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Introduction Large Language Models (LLMs) contributed to the progress of Natural Language Processing (NLP), but they also raised some important questions about computational efficiency. These models have become too large, so the training and inference cost is no longer within reasonable limits. To address this, the Chinchilla Scaling Law, introduced by Hoffmann et al. in […] The post What is the Chinchilla Scaling Law?
The field of artificial intelligence is evolving at a breathtaking pace, with large language models (LLMs) leading the charge in natural language processing and understanding. As we navigate this, a new generation of LLMs has emerged, each pushing the boundaries of what's possible in AI. In this overview of the best LLMs, we'll explore the key features, benchmark performances, and potential applications of these cutting-edge language models, offering insights into how they're shaping the future
Introduction Have you ever wished you could simply chat with your database, asking questions in plain language and getting instant, relevant answers? Imagine the possibilities – no more complex SQL queries or digging through spreadsheets. Well, with the power of LangChain and its new SQL toolkit, that’s exactly what you can do! Diving into the […] The post Building a Conversational AI SQL Assistant with LangChain, GROQ, and Streamlit appeared first on Analytics Vidhya.
We've been working with Activepieces to make AssemblyAI's Speech AI available to no-code and low-code builders. With the AssemblyAI piece for Activepieces , you can use AssemblyAI's models to transcribe audio with speech recognition models, analyze audio with audio intelligence models, and build generative features on top of audio with LLMs using LeMUR.
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 Transition from outdated, human-first strategies to an AI-driven approach that enhances customer engagement and operational efficiency.
Introduction Hey there, Coding ninja! What coding-related tasks do you have planned for the day? Before you dive further into this blog, I want you to think about all your coding-related woes—better list those down. Done? – Let’s get started Now! Imagine being a software developer in the 2000s. The entire coding process required many […] The post 10 Generative AI Coding Extensions in VS Code You Must Explore appeared first on Analytics Vidhya.
The rise of Artificial Intelligence (AI) is set to transform many aspects of business, and sales is no exception. AI's integration into sales processes can significantly enhance efficiency, streamline workflows, and drive business success through insights derived from complex data. Automating Routine Tasks Sales professionals often spend a significant amount of time on repetitive tasks such as data entry, email management, and scheduling.
The rise of Artificial Intelligence (AI) is set to transform many aspects of business, and sales is no exception. AI's integration into sales processes can significantly enhance efficiency, streamline workflows, and drive business success through insights derived from complex data. Automating Routine Tasks Sales professionals often spend a significant amount of time on repetitive tasks such as data entry, email management, and scheduling.
Introduction In 2022, the launch of ChatGPT revolutionized both tech and non-tech industries, empowering individuals and organizations with generative AI. Throughout 2023, efforts concentrated on leveraging large language models (LLMs) to manage vast data and automate processes, leading to the development of Retrieval-Augmented Generation (RAG). Now, let’s say you’re managing a sophisticated AI pipeline expected […] The post How to Monitor Production-grade Agentic RAG Pipelines?
OpenAI, the pioneer behind the GPT series, has just unveiled a new series of AI models, dubbed o1 , that can “think” longer before they respond. The model is developed to handle more complex tasks, particularly in science, coding, and mathematics. Although OpenAI has kept much of the model's workings under wraps, some clues offer insight into its capabilities and what it may signal about OpenAI's evolving strategy.
Introduction Imagine you’re scrolling through your favorite social media platform when, out of nowhere, an offensive post pops up. Before you can even hit the report button, it’s gone. That’s content moderation in action. Behind the scenes, platforms rely on sophisticated algorithms to keep harmful content at bay, and the rapid growth of artificial intelligence […] The post Building Multi-Modal Models for Content Moderation on Social Media appeared first on Analytics Vidh
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.
Introduction Imagine running a busy café where every second counts. Instead of constantly checking separate inventory and order lists, you consolidate all key details onto one easy-to-read board. This is similar to denormalization in databases: by intentionally introducing redundancy and simplifying data storage, it speeds up data retrieval and makes complex queries faster and more […] The post What is Denormalization in Databases?
