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Training Diffusion Models with Reinforcement Learning We deployed 100 reinforcement learning (RL)-controlled cars into rush-hour highway traffic to smooth congestion and reduce fuel consumption for everyone. Our goal is to tackle "stop-and-go" waves , those frustrating slowdowns and speedups that usually have no clear cause but lead to congestion and significant energy waste.
Youve built applications with LLMs. Youve played with agents. Maybe youve even worked with LangChain, AutoGen, or OpenAIs Assistants API. Isnt it impressive how much these models can reason, understand, and generate? But the moment your agent needs to do something real, like check a database, read from a CRM, or fetch a Google Doc; […] The post How to Use MCP: Model Context Protocol appeared first on Analytics Vidhya.
DeepSeek V3-0324 has become the highest-scoring non-reasoning model on the Artificial Analysis Intelligence Index in a landmark achievement for open-source AI. The new model advanced seven points in the benchmark to surpass proprietary counterparts such as Googles Gemini 2.0 Pro , Anthropics Claude 3.7 Sonnet , and Metas Llama 3.3 70B. While V3-0324 trails behind reasoning models, including DeepSeeks own R1 and offerings from OpenAI and Alibaba , the achievement highlights the growing viability
As AI models advance, their programming and software development capabilities have become key benchmarks. Two leading contenders in the coding scene are DeepSeek V3 and Claude 3.7. DeepSeek V3-0324, the latest from DeepSeek AI, comes with promising benchmark results on coding tasks. Meanwhile, Anthropics newest model, Claude 3.7, is a stronger generalist AI with superior […] The post DeepSeek V3-0324 vs Claude 3.7: Which is the Better Coder?
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Are you juggling multiple AI subscriptions, each with its own pricing plan and renewal dates? One platform gives you ChatGPT, another offers Claude , a third lets you generate images and another handles video creation. Before you know it, your expenses for these AI tools have spiraled out of control. You end up overwhelmed by how many tools you need to manage.
How can you ensure your machine learning models get the high-quality data they need to thrive? In todays machine learning landscape, handling data well is as important as building strong models. Feeding high-quality, well-structured data into your models can significantly impact performance and training speed. The TensorFlow Dataset API simplifies this process by offering set […] The post Building TensorFlow Pipelines with Vertex AI appeared first on Analytics Vidhya.
How can you ensure your machine learning models get the high-quality data they need to thrive? In todays machine learning landscape, handling data well is as important as building strong models. Feeding high-quality, well-structured data into your models can significantly impact performance and training speed. The TensorFlow Dataset API simplifies this process by offering set […] The post Building TensorFlow Pipelines with Vertex AI appeared first on Analytics Vidhya.
ARC Prize has launched the hardcore ARC-AGI-2 benchmark, accompanied by the announcement of their 2025 competition with $1 million in prizes. As AI progresses from performing narrow tasks to demonstrating general, adaptive intelligence, the ARC-AGI-2 challenges aim to uncover capability gaps and actively guide innovation. Good AGI benchmarks act as useful progress indicators.
OpenAIs Agent SDK has taken things up a notch with the release of its Voice Agent feature, enabling you to create intelligent, real-time, speech-driven applications. Whether you’re building a language tutor, a virtual assistant, or a support bot, this new capability brings in a whole new level of interactionnatural, dynamic, and human-like. Lets break it […] The post How to Build Multilingual Voice Agent Using OpenAI Agent SDK?
Inside the nation’s largest health insurance companies, artificial intelligence is taking off like a rocket. Elevance, which covers about 110 million people, has rolled out a generative AI model to 50,000 employees. Centene Corp, which serves more than 28 million people, is using it to manage contracts with medical groups and measure their performance.
New research from Russia proposes an unconventional method to detect unrealistic AI-generated images not by improving the accuracy of large vision-language models (LVLMs), but by intentionally leveraging their tendency to hallucinate. The novel approach extracts multiple ‘atomic facts' about an image using LVLMs, then applies natural language inference (NLI) to systematically measure contradictions among these statements effectively turning the model's flaws into a diagnostic tool for de
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 long-awaited, emerging computer network component may finally be having its moment. At Nvidias GTC event last week in San Jose, the company announced that it will produce an optical network switch designed to drastically cut the power consumption of AI data centers. The systemcalled a co-packaged optics, or CPO, switch can route tens of terabits per second from computers in one rack to computers in another.
Customer support software is evolving quickly thanks to AI. The tools on this list combine traditional help desk capabilities (like ticketing, knowledge bases, and multi-channel support) with powerful artificial intelligence to automate responses, assist agents, and improve customer satisfaction. Below is a comparison of some of the leading platforms, followed by detailed insights into each.
