the effect of technology in the short term and significantly underestimate the long term.

  continue reading

Capítulos

1. Innovation and Transformation in Technology (00:00:00)

2. Journey Into Consumer Technology Innovation (00:09:56)

3. The Innovation Spectrum in Technology (00:17:13)

4. Navigating Technology Innovation and Failure (00:34:14)

5. Managing AI Hype and Expectations (00:43:06)

6. Embracing AI Innovation Opportunities (00:46:48)

61 episódios

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