Unite.AI

OCTOBER 19, 2024

Have you ever left a video call wondering how your tone came across or how others really felt about the conversation? Imagine if you could instantly understand what was said and the emotions behind it! I recently came across Read AI , an AI meeting assistant designed to analyze emotions in real-time during video calls. Research shows that 93% of communication is nonverbal , meaning much of what we convey during meetings goes beyond words.

AI 195

AI AI Natural Language Processing Automation 195

Analytics Vidhya

OCTOBER 19, 2024

OpenAI, a leading AI company, offers API keys for developers to interact with its platform and utilize its LLM models in various projects. In this article, you’ll learn how to create your own OpenAI API Key, updated as of 2024. The simplest and recommended way to generate your API key is through the OpenAI developer […] The post How to Generate Your Own OpenAI API Key and Add Credits?

OpenAI 184

OpenAI LLM AI AI 184

AssemblyAI

OCTOBER 19, 2024

Speech recognition has become an increasingly popular feature in modern web applications. With the Web Speech API , developers can easily incorporate speech-to-text functionality into their web projects. This API provides the tools needed to perform real-time transcription directly in the browser, allowing users to control your app with voice commands or simply dictate text.

Machine Learning 144

Machine Learning AI AI 144

Analytics Vidhya

OCTOBER 19, 2024

Image segmentation has become a popular technology, with different fine-tuned models available for various purposes. The model labels every pixel in an image by streaming every region of the input image; this concept makes the idea of semantic segmentation into reality and application. This Face parsing model is a semantic segmentation technology fine-tuned from Nvidia’s […] The post Understanding Face Parsing: A Deep Dive into Semantic Segmentation Technology appeared first on Analytics V

Computer Vision 168

Computer Vision 168

Speaker: Jay Allardyce

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.

Business Intelligence

Marktechpost

OCTOBER 19, 2024

The rise of Transformer-based models has significantly advanced the field of natural language processing. However, the training of these models is often computationally intensive, requiring substantial resources and time. This research addresses the issue of improving the training efficiency of Transformer models without compromising their performance.

Natural Language Processing 127

Natural Language Processing Large Language Models AI AI 127

Marktechpost

OCTOBER 19, 2024

AI has significantly impacted healthcare, particularly in disease diagnosis and treatment planning. One area gaining attention is the development of Medical Large Vision-Language Models (Med-LVLMs), which combine visual and textual data for advanced diagnostic tools. These models have shown great potential for improving the analysis of complex medical images, offering interactive and intelligent responses that can assist doctors in clinical decision-making.

Inference Engine 113

Inference Engine ML AI AI 113

Analytics Vidhya

OCTOBER 19, 2024

Have you ever wondered how to build a multilingual application that can effortlessly translate text from English to other languages? Imagine creating your very own translation tool, leveraging the power of LangChain to handle the heavy lifting. In this article, we will learn how to build a basic application using LangChain to translate text from […] The post How to Build a Simple LLM Application with LCEL?

LLM 146

LLM Large Language Models Generative AI AI 146

Marktechpost

OCTOBER 19, 2024

Large language models (LLMs) like GPT-4, Gemini, and Llama 3 have revolutionized natural language processing through extensive pre-training and supervised fine-tuning (SFT). However, these models come with high computational costs for training and inference. Structured pruning has emerged as a promising method to improve LLM efficiency by selectively removing less critical components.

Large Language Models 111

Large Language Models Inference Engine Natural Language Processing LLM 111

Towards AI

OCTOBER 19, 2024

Author(s): Paul Ferguson, Ph.D. Originally published on Towards AI. Why We’re Demanding Answers from Our Smartest Machines Image generated by Gemini AI Artificial intelligence is making decisions that impact our lives in profound ways, from loan approvals to medical diagnoses. Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives.

Explainability 80

Explainability Explainable AI Natural Language Processing Prompt Engineering 80

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Marktechpost

OCTOBER 19, 2024

Bayesian Optimization, widely used in experimental design and black-box optimization, traditionally relies on regression models for predicting the performance of solutions within fixed search spaces. However, many regression methods are task-specific due to modeling assumptions and input constraints. This issue is especially prevalent in learning-based regression, which depends on fixed-length tensor inputs.