Ray has emerged as a powerful framework for distributed computing in AI and ML workloads, enabling researchers and practitioners to scale their applications from laptops to clusters with minimal code changes. This guide provides an in-depth exploration of Ray’s architecture, capabilities, and applications in modern machine learning workflows, complete with a practical project implementation.
One of the greatest challenges of Generative AI solutions like ChatGPT is hallucination. They create fear in professionals as well as nightmares involving the lawyer that used ChatGPT and filed a fictitious case with a judge. Hallucinations are a problem because GenAI solutions like ChatGPT are not databases, even though they appear to behave like search engines that provide a custom answer to a question.
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
A few days ago, Gemini rolled out its image generation feature in the 2.0 Flash version, and the internet erupted with stunning examples. Now, OpenAI is stepping up to the plate, raising the bar even higher by introducing native image generation (powered by GPT-4o) in ChatGPT. Sam Altman introduced the new feature with enthusiasm, describing […] The post OpenAI’s 4o Image Generation is SUPER COOL appeared first on Analytics Vidhya.
Y ou’re reading the web edition of STAT’s Health Tech newsletter, our guide to how technology is transforming the life sciences. Sign up to get it delivered in your inbox every Tuesday and Thursday. How insurers use AI Executives of the nation’s largest health insurance companies regularly highlight their use of AI tools in earnings calls and meetings with investors.
Google DeepMind has recently unveiled its latest advancement in artificial intelligence: the Gemini 2.5 Pro (experimental) model. Within just a few hours of release, this new model has taken the AI world by storm, ranking #1 on the LMArena Leaderboard! Built upon its predecessors, this new model promises enhanced capabilities and features designed to cater […] The post We Tried the Google 2.5 Pro Experimental Model and Its Mind-Blowing!
Generative AI is unlocking new capabilities for PCs and workstations, including game assistants, enhanced content-creation and productivity tools and more. NVIDIA NIM microservices, available now, and AI Blueprints , in the coming weeks, accelerate AI development and improve its accessibility. Announced at the CES trade show in January, NVIDIA NIM provides prepackaged, state-of-the-art AI models optimized for the NVIDIA RTX platform, including the NVIDIA GeForce RTX 50 Series and, now, the new N
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
Retrieval-Augmented Generation (RAG) has transformed AI by dynamically retrieving external knowledge, but it comes with limitations such as latency and dependency on external sources. To overcome these challenges, Cache-Augmented Generation (CAG) has emerged as a powerful alternative. CAG implementation focuses on caching relevant information, enabling faster, more efficient responses while enhancing scalability, accuracy, and reliability. […] The post Cache-Augmented Generation (CAG): Is
In this post, we present an approach to using natural language processing (NLP) to query an Amazon Aurora PostgreSQL-Compatible Edition database. The solution presented in this post assumes that an organization has an Aurora PostgreSQL database. We create a web application framework using Flask for the user to interact with the database. JavaScript and Python code act as the interface between the web framework, Amazon Bedrock, and the database.
Since Amazon Q Business became generally available in 2024, customers have used this fully managed, generative AI-powered assistant to enhance their productivity and efficiency. The assistant enables users to answer questions, generate summaries, create content, and complete tasks using enterprise data. Todays workforce faces significant application overload.
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.
Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Session Management APIs provide an out-of-the-box solution that enables developers to securely manage state and conversation context across multi-step generative AI workflows, alleviating the need to build, maintain, or scale custom backen
Lets be real: building LLM applications today feels like purgatory. Someone hacks together a quick demo with ChatGPT and LlamaIndex. Leadership gets excited. We can answer any question about our docs! But then reality hits. The system is inconsistent, slow, hallucinatingand that amazing demo starts collecting digital dust. We call this POC Purgatorythat frustrating limbo where you’ve built something cool but can’t quite turn it into something real.
China - Recent Storyline: AI talent in high demand during China's spring hiring season [Voice_over] China's spring hiring season is underway with companies in emerging sectors, especially those in the AI industry, leading the race for talent. At a recent job fair for university graduates in Shanghai, private companies made a strong presence, accounting for nearly 50 percent of employers.
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.
Deploying models efficiently, reliably, and cost-effectively is a critical challenge for organizations of all sizes. As organizations increasingly deploy foundation models (FMs) and other machine learning (ML) models to production, they face challenges related to resource utilization, cost-efficiency, and maintaining high availability during updates.
As the company engages major studios and throws its own short film festival (with Universal, Disney and talent agency execs in attendance), its executives see a future unconstrained by legal or labor guardrails.
Amazon Bedrock Knowledge Bases is a fully managed capability that helps implement entire Retrieval Augmented Generation (RAG) workflows from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows. There is no single way to optimize knowledge base performance: each use case is impacted differently by configuration parameters.
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