Companies Struggle to Explain Their Own AI Investment Returns
Plus, more highlights from the WSJ Technology Council Summit
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Plus, more highlights from the WSJ Technology Council Summit
The companies said their collaboration aims to address key challenges in the drug-discovery process by developing targeted solutions and workflows.
Plus, Elon Musk trains his political chaos machine on the U.K., and we break down what to watch for at the year’s biggest Fed meeting.
With the Food and Drug Administration’s hard-liners gone, investors are rushing back into rare-disease bets.
Mistral said Mozilla would leverage its artificial-intelligence models to power Firefox’s AI assistant, betting on a partnership with a browser provider known for its privacy and data protections to win over more users and expand its consumer base.
Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help — but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the…
AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use…
System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments. …
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