Fri.Oct 18, 2024

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AI meets blockchain and decentralised data

AI News

Blockchain can become a potent force as the foundation of decentralised AI systems, transparent and fair – ensuring everyone can access not only the technology, but the rewards it delivers. Blockchain has enormous potential to democratise access to AI by addressing concerns around centralisation that have emerged with the growing dominance of companies like OpenAI, Google, and Anthropic.

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6 best practices for choosing a business planning solution

IBM Journey to AI blog

Effective planning isn’t just a routine task—it’s a critical function that drives an organization’s strategic direction. As companies face rapid technological advancements, evolving consumer demands and global competition, business planning must adapt to stay relevant. When it comes to integrated planning solutions, it’s important to choose one that optimizes planning processes and delivers tangible economic impact.

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Google announces restructuring to accelerate AI initiatives

AI News

Google CEO Sundar Pichai has announced a series of structural changes and leadership appointments aimed at accelerating the company’s AI initiatives. The restructuring sees the Gemini app team, led by Sissie Hsiao, joining Google DeepMind under the leadership of Demis Hassabis. “Bringing the teams closer together will improve feedback loops, enable fast deployment of our new models in the Gemini app, make our post-training work proceed more efficiently and build on our great product

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12 Ways to Use Generative AI for SEO

Analytics Vidhya

The rise of generative AI (GenAI) is transforming the way digital marketers approach search engine optimization (SEO). GenAI-driven tools are helping businesses improve search rankings and drive organic traffic more efficiently than ever. According to a survey by seoClarity, 86% of companies have already integrated AI into their SEO strategy, and 83% of them have […] The post 12 Ways to Use Generative AI for SEO appeared first on Analytics Vidhya.

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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O’Neill Stoll

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

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How AI Researchers Won Nobel Prizes in Physics and Chemistry: Two Key Lessons for Future Scientific Discoveries

Unite.AI

The 2024 Nobel Prizes have taken many by surprise, as AI researchers are among the distinguished recipients in both Physics and Chemistry. Geoffrey Hinton and John J. Hopfield received the Nobel Prize in Physics for their foundational work on neural networks. In contrast, Demis Hassabis and his colleagues John Jumper and David Baker received the Chemistry prize for their groundbreaking AI tool that predicts protein structures.

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Jon Potter, Partner at The RXN Group – Interview Series

Unite.AI

Jon Potter is a Partner and leads the State-Level AI Practice at RXN Group. He is an experienced lawyer, lobbyist, and communicator, has founded and led two industry associations and a consumer organization, and consulted many industries and organizations on legislative, communications and issue advocacy challenges. Jon founded the Digital Media Association, Fan Freedom, and the Application Developers Alliance, was Executive Vice President of the global communications firm Burson-Marsteller, and

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Learning Path for AI Agents

Analytics Vidhya

If you’ve landed on this blog, you’ve probably heard the terms AI Agents or Agentic AI trending everywhere. Maybe you’re wondering what they are and how to learn about them – well, you’re in the right place! Welcome to the AI Agents Learning Path! This path will guide you through essential concepts, tools, and techniques […] The post Learning Path for AI Agents appeared first on Analytics Vidhya.

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Meta AI Releases Meta Spirit LM: An Open Source Multimodal Language Model Mixing Text and Speech

Marktechpost

One of the primary challenges in developing advanced text-to-speech (TTS) systems is the lack of expressivity when transcribing and generating speech. Traditionally, large language models (LLMs) used for building TTS pipelines convert speech to text using automatic speech recognition (ASR), process it using an LLM, and then convert the output back to speech via TTS.

