Eugene Yan

APRIL 6, 2024

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

LLM 267

LLM AI AI 267

Aiiot Talk

APRIL 6, 2024

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.

Robotics 130

Robotics Artificial Intelligence Artificial Intelligence Automation 130

Marktechpost

APRIL 6, 2024

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.

ML 144

ML AI AI Artificial Intelligence 144

Extreme Tech

APRIL 6, 2024

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.

Explainability 126

Explainability 126

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

Marktechpost

APRIL 6, 2024

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.

Neural Network 139

Neural Network Deep Learning ML AI 139

Marktechpost

APRIL 6, 2024

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.

Large Language Models 139

Large Language Models LLM Artificial Intelligence Artificial Intelligence 139

Machine Learning Mastery

APRIL 6, 2024

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.

Chatbots 70

Chatbots ChatGPT Generative AI AI 70

Marktechpost

APRIL 6, 2024

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

Large Language Models 136

Large Language Models Automation Natural Language Processing Categorization 136

Bugra Akyildiz

APRIL 6, 2024

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.

Neural Network 52

Neural Network Natural Language Processing NLP Machine Learning 52

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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.

Marktechpost

APRIL 6, 2024

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.

Large Language Models 124

Large Language Models NLP Convolutional Neural Networks Neural Network 124

Marktechpost

APRIL 6, 2024

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.

Machine Learning 119

Machine Learning Algorithm LLM Neural Network 119

Marktechpost

APRIL 6, 2024

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.

Large Language Models 122

Large Language Models BERT OpenAI LLM 122

Marktechpost

APRIL 6, 2024

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.

Large Language Models 116

Large Language Models LLM ML AI 116

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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?

Business Intelligence

Marktechpost

APRIL 6, 2024

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.

AI Researcher 111

AI Researcher AI Research Large Language Models LLM 111

Marktechpost

APRIL 6, 2024

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.

Algorithm 110

Algorithm AI AI ML 110

Marktechpost

APRIL 6, 2024

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.

Data Analysis 113

Data Analysis Machine Learning Python Data Science 113

Marktechpost

APRIL 6, 2024

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.

LLM 135

LLM Large Language Models AI Researcher AI Research 135

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

Marktechpost

APRIL 6, 2024

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

Actionable Intelligence 131

Actionable Intelligence Large Language Models Automation Business Intelligence 131