LLMs
However development time, and maintenance can offset these savings. Hiring skilled data scientists, machine learning engineers, and DevOps professionals can be expensive and time consuming. Using available resources for “reimplementing” solutions hinder innovation and lead to a lack of focus. Since You not longer work on improving your model or... See more
Understanding the Cost of Generative AI Models in Production
ANY
LLM of your choice, statistical methods, or NLP models that runs
locally on your machine
:
- G-Eval
- Summarization
- Answer Relevancy
- Faithfulness
- Contextual Recall
- Contextual Precision
- RAGAS
- Hallucination
- Toxicity
- Bias
- etc.
GitHub - confident-ai/deepeval: The LLM Evaluation Framework
In addition to using our built-in capabilities, you can also define custom actions by making one or more APIs available to the GPT. Like plugins, actions allow GPTs to integrate external data or interact with the real-world. Connect GPTs to databases, plug them into emails, or make them your shopping assistant. For example, you could integrate a... See more
Introducing GPTs
Menlo Ventures released a report on ‘The State of Generative AI in the Enterprise’ and found that adoption is trailing the hype. Details below:
Generative AI still represents less than 1% of cloud spend by surveyed enterprises, including just an 8% increase in 2023.
Safety and ROI continue to be prime concerns, and the tangible advantages of being... See more
Generative AI still represents less than 1% of cloud spend by surveyed enterprises, including just an 8% increase in 2023.
Safety and ROI continue to be prime concerns, and the tangible advantages of being... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Setting up the necessary machine learning infrastructure to run these big models is another challenge. We need a dedicated model server for running model inference (using frameworks like Triton oder vLLM), powerful GPUs to run everything robustly, and configurability in our servers to make sure they're high throughput and low latency. Tuning the... See more
Developing Rapidly with Generative AI
MLServer aims to provide an easy way to start serving your machine learning models through a REST and gRPC interface, fully compliant with KFServing's V2 Dataplane spec. Watch a quick video introducing the project here.
- Multi-model serving, letting users run multiple models within the same process.
- Ability to run inference in parallel for vertical
GitHub - SeldonIO/MLServer: An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Today, we’re releasing the Assistants API, our first step towards helping developers build agent-like experiences within their own applications. An assistant is a purpose-built AI that has specific instructions, leverages extra knowledge, and can call models and tools to perform tasks. The new Assistants API provides new capabilities such as Code... See more
New models and developer products announced at DevDay
Mem0: The Memory Layer for Personalized AI
Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.
Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.
Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the embedchai... See more
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