Articles for category: AI News

INDIA Wins ICC Champions Trophy

Lately, after having worked with one great LLM after the other, I keep asking myself—what can’t they do? Need a meal plan? Done. Want to design an app? Easy. Crack a joke? Too simple. Research a topic? Challenging, but possible. Scan through hundreds of websites? Effortless. But predict the future? Now that is uncharted territory! With the ICC Champions Trophy final just around the corner, it’s time to push the two latest LLMs – GPT 4.5 and Grok 3 – to their limits. Can they analyze team stats, player performances, and historical data to predict the next cricket champion? In

Starter Guide For Running Large Language Models LLMs

Running large language models (LLMs) presents significant challenges due to their hardware demands, but numerous options exist to make these powerful tools accessible. Today’s landscape offers several approaches – from consuming models through APIs provided by major players like OpenAI and Anthropic, to deploying open-source alternatives via platforms such as Hugging Face and Ollama. Whether you’re interfacing with models remotely or running them locally, understanding key techniques like prompt engineering and output structuring can substantially improve performance for your specific applications. This article explores the practical aspects of implementing LLMs, providing developers with the knowledge to navigate hardware constraints, select

Google Launches Data Science Agent for Colab

Getting started with data science and AI often means spending a lot of time setting things up – loading libraries, organizing data, and setting environments. This tedious work can often take away focus from tasks that truly matter, such as data exploration and deriving insights from data.  Recent AI advancements are helping make it easier to skip the setup phase. We know how much hype has been created by AI Agents over the last few months. What if there is an agent specifically designed for data analysis? Could it help analyze, sort, and draw insights from vast volumes of data? 

Ceramic.ai Emerges from Stealth, Reports 2.5x Faster Model Training

SAN FRANCISCO — March 5, 2025 — Ceramic.ai emerged from stealth today with software for foundation model training infrastructure designed to enable enterprises to build and fine-tune generative AI models more efficiently. Founded by Anna Patterson, former Google VP of Engineering and Gradient Ventures founder, Ceramic.ai said it improves AI model training speed and cost-efficiency, offering up to a 2.5x performance boost, accelerated by NVIDIA. Ceramic.ai also said it secured $12 million in seed funding from NEA, IBM, Samsung Next, Earthshot Ventures and Alumni Ventures. “In the midst of a surge in AI adoption, too many companies are still hindered

The key new features in .NET 10

Supporting next-generation silicon Other compiler-level features target upcoming new x64 instructions, specifically AVX 10.2. These add important new processor features across a wide selection of different tasks: from AI to WebAssembly and cryptography. More and more of today’s software depends on vector processing, and support for these new features will allow .NET code to work more effectively. However, silicon that supports these new functions is still under development, so while there’s support ready for when processors ship, it’s currently disabled. With a three-year support window, getting features like this baked into .NET early makes a lot of sense. Microsoft can

AI Overthinking: How LLMs Fall into Analysis Paralysis

Recent advances in large language models (LLMs) have drastically improved their ability to reason through answers to prompts. But it turns out that as their ability to reason improves, they increasingly fall victim to a relatable problem: analysis paralysis. A recent preprint paper from a large team, which includes authors from the University of California, Berkeley; ETH Zurich; Carnegie Mellon University; and the University of Illinois Urbana Champaign, found that LLMs with reasoning are prone to overthinking. In other words, the model gets stuck in its own head. What does it mean to overthink? The paper on overthinking, which has

How to Use AI in Business

Artificial intelligence is taking the business world by storm, as it is an impressive technology that can serve many uses within the workplace. While the future of AI is not guaranteed, the AI market size worldwide grew beyond $184 billion in 2024 and is expected to grow past $826 billion in 2030, according to Statista. With so many organizations profiting through the integration of AI within their internal operations, business owners don’t want to be left behind in this lucrative movement. Fortunately, AI technology is more accessible than ever before, allowing more businesses to take advantage of its benefits to

My compliments to the chef: Researcher studies robots in the kitchen

Walking into your favorite restaurant and seeing a robot chef in the kitchen may seem far-fetched, but a University of Mississippi professor’s research says bots could be a solution to persistent labor shortages in the industry. Jeffrey Pittman II, instructional assistant professor in nutrition and hospitality management, is researching the potential benefits — and numerous doubts — that surround robots invading the kitchen. “We have to look at this from the standpoint of, ‘What benefits can these robots offer if they are implemented?'” he said. “What benefit can they have not just to the restaurant owner, but to the other

DOGE’s $1 Federal Spending Limit Is Straight Out of the Twitter Playbook

Katie Drummond: Right. Move fast and break things as we’ve been saying a lot at WIRED in the last few months. We’re going to take a short break, when we come back, what you need to read on WIRED today. Welcome back to Uncanny Valley. I’m Katie Drummond, WIRED’s global editorial director. I’m joined by WIRED’s director of business and industry, Zoë Schiffer. Now Zoë, before I let you go, tell our listeners what they absolutely must read, must read on WIRED.com today, other than the stories we talked about in this episode. Zoë Schiffer: OK. I wish I had