Sat.Apr 06, 2024

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Taming my Monkey Mind: How I Built a 24/7 AI Coach

Eugene Yan

Building an AI coach with speech-to-text, text-to-speech, an LLM, and a virtual number.

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How Does IoT Improve Efficiency in Business Communication?

Aiiot Talk

Businesses worldwide are seeing the potential of IoT (Internet of Things) and its promise to streamline communication. It is forging deeper connections with customers and enhancing operational efficiency. As more companies realize the positives of adopting IoT, many speculate what it could mean for the future. IoT is shaping companies’ strategies and formulating communication efficiencies to benefit you in numerous ways.

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Google DeepMind Presents Mixture-of-Depths: Optimizing Transformer Models for Dynamic Resource Allocation and Enhanced Computational Sustainability

Marktechpost

The transformer model has emerged as a cornerstone technology in AI, revolutionizing tasks such as language processing and machine translation. These models allocate computational resources uniformly across input sequences, a method that, while straightforward, overlooks the nuanced variability in the computational demands of different parts of the data.

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What Are Semiconductors, and What Are They Made Of?

Extreme Tech

Semiconductors are at the heart of most electronics, but have you ever wondered how they work? In this article, we explain what semiconductors are, how they work, and just how tiny those transistors can get.

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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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Unifying Neural Network Design with Category Theory: A Comprehensive Framework for Deep Learning Architecture

Marktechpost

In deep learning, a unifying framework to design neural network architectures has been a challenge and a focal point of recent research. Earlier models have been described by the constraints they must satisfy or the sequence of operations they perform. This dual approach, while useful, has lacked a cohesive framework to integrate both perspectives seamlessly.

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Researchers at Stanford University Introduce Octopus v2: Empowering On-Device Language Models for Super Agent Functionality

Marktechpost

A critical challenge in Artificial intelligence, specifically regarding large language models (LLMs), is balancing model performance and practical constraints like privacy, cost, and device compatibility. While large cloud-based models offer high accuracy, their reliance on constant internet connectivity, potential privacy breaches, and high costs pose limitations.

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A Technical Introduction to Stable Diffusion

Machine Learning Mastery

The introduction of GPT-3, particularly its chatbot form, i.e. the ChatGPT, has proven to be a monumental moment in the AI landscape, marking the onset of the generative AI (GenAI) revolution. Although prior models existed in the image generation space, it’s the GenAI wave that caught everyone’s attention. Stable Diffusion is a member of the […] The post A Technical Introduction to Stable Diffusion appeared first on MachineLearningMastery.com.

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AutoTRIZ: An Artificial Ideation Tool that Leverages Large Language Models (LLMs) to Automate and Enhance the TRIZ (Theory of Inventive Problem Solving) Methodology

Marktechpost

Human designers’ creative ideation for concept generation has been aided by intuitive or structured ideation methods such as brainstorming, morphological analysis, and mind mapping. Among such methods, the Theory of Inventive Problem Solving (TRIZ) is widely adopted for systematic innovation and has become a well-known approach. TRIZ is a knowledge-based ideation methodology that provides a structured framework for engineering problem-solving by identifying and overcoming technical contrad

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Pinterest introduces LinkSage, Google combines Neural Networks with Bayesian theory

Bugra Akyildiz

Articles Pinterest wrote an article on LinkSage that allows them to do offline content understanding by taking the following problem to solve: Challenges of Understanding Off-Site Content: Understanding off-site content is challenging because Pinterest doesn't have direct control over the content or the way it is structured. This makes it difficult to use traditional techniques like natural language processing (NLP) to understand the content.

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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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Role Of Transformers in NLP – How are Large Language Models (LLMs) Trained Using Transformers?

Marktechpost

Transformers have transformed the field of NLP over the last few years, with LLMs like OpenAI’s GPT series, BERT, and Claude Series, etc. The introduction of the transformer architecture has provided a new paradigm for building models that understand and generate human language with unprecedented accuracy and fluency. Let’s delve into the role of transformers in NLP and elucidate the process of training LLMs using this innovative architecture.