Machine Learning 108

Machine Learning Neural Network Categorization Algorithm 108

Towards AI

OCTOBER 19, 2024

Last Updated on October 19, 2024 by Editorial Team Author(s): Allohvk Originally published on Towards AI. Quantization explained in plain English When BERT was released around 5 years ago, it triggered a wave of Large Language Models with ever increasing sizes. As the model size got bigger, the performance improved with no apparent upper limit to the improvement!

Explainability 90

Explainability LLM BERT Large Language Models 90

Marktechpost

OCTOBER 19, 2024

Human beings possess innate extraordinary perceptual judgments, and when computer vision models are aligned with them, model’s performance can be improved manifold. Various attributes such as scene layout, subject location, camera pose, color, perspective, and semantics help us have a clear picture of the world and objects within. The alignment of vision models with visual perception makes them sensitive to these attributes and more human-like.

Computer Vision 108

Computer Vision Inference Engine AI AI 108

Towards AI

OCTOBER 19, 2024

Last Updated on October 20, 2024 by Editorial Team Author(s): Anoop Maurya Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Photo by Amr Taha™ on Unsplash In the realm of artificial intelligence, the emergence of transformer models has revolutionized natural language processing (NLP). While large models with billions of parameters dominate the landscape, smaller models can still deliver impressive results.

BERT 68

BERT Natural Language Processing Deep Learning Artificial Intelligence 68

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.

Generative AI

Marktechpost

OCTOBER 19, 2024

Visual and action data are interconnected in robotic tasks, forming a perception-action loop. Robots rely on control parameters for movement, while VFMs excel in processing visual data. However, a modality gap exists between visual and action data arising from the fundamental differences in their sensory modalities, abstraction levels, temporal dynamics, contextual dependence, and susceptibility to noise.

Robotics 108

Robotics Inference Engine Algorithm ML 108

Towards AI

OCTOBER 19, 2024

Last Updated on October 19, 2024 by Editorial Team Author(s): Shenggang Li Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Time Series Clustering Using Auto-Regressive Models, Moving Averages, and Nonlinear Trend Functions Photo by Ricardo Gomez Angel on Unsplash Clustering time series data, like stock prices or gene expression, is often difficult.

AI 82

AI AI Machine Learning 82

Marktechpost

OCTOBER 19, 2024

The problem of over-optimization of likelihood in Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), arises when these methods fail to improve model performance despite increasing the likelihood of preferred outcomes. These algorithms, which are alternatives to Reinforcement Learning from Human Feedback (RLHF), aim to align language models with human preferences by directly optimizing for desired outcomes without explicit

Inference Engine 108

Inference Engine Algorithm LLM ML 108

Towards AI

OCTOBER 19, 2024

Author(s): ronilpatil Originally published on Towards AI. Image by Author Table of Content — Introduction—The Challenge—Cache Mechanism—Caching with DiskCache—Caching with Redis—Redis on Upstash—GitHub Repository—Conclusion Introduction In the fast-paced world of web applications, speed and efficiency are the most critical aspects, especially when you’re integrating AI models.

Deep Learning 75

Deep Learning Machine Learning ML Python 75

Speaker: Brendan Sweeney, VP of Sales & Devyn Blume, Sr. Account Executive

Are you curious about how artificial intelligence is reshaping sales coaching, learning, and development? Join Brendan Sweeney and Devyn Blume of Allego for an engaging new webinar exploring AI's transformative role in sales coaching and performance improvement! Brendan and Devyn will share actionable insights and strategies for integrating AI into coaching and development - ensuring personalized, effective, and scalable training!

AI

Marktechpost

OCTOBER 19, 2024

Large language models (LLMs) have demonstrated consistent scaling laws, revealing a power-law relationship between pretraining performance and computational resources. This relationship, expressed as C = 6ND (where C is compute, N is model size, and D is data quantity), has proven invaluable for optimizing resource allocation and maximizing computational efficiency.

