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Claude is more than just a middle-of-the-road, sycophantic AI that agrees with the user. Claude's personality and character have been specifically designed using a character variant of Constitutional AI. This post goes in-depth on how post-training is used to steer the type of output often generated by Claude to represent this desired character.
Databricks has acquired Tabular, uniting key contributors to Apache Iceberg and Delta Lake to focus on data format compatibility for its lakehouse architecture. The goal is to achieve a single open standard for data interoperability to prevent data silos, starting with Delta Lake UniForm's compatibility solution.
Researchers have developed a Synthetic-Domain Alignment (SDA) framework to enhance test-time adaptation (TTA) methods. SDA effectively aligns source and synthetic domains by fine-tuning pretrained models with synthetic data generated through a conditional diffusion model.
Reward-based Noise Optimization (ReNO) is a new approach to enhance Text-to-Image (T2I) models during inference that optimizes the initial noise using signals from human preference reward models.
Researchers have upgraded the popular YOLO object detectors with YOLO-World, introducing open-vocabulary detection. This approach combines vision-language modeling and large-scale dataset training, allowing it to identify a vast array of objects quickly and accurately, even in scenarios it wasn't specifically trained for.
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GPT-2 style transformer model contained entirely in a spreadsheet that includes all weights, parameters, and connections. It is a small model based on NanoGPT that is entirely contained in the rows and columns of a spreadsheet.
Inspectus is a versatile visualization tool for large language models that offers diverse insights into language model behaviors.
Researchers have created a new privacy-friendly method for camera localization using unique scene landmarks. This approach, which uses a CNN-based heatmap and 3D scene landmarks, is both storage-efficient and highly accurate, all without relying on actual 3D point clouds for localization.
New dataset with 700k+ images and 2m+ annotations for computer vision 6D motion estimation (e.g., positions and rotations).
Large language models (LLMs) like ChatGPT are not databases and can produce imprecise answers to questions, but they excel at generating responses that appear correct. The future of AI involves integrating LLMs into specialized tools or embedding them into existing applications, enhancing functionality while mitigating errors and improving user experience by contextualizing AI outputs within specific, manageable domains.
This model uses a number of computer vision techniques to reason about absolute and relative sizes of objects in monocular images.
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Daniel Kokotajlo joined OpenAI with the hope that it would invest much more in safety research, but the company never made that pivot.
OpenAI's CEO clarified that the voice of 'Sky' in ChatGPT isn't Scarlett Johansson's and has paused its use after a miscommunication.
Microsoft launched Copilot, powered by GPT, on Telegram.
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Qwen 2 is a new flagship language model from Alibaba Cloud. It slightly surpasses Llama 3 70B on benchmark performance in English while being a better multilingual model.
Elon Musk redirected 12,000 H100 GPUs ordered by Tesla to X. He had told investors in April that Tesla had spent $1 billion on GPUs in the three months of the year. Tesla has been developing its own in-house supercomputer for AI, but Musk has previously said that it would be redundant if the company could source more H100s. X's order of 12,000 H100s will be redirected to Tesla.
OpenAI has outlined the security architecture of its AI training supercomputers, emphasizing the protection of sensitive model weights and other assets using Azure-based infrastructure and Kubernetes for orchestration.
The team at OpenAI has discovered 16 million interpretable features in GPT-4 including price increases, algebraic rings, and who/what correspondence. This is a great step forward for SAE interpretability at scale. They shared the code in a companion GitHub repository.
The Together AI team has a novel VLM that excels at extremely high resolution images due to its efficient architecture.
Researchers have developed a novel approach called FFNification that transforms self-attention mechanisms into more efficient token mixers using only convolutions while keeping the query-key-value framework.
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Google has released a competitor to Gradio, a popular AI prototyping framework. Mesop is pure Python and has slightly more composability but is less mature than Gradio.
GrootVL is a network that improves state space models by dynamically generating a tree topology based on spatial relationships and input features.
Researchers have developed a new two-stage training method to improve Visual Geo-localization (VG), enhancing its performance in applications like autonomous driving, augmented reality, and SLAM.
The AI industry has seen several hype cycles throughout the decades, each producing genuinely useful technology and lasting longer than the last. Every cycle follows the process of a sigmoid curve rather than an exponential one. All strategies for developing the technology inevitably have a limit that doesn't take too long to find. While the current AI hype cycle is unlike any that have come before it, it will likely follow a similar trajectory as previous cycles.
Andreessen Horowitz put together a blog post and deck outlining the state of play for AI voice agents and where it sees opportunities for innovation and investment. It covers the currently leading infrastructure stack and maps out the current B2B and B2C application layer landscape.
Researchers have revisited the use of ReLU activation functions in learning implicit neural representations (INRs). Inspired by second-order B-spline wavelets, they introduced simple constraints to ReLU neurons to counter spectral bias.
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MMLU is the standard measure of reasoning and knowledge for language models.
Nvidia became the second most valuable company in the world on Wednesday afternoon as its market capitalization hit $3.01 trillion.
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Cartwheel, a motion synthesis start-up by our very own Andrew Carr, has raised a seed round led by Accel and KV. The company has built a text-to-animation tool and powerful integration into existing 3D workflows.
Mistral has launched customization for its models via its platform and API.
Google has scaled back AI Overviews. The AI-generated answers are now appearing in around 11 percent of queries, down from around 27 percent when the feature was launched last month. The company is still in the process of refining the feature. AI Overviews are appearing most in health-focused searches, despite the company highlighting the tool's use for shopping, restaurant recommendations, and travel in its marketing.
The operations research group at Google improved mathematical optimization for cargo shipping routes. They found a 13% reduction in fuel usage and costs.
Dream Mat is a great way to improve texture generation for 3D objects. It uses a number of classical graphic techniques such as Albedo, Metallic, and Roughness to render an extremely compelling output given a 3D mesh.
Researchers have introduced LlamaCare, a fine-tuned large language model (LLM) for medical knowledge, along with Extended Classification Integration (ECI) to address classification issues in LLMs.
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Security teams have long struggled to understand what's in their cloud environments and their exposure to risks. As part of Orca's move towards AI-driven cloud security [12], the platform now answers natural language questions such as “do we have any S3 Buckets that allow public READ access?”. Read more and see examples on the Orca
XRec is a model-agnostic framework that leverages the language capabilities of large language models to enhance explainable recommender systems.
GenS is an end-to-end generalizable neural surface reconstruction model that excels in reconstructing surfaces from multi-view images without 3D supervision.
Researchers have found a way to eliminate matrix multiplication (MatMul) from large language models while maintaining strong performance, even at the billion-parameter scale.