From hallucinations to hardware: Lessons from a real-world computer vision project gone sideways
What we tried, what didn’t work and how a combination of approaches eventually helped us build a reliable computer vision model.Read More
What we tried, what didn’t work and how a combination of approaches eventually helped us build a reliable computer vision model.Read More
Mark Zuckerberg has been working to poach talent from rival labs for his new superintelligence team.
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As language models support larger and larger context sizes, evaluating their ability to make effective use of that context becomes increasingly important. We analyze the ability of several code generation models to handle long range dependencies using a suite of multi-step key retrieval tasks in context windows up to 8k tokens in length. The tasks …
Read more “Evaluating Long Range Dependency Handling in Code Generation LLMs”
Managing and optimizing AWS infrastructure costs is a critical challenge for organizations of all sizes. Traditional cost analysis approaches often involve the following: Complex spreadsheets – Creating and maintaining detailed cost models, which requires significant effort Multiple tools – Switching between the AWS Pricing Calculator, AWS Cost Explorer, and third-party tools Specialized knowledge – Understanding …
Read more “AWS costs estimation using Amazon Q CLI and AWS Cost Analysis MCP”
San Francisco-based CTGT, a startup focused on making AI more trustworthy through feature-level model customization, won the Best Presentation Style award at VB Transform 2025 in San Francisco. Founded by 23-year-old Cyril Gorlla, the company showcased how its technology helps enterprises overcome AI trust barriers by directly modifying model featu…Read More
Whether you need a tent, sleeping pad, rain jacket, or new pack, REI’s Independence Day sale has something for everyone.
You can find the workflow by scrolling down on this page: https://comfyanonymous.github.io/ComfyUI_examples/flux/ submitted by /u/comfyanonymous [link] [comments]
Machine learning practitioners spend countless hours on repetitive tasks: monitoring model performance, retraining pipelines, data quality checks, and experiment tracking.
This post is divided into four parts; they are: • Why Attention Masking is Needed • Implementation of Attention Masks • Mask Creation • Using PyTorch’s Built-in Attention In the