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Artificial intelligence has made remarkable strides in recent years, with large language models (LLMs) leading in natural language understanding, reasoning, and creative expression. Yet, despite their capabilities, these models still depend entirely on external feedback to improve. Unlike humans, who learn by reflecting on their experiences, recognizing mistakes, and adjusting their approach, LLMs lack an internal mechanism for self-correction.
Google has launched Gemma 3, the latest version of its family of open AI models that aim to set a new benchmark for AI accessibility. Built upon the foundations of the companys Gemini 2.0 models, Gemma 3 is engineered to be lightweight, portable, and adaptableenabling developers to create AI applications across a wide range of devices. This release comes hot on the heels of Gemmas first birthday, an anniversary underscored by impressive adoption metrics.
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.
You can only throw so much money at a problem. This, more or less, is the line being taken by AI researchers in a recent survey. Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed.
Start building the AI workforce of the future with our comprehensive guide to creating an AI-first contact center. Learn how Conversational and Generative AI can transform traditional operations into scalable, efficient, and customer-centric experiences. What is AI-First? Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
I’ve had several conversations about using LLMs over the past few weeks where the people I talked to had little idea of what LLMs could and could not do, and how LLMs could and could not help them. Which is worrying, because if we want AI to actually help people, them the people being helped need to understand what to use AI for! A few examples: A student was trying to use obscure software library, could not not find info.
Every second, businesses worldwide are making critical decisions. A logistics company decides which trucks to send where. A retailer figures out how to stock its shelves. An airline scrambles to reroute flights after a storm. These arent just routing choices theyre high-stakes puzzles with millions of variables, and getting them wrong costs money and, sometimes, customers.
Every second, businesses worldwide are making critical decisions. A logistics company decides which trucks to send where. A retailer figures out how to stock its shelves. An airline scrambles to reroute flights after a storm. These arent just routing choices theyre high-stakes puzzles with millions of variables, and getting them wrong costs money and, sometimes, customers.
For years, Artificial Intelligence (AI) has made impressive developments, but it has always had a fundamental limitation in its inability to process different types of data the way humans do. Most AI models are unimodal, meaning they specialize in just one format like text, images, video, or audio. While adequate for specific tasks, this approach makes AI rigid, preventing it from connecting the dots across multiple data types and truly understanding context.
The newly-formed Autoscience Institute has unveiled Carl, the first AI system crafting academic research papers to pass a rigorous double-blind peer-review process. Carls research papers were accepted in the Tiny Papers track at the International Conference on Learning Representations (ICLR). Critically, these submissions were generated with minimal human involvement, heralding a new era for AI-driven scientific discovery.
yFiles is a powerful SDK designed to simplify the visualization of complex networks and data relationships. When combined with LlamaIndex, it becomes a powerful tool for visualizing and interacting with knowledge graphs in real time. This guide walks you through the integration process, highlights essential steps, and demonstrates key features for an impactful, useful and […] The post How to Integrate yFiles with LlamaIndex for Knowledge Graph Visualization?
A new study examining meme creation found that AI-generated meme captions on existing famous meme images scored higher on average for humor, creativity, and "shareability" than those made by people. Even so, people still created the most exceptional individual examples. The research, which will be presented at the 2025 International Conference on Intelligent User Interfaces , reveals a nuanced picture of how AI and humans perform differently in humor creation tasks.
Today’s buyers expect more than generic outreach–they want relevant, personalized interactions that address their specific needs. For sales teams managing hundreds or thousands of prospects, however, delivering this level of personalization without automation is nearly impossible. The key is integrating AI in a way that enhances customer engagement rather than making it feel robotic.
Powered by metronome.com Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Heres why Google pitched its $32B Wiz acquisition as multicloud Tuesdays big news that Google is acquiring security startup Wiz for a record-breaking $32 billion comes with a very big qualifier. techcrunch.com Sponsor Transitioning to Usage-Based Pricing Webinar with Sam Lee Join Sam Lee and Scott Woody for a
Smart technology is no longer a luxury for businesses but a critical driver of efficiency, growth, and innovation. As technology advances, companies are continually seeking ways to stay ahead in a highly competitive landscape, and the integration of smart solutions plays a pivotal role in shaping their future. By leveraging emerging technologies, businesses can streamline operations, improve productivity, and unlock new paths for innovation.
Moores Law was the gold standard for predicting technological progress for years. Introduced by Gordon Moore, co-founder of Intel, in 1965, it stated that the number of transistors on a chip would double every two years, making computers faster, smaller, and cheaper over time. This steady advancement fuelled everything from personal computers and smartphones to the rise of the internet.
The way we interact with our computers and smart devices is very different from previous years. Over the decades, human-computer interfaces have transformed, progressing from simple cardboard punch cards to keyboards and mice, and now extended reality-based AI agents that can converse with us in the same way as we do with friends. With each advance in human-computer interfaces, we’re getting closer to achieving the goal of interactions with machines, making computers more accessible and in
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
I still remember last year’s NVIDIA GTC, Jensen Huang with its visionary approach along with a touch of humour introduced the developers with promises to redefine technology. From Blackwell architecture, Generative AI with NIM, GB200 AI Chip to Project Groot and other things, we got a glimpse into the future of technology. Now the future […] The post 10 NVIDIA GTC 2025 Announements that You Must Know appeared first on Analytics Vidhya.
There's a new Google AI model in town, and it can generate or edit images as easily as it can create textas part of its chatbot conversation. The results aren't perfect, but it's quite possible everyone in the near future will be able to manipulate images this way. Last Wednesday, Google expanded access to Gemini 2.0 Flash's native image generation capabilities, making the experimental feature available to anyone using Google AI Studio.
