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How can you avoid incomplete, inaccurate responses in your GenAl app? Neo4j knowledge graphs [7] offer the capabilities you need. 🚀 Power LLMS with your company's data using retrieval augmented generation (RAG)
Video understanding is an old field that is just now starting to find success. The main driver of success is quality datasets. This work from Meta includes many sensor data sources and hand poses. It provides baseline performance for existing methods.
Snapchat is introducing new AI-powered features for Snapchat+ subscribers, including an AI image generator that creates images from text prompts and a Dream selfie feature that creates fantastical images with friends. A new AI extend tool allows users to automatically expand and fill in the background of photos. These features are rolling out regionally to over 7 million Snapchat+ subscribers.
Google has launched Gemini Pro, a lightweight version of its advanced AI model Gemini Ultra, for public preview in Vertex AI, offering text and image processing capabilities and customizable contexts for various use cases.
Transformers, as amazing as they are, are often hard to train, with their many instabilities. One of the main issues is when an Attention matrix’s entropy collapses. This work is a way to prevent that with a simple reparametrization.
This project introduces a novel technique for estimating lighting in images, overcoming the limitations of current methods that rely on HDR panorama datasets. By using diffusion models to render chrome balls into standard images, the technique reveals a unique relationship between chrome balls and diffusion noise.
DriveMLM is a new framework that uses large language models to enhance autonomous driving. This system, which combines language decisions with vehicle controls, not only integrates with existing autonomous driving systems, but also shows better performance in simulations.
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LLMs work best with clean, curated data. But most of this data is
extracts and transform complex data (webpages, docs, images…) for use with every major vector database and LLM framework [16]. “Unstructured has solved the most difficult part of building an LLM application.” — LangChain Co-founder Harrison Chase. Make your
Coffee, launched last week, helps streamline frontend development with AI by plugging into existing codebases. The project focuses specifically on a first-class DX based on learnings the Coframe team has gathered from their own experience in generating 80%+ of their frontend with AI.
DeepEval is an all-in-one evaluation framework for LLM apps that allows users to easily identify and iterate on unsatisfactory LLM outputs. It currently offers 14+ evaluation metrics such as hallucination, summarization, G-Eval, RAGAS, etc., for users to evaluate entire datasets in a Pytest-like or component-based fashion.
One of the biggest challenges for practitioners using Pytorch has been figuring out why things run out of memory. Some amazing new tools in Pytorch 2.1 give insight into memory usage. It can even be used to classify the usage into familiar buckets (e.g., activations, gradients).
MI300X is AMD’s flagship AI accelerator that, with ROCm 6, is now close to NVIDIA performance for inference workloads. This is great news for the community, as it opens up alternative chips for emerging AI companies.
An experiment with fine-tuning to enhance GPT-4's capabilities using Magic: The Gathering draft as a test case led to a fine-tuned 7B parameter model that closely matched human-level performance.
Leading founders and venture investors talk about what's happening in AI, from the application of LLMs to enterprise innovation. If the pace of “things you should know about AI” is somewhat overwhelming, this is a good quick recap.
Medprompt+ from Microsoft is the current best prompting method for MMLU. Microsoft has released the template along with many other chain-of-thought style templates that are standard across the evaluation community.
Analyze your (or a competitor’s) pricing page.
Generative AI and large language models are transforming robotics. Agility's bipedal robot Digit can now perform complex tasks based on natural language commands, signaling a shift towards more human-like, intuitive robotic interactions.