Telecommunications providers are transforming beyond voice and data services with an AI computing infrastructure to optimize wireless networks and serve the next-generation needs of generative AI on mobile, robots, autonomous vehicles, smart factories, 5G and much more. Launched today, NVIDIA AI Aerial is a suite of accelerated computing software and hardware for designing, simulating, training and deploying AI radio access network technology (AI-RAN) for wireless networks in the AI era.
Introduction Artificial Intelligence has entered a new era. Gone are the days when models would simply output information based on predefined rules. The cutting-edge approach in AI today revolves around RAG (Retrieval-Augmented Generation) systems, and more specifically, the use of agents to intelligently retrieve, analyze, and verify information. This is the future of intelligent data […] The post How Agentic RAG Systems with CrewAI and LangChain Transform Tech?
The Databricks Generative AI Startup Challenge offers $1M+ in prizes for innovative startups building Generative AI use cases on Databricks. Apply by November 1, 2024!
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
Introduction The capabilities of large language models (LLMs) are advancing rapidly. They enable us to build a variety of LLM applications. These range from task automation to workflow optimization. One exciting application is using LLMs to create an intelligent news digest or newsletter agent. This agent can pull in relevant content, summarize it, and deliver […] The post How to Create Your Personalized News Digest Using AI Agents?
In the field of technology and creative design, logo design and creation has adapted and evolved at a rapid pace. From the hieroglyphs of ancient Egypt to the sleek minimalism of today’s tech giants, the visual identities that define our favorite brands have undergone a remarkable transformation. Today, the world of creative design is once again being transformed by the emergence of generative AI.
Introduction Handling huge datasets can be pretty overwhelming in today’s data-heavy world. That’s where InsightMate comes in. It’s designed to make exploring your data a breeze. Just upload your dataset, and you’ll get instant insights, visualizations, and answers to your questions. What’s cool about InsightMate is how it mixes automation with flexibility.
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
Which companies that pioneered the field of legal AI are still with us as independent outfits and have neither been sold, nor disappeared entirely? As.
At Databricks, we know that data is one of your most valuable assets. Our product and security teams work together to deliver an enterprise-grade Data Intelligence Platform that enables you to defend against security risks and meet your compliance obligations. In this blog, we'll explain how you can leverage our platform's security features to establish a robust defense-in-depth posture that protects your data and AI assets from risks.
Sydney-based Mary Technology has gained $920,000 in Pre-Seed funding in a round led by Empress Capital, which included Sam Nickless, CEO of top Australian law.
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.
Feature engineering helps make models work better. It involves selecting and modifying data to improve predictions. This article explains feature engineering and how to use it to get better results. What is Feature Engineering? Raw data is often messy and not ready for predictions. Features are important details in your data. They help the model […] The post The Concise Guide to Feature Engineering for Better Model Performance appeared first on MachineLearningMastery.com.
Early attempts in 3D generation focused on single-view reconstruction using category-specific models. Recent advancements utilize pre-trained image and video generators, particularly diffusion models, to enable open-domain generation. Fine-tuning on multi-view datasets improved results, but challenges persisted in generating complex compositions and interactions.
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.
Eve, a new legal genAI startup – which just a year ago bagged $14m in Seed funding from top VCs Lightspeed and Menlo Ventures – has announced a swathe of new features to add to its already very bro…
The Qwen team from Alibaba has recently made waves in the AI/ML community by releasing their latest series of large language models (LLMs), Qwen2.5. These models have taken the AI landscape by storm, boasting significant capabilities, benchmarks, and scalability upgrades. From 0.5 billion to 72 billion parameters, Qwen2.5 has introduced notable improvements across several key areas, including coding, mathematics, instruction-following, and multilingual support.
In recent years, FM sizes have been increasing. It is important to consider the massive amount of compute often required to train these models. The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud.
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