#Optimization

Small language model optimization cracks complex business math

Microsoft’s OptiMind is a 20-billion parameter small language model that achieves high accuracy in converting natural language business problems into mathematical optimization models through expert-aligned training.

AI Wins Optimization Contest, Costs $1,300 to Beat Humans

UCSD Lab Advances Low-Latency LLM Serving with DGX B200

AI startup Rookoo funding targets event admin chaos

The Unseen Challenge of Reliable AI

Fal.ai's Blueprint for AI Video Dominance: Speed, Specialization, and Relentless Optimization

Tibo Energy Secures $6.5 Million in Seed Funding

Sedai Secures $20 Million Series B to Revolutionize Cloud Optimization with AI Agents

The company's platform currently manages over $1.2 billion in cloud spend for its diverse customer base, which includes industry giants like Palo Alto Networks and HP.

Speedata Secures $44M Series B Funding to Revolutionize Data Analytics

Future AGI Secured $1.6M to Optimize Agentic AI Workflows

enSights Secures $10M in Series A Funding for Clean Energy Optimization Expansion

3D Printing Startup CASTOR Raises Funding From Asahi Kasei

Accelerating Deep Learning: Transforming Batch Processing into Real-Time Mastery

How to Reduce Multi-Cloud Costs with Kyndryl and CloudWize

Making Machine Learning Inference Meet Real-World Performance Demands

FPGAs offer the configurability needed for real-time machine learning inference, with the flexibility to adapt to future workloads. Making these advantages accessible to data-scientists and developers calls for tools that are both comprehensive and easy to use. Daniel Eaton, Sr Manager, Strategic Marketing Development, Xilinx