Unite.AI

OCTOBER 5, 2023

These earlier systems paved the way for groundbreaking advancements, leading to the development of more sophisticated approaches like neural networks and convolutional neural networks. He meticulously presents how distinct LLMs exhibit emergent properties capable of intuitively understanding the theory of mind.

Convolutional Neural Networks 147

Convolutional Neural Networks Neural Network Machine Learning Large Language Models 147

Unite.AI

SEPTEMBER 13, 2023

These approaches indicate that LLM frameworks might have some applications for visual tasks. The AnomalyGPT framework uses a LLM and a pre-trained image encoder to align images with their corresponding textual descriptions using stimulated anomaly data. Finally, the model feeds the embeddings and original image information to the LLM.

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Convolutional Neural Networks LLM Neural Network Large Language Models 288

Marktechpost

MARCH 10, 2025

Deep neural networks’ seemingly anomalous generalization behaviors, benign overfitting, double descent, and successful overparametrization are neither unique to neural networks nor inherently mysterious. These phenomena can be understood through established frameworks like PAC-Bayes and countable hypothesis bounds.

Deep Learning 46

Deep Learning Convolutional Neural Networks Neural Network Explainability 46

Towards AI

MAY 9, 2024

What’s AI Weekly Since I’ve been involved in building many LLM and RAG-based applications and courses, I wanted to find the best, cheapest, and easiest way possible to build an RAG chatbot hosted on Discord, which I use daily. If you would like to collaborate on a test of this system, contact them in the thread! Meme of the week!

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Convolutional Neural Networks Neural Network Large Language Models AI 96

Marktechpost

APRIL 6, 2024

in 2017, marking a departure from the previous reliance on recurrent neural networks (RNNs) and convolutional neural networks (CNNs) for processing sequential data. This includes the weights of the neural network layers and the parameters of the attention mechanisms.

Large Language Models 120

Large Language Models NLP Convolutional Neural Networks Neural Network 120

Unite.AI

JUNE 21, 2024

Accelerating LLM Inference with NVIDIA TensorRT While GPUs have been instrumental in training LLMs, efficient inference is equally crucial for deploying these models in production environments. Accelerating LLM Training with GPUs and CUDA. 122 ~/local 1 Verify the installation: ~/local/cuda-12.2/bin/nvcc

Deep Learning 130

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Marktechpost

OCTOBER 11, 2023

One challenge, for instance, is to boost the performance of a Convolution Neural Networks (CNN) model by more than 10% on the cifar10 dataset. At a high level, they simply ask the LLMs to take the next action, using a prompt that is automatically produced based on the available information about the task and previous steps.

Machine Learning 103

Machine Learning AI Research AI Researcher Convolutional Neural Networks 103

Marktechpost

JUNE 3, 2024

Attempts to solve combinatorial optimization issues like the Traveling Salesman Problem (TSP) using deep learning have progressed logically from convolutional neural networks (CNNs) to recurrent neural networks (RNNs) and finally to transformer-based models.

Convolutional Neural Networks 101

Convolutional Neural Networks Neural Network Large Language Models Algorithm 101

Machine Learning (Theory)

MARCH 5, 2025

Support Vector Machines were disrupted by deep learning, and convolutional neural networks were displaced by transformers. This pattern may repeat for the current transformer/large language model (LLM) paradigm. Here are some quick calculations suggesting it may be possible to do significantly better along multiple axes.

AI Development 63

AI Development AI Developer Convolutional Neural Networks Large Language Models 63

Unite.AI

APRIL 2, 2024

Many frameworks employ a generic neural network for a wide range of image restoration tasks, but these networks are each trained separately. These deep learning image restoration models propose to use neural networks based on Transformers and Convolutional Neural Networks.

Computer Vision 130

Computer Vision Neural Network Convolutional Neural Networks Deep Learning 130

Marktechpost

JANUARY 2, 2025

These models rely on Convolutional Neural Networks (CNNs) or transformers with conditioning techniques like FiLM. Current methods in robotics , such as Transformer-based Diffusion Models , are used for tasks like Imitation Learning , Offline Reinforcement Learning , and robot design. Dont Forget to join our 60k+ ML SubReddit.

