Viral News - CybAI news

27 May

Data Augmentation Method Utilizing Template Sentences for Variable Definition Extraction

stp2y0 CommentsViral News

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

27 May

Data Machina #237

stp2y0 CommentsViral News

AI Code Generation: A New Paradigm. Several developer surveys indicate that devs -especially Sr. devs- who use AI tools are “more productive.” Today you can use lots of AI tools for code completion, pair programming, data generation, an even having a team of AI coding agents to complete tedious tasks for you. Back in October, the team at DeepSense wrote an excellent blogpost on the state of the art in AI coding agents, detailing the pros & cos, and workflows of each AI coding agent. Worth mentioning that -fundamentally- all these AI coding agents are mostly based on prompt engineering,…

27 May

Six Use Cases of Conversational AI in Public Sector Governance

stp2y0 CommentsViral News

Today's citizens expect seamless, convenient interactions with government entities, akin to the experiences they have with consumer-facing businesses. However, public sector organizations often struggle to meet these rising expectations due to limited resources, complex bureaucracies, and outdated technological infrastructures. This is where conversational AI – including technologies like chatbots and virtual assistants – emerges as a powerful tool for enhancing public services. It uses the power of natural language processing (NLP) and machine learning to transform how citizens interact with government services. This allows public sector organizations to streamline processes, enhance citizen engagement, and deliver more efficient and responsive governance.…

27 May

Disrupting the Status Quo Through Data and AI: Celebrating the 2024 Data Team Disruptor Award Nominees

stp2y0 CommentsViral News

The annual Data Team Awards highlight how diverse enterprise data teams are tackling some of the most prevalent and complex issues facing the business world.This year, more than 200 nominations reflect a variety of industries from around the world. Spread across six distinct categories, these finalists highlight the exceptional creativity and ingenuity that organizations apply in their data and AI endeavors. We're excited to share this groundbreaking work with our community of data experts and enthusiasts. The Data Team Disruptor Award recognizes the enterprise data teams fundamentally changing how their field approaches data management and activation. Honoring those who challenge the…

27 May

Reservoir Computing with Generalized Readout based on Generalized Synchronization

stp2y0 CommentsViral News

[Submitted on 3 May 2024] View a PDF of the paper titled Reservoir Computing with Generalized Readout based on Generalized Synchronization, by Akane Ookubo and Masanobu Inubushi View PDF HTML (experimental) Abstract:Reservoir computing is a machine learning framework that exploits nonlinear dynamics, exhibiting significant computational capabilities. One of the defining characteristics of reservoir computing is its low cost and straightforward training algorithm, i.e. only the readout, given by a linear combination of reservoir variables, is trained. Inspired by recent mathematical studies based on dynamical system theory, in particular generalized synchronization, we propose a novel reservoir computing framework with generalized readout,…

27 May

Investigating Robustness of Open-Vocabulary Foundation Object Detectors under Distribution Shifts

stp2y0 CommentsViral News

[Submitted on 1 Apr 2024] View a PDF of the paper titled Investigating Robustness of Open-Vocabulary Foundation Object Detectors under Distribution Shifts, by Prakash Chandra Chhipa and 4 other authors View PDF Abstract:The challenge of Out-Of-Distribution (OOD) robustness remains a critical hurdle towards deploying deep vision models. Open-vocabulary object detection extends the capabilities of traditional object detection frameworks to recognize and classify objects beyond predefined categories. Investigating OOD robustness in open-vocabulary object detection is essential to increase the trustworthiness of these models. This study presents a comprehensive robustness comparison of zero-shot capabilities of three recent open-vocabulary foundation object detection models,…

27 May

DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning

stp2y0 CommentsViral News

arXiv:2405.14899v1 Announce Type: new Abstract: In-context learning (ICL) allows transformer-based language models that are pre-trained on general text to quickly learn a specific task with a few "task demonstrations" without updating their parameters, significantly boosting their flexibility and generality. ICL possesses many distinct characteristics from conventional machine learning, thereby requiring new approaches to interpret this learning paradigm. Taking the viewpoint of recent works showing that transformers learn in context by formulating an internal optimizer, we propose an influence function-based attribution technique, DETAIL, that addresses the specific characteristics of ICL. We empirically verify the effectiveness of our approach for demonstration attribution…

27 May

Data Machina #238

stp2y0 CommentsViral News

Non-stop AI Innovation Every Single Week. Well yeah, thats’s right: There is no single week without something new, exciting, or amazing happening in AI. This is a selection of interesting, cool stuff that happened in the last 7 days or so:OpenAI introduced new, faster, and more efficient embedding models. Buried in the blog announcement, it says: “the new embedding models were trained with a technique that allows developers to shorten embeddings without the embedding losing its concept-representing properties.” Well - for some reason- it seems the blog fails to mention that the technique is called Matryoshka Representation Learning (paper, repo),…

27 May

Improving Text2SQL Performance with Ease on Databricks

stp2y0 CommentsViral News

Want to raise your LLM into the top 10 of Spider, a widely used benchmark for text-to-SQL tasks? Spider evaluates how well LLMs can convert text queries into SQL code.For those unfamiliar with text-to-SQL, its significance lies in transforming how businesses interact with their data. Instead of relying on SQL experts to write queries, people can simply ask questions of their data in plain English and receive precise answers. This democratizes access to data, enhancing business intelligence and enabling more informed decision-making.The Spider benchmark is a widely recognized standard for evaluating the performance of text-to-SQL systems. It challenges LLMs to…

27 May

Data Machina #239

stp2y0 CommentsViral News

The Power of Truly Open Source AI. The spin doctors of some big closed-AI companies have been busy inflating the “AGI is here soon, AGI will be an existential risk” bubble. But that thankfully that is deflating quickly, and backfiring somehow. In the meantime, the open source AI community is stubbornly embarked upon releasing truly open source, efficient, smallish, powerful AI models that match or beat the closed AI models from big companies. The reaction from these big closed AI companies: “Oh! open source AI models are dangerous, we need to regulate open source AI. And btw: We’re dropping the…