The journey to enterprise AI success depends on a much scarcer resource: predictability in both cost and outcomes.
If success is defined only by function, performance will fragment. If success is defined collectively, teams begin to act as one because the system requires it.
Like many AI systems, Instacart’s product-replacement system needs to gauge its own confidence in order to turn predictions into actions.
A novel “decoupled risk investor model.” provides a new way to fund open hardware development to accelerate sustainable science innovation.
As we learn more about the flood-related tragedy in Nepal, scientists are asking what role might glaciers and permafrost have played in a warming climate.
For years, the dominant question surrounding artificial intelligence has been rooted in a subtle, quiet anxiety: What will AI take from us?
Companies spent the last few years asking where AI could be added. The next phase should focus on how much unnecessary compute can be removed without lowering quality.
AI authority depends on how marketing signals work together.
Enterprise AI should begin with a business problem, a clearly understood workflow and an outcome that can be measured.
LiDAR propelled the development of semiconductor technologies for optical beam scanning. These technologies are being deployed for optical switching in datacenters.