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Implementation of REAcT Agent using LlamaIndex and Gemini

Analytics Vidhya

In the past 2-3 years, we’ve witnessed unreal development in the field of AI, mainly in large language models, diffusion models, multimodals, and so on. One of my favorite interests has been in agentic workflows. Early this year, Andrew Ng, the founder of Coursera and a pioneer in deep learning, made a tweet saying “Agentic […] The post Implementation of REAcT Agent using LlamaIndex and Gemini appeared first on Analytics Vidhya.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Graph-Constrained Reasoning (GCR): A Novel AI Framework that Bridges Structured Knowledge in Knowledge Graphs with Unstructured Reasoning in LLMs

Marktechpost

Large language models (LLMs) have demonstrated significant reasoning capabilities, yet they face issues like hallucinations and the inability to conduct faithful reasoning. These challenges stem from knowledge gaps, leading to factual errors during complex tasks. While knowledge graphs (KGs) are increasingly used to bolster LLM reasoning, current KG-enhanced approaches—retrieval-based and agent-based—struggle with either accurate knowledge retrieval or efficiency in reasoning on a large scale.

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Navigating the Vector Database Landscape: Choosing the Right One for Your Project

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Reslley Gabriel Originally published on Towards AI. We’ll explore the key factors to consider when choosing a vector database, including critical insights from recent industry analyses. Also, we’ll provide comparison tables to help you evaluate some of the leading options available today.

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Salesforce AI Introduces ReGenesis: A Novel AI Approach to Improving Large Language Model Reasoning Capabilities

Marktechpost

Large language models (LLMs) have revolutionized how machines process and generate human language, but their ability to reason effectively across diverse tasks remains a significant challenge. Researchers in AI are working to enable these models to perform not just language understanding but also complex reasoning tasks like problem-solving in mathematics, logic, and general knowledge.

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A Complete Guide to Embedding For NLP & Generative AI/LLM

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Mdabdullahalhasib Originally published on Towards AI. Understand the concept of vector embedding, why it is needed, and implementation with LangChain. This member-only story is on us. Upgrade to access all of Medium. Source: Image by Author (converting word into Vector) If you want to learn something efficiently, first, you should ask questions yourself or generate questions about the topics.

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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Baichuan-Omni: An Open-Source 7B Multimodal Large Language Model for Image, Video, Audio, and Text Processing

Marktechpost

Recent advancements in Large Language Models (LLMs) have reshaped the Artificial intelligence (AI)landscape, paving the way for the creation of Multimodal Large Language Models (MLLMs). These advanced models expand AI capabilities beyond text, allowing understanding and generation of content like images, audio, and video, signaling a significant leap in AI development.

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Reconstruction of Clean Images from Noisy Data: A Bayesian Inference Perspective

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Bhavesh Agone Originally published on Towards AI. An Introduction to Bayesian Analysis In its most basic form, Bayesian Inference is just a technique for summarizing statistical inference which states how likely an hypothesis is given any new evidence. The method comes from Bayes’ Theorem, which provides a way to calculate the probability that an event will happen or has happened, given any prior knowledge of conditions (from which an

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Agent-as-a-Judge: An Advanced AI Framework for Scalable and Accurate Evaluation of AI Systems Through Continuous Feedback and Human-level Judgments

Marktechpost

Agentic systems have evolved rapidly in recent years, showing potential to solve complex tasks that mimic human-like decision-making processes. These systems are designed to act step-by-step, analyzing intermediate stages in tasks like humans do. However, one of the biggest challenges in this field is evaluating these systems effectively. Traditional evaluation methods focus only on the outcomes, leaving out critical feedback that could help improve the intermediate steps of problem-solving.

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How I Built an AI-Powered Edge Computing Application with Python

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Gabe Araujo, M.Sc. Originally published on Towards AI. My journey deploying machine learning models on edge devices for real-time analytics. This member-only story is on us. Upgrade to access all of Medium. As the world of technology rapidly advances, there’s a growing demand to process data closer to its source rather than relying solely on the cloud.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Google DeepMind Introduces Omni×R: A Comprehensive Evaluation Framework for Benchmarking Reasoning Capabilities of Omni-Modality Language Models Across Text, Audio, Image, and Video Inputs

Marktechpost

Omni-modality language models (OLMs) are a rapidly advancing area of AI that enables understanding and reasoning across multiple data types, including text, audio, video, and images. These models aim to simulate human-like comprehension by processing diverse inputs simultaneously, making them highly useful in complex, real-world applications. The research in this field seeks to create AI systems that can seamlessly integrate these varied data types and generate accurate responses across differen

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Getting Started with AgentOps: A Quick Setup Guide

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re the captain of a high-tech ship, with intelligent agents ready to work for you — each agent skilled at analyzing data, generating insights, or performing specific actions.