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Researchers at Microsoft AI Propose LLM-ABR: A Machine Learning System that Utilizes LLMs to Design Adaptive Bitrate (ABR) Algorithms

Marktechpost

Large Language models (LLMs) have demonstrated exceptional capabilities in generating high-quality text and code. Trained on vast collections of text corpus, LLMs can generate code with the help of human instructions. These trained models are proficient in translating user requests into code snippets, crafting specific functions, and constructing entire projects from scratch.

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NAVER Cloud Researchers Introduce HyperCLOVA X: A Multilingual Language Model Tailored to Korean Language and Culture

Marktechpost

The evolution of large language models (LLMs) marks a transition toward systems capable of understanding and expressing languages beyond the dominant English, acknowledging the global diversity of linguistic and cultural landscapes. Historically, the development of LLMs has been predominantly English-centric, reflecting primarily the norms and values of English-speaking societies, particularly those in North America.

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Researchers at Intel Labs Introduce LLaVA-Gemma: A Compact Vision-Language Model Leveraging the Gemma Large Language Model in Two Variants (Gemma-2B and Gemma-7B)

Marktechpost

Recent advancements in large language models (LLMs) and Multimodal Foundation Models (MMFMs) have spurred interest in large multimodal models (LMMs). Models like GPT-4, LLaVA, and their derivatives have shown remarkable performance in vision-language tasks such as Visual Question Answering and image captioning. However, their high computational demands have prompted exploration into smaller-scale LMMs.

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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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Meet Empower: An AI Research Startup Unleashing GPT-4 Level Function Call Capabilities at 3x the Speed and 10 Times Lower Cost

Marktechpost

Large Language Models (LLMs) reach their full potential not just through conversation but by integrating with external APIs, enabling functionalities like identity verification, booking, and processing transactions. This capability is essential for applications in workflow automation and support tasks. The main choice lies between OpenAI’s GPT-4, known for high quality but facing latency and cost issues, and GPT-3.5, which is quicker and cheaper but less accurate.

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Google AI Unveils New Benchmarks in Video Analysis with Streaming Dense Captioning Model

Marktechpost

A team of Google researchers introduced the Streaming Dense Video Captioning model to address the challenge of dense video captioning, which involves localizing events temporally in a video and generating captions for them. Existing models for video understanding often process only a limited number of frames, leading to incomplete or coarse descriptions of videos.

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How to Use Google Colab: A Beginner’s Guide

Marktechpost

Google Colab, short for Google Colaboratory, is a free cloud service that supports Python programming and machine learning. It’s a dynamic tool that enables anyone to write and execute Python codes on a browser. This platform is favored for its zero-configuration required, easy sharing of projects, good free GPUs, and great paid ones, making it a go-to for students, data scientists, and AI researchers.

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Alibaba-Qwen Releases Qwen1.5 32B: A New Multilingual dense LLM with a context of 32k and Outperforming Mixtral on the Open LLM Leaderboard

Marktechpost

Alibaba’s AI research division has unveiled the latest addition to its Qwen language model series – the Qwen1.5-32B- in a remarkable stride towards balancing high-performance computing with resource efficiency. With its 32 billion parameters and impressive 32k token context size, this model not only carves a niche in the realm of open-source large language models (LLMs) but also sets new benchmarks for efficiency and accessibility in AI technologies.

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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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Meet RAGFlow: An Open-Source RAG (Retrieval-Augmented Generation) Engine Based on Deep Document Understanding

Marktechpost

In the ever-evolving landscape of artificial intelligence, businesses face the perpetual challenge of harnessing vast amounts of unstructured data. Meet RAGFlow , a groundbreaking open-source AI project that promises to revolutionize how companies extract insights and answer complex queries with an unprecedented level of truthfulness and accuracy. What Sets RAGFlow Apart RAGFlow is an innovative engine that leverages Retrieval-Augmented Generation (RAG) technology to provide a powerful solution