Research by the UK Treasury’s Productivity Programme has identified opportunities to reduce administrative work, harness AI, and improve public services. The Home Office will publish recommendations on utilizing AI for routine tasks, potentially saving teaching and police hours. AI is already being used in education and healthcare, with positive outcomes such as improved stroke treatment.…

Google Research, Google DeepMind, and the University of Waterloo have introduced SWIM-IR, a synthetic retrieval training dataset for multilingual retrieval models. Using the SAP method, the dataset allows for fine-tuning of dense retrieval models without human supervision. SWIM-X models trained on SWIM-IR show competitive performance on various benchmarks. The research highlights the potential of synthetic…

AI’s effectiveness heavily relies on data availability for training purposes. However, a study by University of Toronto Engineering researchers suggests that deep learning models may not always require a lot of training data. The researchers found that smaller subsets of data can be used to train models without compromising accuracy. The study emphasizes the significance…

Microsoft has officially announced its in-house designed chips, the Azure Maia 100 AI accelerator and Azure Cobalt CPU, at the Ignite conference. These chips demonstrate Microsoft’s commitment to innovation and self-sufficiency across hardware and software. They are set to power Azure’s AI workloads and will be integrated into specially designed server motherboards and racks. Microsoft…

GOAT is a universal navigation system developed by researchers from various universities and organizations. It operates autonomously in home and warehouse environments, using category labels, target images, and language descriptions to interpret goals. GOAT creates a 3D semantic voxel map for accurate object detection and memory storage, and it has demonstrated superior performance in reaching…

Researchers from MIT and IAIFI have developed a framework called Feature Fields for Robotic Manipulation (F3RM), which addresses the challenge of enabling robots to manipulate objects in cluttered environments. F3RM leverages distilled feature fields to combine 3D geometry with semantic information from 2D models, bridging the gap between 2D image features and 3D geometry. The…

UrbanGIRAFFE, a new approach by researchers from Zhejiang University, addresses the challenges in generating urban scenes for camera viewpoint control and scene editing. By breaking down the scene into stuff, objects, and sky, the model allows for diverse controllability, including large camera movements and object manipulation. UrbanGIRAFFE outperforms existing methods and offers remarkable versatility for…

Researchers from the University of Washington and Microsoft have developed noise-canceling headphones with semantic hearing capabilities, enabled by advanced machine learning algorithms. These headphones allow users to selectively choose the sounds they want to hear while blocking out other distractions. The innovation relies on a smartphone’s powerful neural network for sound processing and has the…

MIT researchers have developed MechGPT, a novel model for extracting insights from scientific texts in the field of materials science. MechGPT employs a two-step process using a general-purpose language model to generate question-answer pairs and enhance clarity. The model is trained using PyTorch and the Hugging Face ecosystem, with additional techniques such as Low-Rank Adaptation…

Researchers at NVIDIA have introduced a GPU-accelerated Weighted Finite State Transducer (WFST) beam search decoder that improves the performance of Automated Speech Recognition (ASR) systems. The decoder enhances efficiency, reduces latency, and supports advanced features like on-the-fly composition for word boosting. In offline testing, the GPU-accelerated decoder showed seven times higher throughput compared to the…