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Evaluating the performance of Large Language Models (LLMs) is an important and necessary step in refining it. LLMs are used in solving many different problems ranging from text classification and information extraction. Choosing the correct metrics to measure the performance of an LLM can greatly increase the effectiveness of the model. In this blog, we will explore one such crucial metric the F1 score.
NEW YORK,Jan. 23, 2025 — Digital Power Optimization, Inc. (“DPO”), a developer and operator of power-dense data centers, today announced it has secured land and a power supply to develop a $200 millionhigh-performance computing facility inWisconsin Rapids, WI. This project will enable up to 20 megawatts of AI computing.
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale Publicly available datasets in recommender research currently shaping the field.
TL;DR: The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architectures with less specialized modules. To test this, we trained reinforcement learning agents with various neural architectures on a naturalistic navigation task.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
At Apple, we believe privacy is a fundamental human right. And we believe in giving our users a great experience while protecting their privacy. For years, weve used techniques like differential privacy as part of our opt-in device analytics program. This lets us gain insights into how our products are used, so we can improve them, while protecting user privacy by preventing Apple from seeing individual-level data from those users.
Ever waited too long for a model to return predictions? We have all been there. Machine learning models, especially the large, complex ones, can be painfully slow to serve in real time. Users, on the other hand, expect instant feedback. That’s where latency becomes a real problem. Technically speaking, one of the biggest problems is […] The post Accelerate Machine Learning Model Serving With FastAPI and Redis Caching appeared first on Analytics Vidhya.
Ever waited too long for a model to return predictions? We have all been there. Machine learning models, especially the large, complex ones, can be painfully slow to serve in real time. Users, on the other hand, expect instant feedback. That’s where latency becomes a real problem. Technically speaking, one of the biggest problems is […] The post Accelerate Machine Learning Model Serving With FastAPI and Redis Caching appeared first on Analytics Vidhya.
Introduction Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise. Data scientists, machine learning practitioners, and AI engineers alike can fall into common training or fine-tuning patterns that could compromise a model’s performance or scalability.
Phishing emails, those deceptive messages designed to steal sensitive information, remain a significant cybersecurity threat. As attackers devise increasingly sophisticated tactics, traditional detection methods often fall short. Researchers from the University of Auckland, have introduced a novel approach to combat this issue. Their paper, titled “ MultiPhishGuard: An LLM-based Multi-Agent System for Phishing Email Detection ,” authored by Yinuo Xue, Eric Spero, Yun Sing Koh, and Gi
In March of 2023 we announced that we were starting work on a safer high performance AV1 decoder called rav1d, written in Rust. We partnered with Immunant to do the engineering work. By September of 2024 rav1d was basically complete and we learned a lot during the process. Today rav1d works wellit passes all the same tests as the dav1d decoder it is based on, which is written in C.
OpenAI is moving to publish the results of its internal AI model safety evaluations more regularly in what the outfit is saying is an effort to increase transparency.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
It is easy to forget how much our devices do for us until your smart assistant dims the lights, adjusts the thermostat, and reminds you to drink water, all on its own. That seamless experience is not just about convenience, but a glimpse into the growing world of agentic AI. Whether it is a self-driving car navigating rush hour or a warehouse robot dodging obstacles while organizing inventory, agentic AI is quietly revolutionizing how things get done.
Donostia, Spain April 8, 2025 Multiverse Computing today released two new AI models compressed by CompactifAI, Multiverse’s AI compressor: 80 percent compressed versions of Llama 3.1-8B and Llama 3.3-70B.
Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Integrating DuckDB & Python: An Analytics Guide Learn how to run lightning-fast SQL queries on local files with ease.
( Dylan Foster and Alex Lamb both helped in creating this.) In thinking about what are good research problems, its sometimes helpful to switch from what is understood to what is clearly possible. This encourages us to think beyond simply improving the existing system. For example, we have seen instances throughout the history of machine learning where researchers have argued for fixing an architecture and using it for short-term success, ignoring potential for long-term disruption.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
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With Apple Intelligence, we're integrating powerful generative AI right into the apps and experiences people use every day, all while protecting their privacy. At the 2025 Worldwide Developers Conference we introduced a new generation of language foundation models specifically developed to enhance the Apple Intelligence features in our latest software releases.
In the era of AI, chatbots have revolutionized how we interact with technology. Perhaps one of the most impactful uses is in the healthcare industry. Chatbots are able to deliver fast, accurate information, and help individuals more effectively manage their health. In this article, we’ll learn how to develop a medical chatbot using Gemini 2.0, […] The post Building a Medical Chatbot with Gemini 2.0, Flask and Vector Embedding appeared first on Analytics Vidhya.
Fine-tuning a large language model (LLM) is the process of taking a pre-trained model — usually a vast one like GPT or Llama models, with millions to billions of weights — and continuing to train it, exposing it to new data so that the model weights (or typically parts of them) get updated.
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
Microsoft has released a new preview update, KB5050094 , for Windows 11 24H2 on Tuesday, which aims to fix multiple bugs affecting the operating system, including issues arising from the January Patch Tuesday update. Microsoft releases preview update KB5050094 for Windows 11 24H2 KB5050094 addresses audio issues where USB headphones, as well as other devices connected through a digital-to-analog converter (DAC), failed to produce sound, displaying the error message: “Insufficient system re
Today's AI systems have human-designed, fixed architectures and cannot autonomously and continuously improve themselves. The advance of AI could itself be automated. If done safely, that would accelerate AI development and allow us to reap its benefits much sooner. Meta-learning can automate the discovery of novel algorithms, but is limited by first-order improvements and the human design of a suitable search space.
AI use in higher education is becoming more popular for students and professors. Ella Stapleton noticed in February that the lecture notes for her organizational behavior class at Northeastern University appeared to have been generated by ChatGPT.
Artificial intelligence is evolving rapidly, reshaping industries from healthcare to finance, and even creative arts. If you want to stay ahead of the curve, networking with top AI minds, exploring cutting-edge innovations, and attending AI conferences is a must. According to Statista, the AI industry is expected to grow at an annual rate of 27.67% , reaching a market size of US$826.70bn by 2030.
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?
NVIDIA said it has achieved a record large language model (LLM) inference speed, announcing that an NVIDIA DGX B200 node with eight NVIDIA Blackwell GPUs achieved more than 1,000tokens per second (TPS) per user on the 400-billion-parameter Llama 4 Maverick model.
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.
Sign languages are essential for the Deaf and Hard-of-Hearing (DHH) community. Sign language generation systems have the potential to support communication by translating from written languages, such as English, into signed videos. However, current systems often fail to meet user needs due to poor translation of grammatical structures, the absence of facial cues and body language, and insufficient visual and motion fidelity.
In this article, we dive into the concepts of machine learning and artificial intelligence model explainability and interpretability. We explore why understanding how models make predictions is crucial, especially as these technologies are used in critical fields like healthcare, finance, and legal systems. Through tools like LIME and SHAP, we demonstrate how to gain insights […] The post ML and AI Model Explainability and Interpretability appeared first on Analytics Vidhya.
Introduction Text-based adventure games have a timeless appeal. They allow players to imagine entire worlds, from shadowy dungeons and towering castles to futuristic spacecraft and mystic realms, all through the power of language.
You’ve experienced it. That flash of frustration when ChatGPT, despite its incredible power, responds in a way that feels… off. Maybe it’s overly wordy, excessively apologetic, weirdly cheerful, or stubbornly evasive. While we might jokingly call it an “annoying personality,” it’s not personality at all. It’s a complex mix of training data, safety protocols, and the inherent nature of large language models (LLMs).
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?
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