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MIT researchers have developed a robot training method that reduces time and cost while improving adaptability to new tasks and environments. The approach – called Heterogeneous Pretrained Transformers (HPT) – combines vast amounts of diverse data from multiple sources into a unified system, effectively creating a shared language that generative AI models can process.
IBM’s latest addition to its Granite series, Granite 3.0, marks a significant leap forward in the field of large language models (LLMs). Granite 3.0 provides enterprise-ready, instruction-tuned models with an emphasis on safety, speed, and cost-efficiency focused on balancing power and practicality. The Granite 3.0 series enhances IBM’s AI offerings, particularly in domains where precision, […] The post IBM Granite-3.0 Model: A Guide to Model Setup and Usage appeared first on Analytics Vid
It’s not exactly breaking news to say that AI has dramatically changed the cybersecurity industry. Both attackers and defenders alike are turning to artificial intelligence to uplevel their capabilities, each striving to stay one step ahead of the other. This cat-and-mouse game is nothing new—attackers have been trying to outsmart security teams for decades, after all—but the emergence of artificial intelligence has introduced a fresh (and often unpredictable) element to the dynamic.
In today’s world of video and image analysis, detector models play a vital role in the technology. They should be ideally accurate, speedy and scalable. Their applications vary from small factory detection tasks to self-driving cars and also help in advanced image processing. The YOLO (You Only Look Once) model has purely pushed the boundaries […] The post A Comprehensive Guide to YOLOv11 Object Detection appeared first on Analytics Vidhya.
AI is reshaping marketing and sales, empowering professionals to work smarter, faster, and more effectively. This webinar will provide a practical introduction to AI, focusing on its current applications, transformative potential, and strategies for successful implementation in your organization. Using real-world examples and actionable insights, we’ll examine how businesses are leveraging AI to increase efficiency, enhance personalization, and drive measurable results.
Curious about the future of AI? Want to witness firsthand how AI can generate creative text, code, or even art? AI playgrounds offer a hands-on experience to explore the limitless possibilities of artificial intelligence. Here is a list of ten free platforms that empower you to shape the future of AI. First, let us understand what is an AI playground.
As large language models (LLMs) continue to grow in scale, so does the need for efficient ways to store, deploy, and run them on low-resource devices. While these models offer powerful capabilities, their size and memory demands can make deployment a challenge, especially on consumer hardware. This is where model quantization and specialized storage formats […] The post How to Convert Models to GGUF Format?
As large language models (LLMs) continue to grow in scale, so does the need for efficient ways to store, deploy, and run them on low-resource devices. While these models offer powerful capabilities, their size and memory demands can make deployment a challenge, especially on consumer hardware. This is where model quantization and specialized storage formats […] The post How to Convert Models to GGUF Format?
LLMWare.ai , a pioneer in deploying and fine-tuning Small Language Models (SLMs) announced today the launching of Model Depot in Hugging Face, one of the largest collections of SLMs that are optimized for Intel PCs. With over 100 models spanning multiple use cases such as chat, coding, math, function calling, and embedding models, Model Depot aims to provide to the open-source AI community an unprecedented collection of the latest SLMs that are optimized for Intel-based PCs in Intel’s OpenVINO a
This guide dives into building a custom conversational agent with LangChain, a powerful framework that integrates Large Language Models (LLMs) with a range of tools and APIs. Designed for versatility, the agent can tackle tasks like generating random numbers, sharing philosophical insights, and dynamically fetching and extracting content from webpages.
Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. In these scenarios, customized model monitoring for near real-time batch inference with Amazon SageMaker is essential, making sure the quality of predic
Are you all set for the upcoming holidays? Or are you bogged down by all the time and effort it’s taking to make all the arrangements? These festivals have become yet another project that we wish to ace, no? Much like any professional project that we take up these days, we can get assistance for […] The post 7 Ways to Celebrate this Festive Season with Generative AI appeared first on Analytics Vidhya.
Speaker: Joe Stephens, J.D., Attorney and Law Professor
Ready to cut through the AI hype and learn exactly how to use these tools in your legal work? Join this webinar to get practical guidance from attorney and AI legal expert, Joe Stephens, who understands what really matters for legal professionals! What You'll Learn: Evaluate AI Tools Like a Pro 🔍 Learn which tools are worth your time and how to spot potential security and ethics risks before they become problems.
