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In artificial intelligence, evaluating the performance of language models presents a unique challenge. Unlike image recognition or numerical predictions, language quality assessment doesn’t yield to simple binary measurements. Enter BLEU (Bilingual Evaluation Understudy), a metric that has become the cornerstone of machine translation evaluation since its introduction by IBM researchers in 2002.
[link] In what is becoming an annual tradition for the @HPCpodcast, we present “Live from Nvidia GTC 2025,” covering highlights from the Nvidia extravaganza with an AI-everywhere theme.
On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deep learning" could achieve things conventional AI techniques could not. Deep learning , which uses multi-layered neural networks that can learn from data without explicit programming, represented a significant departure from traditional AI approaches that relied on hand-crafted ru
In this work, we dive into the fundamental challenges of evaluating Text2SQL solutions and highlight potential failure causes and the potential risks of relying on aggregate metrics in existing benchmarks. We identify two largely unaddressed limitations in current open benchmarks: (1) data quality issues in the evaluation data mainly attributed to the lack of capturing the probabilistic nature of translating a natural language description into a structured query (e.g., NL ambiguity), and (2) the
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
We introduce SmolDocling, an ultra-compact vision-language model targeting end-to-end document conversion. Our model comprehensively processes entire pages by generating DocTags, a new universal markup format that captures all page elements in their full context with location. Unlike existing approaches that rely on large foundational models, or ensemble solutions that rely on handcrafted pipelines of multiple specialized models, SmolDocling offers an end-to-end conversion for accurately capturi
Digital documents have long presented a dual challenge for both human readers and automated systems: preserving rich structural nuances while converting content into machine-processable formats. Traditional methods, whether relying on complex ensemble pipelines or massive foundational models, often struggle to balance accuracy with computational efficiency.
For all the revolutionary change artificial intelligence promises, it also makes lofty demands. For starters, AI is extraordinarily power hungry. Generating all the electricity that AI datacenters consume takes forest-loads of energy, not to mention hardware and cooling infrastructure. That stuff all costs a lot, making AI a huge money pit. That's had a big effect on our economy, as the tiniest bit of AI hype can send huge shockwaves through Wall Street and beyond.
Natural language processing models including the wide variety of contemporary large language models (LLMs) have become popular and useful in recent years as their application to a wide variety of problem domains have become increasingly capable, especially those related to text generation.
This is a collection of (mostly) pen-and-paper exercises in machine learning. The exercises are on the following topics: linear algebra, optimisation, directed graphical models, undirected graphical models, expressive power of graphical models, factor graphs and message passing, inference for hidden Markov models, model-based learning (including ICA and unnormalised models), sampling and Monte-Carlo integration, and variational inference.
Large language models answer questions using the knowledge they learned during training. This fixed knowledge base limits them. They can’t give you current or highly specific information. Retrieval-Augmented Generation (RAG) helps by letting LLMs pull in external data, but even RAG needs help with complex questions. Adaptive RAG offers a solution.
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
Youd think predicting dementia death rates or mapping city noise would require teams of experts, ground surveys, and satellite imaging firms. But a new AI modeldeveloped by researchers at Beijing Jiaotong University and the University of Montrealclaims it can do all of that at once, just by looking at maps, tweets, and images. The system is called OmniGeo , and if the research lives up to its promise, it could redefine how we read cities, disasters, and human environments in real time.
IT operations teams face the challenge of providing smooth functioning of critical systems while managing a high volume of incidents filed by end-users. Manual intervention in incident management can be time-consuming and error prone because it relies on repetitive tasks, human judgment, and potential communication gaps. Using generative AI for IT operations offers a transformative solution that helps automate incident detection, diagnosis, and remediation, enhancing operational efficiency.
This post is divided into three parts; they are: Setting up the translation pipeline Translation with alternatives Quality estimation Text translation is a fundamental task in natural language processing, and it inspired the invention of the original transformer model.
All My Blog Posts In OnePlace (And its not thisplace.) If youre one of my 178,000 readers here on medium.com, I invite you to join me for a last hurrah before I migrate my articles from this hallowed platform to my newsletter and I offer you something in what might be our mutual love language: a spreadsheet! This spreadsheet. In it, youll find a link to every single medium.com blog post Ive ever published, along with its FriendLink.
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
Tired of manually sifting through hours of audio to find key insights? This guide teaches you to build an AI-powered chatbot that transforms recordings – meetings, podcasts, interviewsinto interactive conversations. Using AssemblyAI for precise transcription with speaker labels, Qdrant for fast data storage, and DeepSeek-R1 via SambaNova Cloud for smart responses, youll create a RAG […] The post Build an Audio RAG with AssemblyAI, Qdrant & DeepSeek-R1 appeared first on Analytics
Generative AI is revolutionizing how businesses interact with their customers through natural conversational interfaces. While organizations can implement AI assistants across various channels, phone calls remain a preferred method for many customers seeking support or information.
Large language models are challenging to adapt to new enterprise tasks. Prompting is error-prone and achieves limited quality gains, while fine-tuning requires large amounts of.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data. However, by using Anthropics Claude on Amazon Bedrock , researchers and engineers can now automate the indexing and tagging of these technical documents.
Bloomberg Law announced its participation in Legalweek, where it will highlight its commitment to enhancing legal professionals’ efficiency through advanced AI-powered solutions and workflow tools. The company will showcase its latest innovations, designed to empower attorneys in a rapidly evolving legal and technological landscape. At Legalweek, Bloomberg Law will feature its comprehensive legal technology, focusing on: AI-powered legal intelligence solutions: Newly released tools like Co
By combining AI agents, you can build an application that not only answers questions and searches the internet but also performs computations and visualizes data effectively.
Forget chatbots and prompt engineering agentic is the latest AI buzzword to captivate and confuse marketers and media execs. In recent months, tech firms like OpenAI have emphasized AI agents and agentic applications of the technology in their mission to popularize generative AI adoption. The latest development comes courtesy of Adobe, which unveiled several AI agent tools last week at its Summit conference in Las Vegas , including a foundation agentic platform and 10 off-the-shelf AI agents.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
UiPath (NYSE: PATH), an enterprise automation and AI software company, today announced the launch of UiPath Test Cloud, a new approach to software testing that uses AI to amplify tester productivity across the testing lifecycle, designed for.
Cybersecurity is increasingly crucial in our digitized world, where personal, financial, and corporate data are constantly at risk of exposure. As cyber threats evolve and become more sophisticated, the need for effective cybersecurity measures is paramount. Organizations must adapt to an array of challenges, employing a multifaceted approach to safeguarding their assets and maintaining trust with their clients.
Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com
Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.
Databricks Apps provide a robust platform for building and hosting interactive applications. React is great for building modern, dynamic web applications that need to update.
ACM, the Association for Computing Machinery, today named Torsten Hoefler, a professor at ETH Zurich, the recipient of the ACM Prize in Computing for fundamental contributions to high-performance computing and the ongoing AI revolution.
For the Washington Post, Emily Giambalvo, Kati Perry, and Jesse Dougherty analyze the playing time for players who transferred from another program. To understand the phenomenon and its impact, look no further than the mens and womens NCAA tournament fields. On the mens side, 53 percent of all rotation players previously logged minutes at another Division I school, according to a Washington Post analysis.
Golden datasets play a pivotal role in the realms of artificial intelligence (AI) and machine learning (ML). They provide a foundation for training algorithms, ensuring that models can make accurate decisions and predictions. As AI technology continues to evolve, the significance of these meticulously curated data collections becomes increasingly apparent.
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
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