Inference Engine 103

Inference Engine Large Language Models Artificial Intelligence Artificial Intelligence 103

Ofemwire

OCTOBER 19, 2024

When using AI tools like ChatGPT or other language models, you might have noticed that sometimes the AI gives great answers, and other times it seems to lose track of the conversation. This has a lot to do with something called the “context window.” But what exactly is a context window, and why does it matter? In simple terms, a context window is the amount of information an AI can “remember” while generating a response.

AI 52

AI AI AI Modeling AI Tools 52

Marktechpost

OCTOBER 19, 2024

Large Language models (LLMs) have long been trained to process vast amounts of data to generate responses that align with patterns seen during training. However, researchers are exploring a more profound concept: introspection, the ability of LLMs to reflect on their behavior and gain knowledge that isn’t directly derived from their training data.

Large Language Models 103

Large Language Models Inference Engine AI AI 103

Towards AI

OCTOBER 19, 2024

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Marktechpost

OCTOBER 19, 2024

Long-context Large language models (LLMs) are designed to handle long input sequences, enabling them to process and understand large amounts of information. As the interference computation power is increased the large language models (LLMs) can perform diverse tasks. Particularly for knowledge-intensive tasks that rely mainly on Retrieval augmented generation (RAG) , increasing the quantity or size of retrieved documents up to a certain level consistently increases the performance.

Large Language Models 103

Large Language Models Inference Engine AI AI 103

Marktechpost

OCTOBER 19, 2024

Recent advancements in large language models (LLMs) have significantly enhanced their ability to handle long contexts, making them highly effective in various tasks, from answering questions to complex reasoning. However, a critical bottleneck has emerged: the memory requirements for storing key-value (KV) caches escalate significantly as the number of model layers and the length of input sequences increase.

Large Language Models 100

Large Language Models Inference Engine ML AI 100

Marktechpost

OCTOBER 19, 2024

Code generation AI models (Code GenAI) are becoming pivotal in developing automated software demonstrating capabilities in writing, debugging, and reasoning about code. However, their ability to autonomously generate code raises concerns about security vulnerabilities. These models may inadvertently introduce insecure code, which could be exploited in cyberattacks.

Inference Engine 97

Inference Engine Large Language Models LLM AI Modeling 97

Marktechpost

OCTOBER 19, 2024

Dynamical systems are mathematical models that explain how a system evolves due to physical interactions or forces. These systems are fundamental to understanding various phenomena across scientific fields like physics, biology, and engineering. For example, they model fluid dynamics, celestial mechanics, and robotic movements. The core challenge in modeling these systems lies in their complexity, often involving nonlinear patterns and multi-agent interactions, making them difficult to predict a

Deep Learning 99

Deep Learning Neural Network Robotics Inference Engine 99

Speaker: Michael Mansard and Katherine Shealy

Generative AI is no longer just an exciting technological advancement––it’s a seismic shift in the SaaS landscape. Companies today are grappling with how to not only integrate AI into their products but how to do so in a way that makes financial sense. With the cost of developing AI capabilities growing, finding a flexible monetization strategy has become mission critical.

AI

Marktechpost

OCTOBER 19, 2024

The key challenge in the image autoencoding process is to create high-quality reconstructions that can retain fine details, especially when the image data has undergone compression. Traditional autoencoders, which rely on pixel-level losses such as mean squared error (MSE), tend to produce blurry outputs without capturing high-frequency details, textual information, and edge information.

Inference Engine 98

Inference Engine AI AI ML 98

Marktechpost

OCTOBER 19, 2024

Point tracking is paramount in video; from 3d reconstruction to editing tasks, a precise approximation of points is necessary to achieve quality results. Over time, trackers have incorporated transformer and neural network-based designs to track individual and multiple points simultaneously. However, these neural networks could be fully exploited only with high-quality training data.

Neural Network 64

Neural Network AI AI ML 64