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Pinecone seems to be one of the go to choices for vector databases. This is useful when you need a language model to interact with external data. You embed that data as a vector and store it in a database like this. One of the key reasons you’d do this is because of the context length problem - pinecone says this is “extending the long term memory of language models”. This certainly is exciting and many people use pinecone in production.
SCM is a new system that allows LLMs to process long inputs. It is composed of three key modules: the language model agent, the memory stream, and the memory controller. SCM has been shown to be effective in processing long inputs, and it has the potential to be used for a variety of tasks.
SparseFormer, a novel method inspired by human sparse visual recognition, represents images using a limited number of tokens in the latent space, achieving competitive performance with lower computational costs. This approach offers better accuracy-throughput tradeoffs and can be easily extended to video classification, potentially inspiring further research on sparse neural architectures.
This article examines the challenges and risks of biases in large-scale language models like ChatGPT, discussing their origins, ethical concerns, and potential mitigation strategies. It emphasizes the need for a multidisciplinary, collaborative effort to develop more equitable, transparent, and responsible AI systems, encouraging thoughtful dialogue within the AI community about the role of biases and the pursuit of ethical AI.
In this study, researchers use Deep Reinforcement Learning (Deep RL) to train a low-cost, miniature humanoid robot with 20 actuated joints to play a simplified 1v1 soccer game, resulting in the development of robust and dynamic movement skills and basic strategic understanding. The combination of high-frequency control, targeted dynamics randomization, and perturbations during simulation training enabled successful transfer to real robots, exhibiting improved performance and agility compared to a scripted baseline.
The study introduces a technique for automatically deforming a triangle mesh based on a text prompt, leveraging differentiable rendering and pre-trained image encoders such as CLIP and DINO. By using Jacobians for mesh deformation representation, the method achieves smooth deformations and avoids noisy gradients, enabling large shape changes and fine details while maintaining coherence from all 3D viewpoints.
This research focuses on multi-view image generation for 3D-related applications such as image viewpoint editing. The proposed ray conditioning method generates multi-view images using a geometry-free approach, conditioning a 2D GAN on a light field prior, which offers improved photo-realism, identity consistency, and explicit viewpoint control while minimizing geometry artifacts and loss of fine-scale details.
A new survey found that 91% of employers are looking to hire workers with ChatGPT experience.
This article dives into the dataset used to train some of the more popular LLMs.
WasmGPT is a ChatGPT-like chatbot in the browser using ggml and emscripten.