12 model-level deep cuts to slash AI training costs

python import torch # PyTorch 2.0 compiler fusion optimized_model = torch.compile(model) 6. Pruning and quantization Deploying a massive, fully precise 16-bit neural network into production often requires renting top-tier cloud instances that destroy an application’s profit margins. Applying algorithmic...

AWS turns its S3 storage service into a file system for AI agents

Some developers, said Kaustubh, turned to FUSE-based tools such as s3fs or Mountpoint to simulate file systems on top of S3, but these often...

Making AI work for databases

At the same time, while these AI systems could make progress on more complex requests, they could not complete the “last mile” by themselves...

ClickHouse buys Langfuse as data platforms race to own the AI feedback loop

By bringing Langfuse in-house, ClickHouse can offer customers a native way to collect, store, and analyze large volumes of LLM telemetry alongside operational and...

AI is powering enterprise development, GitHub says

AI is becoming increasingly important in enterprise software development, particularly with the rise of accompanying agentic models, GitHub’s Martin Woodward, vice president of developer...

Lessons from building retrieval systems for AI assistants

Hybrid search While semantic search using vector embeddings performs well for capturing rephrased or paraphrased meanings, it might not do well on searches that involve...
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Mac Studio (M3 Ultra) review

The 2025 Mac Studio steps performance up to the extreme, with options for huge amounts of memory, and the same awesome design. Pros Sleek design ...
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