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Anthropic has provided a more detailed look into the complex inner workings of their advanced language model, Claude. This work aims to demystify how these sophisticated AI systems process information, learn strategies, and ultimately generate human-like text. As the researchers initially highlighted, the internal processes of these models can be remarkably opaque, with their problem-solving methods often “inscrutable to us, the models developers.” Gaining a deeper understanding of t
Large language models (LLMs) are rapidly evolving from simple text prediction systems into advanced reasoning engines capable of tackling complex challenges. Initially designed to predict the next word in a sentence, these models have now advanced to solving mathematical equations, writing functional code, and making data-driven decisions. The development of reasoning techniques is the key driver behind this transformation, allowing AI models to process information in a structured and logical ma
Gemini 2.5 is being hailed by Google DeepMind as its “most intelligent AI model” to date. The first model from this latest generation is an experimental version of Gemini 2.5 Pro, which DeepMind says has achieved state-of-the-art results across a wide range of benchmarks. According to Koray Kavukcuoglu, CTO of Google DeepMind, the Gemini 2.5 models are “thinking models” This signifies their capability to reason through their thoughts before generating a response, leading
To improve AI interoperability, OpenAI has announced its support for Anthropic’s Model Context Protocol (MCP), an open-source standard designed to streamline the integration between AI assistants and various data systems. This collaboration marks a pivotal step in creating a unified framework for AI applications to access and utilize external data sources effectively.
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
The arrival of OpenAI's DALL-E 2 in the spring of 2022 marked a turning point in AI when text-to-image generation suddenly became accessible to a select group of users, creating a community of digital explorers who experienced wonder and controversy as the technology automated the act of visual creation. But like many early AI systems, DALL-E 2 struggled with consistent text rendering, often producing garbled words and phrases within images.
Developing therapeutics continues to be an inherently costly and challenging endeavor, characterized by high failure rates and prolonged development timelines. The traditional drug discovery process necessitates extensive experimental validations from initial target identification to late-stage clinical trials, consuming substantial resources and time.
Developing therapeutics continues to be an inherently costly and challenging endeavor, characterized by high failure rates and prolonged development timelines. The traditional drug discovery process necessitates extensive experimental validations from initial target identification to late-stage clinical trials, consuming substantial resources and time.
The AI race is heating up with newer, competing models launched every other day. Amid this rapid innovation, Google Gemini 2.5 Pro challenges OpenAI GPT-4.5, both offering cutting-edge advancements in AI capabilities. In this Gemini 2.5 Pro vs GPT-4.5 article, we will compare the features, benchmark results, and performance of both these models in various […] The post Gemini 2.5 Pro vs GPT 4.5: Does Google’s Latest Beat OpenAI’s Best?
Google has unveiled Gemini 2.5 Pro , calling it its most intelligent AI model to date. This latest large language model, developed by the Google DeepMind team, is described as a thinking model designed to tackle complex problems by reasoning through steps internally before responding. Early benchmarks back up Googles confidence: Gemini 2.5 Pro (an experimental first release of the 2.5 series) is debuting at #1 on the LMArena leaderboard of AI assistants by a significant margin, and it leads many
One of the perks of Angie Adams job at Samsung is that every year, she gets to witness how some of the countrys most talented emerging scientists are tackling difficult problems in creative ways. Theyre working on AI tools that can recognize the signs of oncoming panic attacks for kids on the autism spectrum in one case, and figuring out how drones can be used effectively to fight wildfires in another.
I recently talked to a journalist about LLM benchmarks, expressing my frustration with the current situation. During our chat, amongst other things the journalist speculated that: Capabilities that cannot be assessed by standard benchmarks are regarded as less interesting and important, this includes the increased emotional sensitivity of GPT 4.5. Standard benchmarks are an essential tool for guiding the development of models.
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.
As the adoption of AI accelerates, organisations may overlook the importance of securing their Gen AI products. Companies must validate and secure the underlying large language models (LLMs) to prevent malicious actors from exploiting these technologies. Furthermore, AI itself should be able to recognise when it is being used for criminal purposes. Enhanced observability and monitoring of model behaviours, along with a focus on data lineage can help identify when LLMs have been compromised.
Recent advancements in reasoning models, such as OpenAI’s o1 and DeepSeek R1, have propelled LLMs to achieve impressive performance through techniques like Chain of Thought (CoT). However, the verbose nature of CoT leads to increased computational costs and latency. A novel paper published by Zoom Communications presents a new prompting technique called Chain of Draft […] The post Chain of Draft Prompting with Gemini and Groq appeared first on Analytics Vidhya.
The AI model market is growing quickly, with companies like Google , Meta , and OpenAI leading the way in developing new AI technologies. Googles Gemma 3 has recently gained attention as one of the most powerful AI models that can run on a single GPU, setting it apart from many other models that need much more computing power. This makes Gemma 3 appealing to many users, from small businesses to researchers.
This post is co-authored with Joao Moura and Tony Kipkemboi from CrewAI. The enterprise AI landscape is undergoing a seismic shift as agentic systems transition from experimental tools to mission-critical business assets. In 2025, AI agents are expected to become integral to business operations, with Deloitte predicting that 25% of enterprises using generative AI will deploy AI agents, growing to 50% by 2027.
