The Federal Trade Commission (FTC) issued 6(b) Orders to Alphabet, Amazon, Anthropic, Microsoft and OpenAI; Oracle finally revealed its Cloud Infrastructure Generative AI service; An MIT study concluded that AI is too expensive to replace human workers at the moment; MLflow 2.10.0, and more.
Latest AI News, A Simple CI/CD Setup for ML Projects, Fine-tune and Deploy Llama 2 Models Cost-Effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium, A Comprehensive Overview of Gaussian Splatting, Self-Rewarding Language Models, PhotoMaker, 4DGen, SiLK, and more.
We've collected a selection of the most notable stories covered by DataPhoenix during 2023. The list includes some trailblazing advances in LLMs, media generation, and research and development. We've also included a small recap of noteworthy partnerships and general interest debates.
Join the Data Phoenix webinar, where Dmytro Spodarets and guest Ramon Perez (Developer Advocate at Seldon) will discuss different machine learning deployment strategies available today for both traditional ML systems and Large Language Models.
Fine-tune a Mistral-7b model with Direct Preference Optimization, How to Detect Hallucinations in LLMs, Efficient Scaling of LLM Inference, Tracking Any Object Amodally, On Noisy Evaluation in Federated Hyperparameter Tuning, StreamDiffusion, AnyText, FlexGen, and more.
A Whirlwind Tour of ML Model Serving Strategies, Evaluating RAG Applications with RAGAs, Mastering Customer Segmentation with LLM, Training XGBoost with MLflow Experiments and HyperOpt Tuning, Generative Powers of Ten, ProlificDreamer, PromptBench, PoseGPT, EdgeSAM, Material Palette, and more.
Join the Data Phoenix webinar, where Dmytro Spodarets and guest Daniel Lenton (CEO at Unify) will discuss the different kinds of decisions needed when deploying AI models in different contexts.
Join the Data Phoenix webinar, where Dmytro Spodarets and guest Philip Tannor (Co-founder and CEO of Deepchecks) will discuss evaluating LLM-based applications.
Evaluating LLM-based Apps and Mitigating Their Risks, Democratizing AI Deployment, Retrieval-Augmented Generation From Theory to LangChain Implementation, Serverless Compute for LLM, Accelerating PyTorch Training Workloads with FP8, Mustango, MEDITRON-70B, DemoFusion, and more.