Convolutional Neural Networks 85

Convolutional Neural Networks Robotics Neural Network LLM 85

Heartbeat

DECEMBER 14, 2023

" {chat_history} Question: {input} {agent_scratchpad} """ llm = OpenAI(temperature=0.0) tools = load_tools(["ddg-search", "llm-math", "wikipedia"], llm=llm) tools[0].description in 1998, In general, LeNet refers to LeNet-5 and is a simple convolutional neural network.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning Computer Scientist 52

Towards AI

MAY 15, 2024

Source: Author/Adobe Firefly) Last week, as I scrolled through my Instagram feed, an animation video popped up in the famous 3Blue1Brown style explaining how Convolution Neural Networks work. AI bot sliding on a sine curve.

Convolutional Neural Networks 103

Convolutional Neural Networks Explainability Python Neural Network 103

Unite.AI

JANUARY 25, 2024

To tackle the challenge, the Osprey framework implements a convolutional CLIP model as the vision encoder in its architecture. Traditionally, Convolutional Neural Networks based CLIP models have demonstrated remarkable generalization capabilities across different input resolutions when put against vision transformer based CLIP models.

Large Language Models 147

Large Language Models Convolutional Neural Networks LLM Neural Network 147

Google Research AI blog

MAY 26, 2023

The prevalence of these methods was because existing end-to-end computer vision models based on convolutional neural networks (CNNs) or transformers pre-trained on natural images could not be easily adapted to visual language. An illustration of the DePlot+LLM method. An illustration of the DePlot+LLM method.

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Convolutional Neural Networks Computer Vision Large Language Models LLM 117

Viso.ai

DECEMBER 1, 2023

A deep learning model, or a DL model, is a neural network that has been trained to learn how to perform a task, such as recognizing objects in digital images and videos, or understanding human speech. The LLM model is notable for its 7.3 Some common examples of ML models include regression models and classification models.

AI Modeling 98

AI Modeling Neural Network Deep Learning Computer Vision 98

Heartbeat

DECEMBER 8, 2023

Agents vs. Chains The core idea of agents is to use an LLM to choose a sequence of actions. Agents use an LLM as a reasoning engine and connect it to two key components: tools and memory. Want to learn how to build modern software with LLMs using the newest tools and techniques in the field? A selection of agents to choose from.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning LLM 52

Topbots

OCTOBER 4, 2023

Image processing : Predictive image processing models, such as convolutional neural networks (CNNs), can classify images into predefined labels (e.g., These models are built by first adding noise to the image and then training the neural network to remove noise. a social media post or product description).

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Google Research AI blog

FEBRUARY 23, 2023

Previous work had shown that convolutional neural networks (CNNs) could interpret ultrasounds acquired by trained sonographers using a standardized acquisition protocol. the LLM would generate a response explaining that yes, stress can cause nosebleeds, and detail some possible mechanisms.

Convolutional Neural Networks 104

Convolutional Neural Networks ML Neural Network Deep Learning 104

Bugra Akyildiz

AUGUST 17, 2024

Articles HALVA (Hallucination Attenuated Language and Vision Assistant) approach involves specific modifications to the model architecture and the objective function to address hallucinations in multimodal large language models (LLMs). The new approach that Google proposed tries to mitigate this large limitation of the vanilla LLMs.

Convolutional Neural Networks 59

Convolutional Neural Networks Large Language Models Neural Network Machine Learning 59

AWS Machine Learning Blog

MARCH 13, 2024

model_id, model_version = "huggingface-llm-gemma-7b-instruct", "*" Choose a model ID from the following table, which details the default configuration options for the JumpStart deployment. Model ID Default inference instance Tensor parallel degree Supported context Length huggingface-llm-gemma-2b ml.g5.xlarge

Machine Learning 126

Machine Learning Large Language Models LLM Python 126

Pragnakalp

JANUARY 1, 2024

What distinguishes Mistral 7B from other LLM is that it is smaller in size but packs a punch with its incredible abilities, performing remarkably well in various tasks. If you wish to deploy the Mistral AI LLM on your infrastructure or system, they have published these models on the Hugging Face Models platform. billion parameters.

Neural Network 52

Neural Network Natural Language Processing Convolutional Neural Networks NLP 52

Heartbeat

OCTOBER 12, 2023

These models, powered by massive neural networks, have catalyzed groundbreaking advancements in natural language processing (NLP) and have reshaped the landscape of machine learning. Architectural Adaptations : LLM architectures are evolving to accommodate multi-modal data as input and derive features from them.

