We are looking for a driven and innovative ML software engineer as our founding AI Engineer to ideate, scope, and train custom models for previously unsolvable problems that deliver significant value for our customers and, in turn, their customers.
Latest AI News, Evaluating LLM Models for Production Systems (Methods and Practices), Generating Images from Audio with ML, Sampling for Text Generation, YOLO-World, InstantID, MoE-LLaVA and more.
Latest AI News, Become a Speaker at Data Phoenix Webinars, Getting Started with Diffusers for Text-to-Image, Merge Large Language Models, Building an LLMOPs Pipeline, Dealing with MRI and Deep Learning with Python, Lumiere, Diffutoon, SEELE, and more.
South Korea-based startup, Rebellions AI closed its successful Series B with $124M; Figure AI is in talks with Microsoft and OpenAI; Eagle-7B is the strongest multi-language open-source LLM to date; The EU AI Act has practically become a law; and other relevant headlines for this week
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.