Financial losses from worldwide credit card transaction fraud are expected to reach $43 billion by 2026. A new NVIDIA AI workflow for fraud detection running on Amazon Web Services (AWS) can help combat this burgeoning epidemic — using accelerated data processing and advanced algorithms to improve AI’s ability to detect and prevent credit card transaction fraud.
In recent years, formal software verification has gained prominence, especially in fields where software reliability is critical, such as aerospace engineering, finance, and healthcare. Proof assistants like Coq have been instrumental in ensuring the correctness of software by enabling developers to create mathematical proofs to verify their code. However, writing such formal proofs is a labor-intensive and time-consuming task, requiring considerable expertise.
After an upcoming remaster was said to be compatible with 'Nintendo platforms,' fans began to speculate that the Switch 2 announcement would come before Nintendo's Nov. 5 earnings report.
Forget predictions, let’s focus on priorities for the year and explore how to supercharge your employee experience. Join Miriam Connaughton and Carolyn Clark as they discuss key HR trends for 2025—and how to turn them into actionable strategies for your organization. In this dynamic webinar, our esteemed speakers will share expert insights and practical tips to help your employee experience adapt and thrive.
To learn more about current AI capabilities and to challenge myself, I decided to see what I could create in just 24 hours. This story is about making a complete music video clip, from start to finish, using AI tools. Everything in this music video is AI-generated, and I mean EVERYTHING: lyrics, music, voice, images, and videos.
An overwhelming 91% of financial services industry (FSI) companies are either assessing artificial intelligence or already have it in the bag as a tool that’s driving innovation, improving operational efficiency and enhancing customer experiences. Generative AI — powered by NVIDIA NIM microservices and accelerated computing — can help organizations improve portfolio optimization, fraud detection , customer service and risk management.
Datasets and pre-trained models come with intrinsic biases. Most methods rely on spotting them by analyzing misclassified samples in a semi-automated human computer validation. Deep neural networks, typically fine-tuned foundational models, are widely used in sectors like healthcare, finance, and criminal justice, where biased predictions can have serious societal impacts.
Speaker: Joe Stephens, J.D., Attorney and Law Professor
Get ready to uncover what attorneys really need from you when it comes to trial prep in this new webinar! Attorney and law professor, Joe Stephens, J.D., will share proven techniques for anticipating attorney needs, organizing critical documents, and transforming complex information into compelling case presentations. Key Learning Objectives: Organization That Makes Sense 🎯 Learn how to structure and organize case materials in ways that align with how attorneys actually work and think.
Knowledge Graph (KG) synthesis is gaining traction in artificial intelligence research because it can construct structured knowledge representations from expansive, unstructured text data. These structured graphs have pivotal applications in areas requiring information retrieval and reasoning, such as question answering, complex data summarization, and retrieval-augmented generation (RAG).
When applying Reinforcement Learning (RL) to real-world applications, two key challenges are often faced during this process. Firstly, the constant online interaction and update cycle in RL places major engineering demands on large systems designed to work with static ML models needing only occasional offline updates. Secondly, RL algorithms usually start from scratch, relying solely on information gathered during these interactions, limiting both their efficiency and adaptability.
Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng
Posted by the TensorFlow team TensorFlow 2.18 has been released! Highlights of this release (and 2.17) include NumPy 2.0, LiteRT repository, CUDA Update, Hermetic CUDA and more. For the full release notes, please click here. Note: Release updates on the new multi-backend Keras will be published on keras.io , starting with Keras 3.0. For more information, please see [link].
This paper was accepted at the Efficient Natural Language and Speech Processing (ENLSP) workshop at NeurIPS Workshop 2024. While large language models (LLMs) dominate the AI landscape, Small-scale large Language Models (SLMs) are gaining attention due to cost and efficiency demands from consumers. However, there is limited research on the training behavior and computational requirements of SLMs.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
Android 16 may introduce Dynamic Island-like 'Rich Ongoing Notifications,' enhancing the user experience with interactive, pill-shaped status bar chips.
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