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Imagine having a casual chat online, assuming you’re speaking to a real person. But what if its not? What if, behind the screen, its an AI model trained to sound human? In a recent 2025 study, researchers from UC San Diego found that large language models like GPT-4.5 could convincingly pass as human, sometimes more […] The post AI Passes the Turing Test: How Are LLMs Like GPT-4.5 Fooling Humans?
In recent years, the AI field has been captivated by the success of large language models (LLMs). Initially designed for natural language processing, these models have evolved into powerful reasoning tools capable of tackling complex problems with human-like step-by-step thought process. However, despite their exceptional reasoning abilities, LLMs come with significant drawbacks, including high computational costs and slow deployment speeds, making them impractical for real-world use in resource
It's a fact of life that automation can make us lazier. Usually, the tradeoffs are worth it. But it feels more pernicious with AI Chatbots, which offer to basically automate thinking itself. Th at's what Sam Schechner, a tech reporter for The Wall Street Journal , began to wise up to after developing a nasty ChatGPT habit. "Artificial intelligence was eating my brain," he wrote in a recent essay for the newspaper.
Have you ever stared at a massive document with the deadline looming and thought, Theres no way Im getting through all of this? Weve all been there, drowning in tabs, buried under PDFs, and juggling half-finished Google Docs. Whether you're a student piecing together a paper , a creator wrestling with research , or a professional trying to make sense of endless reports, the chaos is real.
Document-heavy workflows slow down productivity, bury institutional knowledge, and drain resources. But with the right AI implementation, these inefficiencies become opportunities for transformation. So how do you identify where to start and how to succeed? Learn how to develop a clear, practical roadmap for leveraging AI to streamline processes, automate knowledge work, and unlock real operational gains.
At a time when major AI companies make the slightest of an update in their interface – a breakthrough moment; Meta AI has redefined this culture. Launching not one but THREE models on the same day under the Llama 4 herd. Llama 4 consists of three models: Scout, Maverick, and Behemoth. Each is designed with […] The post Llama 4 Models: Meta AI is Open Sourcing the Best!
Enterprises increasingly adopt agentic frameworks to build intelligent systems capable of performing complex tasks by chaining tools, models, and memory components. However, as organizations build these systems across multiple frameworks, challenges arise regarding interoperability, observability, performance profiling, and workflow evaluation. Teams are often locked into particular frameworks, making it hard to scale or reuse agents and tools across different contexts.
Enterprises increasingly adopt agentic frameworks to build intelligent systems capable of performing complex tasks by chaining tools, models, and memory components. However, as organizations build these systems across multiple frameworks, challenges arise regarding interoperability, observability, performance profiling, and workflow evaluation. Teams are often locked into particular frameworks, making it hard to scale or reuse agents and tools across different contexts.
AI tools are changing how developers work, and Devin 2.0 is part of that shift. Built by Cognition AI, it improves on the previous version in many ways. Devin 2.0 is faster, more efficient, and easier to use. It supports planning, coding, debugging, and task execution with simple prompts. Unlike the earlier version, it now […] The post Devin 2.0 Explained: Features, Use Cases, and How It Compares to Windsurf and Cursor appeared first on Analytics Vidhya.
Microsofts 50th anniversary event was quite loaded, but the company reserved most of its attention for the Copilot AI stack. The buzzy event introduced two crucial upgrades Actions and Deep Research which firmly push Copilot into the realm of agentic AI.
GenSpark Super Agent (often just called GenSpark ) is a new general-purpose AI agent designed to autonomously handle complex tasks across domains. Unlike a simple chatbot or script, GenSpark can think, plan, act, and use tools much like a human assistant. It doesnt just generate text; it can take actions on your behalf. You give GenSpark high-level instructions (akin to a project brief or SOP), and it will internally break down the problem, decide on a plan, and execute that plan step by step wi
Neural style transfer (NST) has opened new possibilities for digital art by enabling the blending of distinct artistic styles with content from various images. However, traditional NST methods often need help balancing style fidelity and content preservation, and many models need more computational efficiency, limiting their applicability for real-time applications.
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.
Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective in enhancing LLMs’ reasoning and coding abilities, particularly in domains where structured reference answers allow clear-cut verification. This approach relies on reference-based signals to determine if a model’s response aligns with a known correct answer, typically through binary correctness labels or graded scores.
Today, Meta AI announced the release of its latest generation multimodal models, Llama 4, featuring two variants: Llama 4 Scout and Llama 4 Maverick. These models represent significant technical advancements in multimodal AI, offering improved capabilities for both text and image understanding. Llama 4 Scout is a 17-billion-active-parameter model structured with 16 expert modules.
The new DGX machines are portable but powerful enough to drive complex AI modules and research, with processing capabilities previously only available in data centers.
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.
A key advancement in AI capabilities is the development and use of chain-of-thought (CoT) reasoning, where models explain their steps before reaching an answer. This structured intermediate reasoning is not just a performance tool; its also expected to enhance interpretability. If models explain their reasoning in natural language, developers can trace the logic and detect faulty assumptions or unintended behaviors.
Optical Character Recognition (OCR) has long been a cornerstone of document digitization, enabling the transformation of printed text into machine-readable formats. However, traditional OCR systems face significant limitations as the world grows increasingly multilingual and dependent on handwritten and visually structured content. These systems often struggle with the complexities of diverse scripts, free-form handwritten content, and documents that include intricate layouts with visual context
Meta claims its new models are superior to those from OpenAI and Google across a broad range of benchmarks. Meta has announced the release of Llama 4, its newest collection of AI models that now power Meta AI on the web and in WhatsApp, Messenger, and Instagram Direct.
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
DeepSeek Libraries DeepSeek released a number of libraries through their “open-source week” and these libraries are especially useful for training large scale models and they have used these libraries in the DeepSeek development. I covered the paper itself in one of the previous newsletter, be sure to check that out first if you have not: Now, let’s dive in for libraries!
At the recent Nvidia GTC conference, the company unveiled what it described as the first single-rack system of servers capable of one exaflop one billion billion, or a quintillion, floating-point operations (FLOPS) per second.
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
The medical field is ahead of the curve on using technology as more devices aim to make spotting skin cancer easier. In 2017, Ezekiel Emanuel, a well-known oncologist and health policy commentator, said radiologists would soon be out of work thanks to machine learning.
Deep Research and AI overview podcasts have been my two favorite Google Gemini features so far. Microsoft has finally implemented them on its Copilot platform.
College admission decisions have landed. Over the last few months, schools have chosen between applicants, and now the decision-making process is back in the students hands.
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.
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