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When Sam Altman announced an April 25 update to OpenAI's ChatGPT-4o model, he promised it would improve "both intelligence and personality" for the AI model. The update certainly did something to its personality, as users quickly found they could do no wrong in the chatbot's eyes. Everything ChatGPT-4o spat out was filled with an overabundance of glee.
Reinforcement learning with verifiable rewards (RLVR) has shown promise in enhancing the reasoning capabilities of large language models by learning directly from outcome-based rewards. Recent RLVR works that operate under the zero setting avoid supervision in labeling the reasoning process, but still depend on manually curated collections of questions and answers for training.
Organizations run AI competitions for a variety of reasons. They want to engage the expertise of a global community. They want to push the limits of available methods for their needs. They want to explore innovative approaches and surface new ideas. They want to benchmark the level of performance that can be achieved with their data. At the end of a competition, these organizations get a few things: Winning solutions, consisting of research code in a Github repository and often shared openly for
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.
San Francisco May 14, 2025 Today, Openlayer, a platform for evaluation and governance of AI systems at the enterprise level, announced a $14.5 million Series A round led by Race Capital with participation from NXTP, KPN Ventures, Mindset, Y Combinator, Quiet Capital, and Telefonica.
San Francisco May 14, 2025 Today, Openlayer, a platform for evaluation and governance of AI systems at the enterprise level, announced a $14.5 million Series A round led by Race Capital with participation from NXTP, KPN Ventures, Mindset, Y Combinator, Quiet Capital, and Telefonica.
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.
NVIDIA announced a partnership with HUMAIN, the AI subsidiary of Saudi Arabias Public Investment Fund, to build AI factories in the kingdom. HUMAIN said the partnership will develop a projected capacity of up to 500 megawatts powered by several hundred thousand of.
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.
Coding is among the top uses of LLMs as per a Harvard 2025 report. Engineers and developers around the world are now using AI to debug their code, test it, validate it, or write scripts for it. In fact, with the way current LLMs are performing at generating code, soon they will be almost like […] The post Gemini 2.5 Pro vs Claude 3.7 Sonnet: Which is Better for Coding Tasks?
Azure Databricks is a first-party Microsoft service, natively integrated with the Azure ecosystem to unify data and AI with high-performance analytics and deep tooling support.
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: 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
With the rise of traffic from AI agents, whats considered a bot is no longer clear-cut. There are some clearly malicious bots, like ones that DoS your site or do credential stuffing, and ones that most site owners do want to interact with their site, like the bot that indexes your site for a search engine, or ones that fetch RSS feeds. Historically, Cloudflare has relied on two main signals to verify legitimate web crawlers from other types of automated traffic: user agent headers and IP address
In a market clamoring for more computational muscle to power the insatiable demands of artificial intelligence, a new contender has emerged from the silicon shadows. TensorWave , a company laser-focused on delivering AI infrastructure built around AMD’s cutting-edge silicon, announced a significant milestone today: a $100 million Series A funding round co-led by investment heavyweight Magnetar and AMD’s venture arm.
Today were announcing the launch of Data Intelligence for Marketing, combining the Databricks Data Intelligence Platform with out-of-the-box integrations to an ecosystem of leading marketing
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.
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.
If youre a student or early professional eager to apply your Machine Learning skills in the real world, an internship is your best starting point. From GenAI-driven logistics to AI-powered finance and legal tech, companies across India are offering exciting ML roles that go far beyond textbook theory. These internships dont just pay – they […] The post 5 Machine Learning Internships in India (2025) appeared first on Analytics Vidhya.
New AI agent evolves algorithms for math and practical applications in computing by combining the creativity of large language models with automated evaluators
AI startup Stability AI has released Stable Audio Open Small, a stereo audio-generating AI model that the company claims is the fastest on the market and efficient enough to run on smartphones.
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?
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.
Modern AI models are advancing at breakneck speed, but the way we evaluate them has barely kept pace. Traditional benchmarks tell us whether a model passed or failed a test but rarely offer insights into why it performed the way it did or how it might fare on unfamiliar challenges. A new research effort from Microsoft and its collaborators proposes a rigorous framework that reimagines how we evaluate AI systems.
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
As the field of AI is evolving, Retrieval-Augmented Generation (RAG) has emerged as a turning point in the field of Artificial Intelligence. Now vision RAG integrates these abilities into the visual space by integrating images, diagrams, and videos. Vision RAG enables models to produce responses that are not just textually correct but visually enriched.
Windsurf, the startup best known for its AI coding assistant tools, has launched a new set of proprietary models aimed at redefining how AI supports software engineering. The newly introduced family includes three models: SWE-1, SWE-1-lite, and SWE-1-mini. Unlike traditional code-generation tools, these models are designed to support the entire software engineering process from end to end.
Googles AI R&D lab DeepMind says it has developed a new AI system to tackle problems with machine-gradable solutions. In experiments, the system, called AlphaEvolve, could help optimize some of the infrastructure Google uses to train its AI models, DeepMind said.
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!
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