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Future AGI
Langfuse
Openlayer
Helicone AI
LangSmith
Better Stack
LangChain
Middleware.io
ImageBind
Milvus
Building an AI agent is easy. Knowing if it works is hard. Keeping it working is impossible. Future AGI is the open-source platform that takes AI agents from first prompt to production - and keeps making them better with every version. โ Experiment with prompts, models, and configurations in one place โ Simulate against thousands of synthetic users - voice and text before launch โ Evaluate every agent data, decision and response, shield every input, in real time โ Route every model call through one gateway with fallback and caching โ Trace and replay every step in production, across every framework โ Auto-improve agents from real production failures, fix by fix Apache 2.0 | Self-hostable | Free.
Future AGI ImageBindImageBind might be a bit more popular than Future AGI. We know about 4 links to it since March 2021 and only 3 links to Future AGI. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Overview: Future AGIโs Synthetic Data Studio allows teams to create evaluation datasets, agent simulation environments, and fine-tuning sets across several modalities. - Source: dev.to / about 1 year ago
I am excited to open-source something we've spent months perfecting at Future AGI: a robust AI Evaluation Library that meets the needs of modern GenAI teams in this probabilistic Agentic world, without black-box limitations. AI evaluation remains the hardest unsolved problem in our field. How do you measure the accuracy of your eval pipeline? How do you evaluate the evaluator? How do you trust your metrics when... - Source: dev.to / about 1 year ago
At Future AGI,we understand the importance of AI-aided quality systems. Our state-of-the-art AI-enhanced solutions for testing and debugging are geared to aid businesses by bettering their development cycles and improving the quality of software. To check further on our novel approach to QA, go to the Future AGI. - Source: dev.to / over 1 year ago
With multimodal models such as TwelveLabs, Gemini Embedding, or ImageBind, you no longer need to decompose video into constituent parts. These models process video, audio, and context natively. They generate unified embeddings that capture complete content semantics in one operation. - Source: dev.to / 7 months ago
Another multi modal embedding is ImageBind from Meta, which supports text, images, and audio. - Source: dev.to / 12 months ago
In the approach described above, the main difference between the candidate models is their input/output modality. When can we expect to unify these models into one? The next-generation โAI power-upโ for LLM Agents is a single multimodal model capable of following instructions across any input/output types. Combined with web search and REPL integrations, this would make for a rather โadvanced AIโ, and research in... Source: about 3 years ago
Google and OpenAI are increasingly restrictive on the research they share, but Meta is taking a different approach. This week: Meta released ImageBind, an AI model capable of โlearningโ from six different modalities, including depth, thermal, and inertia. Source: about 3 years ago
Langfuse - Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Openlayer - Test, fix, and improve your ML models
Helicone AI - Open-source LLM Observability for Developers
LangSmith - Build and deploy LLM applications with confidence
Better Stack - Everything you need to ship higherโquality software faster.