Everything you control, you control through decisions—and at work, decisions are the actual product. The next four chapters are about what a decision is, what your body knows, who you think with, and how to own one, and how AI is changing our decisions without us being aware.
Helen Edwards is a Co-Founder of Artificiality. She previously co-founded Intelligentsia.ai (acquired by Atlantic Media) and worked at Meridian Energy, Pacific Gas & Electric, Quartz, and Transpower.
Artificiality Co-founders, Helen and Dave Edwards, spoke about Rethinking Value in the Age of AI at the EY Innovation Realized conference at the Palace of Fine Arts in San Francisco on April 16 & 17.
AI will force us to broaden our view of intelligence. The real success in AI development will be in discovering forms of intelligence that go beyond anything we've known, transforming how we understand and interact with the world around us.
Recent research demonstrates through empirical evidence that GPT-4 can autonomously develop pricing strategies that edge towards collusion without explicit human direction or inter-firm communication.
On April 9th, we presented our research update on the State of AI & Complex Change which focused on confusion about AI, status of AI adoption and deployments, anxiety about AI, and AI in the Wild.
A guide for organizational transformation for generative AI. By taking these critical steps, organizations can lay the foundation for effective use, setting themselves up for future success in an increasingly AI-driven world.
The future of the extended mind is not a fixed destination but an ongoing journey that requires our active participation and reflection as we redefine what it means to be human in an age of artificial intelligence.
Complex change recognizes that change is non-linear, emergent, and deeply interconnected with the system in which it occurs. This is even more important as we adapt to the complexity of generative AI.
AI's potential is vast but many applications remain incremental, simply grafting AI onto outdated frameworks. This is why we embrace complexity. We think about designing incentives, understanding self-organization and distributed control, and planning for emergence and adaptation.
Enterprises face a critical choice in their generative AI adoption strategy: fine-tuning or Retrieval-Augmented Generation (RAG)? While fine-tuning has been the go-to approach for early adopters, a new study suggests that RAG may be the more powerful and sustainable path forward.
By enabling different AI models to 'speak' to each other and combine their strengths, CALM opens up new possibilities for solving complex problems across various domains and tackling tasks with expertise and precision, in a data and compute efficient way.
