Marktechpost

MARCH 26, 2024

In conclusion, the LLM2LLM framework offers a robust solution to the critical challenge of data scarcity. By harnessing the power of one LLM to improve another, it demonstrates a novel, efficient pathway to fine-tune models for specific tasks with limited initial data. Similarly, on the CaseHOLD dataset, there was a 32.6%

Large Language Models 119

Large Language Models Data Scarcity Natural Language Processing LLM 119

Marktechpost

JULY 23, 2023

The number of AI and, in particular, machine learning (ML) publications related to medical imaging has increased dramatically in recent years. ML models are constantly being developed to improve healthcare efficiency and outcomes, from classification to semantic segmentation, object detection, and image generation.

Machine Learning 79

Machine Learning Data Scarcity Algorithm AI Researcher 79

Marktechpost

JANUARY 29, 2024

Other effective strategies to address data scarcity include vocabulary extension and ongoing pretraining. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Even the Glot500-c corpora, which spans 534 languages from 47 language families, benefited the low-resource languages.

Large Language Models 122

Large Language Models Data Scarcity Artificial Intelligence Artificial Intelligence 122

Marktechpost

MARCH 16, 2024

This method leverages pre-trained generative text and image models to create synthetic paired data for VLMs, addressing data scarcity, cost, and noise challenges. It generates both text and images synthetically, avoiding reliance on real-world data. The researchers from Google DeepMind have proposed Synth2.

Data Scarcity 88

Data Scarcity Computer Vision ML Artificial Intelligence 88

Marktechpost

JANUARY 15, 2024

Developed by researchers from Apple, aiming to enhance machine translation, AlignInstruct represents a paradigm shift in tackling data scarcity. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Check out the Paper. Also, don’t forget to follow us on Twitter.

Large Language Models 113

Large Language Models Data Scarcity Computational Linguistics Natural Language Processing 113

Marktechpost

APRIL 5, 2024

However, there’s potential to significantly improve models for smaller languages through multilingual training, which could mitigate the data scarcity issue. Also, don’t forget to follow us on Twitter. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Data Scarcity 110

Data Scarcity AI Modeling AI AI 110

Marktechpost

APRIL 23, 2024

Unlike conventional methods, this approach utilizes Bayesian inference and Monte Carlo techniques to effectively manage uncertainty and data scarcity. Also, don’t forget to follow us on Twitter. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Deep Learning 77

Deep Learning Data Scarcity Artificial Intelligence Artificial Intelligence 77

Marktechpost

DECEMBER 31, 2023

He highlighted the necessity for effective data use by stressing the significant amount of data many AI systems consume. Another researcher highlighted the challenge of considering AI model-free due to market data scarcity for training, particularly in realistic derivative markets. Check out the Paper.

Neural Network 112

Neural Network Data Scarcity Artificial Intelligence Artificial Intelligence 112

Marktechpost

DECEMBER 30, 2023

link] To conclude, the TF-T2V framework offers several key advantages: It innovatively utilizes text-free videos, addressing the data scarcity issue prevalent in the field. The dual-branch structure, focusing on spatial appearance and motion dynamics, generates high-quality, coherent video. Check out the Paper.

Data Scarcity 97

Data Scarcity Computer Vision Artificial Intelligence Artificial Intelligence 97

Marktechpost

FEBRUARY 28, 2024

By aligning the embedding space of unimodal FMs through cross-modal transformation models utilizing KG triplets, BioBRIDGE maintains data sufficiency and efficiency and navigates the challenges posed by computational costs and data scarcity that hinder the scalability of multimodal approaches. Check out the Paper.

Machine Learning 79

Machine Learning AI Researcher AI Research Data Scarcity 79

Marktechpost

FEBRUARY 27, 2024

For instance, BloomberGPT excels in finance with private financial data spanning 40 years. Collaborative training on decentralized personal data, without direct sharing, emerges as a critical approach to support the development of modern LLMs amid data scarcity and privacy concerns. Check out the Paper and Github.

Large Language Models 78

Large Language Models Machine Learning Data Scarcity LLM 78

TheSequence

APRIL 14, 2024

One of the most interesting options to address these limitations comes from a pretty old ML school: neuro-symbolic models. 🔎 ML Research Persuasiveness in LLMs Anthropic Research published a paper proposing a method to measure persuasiveness in LLMs. Neuro-symbolic models are back!

Data Scarcity 52

Data Scarcity LLM Neural Network ML 52

Marktechpost

NOVEMBER 9, 2023

They also make available a sizable collection of artificially photorealistic photos matched with ground truth labels for these kinds of signals to overcome data scarcity. It can also be used for data obtained from a consumer’s cell phone. Check out the Paper and Project.

Data Scarcity 126

Data Scarcity Computer Vision AI AI 126

Marktechpost

MARCH 11, 2024

The developed CAT-SD scheme effectively mitigates catastrophic forgetting, addresses data scarcity, and ensures privacy in medical datasets. Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. Check out the Paper and Github. If you like our work, you will love our newsletter.

Neural Network 84

Neural Network Continuous Learning Robotics Data Scarcity 84

Marktechpost

SEPTEMBER 2, 2023

They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first. With just a few normal samples, AnomalyGPT can also learn in context, allowing for quick adjustment to new objects.

