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Digital transformation mindcandy 17 January 2024
Today’s topics are additive manufacturing, digital transformation, data strategy, data monetization, IoT, coding, agility vs. anticipation, and the commoditization of large language models.
Looking ahead to additive manufacturing in 2025
https://www.engineering.com/looking-ahead-to-additive-manufacturing-in-2025/
Exclusive insights from the experts at EOS, 3D Systems, Materialise and more on the year ahead in 3D printing.
Fueling the future of digital transformation
https://www.technologyreview.com/2025/01/15/1109982/fueling-the-future-of-digital-transformation/
Transformation isn’t just about emerging technologies—it’s about people, culture, and safety, says digital manager of technology ventures, and innovation at Chevron, Luis Niño.
Shaping an Impactful Data Product Strategy
https://www.infoq.com/news/2025/01/impatful-data-product-strategy/
Data teams are often a costly afterthought in organisations’ data-centric strategies. Create a collaborative 3-year roadmap to ensure alignment, evolution, and delivery of impactful capabilities.
3 ways to build a culture of data monetization
https://mitsloan.mit.edu/ideas-made-to-matter/3-ways-to-build-a-culture-data-monetization
CEO-level data leadership, data value management, and data life-cycle measurement can boost the financial impact of data monetization.
IoT 2024 in review: The 10 most relevant IoT developments of the year
https://iot-analytics.com/iot-2024-review/
A year characterized by a challenging macroeconomic environment and vast expansion in—and excitement for—AI.
Replit CEO on AI breakthroughs: ‘We don’t care about professional coders anymore’
Essentially, a very basic understanding of the way software works enables people to take advantage of AI tools that are growing ever more capable.
Why Agility Alone Won’t Save You in Today’s Market
https://www.burrus.com/2025/01/why-agility-alone-wont-save-you-in-todays-market/
Agility vs. Anticipation: What’s the Difference?
2025 Predictions: Year of the Commoditization of Large Language Models (LLMS)
The accelerated adoption of large language models (LLMs) is shifting from experimentation to operationalization, fueled by cost reductions, advancements in symbolic knowledge generation, and a focus on energy-efficient AI.