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
Visual Studio Code (VSCode) is a powerful, free source-code editor that makes it easy to write and run Python code. This guide will walk you through setting up VSCode for Python development, step by step. Prerequisites Before we begin, make sure you have: Python installed on your computer An internet connection Basic familiarity with your computer’s operating system Step 1: Download and Install Visual Studio Code Windows, macOS, and Linux Go to the official VSCode website: [link] Click the
Dame Wendy Hall is a pioneering force in AI and computer science. As a renowned ethical AI speaker and one of the leading voices in technology, she has dedicated her career to shaping the ethical, technical and societal dimensions of emerging technologies. She is the co-founder of the Web Science Research Initiative, an AI Council Member and was named as one of the 100 Most Powerful Women in the UK by Woman’s Hour on BBC Radio 4.
Imagine an AI that can write poetry, draft legal documents, or summarize complex research papersbut how do we truly measure its effectiveness? As Large Language Models (LLMs) blur the lines between human and machine-generated content, the quest for reliable evaluation metrics has become more critical than ever. Enter ROUGE (Recall-Oriented Understudy for Gisting Evaluation), a […] The post ROUGE: Decoding the Quality of Machine-Generated Text appeared first on Analytics Vidhya.
For years, creating robots that can move, communicate, and adapt like humans has been a major goal in artificial intelligence. While significant progress has been made, developing robots capable of adapting to new environments or learning new skills has remained a complex challenge. Recent advances in large language models (LLMs) are now changing this.
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.
A complaint about poverty in rural China. A news report about a corrupt Communist Party member. A cry for help about corrupt cops shaking down entrepreneurs.
Amazon Bedrock cross-Region inference capability that provides organizations with flexibility to access foundation models (FMs) across AWS Regions while maintaining optimal performance and availability. However, some enterprises implement strict Regional access controls through service control policies (SCPs) or AWS Control Tower to adhere to compliance requirements, inadvertently blocking cross-Region inference functionality in Amazon Bedrock.
Research conducted by Vlerick Business School has discovered that in the area of AI financial planning, the technology consistently outperforms humans when allocating budgets with strategic guidelines in place. Businesses that use AI for budgeting processes experience substantial improvements in the accuracy and efficiency of budgeting plans compared to human decision-making.
Can AI generate truly relevant answers at scale? How do we make sure it understands complex, multi-turn conversations? And how do we keep it from confidently spitting out incorrect facts? These are the kinds of challenges that modern AI systems face, especially those built using RAG. RAG combines the power of document retrieval with the […] The post Top 13 Advanced RAG Techniques for Your Next Project appeared first on Analytics Vidhya.
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.
In a major leap forward for productivity software, Sourcetable has announced a $4.3 million seed round and the launch of what it calls the worlds first autonomous, AI-powered spreadsheet a “self-driving” experience that reimagines how humans interact with data. With backing from top investors including Bee Partners , Julien Chaumond (Hugging Face), Preston-Werner Ventures (GitHub co-founder), Roger Bamford (MongoDB), and James Beshara (Magic Mind), Sourcetable is taking aim at a pro
One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information , hallucinating answers that are not supported by its training data. From a human perspective, it can be hard to understand why these models don't simply say "I don't know" instead of making up some plausible-sounding nonsense.
AI agents extend large language models (LLMs) by interacting with external systems, executing complex workflows, and maintaining contextual awareness across operations. Amazon Bedrock Agents enables this functionality by orchestrating foundation models (FMs) with data sources, applications, and user inputs to complete goal-oriented tasks through API integration and knowledge base augmentation.
A new study from the AI Disclosures Project has raised questions about the data OpenAI uses to train its large language models (LLMs). The research indicates the GPT-4o model from OpenAI demonstrates a “strong recognition” of paywalled and copyrighted data from O’Reilly Media books. The AI Disclosures Project, led by technologist Tim O’Reilly and economist Ilan Strauss, aims to address the potentially harmful societal impacts of AI’s commercialisation by advocating
The guide for revolutionizing the customer experience and operational efficiency This eBook serves as your comprehensive guide to: AI Agents for your Business: Discover how AI Agents can handle high-volume, low-complexity tasks, reducing the workload on human agents while providing 24/7 multilingual support. Enhanced Customer Interaction: Learn how the combination of Conversational AI and Generative AI enables AI Agents to offer natural, contextually relevant interactions to improve customer exp
While interacting with AI agents, we often find ourselves repeatedly sharing the same preferences, facts, and information. This lack of long-term memory means the agent cannot learn from past conversations or adapt its responses. Imagine if these AI agents could remember your preferences, learn from previous interactions, and optimize its behavior accordingly, retaining the knowledge […] The post LangMem SDK: Personalizing AI Agents with Semantic Memory appeared first on Analytics Vidhya.
Retrieval-Augmented Generation (RAG) is an approach to building AI systems that combines a language model with an external knowledge source. In simple terms, the AI first searches for relevant documents (like articles or webpages) related to a users query, and then uses those documents to generate a more accurate answer. This method has been celebrated for helping large language models (LLMs) stay factual and reduce hallucinations by grounding their responses in real data.
OpenAI released a new image generator this week, and AI -generated Studio Ghibli slop is now all over the internet. In the livestream demo of the native image generation in ChatGPT and Sora , OpenAI took a selfie and asked the new generator to turn it into an anime frame. The result looked a lot like art from a Studio Ghibli film. It went viral, despite some social media users pointing out the potential copyright violations.
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