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.
In science, traditional human search strategies are like wandering through a wilderness with limited visibility, relying on intuition and serendipity. AI, in contrast, can take in the whole landscape, quickly and effectively exploring the vast range of possible combinations.
New research on developing AI that builds robust world models shows an AI's ability to seek out surprise, motivation, and novelty, enabling it to navigate and understand the complexities of the world through self-driven exploration rather than just following predetermined reward pathways.
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AI's potential is vast but many applications remain incremental, simply grafting AI onto outdated frameworks.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.
