Sakana AI
Sakana AI researchers demonstrated that parametric and nonparametric black-box optimization methods share the same underlying mathematical framework, enabling hybrid optimizers for tasks like foundation model merging. The team developed two hybrid optimizers, AdaPol and SchedPol, that reduced computational costs for large language model merging by finding multiple solutions on smaller evaluation datasets instead of overfitting with standard methods. This theoretical unification allows engineers to design custom optimizers tailored to specific tasks while reducing the computational overhead of evaluating large models.
Meta AI Blog
TRIBE v2 is an AI model trained to predict how the human brain responds to visual, auditory, and language stimuli by learning from fMRI scans of over 700 volunteers. The model was trained on more than 700 healthy volunteers presented with diverse media including images, podcasts, videos, and text, and can make predictions for new subjects, languages, and tasks without additional brain imaging data. Researchers can now test hypotheses about brain function computationally, reducing the need for human subjects in experimental studies and potentially accelerating neuroscience discovery.
Tech.eu
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10 hours ago
Applied Computing, an AI company building foundation models for energy operations, raised $20 million led by KBR with participation from Databricks Ventures. The company's flagship platform Orbital combines physics-informed AI with chemical engineering and forecasting models, designed specifically for upstream, downstream and petrochemical operations. The funding will accelerate international expansion, opening a Houston office, and increase commercial deployment of Orbital across major energy customers globally.
TechCrunch AI
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13 hours ago
Applied Computing, a London-based startup, raised $20 million in Series A funding to deploy an AI model called Orbital that helps oil and gas facilities integrate sensor data, engineering documentation, and physics-based analysis. The company claims Orbital can compress investigations that previously took days or weeks into seconds, and is already generating double-digit millions in annual recurring revenue across unnamed large, publicly listed energy operators. With the funding, Applied Computing plans to expand internationally, hire AI researchers, and establish operations in Houston and the Middle East to serve more energy clients.
