Globant reveals its 2024 Tech Trends
The annual report delves into key areas anticipated to undergo significant changes in the foreseeable future. Additionally, it presents fresh insights into consumer expectations regarding the utilization of artificial intelligence:…
Unveiling the Commonsense Reasoning Capabilities of Google Gemini: A Comprehensive Analysis Beyond Preliminary Benchmarks
Commonsense reasoning is an essential facet of human cognition that enables intuitive interpretation and interaction with the world. In NLP, this translates into the ability of LLMs and Multimodal Large…
Meet CLOVA: A Closed-Loop AI Framework for Enhanced Learning and Adaptation in Diverse Environments
The challenge of creating adaptable and versatile visual assistants has become increasingly evident in the rapidly evolving Artificial Intelligence. Traditional models often grapple with fixed capabilities and need help to…
Lisa P. Young appointed to Valo’s Board of Directors
Former Ernst and Young Senior Partner to serve as Chair of Audit Committee Valo Health, Inc (“Valo”), a technology company focused on utilizing large scale data and artificial intelligence (“AI”) driven computation…
FriendliAI announced the launch of Friendli Serverless Endpoints
FriendliAI, a leader in inference serving for generative AI, announced the launch of Friendli Serverless Endpoints today for accessible development with generative AI models. This service removes the technical barriers of managing…
This Paper Explores Deep Learning Strategies for Running Advanced MoE Language Models on Consumer-Level Hardware
With the widespread adoption of Large Language Models (LLMs), the quest for efficient ways to run these models on consumer hardware has gained prominence. One promising strategy involves using sparse…
MosaicML Proposes Modifying Chinchilla Scaling Laws to Account for Inference Costs when Determining Optimal LLM Size
LLMs represent a significant leap in understanding and generating human language. These models are instrumental in various AI applications, from automated translation to conversational agents. Their development involves a delicate…
This AI Paper from UT Austin and Meta AI Introduces FlowVid: A Consistent Video-to-Video Synthesis Method Using Joint Spatial-Temporal Conditions
In the domain of computer vision, particularly in video-to-video (V2V) synthesis, maintaining temporal consistency across video frames has been a persistent challenge. Achieving this consistency is crucial for synthesized videos’…
Google and MIT Researchers Introduce Synclr: A Novel AI Approach for Learning Visual Representations Exclusively from Synthetic Images and Synthetic Captions without any Real Data
Raw and frequently unlabeled data can be retrieved and organized using representation learning. The ability of the model to develop a good representation depends on the quantity, quality, and diversity…
Meet Vald: An Open-Sourced, Highly Scalable Distributed Vector Search Engine
The challenge of efficiently searching and retrieving information in digital data has become more pronounced. Traditional search methods need help with vast amounts of unstructured data like images, audio, videos,…