Wan 2.2 human image generation is very good. This open model has a great future.
submitted by /u/yomasexbomb [link] [comments]
Your First Containerized Machine Learning Deployment with Docker and FastAPI
Deploying machine learning models can seem complex, but modern tools can streamline the process.
Mistral-Small-3.2-24B-Instruct-2506 is now available on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart
Today, we’re excited to announce that Mistral-Small-3.2-24B-Instruct-2506—a 24-billion-parameter large language model (LLM) from Mistral AI that’s optimized for enhanced instruction following and reduced repetition errors—is available for customers through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a capability in Amazon Bedrock that developers can use to discover, test, and use over …
AI vs. AI: Prophet Security raises $30M to replace human analysts with autonomous defenders
Prophet Security raises $30 million to launch a fully autonomous AI cybersecurity platform that investigates and responds to threats without human intervention, promising 10x faster response times and 96% fewer false positives.Read More
To explore AI bias, researchers pose a question: How do you imagine a tree?
To confront bias, scientists say we must examine the ontological frameworks within large language models—and how our perceptions influence outputs.
Be honest: How realistic is my new vintage AI lora?
No workflow since it’s only a WIP lora. submitted by /u/I_SHOOT_FRAMES [link] [comments]
Building a Seq2Seq Model with Attention for Language Translation
This post is divided into four parts; they are: • Why Attnetion Matters: Limitations of Basic Seq2Seq Models • Implementing Seq2Seq Model with Attention • Training and Evaluating the Model • Using the Model Traditional seq2seq models use an encoder-decoder architecture where the encoder compresses the input sequence into a single context vector, which the …
Read more “Building a Seq2Seq Model with Attention for Language Translation”
Beyond Pandas: 7 Advanced Data Manipulation Techniques for Large Datasets
If you’ve worked with data in Python, chances are you’ve used Pandas many times.
Build a drug discovery research assistant using Strands Agents and Amazon Bedrock
Drug discovery is a complex, time-intensive process that requires researchers to navigate vast amounts of scientific literature, clinical trial data, and molecular databases. Life science customers like Genentech and AstraZeneca are using AI agents and other generative AI tools to increase the speed of scientific discovery. Builders at these organizations are already using the fully …
Read more “Build a drug discovery research assistant using Strands Agents and Amazon Bedrock”
Understanding Calendar mode for Dynamic Workload Scheduler: Reserve ML GPUs and TPUs
Organizations need ML compute resources that can accommodate bursty peaks and periodic troughs. That means the consumption models for AI infrastructure need to evolve to be more cost-efficient, provide term flexibility, and support rapid development on the latest GPU and TPU accelerators. Calendar mode is currently available in preview as the newest feature of Dynamic …
Read more “Understanding Calendar mode for Dynamic Workload Scheduler: Reserve ML GPUs and TPUs”