Researchers from ETH Zurich and Microsoft Introduce SliceGPT for Efficient Compression of Large Language Models through Sparsification
Large language models (LLMs) like GPT-4 require substantial computational power and memory, posing challenges for their efficient deployment. While sparsification methods have been developed to mitigate these resource demands, they…
This AI Paper Introduces Investigate-Consolidate-Exploit (ICE): A Novel AI Strategy to Facilitate the Agent’s Inter-Task Self-Evolution
A groundbreaking development is emerging in artificial intelligence and machine learning: intelligent agents that can seamlessly adapt and evolve by integrating past experiences into new and diverse tasks. These agents,…
Researchers from the University of Kentucky Propose MambaTab: A New Machine Learning Method based on Mamba for Handling Tabular Data
With its structured format, Tabular data dominates the data analysis landscape across various sectors such as industry, healthcare, and academia. Despite the surge in the use of images and texts…
Meet DrugAssist: An Interactive Molecule Optimization Model that can Interact with Humans in Real-Time Using Natural Language
With the rise of Large Language Models (LLMs) in recent years, generative AI has made significant strides in the field of language processing, showcasing impressive abilities in a wide array…
A decoder-only foundation model for time-series forecasting
Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturing, healthcare and natural sciences. In retail use cases, for…
Intervening on early readouts for mitigating spurious features and simplicity bias
Posted by Rishabh Tiwari, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research Machine learning models in the real world are often trained on limited data that may contain unintended…
Seeking Faster, More Efficient AI? Meet FP6-LLM: the Breakthrough in GPU-Based Quantization for Large Language Models
In computational linguistics and artificial intelligence, researchers continually strive to optimize the performance of large language models (LLMs). These models, renowned for their capacity to process a vast array of…
Seeking Speed without Loss in Large Language Models? Meet EAGLE: A Machine Learning Framework Setting New Standards for Lossless Acceleration
For LLMs, auto-regressive decoding is now considered the gold standard. Because LLMs generate output tokens individually, the procedure is time-consuming and expensive. Methods based on speculative sampling provide an answer…
Bank of England Governor: AI won’t lead to mass job losses
Andrew Bailey, Governor of the Bank of England, has rebutted fears that AI will lead to widespread unemployment. “I’m an economic historian, before I became a central banker. Economies adapt,…
Aetina introduces New MXM GPUs Powered by NVIDIA Ada Lovelace
Aetina, a leading global Edge AI solution provider, announces the release of its new embedded MXM GPU series utilizing the NVIDIA Ada Lovelace architecture – MX2000A-VP, MX3500A-SP, and MX5000A-WP. Designed for real-time ray…