Large Language Models 59

Large Language Models Neural Network Convolutional Neural Networks Artificial Intelligence 59

Snorkel AI

MARCH 1, 2023

Model architectures that qualify as “supervised learning”—from traditional regression models to random forests to most neural networks—require labeled data for training. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Radford et al. What are some examples of Foundation Models?

BERT 83

BERT Natural Language Processing Large Language Models NLP 83

ODSC - Open Data Science

MARCH 8, 2024

Let’s explore why RAG is important and how it bridges the gap between LLMs and external knowledge. RAG is an architectural framework for LLM-powered applications which consists of two main steps: Retrieval. By doing so, it enhances the accuracy and credibility of LLM-generated content. What is RAG? turbo or the Llama 2).

Convolutional Neural Networks 52

Convolutional Neural Networks Large Language Models Neural Network LLM 52

Mlearning.ai

JUNE 8, 2023

Hidden secret to empower semantic search This is the third article of building LLM-powered AI applications series. From the previous article , we know that in order to provide context to LLM, we need semantic search and complex query to find relevant context (traditional keyword search, full-text search won’t be enough).

Machine Learning 52

Machine Learning BERT Neural Network Convolutional Neural Networks 52

The MLOps Blog

FEBRUARY 22, 2024

If you serve clients from various countries and need to train a personalized text classifier for each of them (task-incremental scenario), you can use a multilingual LLM (Large Language Model) as the core model and select a different classification layer based on the input text’s language. Or is remembering the past the priority?

Continuous Learning 59

Continuous Learning Machine Learning ML Neural Network 59

Unite.AI

AUGUST 8, 2023

The Technologies Behind Generative Models Generative models owe their existence to deep neural networks, sophisticated structures designed to mimic the human brain's functionality. By capturing and processing multifaceted variations in data, these networks serve as the backbone of numerous generative models. How Are LLMs Used?

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

Bugra Akyildiz

JANUARY 27, 2024

Featuring: Very low latency <1000 lines of python No dependencies other than PyTorch and sentencepiece int8/int4 quantization Speculative decoding Tensor parallelism Supports Nvidia and AMD GPUs LlamaIndex (GPT Index) is a data framework for your LLM application. LlamaIndex is a "data framework" to help you build LLM apps.

Deep Learning 59

Deep Learning Convolutional Neural Networks Large Language Models LLM 59

John Snow Labs

MAY 8, 2024

Model Architecture The architecture of pathology-specific LLMs often incorporates multimodal learning frameworks, integrating NLP with computer vision (CV) to analyze both text and images. The project involved training an LLM on a dataset comprising thousands of annotated pathology reports and corresponding histopathology images.

Large Language Models 40

Large Language Models Automation NLP Machine Learning 40

Towards AI

OCTOBER 31, 2023

Five 5-minute reads/videos to keep you learning Master LLMs: Top Strategies To Evaluate LLM Performance This guide shares how to evaluate and benchmark Large Language Models (LLMs) effectively. Learn more about perplexity, other evaluation metrics, and curated benchmarks to compare LLM performance.

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Convolutional Neural Networks Large Language Models LLM Chatbots 105

AWS Machine Learning Blog

NOVEMBER 7, 2024

The improved architecture combines the strengths of various deep learning techniques, including transformer encoders for text understanding, convolutional neural networks (CNNs) for efficient image processing, and attention mechanisms for capturing long-range dependencies and fine-grained details. Stable Image Ultra 1.0

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Convolutional Neural Networks LLM Generative AI Prompt Engineer 118

AI Weekly

SEPTEMBER 5, 2024

techxplore.com A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly This paper explores the intersection of LLMs with security and privacy. A new study published in Frontiers in Robotics and AI investigates what people think of robots that deceive their users.

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Convolutional Neural Networks Robotics Artificial Intelligence Artificial Intelligence 261

Bugra Akyildiz

NOVEMBER 17, 2024

They have shown impressive performance in various computer vision tasks, often outperforming traditional convolutional neural networks (CNNs). Generate metadata using local AI models and LLM APIs. 2020) OpenCoder is an open and reproducible code LLM family which includes 1.5B Filter, join, and group by metadata.

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Convolutional Neural Networks Metadata Python Computer Vision 52