- Wed. Nov 27th, 2024
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SignalFire announces Strategic Growth adding Nine New Team Members
The firm is strengthening the team with new hires and promotions, deepening the commitment to helping innovative founders grow their businesses SignalFire, a tech-enabled early-stage venture capital firm harnessing data…
Meet Slope TransFormer: A Large Language Model (LLM) Trained Specifically to Understand the Language of Banks
In payments, understanding transactions is crucial for assessing risks in businesses. However, deciphering messy bank transaction data poses a challenge, as it is expressed in various ways across different banks.…
Anthropic Releases Claude 2.1: Revolutionizing Enterprise AI with Extended Context Window and Enhanced Accuracy
While various AI models exist, the recently launched Claude 2.1 by Anthropic addresses some of the prevailing issues. Unlike its predecessors, this model boasts a remarkable 200,000-token context window, allowing…
IBM collaborates with AWS to launch a New Cloud Database Offering
Combines IBM Db2 database and Amazon RDS to help businesses manage data with flexibility, security, and scalability to help unlock greater value IBM (NYSE: IBM) announced today at AWS re:Invent 2023 that…
This AI Paper from China Introduces ‘Monkey’: A Novel Artificial Intelligence Approach to Enhance Input Resolution and Contextual Association in Large Multimodal Models
Large multimodal models are becoming increasingly popular due to their ability to handle and analyze various data, including text and pictures. Academics have noticed their knowledge in various multimodal activities,…
Meet LEO: A Groundbreaking Embodied Multi-Modal Agent for Advanced 3D World Interaction and Task Solving
AI systems capable of handling multiple tasks or domains without significant reprogramming or retraining are generalist agents. These agents aim to generalize knowledge and skills across various domains, exhibiting flexibility…
Microsoft Researchers Propose PIT (Permutation Invariant Transformation): A Deep Learning Compiler for Dynamic Sparsity
Recently, deep learning has been marked by a surge in research aimed at optimizing models for dynamic sparsity. In this scenario, sparsity patterns only reveal themselves at runtime, posing a…
McMaster University and FAIR Meta Researchers Propose a Novel Machine Learning Approach by Parameterizing the Electronic Density with a Normalizing Flow Ansatz
Researchers from McMaster University and FAIR Meta have developed a new machine learning (ML) technique for orbital-free density functional theory (OF-DFT). This ML method optimizes the total energy function and…
‘Lookahead Decoding’: A Parallel Decoding Algorithm to Accelerate LLM Inference
Although large language models (LLMs) such as GPT-4 and LLaMA are rapidly reimagining modern-day applications, their inference is slow and difficult to optimize because it is based on autoregressive decoding.…
ETH Zurich Researchers Introduce UltraFastBERT: A BERT Variant that Uses 0.3% of its Neurons during Inference while Performing on Par with Similar BERT Models
The development of UltraFastBERT by researchers at ETH Zurich addressed the problem of reducing the number of neurons used during inference while maintaining performance levels similar to other models. It…