Whats next in AI is at GTC 2025. Not only the technology, but the people and ideas that are pushing AI forward creating new opportunities, novel solutions and whole new ways of thinking. For all of that, this is the place. Heres where to find the news, hear the discussions, see the robots and ponder the just-plain mind-blowing. From the keynote to the final session, check back for live coverage kicking off when the doors open on Monday, March 17, in San Jose, California.
Gartner predicts that by 2027, 40% of generative AI solutions will be multimodal (text, image, audio and video) by 2027, up from 1% in 2023. The McKinsey 2023 State of AI Report identifies data management as a major obstacle to AI adoption and scaling. Enterprises generate massive volumes of unstructured data, from legal contracts to customer interactions, yet extracting meaningful insights remains a challenge.
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Just as the dust begins to settle on DeepSeek , another breakthrough from a Chinese startup has taken the internet by storm. This time, its not a generative AI model, but a fully autonomous AI agent, Manus , launched by Chinese company Monica on March 6, 2025. Unlike generative AI models like ChatGPT and DeepSeek that simply respond to prompts, Manus is designed to work independently, making decisions, executing tasks, and producing results with minimal human involvement.
Hugging Face has called on the US government to prioritise open-source development in its forthcoming AI Action Plan. In a statement to the Office of Science and Technology Policy (OSTP), Hugging Face emphasised that thoughtful policy can support innovation while ensuring that AI development remains competitive, and aligned with American values. Hugging Face, which hosts over 1.5 million public models across various sectors and serves seven million users, proposes an AI Action Plan centred on th
Imagine a journalist piecing together a storynot just relying on memory but searching archives and verifying facts. Thats how a Retrieval-Augmented Generation (RAG) model works, retrieving real-time knowledge for better accuracy. Just like strong research skills, choosing the best embedding for the RAG model is also crucial for retrieving and ranking relevant information.
AI search tools confidently spit out wrong answers at a high clip, a new study found. Columbia Journalism Review (CJR) conducted a study in which it fed eight AI tools an excerpt of an article and asked the chatbots to identify the "corresponding article’s headline, original publisher, publication date, and URL." Collectively, the study noted that the chatbots "provided incorrect answers to more than 60 percent of queries.
Speaker: Alexa Acosta, Director of Growth Marketing & B2B Marketing Leader
Marketing is evolving at breakneck speed—new tools, AI-driven automation, and changing buyer behaviors are rewriting the playbook. With so many trends competing for attention, how do you cut through the noise and focus on what truly moves the needle? In this webinar, industry expert Alexa Acosta will break down the most impactful marketing trends shaping the industry today and how to turn them into real, revenue-generating strategies.
The first NVIDIA Blackwell-powered data center GPU built for both enterprise AI and visual computing the NVIDIA RTX PRO 6000 Blackwell Server Edition is designed to accelerate the most demanding AI and graphics applications for every industry. Compared to the previous-generation NVIDIA Ada Lovelace architecture L40S GPU, the RTX PRO 6000 Blackwell Server Edition GPU will deliver a multifold increase in performance across a wide array of enterprise workloads up to 5x higher large language mode
LLMs are widely used for conversational AI, content generation, and enterprise automation. However, balancing performance with computational efficiency is a key challenge in this field. Many state-of-the-art models require extensive hardware resources, making them impractical for smaller enterprises. The demand for cost-effective AI solutions has led researchers to develop models that deliver high performance with lower computational requirements.
A Nordic deep-tech startup has announced a breakthrough in artificial intelligence with the creation of the first functional “digital nervous system” capable of autonomous learning. IntuiCell , a spin-out from Lund University, revealed on March 19, 2025, that they have successfully engineered AI that learns and adapts like biological organisms, potentially rendering current AI paradigms obsolete in many applications.
The Qwen team at Alibaba has unveiled QwQ-32B, a 32 billion parameter AI model that demonstrates performance rivalling the much larger DeepSeek-R1. This breakthrough highlights the potential of scaling Reinforcement Learning (RL) on robust foundation models. The Qwen team have successfully integrated agent capabilities into the reasoning model, enabling it to think critically, utilise tools, and adapt its reasoning based on environmental feedback. “Scaling RL has the potential to enhance m
Speaker: Joe Stephens, J.D., Attorney and Law Professor
Ready to cut through the AI hype and learn exactly how to use these tools in your legal work? Join this webinar to get practical guidance from attorney and AI legal expert, Joe Stephens, who understands what really matters for legal professionals! What You'll Learn: Evaluate AI Tools Like a Pro 🔍 Learn which tools are worth your time and how to spot potential security and ethics risks before they become problems.
In the world of large language models (LLMs) there is an assumption that larger models inherently perform better. Qwen has recently introduced its latest model, QwQ-32B, positioning it as a direct competitor to the massive DeepSeek-R1 despite having significantly fewer parameters. This raises a compelling question: can a model with just 32 billion parameters stand […] The post QwQ-32B Vs DeepSeek-R1: Can a 32B Model Challenge a 671B Parameter Model?
Enjoy the laptop lifestyle while it lasts, folks. | Smith Collection/Gado/Getty Images My entire job takes place on my laptop. I write stories like this in Google Docs on my laptop. I coordinate with my editor in Slack on my laptop. I reach out to sources with Gmail and then interview them over Zoom, on my laptop. This isnt true of all journalists some go to war zones but its true of many of us, and for accountants, tax preparers, software engineers, and many more workers, maybe over one in 10
A new AI education initiative in the State of Utah, developed in collaboration with NVIDIA, is set to advance the states commitment to workforce training and economic growth. The public-private partnership aims to equip universities, community colleges and adult education programs across Utah with the resources to develop skills in generative AI. AI will continue to grow in importance, affecting every sector of Utahs economy, said Spencer Cox, governor of Utah.
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