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Understanding Local Rank and Information Compression in Deep Neural Networks

Marktechpost

Deep neural networks are powerful tools that excel in learning complex patterns, but understanding how they efficiently compress input data into meaningful representations remains a challenging research problem. Researchers from the University of California, Los Angeles, and New York University propose a new metric, called local rank, to measure the intrinsic dimensionality of feature manifolds within neural networks.

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Mistral AI Unveils Ministral 3B and 8B Models

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Get The Gist Originally published on Towards AI. Welcome to Get The Gist, where every weekday we share an easy-to-read summary of the latest and greatest developments in AI — news, innovations, and trends — all delivered in under 5 minutes! ⏱ In today’s edition: Mistral AI Unveils Ministral 3B and 8B Models for Edge Computing Nvidia Quietly Launches AI Model that Outperforms GPT-4 YouTube Rolls Out AI Music Tool “Dream Tracks” to U.S.

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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The future of data science: Emerging trends and technologies to watch

SAS Software

Data science continues to be a pivotal force driving innovation across industries. From enhancing customer experiences to optimizing operational efficiencies, the role of data science is expanding, bringing with it new challenges and opportunities. This article explores the emerging trends and technologies that are shaping the future of data science [.

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5 Smart Ways to Use Retrieval-Augmented Generation (RaG) for Real-Time NLP Enhancements

Towards AI

Last Updated on October 19, 2024 by Editorial Team Author(s): Mukundan Sankar Originally published on Towards AI. How Retrieval-Augmented Generation (RAG) Can Boost NLP Projects with Real-Time Data for Smarter AI Models This member-only story is on us. Upgrade to access all of Medium. Image illustrating how Retrieval-Augmented Generation (RAG) can boost NLP projects with real-time data for smarter AI models generated using ChatGPT by the Author We’ve seen some pretty amazing advancements in Natu

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DeepSeek AI Releases Janus: A 1.3B Multimodal Model with Image Generation Capabilities

Marktechpost

Multimodal AI models are powerful tools capable of both understanding and generating visual content. However, existing approaches often use a single visual encoder for both tasks, which leads to suboptimal performance due to the fundamentally different requirements of understanding and generation. Understanding requires high-level semantic abstraction, while generation focuses on local details and global consistency.

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A Practical Guide to Deploying Machine Learning Models

Machine Learning Mastery

As a data scientist, you probably know how to build machine learning models. But it’s only when you deploy the model that you get a useful machine learning solution. And if you’re looking to learn more about deploying machine learning models, this guide is for you.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Emergence of Intelligence in LLMs: The Role of Complexity in Rule-Based Systems

Marktechpost

The study investigates the emergence of intelligent behavior in artificial systems by examining how the complexity of rule-based systems influences the capabilities of models trained to predict those rules. Traditionally, AI development has focused on training models using datasets that reflect human intelligence, such as language corpora or expert-annotated data.

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Windows Finally Gets a ChatGPT App Months After macOS

Extreme Tech

The Windows app does not yet support voice commands, and some integrations with OpenAI's GPT Store are currently unavailable.

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Train, optimize, and deploy models on edge devices using Amazon SageMaker and Qualcomm AI Hub

AWS Machine Learning Blog

This post is co-written Rodrigo Amaral, Ashwin Murthy and Meghan Stronach from Qualcomm. In this post, we introduce an innovative solution for end-to-end model customization and deployment at the edge using Amazon SageMaker and Qualcomm AI Hub. This seamless cloud-to-edge AI development experience will enable developers to create optimized, highly performant, and custom managed machine learning solutions where you can bring you own model (BYOM) and bring your own data (BYOD) to meet varied busin