Articles for category: AI News

March 5, 2025

ikayaniaamirshahzad@gmail.com

Automating Artificial Life Discovery: The Power of Foundation Models

The recent Nobel Prize for groundbreaking advancements in protein discovery underscores the transformative potential of foundation models (FMs) in exploring vast combinatorial spaces. These models are poised to revolutionize numerous scientific disciplines, yet the field of Artificial Life (ALife) has been slow to adopt them. This gap presents a unique opportunity to overcome the traditional reliance on manual design and trial-and-error methods for uncovering lifelike simulation configurations. In a new paper Automating the Search for Artificial Life with Foundation Models, a research team from MIT, Sakana AI, OpenAI, The Swiss AI Lab IDSIA and Independent introduces Automated Search for Artificial

March 5, 2025

ikayaniaamirshahzad@gmail.com

Chain of Draft approach allows AI models to carry out tasks using far fewer resources

Comparison of Claude 3.5 Sonnet’s accuracy and token usage across different tasks with three different prompt strategies: direct answer (Standard), Chain of Thought (CoT), and Chain of Draft (CoD). Credit: arXiv (2025). DOI: 10.48550/arxiv.2502.18600 A small team of AI engineers at Zoom Communications has developed a new approach to training AI systems that uses far fewer resources than the standard approach now in use. The team has published their results on the arXiv preprint server. The new approach developed at Zoom is called Chain of Draft (CoD), an update of the traditional approach now in use called Chain of Thought

March 5, 2025

ikayaniaamirshahzad@gmail.com

Visualizing nanoparticle dynamics using AI-based method

Static image taken from video (shown below). Left: a platinum nanoparticle imaged via electron microscopy. Right: using AI-based method to remove the noise. By Patricia Waldron A team of scientists has developed a method to illuminate the dynamic behavior of nanoparticles. The work, reported in Visualizing Nanoparticle Surface Dynamics and Instabilities Enabled by Deep Denoising, in the journal Science, combines artificial intelligence with electron microscopy to render visuals of how these tiny bits of matter respond to stimuli. “The nature of changes in the particle is exceptionally diverse, including fluxional periods, manifesting as rapid changes in atomic structure, particle shape,

March 5, 2025

ikayaniaamirshahzad@gmail.com

What is Apache Arrow? Features, How to Use and More

Data is at the core of everything, from business decisions to machine learning. But processing large-scale data across different systems is often slow. Constant format conversions add processing time and memory overhead. Traditional row-based storage formats struggle to keep up with modern analytics. This leads to slower computations, higher memory usage, and performance bottlenecks. Apache Arrow solves these issues. It is an open source, columnar in-memory data format designed for speed and efficiency. Arrow provides a common way to represent tabular data, eliminating costly conversions and enabling seamless interoperability. Key Benefits of Apache Arrow Zero-Copy Data Sharing – Transfers data

March 5, 2025

ikayaniaamirshahzad@gmail.com

Step by Step Guide to Build an AI Research Assistant with Hugging Face SmolAgents: Automating Web Search and Article Summarization Using LLM-Powered Autonomous Agents

Hugging Face’s SmolAgents framework provides a lightweight and efficient way to build AI agents that leverage tools like web search and code execution. In this tutorial, we demonstrate how to build an AI-powered research assistant that can autonomously search the web and summarize articles using SmolAgents. This implementation runs seamlessly, requiring minimal setup, and showcases the power of AI agents in automating real-world tasks such as research, summarization, and information retrieval. !pip install smolagents beautifulsoup4 First, we install smolagents beautifulsoup4, which enables AI agents to use tools like web search and code execution, and BeautifulSoup4, a Python library for parsing

March 5, 2025

ikayaniaamirshahzad@gmail.com

Alternative Data Use Grows Strongly Among Investors, Thanks to AI

(Zakharchuk/Shutterstock) Investment advisors are expanding their use of alternative data thanks to generative AI and the competitive advantages they plan to obtain through it, according to the latest report on alternative data from Lowenstein Sandler. Alternative data is the investment arena refers to anything that doesn’t appear in company filings, press releases, analyst reports, and other traditional sources. Investors are looking to alternative data like company credit card transactions, geolocation, mobile device data, and social media in order to gain a potentially lucrative signal that can be exploited for competitive advantage. Lowenstein Sandler is a law firm that has been

March 5, 2025

ikayaniaamirshahzad@gmail.com

Nexla Expands AI-Powered Integration Platform for Enterprise-Grade GenAI

SAN MATEO, Calif., March 04, 2025 — AI-powered integration company Nexla announced a major update to the Nexla Integration Platform, expanding its no-code integration, RAG pipeline engineering, and data governance capabilities with the intent to make enterprise-grade GenAI more accessible. The Nexla integration platform is the first integration platform powered by AI and built to handle today’s data variety. With Nexla, you can integrate any data, create AI-ready data products, and deliver GenAI projects without coding and up to 10x faster than the alternatives. Nexla uses AI to connect, extract metadata, and transform source data into human-readable data products, called

March 5, 2025

ikayaniaamirshahzad@gmail.com

JDK 25 kicks off with a stable values API

While Java Development Kit 25 is not set to arrive until September, the first feature already has been proposed for it — a preview of a stable values API that promises to improve startup of Java applications. Stable values are objects that hold immutable data. Because stable values are treated as constants by the JVM, they allow for the same performance optimizations that are enabled by declaring a field final. At the same time, they offer greater flexibility as to the timing of initialization. Thus they could be used to improve the startup of Java applications by breaking up the

March 5, 2025

ikayaniaamirshahzad@gmail.com

The Challenges and Upsides of Using AI in Scientific Writing

This is a guest post. The views expressed here are the author’s own and do not represent positions of IEEE Spectrum, The Institute or IEEE. Scientific writing is at a pivotal stage, driven by artificial intelligence as a disruptor and enabler. Academics, publishers, and policymakers are attempting to weigh the value of using AI responsibly to enhance productivity versus risking the integrity and purpose of scholarly communication. In this context, the responsible use of the technology in scientific writing pertains to employing AI tools in ways that uphold the integrity, transparency, and ethical standards of scholarly communication. As we collectively