What's the next technological paradigm shift?

Augmented & Virtual Reality (AR/VR)Applications & Platforms
2.2k viewscircle icon1 Upvotecircle icon3 Comments
Sort by:
Managing Partner in Miscellaneous3 years ago

The decoupling of the production of energy from consumption of energy. The most obvious example would be a BEV replacing an ICE vehicle. Consider also advances in grid-scale storage - not just battery but gravity (pump water uphill during periods of surplus generation, release thru turbine during periods of peak demand) and also advances in localized personal production like rooftop solar. Electricity replaces fossil fuels because there are a hundred ways to make it and increasingly store and transport it. The end of the fossil fuel era is much closer than most people think - not because of regulation but because it’s simply better tech and massively cheaper in the long run.

Managing Director in Manufacturing3 years ago

The adoption of AI at the end user level. For example, daily information workers begin leveraging AI on a regular basis to complete and offload work items.

Director in Manufacturing3 years ago

I believe the amount of robotics is going to explode is everything and everywhere. I believe Elon Musk said the value in Tesla isn’t the vehicle. It’s the sensors and cameras for self driving. Solve that and you can probably get a robot to do everything. Flip a burger, paint a house, weld a pipeline. This is going to change the workforce.

Lightbulb on2

Content you might like

AI and Research in Marketing and Communications: How Are You Ensuring Quality and Truth Over Speed? As AI becomes embedded in our day-to-day marketing operations, from customer insight to content strategy, it’s clear we’re gaining speed and scale. But are we sacrificing veracity and quality of output in the process? One of the biggest challenges I'm seeing is the rise of hallucinated content in AI-generated research.   - How do we ensure AI systems are surfacing trustworthy, contextually accurate, and well-sourced information? - Are we building enough verification layers into our AI-driven content and research workflows? - And how are you educating teams (and execs) to challenge AI outputs, rather than accept them at face value? - What frameworks, tools, or governance models have you adopted to maintain integrity and depth in AI-led research and insight creation? - Have you had success (or struggles) balancing speed vs. substance in AI-powered strategies? Your thoughts, examples, and recommendations would be incredibly valuable in helping others try to navigate this shift responsibly.

When it comes to agentic AI solutions, are most vendor offerings you've seen so far authentic? Which tools are truly AI agents and which are just RPA/chatbots rebranded as agentic AI?

Read More Comments

What are the biggest technical challenges preventing organizations from being able to use their existing data to enable digital transformation?

Finding data and putting it to good use13%

Controlling the security and privacy of data45%

Understanding how data is currently being used20%

All of the above19%

None of the above1%

View Results

Thinking of running Kafka on-prem for a high-throughput platform. My team says it’s far more complex than RabbitMQ etc — one said their old company had 20 people just managing it. What are the biggest challenges? Would using Confluent help?

What will be the effects of AI on meaningful work?

Mostly Replacing18%

Managing the Machine65%

Minding the Machine62%

Amplifying- Productivity Boost37%

View Results