Data Scarcity 120

Data Scarcity Large Language Models Natural Language Processing LLM 120

Marktechpost

JULY 29, 2023

They aimed to train a generative model that can synthesize features by providing class names, which enables them to generate features for categories without data. Also, don’t forget to join our 27k+ ML SubReddit , Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

AI Researcher 79

AI Researcher AI Research Generative AI Data Scarcity 79

John Snow Labs

OCTOBER 16, 2023

Strategy and Data: Non-top-performers highlight strategizing (24%), talent availability (21%), and data scarcity (18%) as their leading challenges. Strategy and Data: Non-top performers highlight strategizing (24%), talent availability (21%), and data scarcity (18%) as their leading challenges.

Large Language Models 52

Large Language Models NLP Metadata LLM 52

Viso.ai

DECEMBER 18, 2023

Access to synthetic data is valuable for developing effective artificial intelligence (AI) and machine learning (ML) models. Real-world data often poses significant challenges, including privacy, availability, and bias. To address these challenges, we introduce synthetic data as an ML model training solution.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52

Mlearning.ai

MAY 23, 2023

This innovative approach tackles the data scarcity issue for less common languages, allowing MMS to surpass this limitation. Meta’s solution stands out by leveraging audio recordings of individuals reading translated texts from the New Testament in various languages. Most of us have used a AI assisant on the phone.

Data Scarcity 52

Data Scarcity Algorithm OpenAI Machine Learning 52

Heartbeat

FEBRUARY 27, 2024

Among these are: Data Augmentation: Data augmentation is a viable solution to some problems that multilingual prompt engineering presents, especially in the context of limited linguistic resources and data scarcity for low-resource languages. We pay our contributors, and we don’t sell ads.

Prompt Engineer 40

Prompt Engineer Prompt Engineering Robotics Deep Learning 40

Heartbeat

NOVEMBER 27, 2023

Data Scarcity and Quality Issues in Medical Imaging One significant challenge in medical image analysis is the need for labeled data, especially for rare diseases or specific patient populations. We're committed to supporting and inspiring developers and engineers from all walks of life.

Deep Learning 59

Deep Learning Convolutional Neural Networks Explainability Neural Network 59

Viso.ai

FEBRUARY 11, 2024

By covering the entire ML pipeline, Viso Suite simplifies the process of implementing computer vision solutions across disciplines, including robotics. It’s capable of scalable, photorealistic data generation that includes accurate annotations for training. To learn more about Viso Suite, book a demo with us.

Computer Vision 52

Computer Vision Robotics Natural Language Processing Data Scarcity 52

Viso.ai

FEBRUARY 11, 2024

By covering the entire ML pipeline, Viso Suite simplifies the process of implementing computer vision solutions across disciplines, including robotics. It’s capable of scalable, photorealistic data generation that includes accurate annotations for training. To learn more about Viso Suite, book a demo with us.

Computer Vision 52

Computer Vision Robotics Natural Language Processing Data Scarcity 52

Marktechpost

FEBRUARY 29, 2024

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. Check out the Paper. All credit for this research goes to the researchers of this project.

Artificial Intelligence 74

Artificial Intelligence Artificial Intelligence Data Scarcity NLP 74

Topbots

DECEMBER 19, 2023

A key finding is that for a fixed compute budget, training with up to four epochs of repeated data shows negligible differences in loss compared to training with unique data. The paper also explores alternative strategies to mitigate data scarcity. Fast, parallel, weakly-synchronized computation dominates in ML.

Large Language Models 110

Large Language Models Natural Language Processing AI Researcher AI Research 110

John Snow Labs

FEBRUARY 29, 2024

They advocate for the importance of transparency, informed consent protections, and the use of health information exchanges to avoid data monopolies and to ensure equitable benefits of Gen AI across different healthcare providers and patients​​. However as AI technology progressed its potential within the field also grew.

Generative AI 40

Generative AI AI AI AI Modeling 40

AWS Machine Learning Blog

MARCH 14, 2024

Beyond hardware, data cleaning and processing, model architecture design, hyperparameter tuning, and training pipeline development demand specialized machine learning (ML) skills. Launched in 2017, Amazon SageMaker is a fully managed service that makes it straightforward to build, train, and deploy ML models.

Generative AI 108

Generative AI Prompt Engineer Prompt Engineering AI 108

Viso.ai

DECEMBER 6, 2023

For instance, CV algorithms can understand Light Detection and Ranging (LIDAR) data for enhanced perceptions of the environment. Few-Shot vs. Zero-Shot Learning: Few-shot and zero-shot learning paradigms are revolutionizing machine learning (ML) development by allowing you to train CV models using only a few to no labeled samples.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Marktechpost

APRIL 15, 2024

However, these approaches face significant hurdles, including the curse of multilinguality, data scarcity, and the substantial computational resources required. Don’t Forget to join our 40k+ ML SubReddit Want to get in front of 1.5 Also, don’t forget to follow us on Twitter. If you like our work, you will love our newsletter.

Machine Learning 123

Machine Learning Data Scarcity Large Language Models Natural Language Processing 123

Viso.ai

JANUARY 16, 2024

The traditional machine learning (ML) paradigm involves training models on extensive labeled datasets. However, the method requires a sufficient volume of labeled training data. For instance, recent research from Carnegie Mellon developed a framework to use audio and text to learn about visual data.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52